EPA-600/5-74-007
MARCH 1974
                              Socioeconomic Environmental Studies Series

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                        RESEARCH  REPORTING  SERIES


Research reports  of  the Office  of Research  and Development, Environmental
Protection Agency, have been  grouped  into five series.  These five broad
categories were established to  facilitate further development and appli-
cation  of environmental technology.   Elimination of traditional grouping
was consciously planned to foster technology  transfer and a maximum inter-
face  in related fields.   The  five series are:

      1.  Environmental Health Effects Research
      2.  Environmental Protection Technology
      3.  Ecological  Research
      4.  Environmental Monitoring
      5.  Socioeconomic Environmental  Studies

This  report has been assigned to  the  SOCIOECONOMIC ENVIRONMENTAL STUDIES
series.  This series includes research that will assist EPA in implement-
ing its environmental protection  responsibilities.  This includes examining
alternative approaches to environmental protection; supporting social and
economic research; identifying new pollution control needs and alternate
control strategies;  and estimating direct social, physical, and economic
cost impacts of environmental pollution.
                          EPA REVIEW NOTICE
This report has been reviewed by the Office of Research and Development,
EPA, and approved for publication.  Approval does not signify that the
contents necessarily reflect the views and policies of the Environmental
Protection Agency, nor does mention of trade names or commercial products
constitute endorsement or recommendation for use.

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                                                EPA-600/5-74-007
                                                March  1974
FEASIBILITY  OF EMISSION STANDARDS BASED ON PARTICLE SIZE
                            By
                       L. J.  Shannon
                        P.G.  Gorman
                          W.  Park
                  Contract No.  68-01-0428
                  Program Element  1HA091
                     Project  Officers

                    Mr. Howard  Bergman
                    Mr. Paul  Gerhardt •
        Washington Environmental Research Center
                  Washington, B.C.  20460
                       Prepared for
             OFFICE OF RESEARCH AND DEVELOPMENT
            U.S.  ENVIRONMENTAL PROTECTION AGENCY
                  WASHINGTON,  D.C.  20460
  For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402 - Price $2.50

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                                ABSTRACT

 The  technical and economic feasibility of participate emission standards
 based on particle size was assessed in this program.   Specific attention
 was  focused on standards to regulate the emission of  fine  particulates—
 particulates below 2 u in size.

 The  program was divided into four major areas  of effort:

 1.   Analysis of approaches for regulating fine particle emissions  from
 stationary  sources.

 2.   Definition  of  technological and  economic requirements  necessary for
 implementation  of  emission standards.

 3.   Identification of benefits that would accrue  if control procedures for
 fine particulates  can be implemented.

4.  Assessment  of  overall  feasibility of  implementation of fine particle
emission standards.

The analysis of the  implications of emission standards based on particle
size identified some deficiencies  in control technology that will  limit
the  type of  standards that  can be  proposed and implemented in  the  near
 future.  The economic impact  of fine particulate  control was found to
vary substantially from industry to  industry.   Estimates of costs  as-
 sociated with the  control  of  fine  particulates varied  from less than 1.0%
 up to 207o of the value  of  the product.

 The  lack of data on  the damages associated with fine  particulate pollution
hampered efforts at  meaningful cost/benefit analysis.  The limited cost/
 benefit analysis performed indicated that the  optimum control  efficiency
 for  fine particulates varied  with  population density.

 In general,  emission standards based on particle  size were judged  to be
 both technically and economically  feasible.  The  most  realistic approach
would be to tailor the  emission standard to specific  sources of fine

                                  ii

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particulate pollutants.  Tailoring of standards permits a greater degree
of flexibility in an overall control plan for fine participates, and
acknowledges the differences in the importance and difficulty of control
of individual sources.
                                  iii

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                                CONTENTS


Abstract                                                                ^

List of Figures                                                        vii

List of Tables                                                          ix

Acknowledgments                                                       x±±±

Sections

I     Summary                                                            ]_

         Goal(s)  for Program to Control Fine Particulates                1
         Approaches for Regulation of Fine Particulate Emissions         2
         Technical Implications of Emission Standards                    3
         Economic Impact of Emission Standards                           5
         Benefit/Cost Relationships for Fine Particulate Control         5
         Overall  Feasibility of Emission Standards Based on
            Particulate Size                                             9

II    Recommendations for Future Work                                   11

         Introduction                                                   11
         Source Sampling and Monitoring Methods                         11
         Fine Particle Emission Rates                                   11
         Control Technology Evaluation                                  12
         Control Technology Development                                 12
         Analysis of Relationships Between Source Emissions and
            Ambient Air Quality                                         12
         Economic Impact Analysis                                       13
         Cost/Benefit Analysis                                          13
                                                                       ' :.TV
III  Introduction                                                       14

IV   Role of Fine Particles in Air Pollution                            16

         Introduction                                                   16
         Effects  of Fine Particulates on Human Health                   20
            Deposition, Retention, and Clearance Processes in the
                  Respiratory System                                     2i
            Clearance of Particulate Matter from the Respiratory
                  System                                                 24
            lexicological Studies of Atmospheric Particulate Matter     24
            Epidemiological Studies of Atmospheric Particulate Matter   26
         Modification of Properties of the Atmosphere                   27
            Visibility                                                  29
            Solar Radiation                                             33
            Weather Modification                                        34
                                  iv

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                         CONTENTS (Continued)
V     Sources of Fine Particulate Emissions                             36

         Nature of the Particulate Pollution Problem                    36
         Principal Sources of Fine Particulates                         40
            Summary of Fine Particle Emissions                          41
         Priority List for Sources of Fine Particle Emissions           46

VI    Approaches for Regulating Fine Particle Emissions                 53

         Introduction                                                   53
         Methods for Regulating Fine Particle Emissions                 56
         Basis for Emission Standards for Fine Particulates             58
            Plume Opacity Standards                                     60
            Minimum Collection Efficiency for Fine Particulates         62
            Mass-Emission Regulations                                   63
         Emission Standards Selected for Evaluation                     66

VII   Technological Implications of Fine Particle Emissions Regulations 68

         Introduction                                                   68
         Requirements for Control Equipment Efficiency                  68
         Capability of Control Technology                               71
            Capability of Existing Control Equipment                    71
            Emerging and New Control Technology                         74
         Summary of Status of Control Technology                        77
         Requirements for Compliance Testing and Monitoring             78
            Compliance Monitoring Methods for Plume Opacity             82
            Compliance  Monitoring Methods for Mass Emissions           85
         Summary of Recommended Compliance Monitoring Methods           92

VIII  Economic Impact of Fine Particle Emission Standards               93

         Introduction                                                   93
         Determination of Cost vs Efficiency Relationships for Control
            Devices                                                     94
         Methodology for Determining Costs Required for Compliance
            with Fine Particle Emission Standards                       98
            Development of Model Plants for Important Industrial
               Sources of Fine Particle Emissions                       98
            Determination of Control Device Performance Requirements    99
            Costs to Model Plant and Industry for Compliance with
               Specific Fine Particle Emission Standards               101
         Estimated Reductions in Fine Particle Emissions               130
         Economic Impact of Fine Particle Emission Standards on
            Selected Sources                                           133
               Example of Calculation of Economic Impact               135
               Control Costs in Selected Industries                    138

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                         CONTENTS  (Continued)
                                                                      Page

IX    Benefit/Cost Relationships for Fine Particulate Control          147

         Introduction                                                  147
         Determination of Economic Damage Attributable to a Specific
            Source                                                     147
               Computing the Impact Area                               149
               Control Costs                                           151
               Economic Damage                                         151
         Total Economic Damages                                        153
         Cost/Benefit Relationships                                    157

X     Overall Feasibility of Emission Standards Based on Particulate
         Size                                                          166

         Introduction                                                  166
         Feasibility of Specific Types of Standards                    166
               Opacity Regulations                                     167
               Regulation Based on Best Installed Control System       168
               Mass Emission Regulations                               168

XI    References                                                       170

XII   Glossary of Terms                                                178

XIII  Appendices                                                       180

         Appendix A - Control Technology for Fine Particles            180
         Appendix B - Example of Procedure for Determining Control     20,7
                         Costs for Compliance with Fine Particle       207
                         Emission  Standards
         Appendix C - Plume Opacity                                    213
                                   vi

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                                FIGURES

No.

 1      Relationship between particle mean residence time and
          particle size	18

 2      Effects of particulate air pollution in the community as
          related to particle size	

 3      Fraction of particles deposited in the three respiratory
          tract compartments as a function of particle diameter .  .  23

 4      Effect of irritants in major bronchi	28

 5      Effect of irritants in terminal bronchioles 	  28

 6      Effect of irritants in alveoli	28

 7      Meteorological visibility vs particle size, ferric
          sulfate aerosol	31
                                                        ^
 8      Meteorological visibility vs particle size, flyash
          aerosol	32

 9      plume opacity as a function of particle diameter and dust
          loading	61

10      Representative emission standards based on potential emis-
          sion rate	65

11      Extrapolated fractional efficiency of control devices ...  73

12      Forces operating on aerosol particles 	  75

13      Recommended manual method for monitoring compliance of
          sources with fine particle emission regulations 	  87

                                  vii

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                            FIGURES  (Concluded)

No.                                                                 Page

14      Semicontinuous  method for monitoring  fine  particle
          emissions	88

15      Schematic  diagram of monitoring system utilizing  quartz
          crystal  microbalance	90

16      Annualized cost for operation of high-voltage  electro-
          static precipitators	95

17      Installed  costs for control equipment 	 96

18      Annualized costs for control equipment	97

19      Interrelationships among factors affecting the economics
          of a firm	134

20      Structure  for microeconomic impact analysis	136

21      Simplified hemispherical pollutant dispersion  model  .  .  .  .150

22      Economic damage resulting from continuous  exposure to
          75 ug/m3 fine particulate concentration	156

23      Fine particulate control costs for 400-MW  coal-fired
          electric generating plant	159

24      Total annual economic costs of fine particulate control
          at various population densities . . ..,	  .164

25      Optimum fine particle control level at various population
          densities	165
                                   viii

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                                TABLES

No.                                                                 Page
        Estimates of Fine Particle Emissions as a Function of
          Emission Standard
        Effect of Control Criteria on Control Costs  in
          Selected Industries
        Total Annual Cost of Achieving BICD-Level Control  of
          Fine Particulates in Selected Industries
 4      Summary of Fine Particulate Control Costs at BICD-
          Level Control .....................     8

 5      Classification of Particulate Pollutants .........    17

 6      Major Industrial Sources of Particulate Pollution  ....    37
              >- ->
 7   ,,-,  Nonindustrial Sources of Particulate Pollution ......    38

 8      All iMa^or Sources of Particulate Pollution ........    39
     ' ;» i
 9      Fine Particle Emissions from Industrial Sources  .....    42
                • ,'*"' f v<"
10      Fine Particle Emissions from Mobile Sources  .......    45

11      Profile of the Characteristics of Particulate Pollutants
          Emitted by Various Industrial Sources  .........    47

12      Priority List for Sources of Fine Particle Emissions.  .  .    52

13   .  Estimated Concentrations of Los Angeles Aerosol
          Particles by Source  ..................    55
                                  ix

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                          TABLES (Continued)

No.                                                                   Page

14       Control  Device Efficiency Required to Achieve Various
           Plume  Opacity Levels ..................     70

15       Measurement and Monitoring Methods for Fine Particu-
           lates ..........................     79

16       Control  Equipment Costs for Coal-Fired Electric Utility
           Plants .........................    102

17       Incremental Annualized Costs for Coal-Fired Electric
           Utility Plants to Meet Fine Particle Emission Stand-
           ards ..........................    103

18       Control  Equipment Costs for Sinter Machine (Windbox) . .  .    105

19       Incremental Annualized Costs for Sinter Machines (Iron
           and Steel) to Meet Fine Particle Emission Standards. .  .    106

20       Control  Equipment Costs for Basic Oxygen Furnaces (Iron
           and Steel Plants) ....................    107

21       Incremental Annualized Costs for Basic Oxygen Furnaces
           to Meet Fine Particle Emission Standards ........
 24
 22      Control Equipment Costs for Electric Arc Furnaces (Iron
           and Steel Plants) ................  ....    110

 23      Incremental Annualized Costs for Electric Arc Furnaces
           to Meet Fine Particle Emission Standards ........    Ill
Control Equipment Costs for Cement Plant Rotary Kilns. .  .    112
 25      Incremental Annualized Costs for Cement Kilns to Meet
           Fine Particle Emission Standards 	    113

 26      Control Equipment Costs for Hot-Mix Asphalt Plant Rotary
           Dryers	    115

 27      Incremental Annualized Costs for Hot-Mix Asphalt Plant
           Rotary Dryers to' Meet Fine Particle Emission Stand-
           ards 	    116

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                            TABLES (Continued)

No.                                                                  Page

28      Control Equipment Costs for Ferroalloy Furnaces
          (Closed Electric Furnace) ................    117

29      Control Equipment Costs for Ferroalloy Furnaces
          (Hooded Open Electric Furnace) .............
30      Control Equipment Costs for Ferroalloy Furnaces
          (Unhooded Open Furnace) .................    H9

31      Control Equipment Costs for Rotary Lime Kilns .......    121

32      Incremental Annualized Costs for Rotary Lime Kilns to
          Meet Fine Particle Emission Standards ..........    122

33      Control Equipment Costs for Municipal Incinerators ....    123

34      Incremental Annualized Costs for Municipal Incinerators
          to Meet Fine Particle Emission Standards ........    124

35      Control Equipment Costs for Iron Foundry Cupolas  .....    125

36      Incremental Annualized Costs for Iron Foundry Cupolas to
          Meet Fine Particle Emission Standards ..........    126

37      Control Equipment Costs for Primary Aluminum-Electrolytic
          Cells .......... ................    128

38      Control Equipment Costs for Primary Copper Plants .....    129

39      Estimates of Fine Particle Emissions as a Function of
          Emission Standard ....................    131

40      Projections of Fine Particle Emissions from Industrial
          Sources .........................
41      Example of Economic Impact of Air Pollution Control
          Requirements on Electric Power Generating Costs .....    137

42      Typical Financial Characteristics of 400-MW Electric
          Generating  Plant  ....................    139
                                  xi

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                              TABLES  (Concluded)

No.                                                                Page

43      Estimated  Control Costs  for  400-MW Electric Generating
           Plant	140

44      Effect of  Control Costs  on Costs  of Electric  Power.  .  .  .   140

45      Effect of  Control Criteria on Control  Costs in Selected
           Industries	142

46      Total Annual Cost of Achieving BICD-Level  Control  of
           Fine Particulates in Selected Industries	143

47       Summary  of Fine Particulate  Control Costs  at  BICD-
           Level  Control	145

48      Unit Value of Output from Selected Industries	146

49      Estimated  Damages Resulting  from  Fine  Particle Pollu-
           tion at  an Ambient Concentration of  75 ug/m3	155

50      Comparison of Estimated Damages Resulting  from Fine
           Particle Pollution at Ambient Concentrations of  75
           and 60 ug/m3-	158

51      Extent of  Impact of Uncontrolled  Fine  Particle Emissions
           for 400-MW Coal-Fired Electric  Plant	   160

52      Economic Costs of Control and Damage Caused by Fine
           Particulate Emissions at Various Population Densi-
           ties and Control Efficiencies  	
 53       Economic Costs of Control and Damage Caused  by  Fine
           Particulate Emissions 	   162
                                 xii

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                        ACKNOWLEDGMENTS
This report was prepared by Midwest Research Institue, 425 Volker
Boulevard, Kansas City, Missouri  64110, under Contract No. 68-01-0428
with the Office of Research and Development of the Environmental
Protection Agency.  Mr. Howard Bergman and Mr. Paul Gerhardt were
EPA's Project Monitors.

The program was centered in MRI's Physical Sciences Division, Dr. H.M.
Hubbard, Director.  Dr. A.E. Vandegrift, Assistant Division Director,
served as Program Manager.  Dr. L. J. Shannon, Head, Environmental
Systems Section, served as the Principal Investigator for MRI.  Other
MRI staff members who contributed significantly to the program were
Mr. P.G. Gorman, Mr. W. Park, and Mr. T. Weast.
                               xiii

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                                 SECTION I
                                  SUMMARY

Particles smaller than 2 u (i.e., fine particulates) are a major factor
in air pollution, affecting both human health and the physical properties
of the atmosphere.  While the overall impact of fine particulate pollu-
tants on man's environment is not precisely quantified, evidence continues
to point to many negative features of fine particulate pollution.  Real-
izing the rapidly developing interest in all aspects of the fine par-
ticulate pollution problem, the Environmental Protection Agency through
its Standards Research Branch contracted with Midwest Research Institute
to perform a study to assess the technical and economic feasibility of
particulate emission standards based on particle size.

The effort in the current program was directed to an analysis of the tech-
nical and economic feasibility of various general bases for emission
standards for fine particulates.  In practice, the diversity of both the
sources and particulate pollutants emitted from various sources will un-
doubtedly rule out the use of a general emission standard for all sources.
However, while the current study is broad in scope, the results have in-
dicated the general feasibility of fine particulate control and the areas
for future research and development activity have been pinpointed.

GOAL(S) FOR PROGRAM TO CONTROL FINE PARTICULATES

Definition of the size of particulates that must be controlled is the
first step in formulating a program to reduce the emission of fine par-
ticulates.  If the aerosol burden in the urban atmosphere is to be re-
duced, a premium must be placed on the collection of particles smaller
than 5 u.  If improved visibility is the goal of fine particulate control,
attention must be focused on particle collection in the 0.1-1.0 u range.
Concern for adverse health effects should direct attention to the control
of the 0.01-7 u size range and to the potentially hazardous constituents
(e.g., lead, cadmium, mercury) of the effluent stream.  Because protection
of human health is the main justification for launching a program to con-
trol fine particulates, the particle size range below 7 u is the general
size range of interest.  Currently available control equipment for par-
ticulate pollutants exhibit good collection efficiency down to a particle

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size of approximately  2 u.   Below  this  particle  size, collection efficiency
for most equipment decreases rapidly.   Therefore, particles less than 2 u
in diameter are of most interest for  future  control activities for partic-
ulate pollutants.

APPROACHES FOR REGULATION OF FINE  PARTICULATE  EMISSIONS

Approaches that could  be  used to regulate  fine particulate emissions in-
clude:  (1) emission standards;  (2) tax incentives; (3) process modifica-
tions;  (4) substitution of ingredients  or  fuels;  and  (5)  cessation of
processing operations  that emit  fine  particles.   The  last alternative is
deemed  untenable  except in very  special situations.   The  other alterna-
tives are viable, although methods (3)  and (4) are  limited in the extent
to which they can be used.   A precedent exists for  utilizing emission
standards as  the  main  method of  control of fine  particulate emissions in
the near term.  Current programs for  the control of particulate pollutants
rely on emission  standards,  and minimum disruption  in control agency
activities would  occur if similar  approaches were used for fine particu-
lates.  However,  the unavailability of  high efficiency control equipment
and adequate  source  compliance monitoring  methods and/or  instrumentation
may limit the utility  of  emission  standards—especially if fine particu-
lates must be controlled  to a very high degree.   Alternative regulatory
strategies based  on  tax incentives might be  attractive in that event.
Effluent charges  or  fees  for the discharge of  fine  particulates is one
definite possibility.  The acquisition  of  the  information necessary to
structure an  effective and equitable  effluent  tax will require extensive
characterization  of  both  sources and  pollutants.  While additional data
are being obtained to  further the  formulation  of intermediate and long-
term strategies for  the control  of fine particulates, near-term activities
could be initiated using  emission  standards.                lirlii W

Emission standards for the control of fine particulate emissions from in-
dustrial sources  may be based on factors such  as:   (1) limitation of the
concentration of  fine  particulates in an effluent stream; (2) specifica-
tion of the required collection efficiency of  control equipment in given
particle size ranges;  (3)  reduction in  plume opacity; and (4) limitations
of the  mass emission rate of fine  particulates.   Our analysis (see
Chapter 4) of the alternative routes  for emission standards for fine par-
ticulates led to  the following conclusions;

1.  The use of emission standards  based on plume  opacity  is a practical
means for reducing fine particulate emissions  in the near term,

2.  An  emission standard  based on  the requirement of the  installation of
the best installed technology on  all sources  in a  specific source cate-
gory could be implemented in either the near-  or  intermediate-term, and

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3.  A mass emission regulation based on the potential emission rate con-
cept is a very attractive approach for the long term.

Emission standards based on plume opacity would require the least amount
of additional data acquisition and they would readily interface with exist-
ing programs for control of particulate pollutants.  An emission standard
requiring the installation of the best installed technology would represent
the attainment of the current practical limit of control equipment per-
formance.  Regulations based on the potential emission rate concept would
establish emission limits which vary with the pollution potential of the
source, e.g., limitation of mass rate of fine particulate emissions in
pounds per hour as a function of potential emission rate, also pounds per
hour.  A regulation of this type could be tailored to the control of
specific sources or specific constituents of a particulate effluent
stream.  The existing data base on potential emission rates of fine par-
ticulates is clearly inadequate for the intelligent selection of allow-
able emission rates.  An extensive data acquisition program will be re-
quired to obtain the needed emission rate data before viable standards
based on potential emission rate can be developed.

TECHNICAL IMPLICATIONS OF EMISSION STANDARDS

An analysis of the technical implications of emission standards requiring
107o and 5% plume opacity indicated that currently available control equip-
ment could achieve the required overall collection efficiency.  Trans-
missometers are also available to permit instrumental evaluation of plume
opacity.  An emission standard based on installation of the best installed
technology obviously stretches current technology to near its limit.  Only
manual methods are currently available for monitoring compliance of sources
with a regulation of this type.

Substantial reductions in fine particulate emissions could be achieved by
either opacity standards or the installation of best installed technology.
Table 1 presents estimates of emission reductions that might be achieved.
The estimated reductions in emissions shown in Table 1 assume that the
control equipment is in operation 10070 of the time that a source is operat-
ing.  This is seldom the case, but accurate data are generally not avail-
able on the reliability of control equipment.  The reliability of control
equipment will have to be improved if efforts to control fine particulates
are to be successful.

Another area in which improvement will be necessary  in order to achieve
control of fine particulates is the capture efficiency of hooding  systems
that are associated with many installations of control devices.  Capture

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                                        Table 1.  ESTIMATES OF FINE PARTICLE EMISSIONS AS A FUNCTION OF EMISSION STANDARD
Estimated Fine Particle Emissions
Uncontrolled

I.
II.



III.
IV.
V.





VI.
VII.
VIII.
Source
Coal combustion
Iron and steel
A. Sinter machines
B. Basic oxygen furnace
C. Electric arc furnace
Cement plants, rotary kilns
Asphalt plants, dryers
Ferroalloy plants
A. Closed electric furnace
B. Hooded open electric
furnace
C. Unhooded open electric
furnace
Lime plants, rotary kilns
Municipal incinerators
Iron foundry, cupola
Lb/Hr
796,000

7,100
400,000
27,400
243,000
3,260,000

92,000

129,500

72,000
75,800
15,000
22,900
Ton/Year
3,184,000

28,400
1,600,000
109,600
972,000
1,956,000

368,000

518,000

288,000
303,200
37,500
22,900
Present
Lb/Hr
243,000

1,400
43,600
3,600
44,300
257,000

11,300

84,100

60,800
22,000
13,100
13,100
Ton/Year
972,000
,
5,600
174,400
14,400
177,200
154,200

45,200

336,400

243,200
88,000
32,800
13,100
BICD Standard^./
Lb/Hr
15,000

64
2,560
645
2,000
25,600

11,300

15,800

28,800
1,200
490
356
Ton/Year
60,000

256
10,240
2,580
8,000
15,360

45,200

63,200

115,200
4,800
1,225
356
10% Opacity Standard 5% Opacity Standard
Lb/Hr
5,050

722
1,540
1,036
25,200
200,000

NC£/

NC

NC
10,500
3,400
5,900
Ton/Year Lb/Hr
20,200 2,510

2,888 354
6,160 800
4,144 683
100,800 12,200
120,000 167,000

NC NC

NC NC

NC NC
42,000 4,800
8,500 1,900
5,900 4,000
Ton/Year
10,040

1,416
3,200
2,732
48,800
100,200

NC

NC

NC
19,200
4,750
4,000
a/  Not calculated.
b_l  BICD-Best installed  control' device  (not  necessarily  the highest efficiency device available, but rather the best  that is generally being  installed
      at present  time).

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efficiency of hood systems that are necessary for many sources is fre-
quently estimated to be less than 95%.  If the control device efficiency
is in excess of 997o, the particulate matter which escapes the hooding
system becomes very significant.

ECONOMIC IMPACT OF EMISSION  STANDARDS

Requirements for a given level of fine particulate control from stationary
sources may have significant economic impacts on an industry, with the ex-
tent of the impact depending on the characteristics of the industrial pro-
cesses involved and on the specific control equipment requirements.

The additional production costs incurred as a result of control practices
will include both operating costs and capital charges, again depending on
the type of control equipment installed.  These costs have been estimated
for a variety of industries, with capital charges computed at four dif-
ferent rates to reflect differences in equipment life, depreciation policies,
and accounting procedures.  In this study estimates of control costs and
the resultant impact on production costs were determined for emission
standards requiring the achievement of 107e or 57, plume opacity and the
installation of best demonstrated technology.  Tables 2 to 4 summarize
the estimated costs for selected industrial sources.  The estimates shown
in Table 4 indicate a widely varying  impact among the industry studied.
In most cases, installation of the best installed technology will have
relatively minor effects on overall production costs, generally amounting
to less than 1.0% of the value of the product produced.

BENEFIT/COST RELATIONSHIPS FOR FINE PARTICULATE CONTROL

To assure the optimum utilization of economic resources, the costs of par-
ticulate control must be weighed against the benefits realized by having
reduced the fine particulate emissions.  The economic damages resulting
from uncontrolled and controlled fine particulate emissions were investi-
gated, although insufficient data are available to draw any definite con-
clusions.  When adequate data become  available through additional research,
it will be possible to define the optimum control strategy for any given
set of conditions.

For illustrative purposes, the economic losses attributable to interactions
between fine particulates at ambient  concentrations of 75 and 60 ug/m^,
and humans, animals, vegetation, materials and aesthetics, were estimated.
The estimates were based on the area  over which exposure takes place, and
on the economic values exposed to damage.

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Table 2.  EFFECT OF CONTROL CRITERIA ON CONTROL COSTS  IN  SELECTED  INDUSTRIES
Source
Coal-fired electric plant
Municipal Incinerator
Cement plant (rotary kiln)
Asphalt plant (rotary dryers)
Iron and steel
(a) Basic oxygen furnace
(b) Electric arc furnace
(c) Sintering (windbox)
Lime plant (rotary kiln)
Iron foundry cupola
Control Fine Particle
Model Plant Total Annual Control Cost ($1,000)
Annual Production at Specified Capital Charge Rate
Criteria Control Efficiency (%) Rate 0.15
BICD
107. Opacity
57. Opacity
BICD
10% Opacity
57. Opacity
BICD
107. Opacity
57. Opacity
BICD
107. Opacity
57. Opacity
BICD
107. Opacity
57. Opacity
BICD
107. Opacity
57. Opacity
BICD
107. Opacity
57. Opacity
BICD
107. Opacity
57. Opacity
BICD
10% Opacity
5% Opacity
98.13
99.36
99.68
96.71
77.41
87.50
99.17
89.58
94.94
99.21
92.86
94.05
99.70
99.82
99.91
97.64
93.54
97.24
99.10
87.76
94.05
98.43
78.04
90.59
98.46
74.29
82.86
2.4 x 109 kwh 241.5
320.0
378.5
80,000 tons 35.5
25.3
29.8
3.0 x 106 bbls 125.1
89.2
98.1
90, 000. tons 13.3
20.9
31.2
1.0 x 106 tons 211.0
227.0
255.0
100,000 tons 50.1
36.1
42.2
1.46 x 106 tons ' 277.0
184.5
204.5
87,500 tons 17.5
41.6
63.4
10,000 tons 15.1
23.8
34.5
0.17
262.1
348.0
409.9
38.9
27.6
32.5
134.3
98.1
107.7
14.3
21.3
31.8
230.2 ,
247.0
274.2
53.7
39.3
46.3
297.0
199.9
221.5
18.9
42.4
64.6
16.3
24.3
35.2
0.20
293.0
390.0
457.0
44.0
31.1
36.6
148.2
111.4
122.1
15.9
22.0
32.7
259.0
277.0
303.0
59.2
44.1
52.4
327.0
223.0
247.0
21.0
43.7
66.3
18.1
25.2
36.3
0.30
396.0
530.0
614.0
61.0
42.7
50.2
194.4
155.8
170.2
21.2
24.1
35.6
355.0
377.0
399.0
77.4
60.2
72.8
427.0
300.0
332.0
28.0
47.9
72.1
24.2
27.9
39.7

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                Table 3.  TOTAL ANNUAL COST OF ACHIEVING  BICDl/-LEVEL CONTROL OF FINE PARTICULATES IN SELECTED INDUSTRIES

Source
Coal-fired electric plant
Municipal incinerator
Cement plant (rotary kiln)

Model Plant
Production
Rate/Year
2.4 x 109 kwh
80,000 tons
3.0 x 106 bbls
Total
Annual Control Cost for
Model Plant at Specified
Capital Charge Rate ($1,000)
0.15
241.5
35.5
125.1
0.17
262.1
38.9
134.3
0.20
293.0
44.0
148.2
0.30
396.0
61.0
194.4
Total Annual
Industry
Production
516 x 109 kwh
18 x 106 tons
400 x 106 bbls
Total
Annual Control Cost for
Industry at Specified Capital
Charge Rate ($106)
0.15
51.9
8.0
16.7
0.17
56.4
8.8
17.9
0.20
63.0
9.9
19.8
0.30
85. L
13.7
25.9
Asphalt plant (rotary
  dryers)

Iron and steel
  (a) Basic oxygen furnace

  (b) Electric arc furnace

  (c) Sintering (windbox)

Ferroalloy
  (a) Unhooded open electric
        furnace

  (b) Hooded open electric
        furnace

  (c) Closed electric
        furnace

Lime plant (rotary kiln)

Iron foundry cupola
90,000 tons


1.0 x 10*> tons

100,000 tons

1.46 x 106 tons



8,000 tons


10,800 tons


13,600 tons

87,500 tons

10,000 tons
 13.3
14.3
15.9     21.2    350 x 10$ tons
211.0    230.2    259.0    355.0    50 x 106 tons

 50.1     53.7     59.2     77.4    21.5 x 10$ tons

277.0    297.0    327.0    427.0    54 x 10$ tons



205.5    220.5    243.0    318.0    600,000 tons


 51.4     55.2     60.8     79.6    1.08 x 106 tons


  3.8      4.1      4.5      6.0    820,000 tons

 17.5     18.9     21.0     28.0    18.5 x 106 tons

 15.1     16.3     18.1     24.2    13.1 x 10& tons
51.7    55.6    61.8    82.4


10.6    11.5    13.0    17.8

10.8    11.5    12.7    16.6

10.2    11.0    12.1    15.8



15.4    16.5    18.2    23.9


 5.1     5.5     6.1     8.0


 0.2     0.2     0.3     0.4

 3.7     4.0     4.4     5.9

19.8    21.4    23.7    31.7
a/  See footnote (b), Table 1, for definition of BICD.

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                                          Table 4.  SUMMARY OF FINE  PARTICULATE CONTROL  COSTS AT  BICD-LEVEL CONTROL
                                                                           ($/Unit of  Production)
oo
Source
Coal-fired electric plant
Municipal incinerator
Cement plant (rotary kiln)
Asphalt plant (rotary dryers)
Iron and steel
(a) Basic oxygen furnace
(b) Electric arc furnace
(c) Sintering (windbox)
Ferroalloy
(a) Unhooded open electric furnace
(b) Hooded open electric furnace
(c) Closed electric furnace
Lime plant (rotary kiln)
Iron foundry cupola
Primary aluminum (electrolytic cells)
Primary copper
Annual Produc-
tion Rate for
Model Plant
2.4 x 109 kwh
80,000 tons
3.0 x 106 bbls
90,000 tons
1.0 x 106 tons
100,000 tons
1.46 x 10*> tons
8,000 tons
10,800 tons
13,600 tons
87,500 tons
10,000 tons
3,000 tons
76,000 tons
Fine
Particle
Control
Efficiency
98.13
96.71
99.17
99.21
99.70
97.64
99.10
60.00
87.80
97.52
98.43
98.46
94.85
98.85
Capital Charge Rate
0.15
0.00010
0.444
0.042
0.147
0.211
0.501
0.190
25.688
4.759
0.276
0.200
1.512
6.52
1.455
0.17
0.00011
0.486
0.045
0.159
0.230
0.537
0.203
27.563
5.107
0.298
0.216
1.613
6.99
1.595
0.20
0.00012
0.550
0.049
0.177
0.259
0.592
0.224
30.375
5.630
0.331
0.240
1.814
7.71
1.805
0.30
0.00017
0.763
0.065
0.236
0.355
0.774
0.292
39.750
7.370
0.441
0.320
2.418
10.08
2.505

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The most important variable is population density.  Total economic losses
attributable to sustained exposure at the prescribed concentrations range
from about $5,000/mile2 in sparsely populated rural areas, to well over
$1 million/mile^ in densely populated urban locations, with per capita
costs ranging from over $500 to less than $30, depending on the char-
acteristics of the area in question.

The control efficiency at which the total of control costs and the costs
of remaining damages is a minimum identifies the optimum control level;
this is also the point at which incremental control costs equal the incre-
mental benefits of control.  A low population density will have a relatively
low minimum net cost and will require a relatively low control efficiency.
Densely populated areas will experience much higher damage costs, and there-
fore justify much higher control efficiencies.

The effectiveness of any program for the control of fine particulate emis-
sions must ultimately be judged by improvements in ambient air quality.
Because both atmospheric conversion processes (chemical and physical) and
sedimentation contribute to the fine particulate burden (in the atmosphere,
it may be' difficult to relate atmospheric levels of fine particulates to
control activities on specific sources.  For example, in Los Angeles, about
35% of the ambient particulate burden is formed in the atmosphere from
gaseous pollutants.  In a city like Los Angeles, reductions in emissions
of fine particulates from stationary sources would not result in a propor-
tionate decrease in ambient fine particulate concentration.  As a conse-
quence, development  of  meaningful benefit/cost relationships  for fine
particulate control may be quite difficult in some urban locations.  While
the assessment of the overall effectiveness of control efforts may be dif-
ficult, the total burden of fine particulates entering the atmosphere would
nonetheless be reduced by direct limitation of source emissions.

OVERALL FEASIBILITY OF EMISSION STANDARDS BASED ON PARTICLE SIZE

Our analysis of the implications of emission standards based on particle
size has identified some technical deficiencies that will limit the type
of standards that can be proposed and implemented in the near future.
However, because the technical deficiencies relate primarily to the lack
of data on particle size distributions of effluents and control equipment
fractional efficiency, there appear to be no insurmountable technical ob-
stacles to emission standards based on particle size.

Although our analysis of various formats for emission standards based on
particle size was performed in the context of general regulations that
.might be applied uniformly to all sources, a more realistic approach would

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be to tailor the emission  standard  to  specific  sources of  fine particulate
pollutants.  Tailoring  of  standards would  permit a greater degree of flexi-
bility in an overall  control  plan for  fine particulates, and would acknowl-
edge the differences  in the importance and difficulty of control of in-
dividual sources.

The exact format of the emission standard(s)  that could be proposed and
implemented  for  specific sources will  be  limited by:   (1)  collection ef-
ficiency ixx  fine particle  size range of available control  equipment; and
(2) availability of source compliance  monitoring techniques.

The economic impact of  fine particulate control was  found  to vary sub-
stantially from  industry to industry.   Estimates of  costs  associated with
the control  of fine particulates varied from less than 1.0% up to 20% of
                                                         ,-r
the value of the product.   The variation  in  economic impact suggests that
it may be necessary  to consider less  restrictive standards for industries
that experience  a  significant adverse  economic  impact.

Because our  understanding  of  the damages  resulting from fine particulate
pollutants is  far  from  complete, definitive  statements regarding the bene-
fits that would  accrue  from improved  control of fine particulate emissions
cannot be made at  this time.   In view  of our  lack of  knowledge of benefits
resulting from control  activities,  it  seems  prudent  to consider a long-
range  strategy based  on the adoption  and  implementation of progressively
more stringent regulations for the  control of fine particulates.  Each
step toward  more  effective control  of  fine particulates would be based
upon improved  knowledge of:   (1) the  effects of fine particulates on human
health and welfare;  (2) the technical  and economic impact  of the more
stringent regulations;  and (3) the  benefits  that would accrue to society
from a further decrease in fine particulate  pollution.
                                   10

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                                SECTION II
                      RECOMMENDATIONS FOR FUTURE WORK
INTRODUCTION
The existing information base in nearly every aspect of the fine particu-
late pollution problem is inadequate.  Research or data acquisition programs
should be formulated and undertaken in several areas, especially:  (1)
Source Sampling and Monitoring Methods; (2) Fine Particle Emission Rates;
(3) Control Technology Evaluation and Development; (4) Analysis of Relation-
ships Between Fine Particle Emissions and Ambient Air Quality; (5) Economic
Impact Analysis; and (6) Cost/Benefit Analysis.  Specific programs in each
of the above categories are delineated in the following sections.

SOURCE SAMPLING AND MONITORING METHODS

Current capability to sample, size and monitor particulate emissions from
stationary sources is inadequate.  Research should be initiated to improve
this capability.  Specific areas of recommended research are:

1.  Laboratory and field evaluations of promising methods for the measure-
ment of the concentration and particle size distribution of particulates
smaller than about 5 um.  Methods that should be evaluated include im-
pactors, cyclones,  beta-tape devices, and piezoelectric crystal devices.

2.  Evaluation of optical techniques for monitoring fine particle emis-
sions.  Attention should be directed to a comprehensive evaluation of the
performance of on-stack transmissometers on a variety of industrial sources.
       •
FINE PARTICLE EMISSION RATES

Emission factors for fine particulates are nearly nonexistent at the pres-
ent time.  Source testing programs shall be initiated to gather data on:

1.  Rates of emission of particulates in the fine particle size range--
nominally less than 2 um.
                                 11

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2.  Chemical composition  of  particles  and  carrier gas emitted from sta-
tionary sources.  Emphasis should  be placed  on  trace metals and potentially
hazardous compounds.

A portion of this recommended  research could be conducted in conjunction
with the programs outlined in  the  preceding  section.  However, because ex-
perience has generally  shown that  no single  sizing device is suitable for
all the sampling  circumstances encountered in a wide variety of stationary
emission sources, individual testing programs may have  to be developed for
specific classes  of sources.

CONTROL TECHNOLOGY  EVALUATION

The ability of  currently  available control equipment to collect fine par-
ticulates is ill-defined.  Programs should be developed to obtain basic
performance data  on particulate control equipment as a  function of particle
size.  Emphasis should  be placed on measuring collection efficiencies in
the fine particle size  range.   These programs should be interfaced with
those  outlined  in the preceding sections so  that the best measuring tech-
niques are utilized.

CONTROL TECHNOLOGY  DEVELOPMENT

Presently available information indicates  that  existing control equipment
may not be adequate for the  collection of  fine  particulates from many in-
dustrial sources.   Research  and development  programs should be formulated
to foster new control technology for fine  particulates.  Attention should
be focused in the following:areas:

1.  Field evaluation of new  or novel and emerging control technology.

2.  Laboratory  and  field  evaluation of particle conditioning processes
which  increase  the  effective size  of particles  and thus makes them less
difficult to 'capture.

3.  Research on methods to improve the performance of existing control
equipment.

ANALYSIS OF RELATIONSHIPS BETWEEN  SOURCE EMISSIONS AND  AMBIENT AIR QUALITY

The effectiveness of any  program for the control of fine particulate emis-
sions  will be judged primarily by   improvements  in ambient  air quality.
Unfortunately,  the  fine  particulate pollution  problem  is only partly a
                                12

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primary particle emission problem.  Secondary conversion processes may con-
tribute significantly to the fine participate burden in some areas.  Because
of the influence of atmospheric conversion processes and sedimentation on
the fine particulate burden, in the atmosphere, it may be difficult to relate
atmospheric fine particulate levels to control activities on specific sources.

Additional research on methods to relate air quality to emission sources is
highly recommended.  Priority should be given to studies for urban and in-
dustrial regions with a high density of fine particulate sources with dif-
fering source characteristics.

ECONOMIC IMPACT ANALYSIS

More refined analysis of the economic impact of fine particulate emission
standards should be conducted.  One phase of this research activity should
focus on the acquisition of more detailed data on the costs of high effi-
ciency control equipment.  Costs of particulate control equipment vary
widely.  The costs cover a range of values because of local conditions and
the nature of the particles, the gas stream, equipment size (gas volume),
and design collection efficiency.  Published average cost figures frequently
do not reflect all cost components and fail to illustrate the great range
in costs.

Future economic impact analysis should focus on definite urban or industrial
regions.  If possible the analysis should include consideration of factors
such as changes in industry structure, price elasticity in specific industries,
and number of potential plant closings.

COST/BENEFIT ANALYSIS

A more refined analysis of the trade-offs between costs and benefits as-
sociated with emission standards based on particle size should be per-
formed.  A major part of this activity should be directed to the quantifi-
cation of the effects of fine particulates on various receptors.  At the
present time, the lack of data on the damages associated with fine partic-
ulate pollution hampers efforts at meaningful cost/benefit analysis.
                               13

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                                SECTION III
                                INTRODUCTION

When air pollution became  a major  concern in the  late 1950's and early
1960's, particulate pollutants  from industrial processes were among the
first to receive  attention and  to  be controlled.  While we have succeeded
in removing the black  cloud from the smoke stack  and with it the major
fraction of mass  emitted from industrial  processes, we have not been nearly
as successful  in  eliminating  the particulates which cause the major adverse
effects—the particulates  below about 2 urn in size (i.e., fine particulates)

Fine particulates resulting frdfo man's activity contribute significantly
to all the major  adverse aspects of air pollution.  Fine particles ban
initiate or contribute to  problems related to human health, changes in
atmospheric physical properties, and materials soiling and damage.  The
effects of particulate matter on human health are, for the most part, re-
lated to injury to the surfaces of the respiratory system.  Particulate
material  in the  respiratory  system may produce injury itself, or it may
act in conjunction with gases,  producing  synergistic effects.  Such injury
may be permanent  or temporary.  It may be confined to the surface, or it
may extend beyond, sometimes  producing functional or other alterations.

Fine particulate  pollutants also affect the  physical properties of the
atmosphere.  The  chemical  and physical properties of the atmosphere af-
fected include:   its electrical properties;  its ability to transmit radiant
energy; its ability to convert  water vapor to fog, cloud, rain, and snow;
its ability to damage  and  to  soil  surfaces..   Concern with atmospheric
transmission of radiant energy  encompasses the entire electromagnetic
spectrum, but  of  particular concern is the infrared region, as it affects
the terrestrial heat balance; the  ultraviolet region, as it affects both
biological processes and photochemical reactions  in the atmosphere; and
the visible spectrum,  as it affects both  our ability to see things, and
our need for artificial illumination.
                                 14

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As man has become more knowledgeable about his environment, he has also
become increasingly aware of the importance to his well-being of the action
of fine particles.  This awareness has resulted in increased attention
being focused on fine particulate pollutants by both governmental and
scientific groups.  Regulations for the control of fine particle emissions
from industrial sources are being considered by both federal and state
pollution control agencies.

The Standards Research Branch, Implementation Research Division, Environ-
mental Protection Agency, realizing the developing interest in controlling
the emission of fine particulate pollutants from industrial operations,
initiated a program with Midwest Research Institute (MRI) to conduct a
study to define the technical and economic feasibility of particulate
emission standards based on particle size.  The program was divided into
four major areas of effort:

1.  Analysis of approaches for regulating fine particle  emissions from
stationary sources.

2.  Definition of technological and economic requirements necessary for
implementation of emission standards.

3.  Identification of benefits that would accrue if control procedures
for fine particulates can be implemented.

4.  Assessment of overall feasibility of implementation of fine particle
emission standards.

In the following chapters of this report we present a discussion of the
nature of fine particulate pollution, a description of the major stationary
sources of fine particle emissions, and the results of activities in the
four major areas of effort delineated in the previous paragraph.  Chapter 2
presents a discussion of the role of fine particles in air pollution,
while Chapter 3 contains a description of the major stationary sources of
fine particle emissions.  Chapters 2 and 3 are included in the report in
order to acquaint £he reader with the nature,  magnitude, and sources of
fine particulate pollution.  Chapter 4 presents our analysis of approaches
for regulating fine particle emissions.  The technological and economic
implications of fine particle control are presented in Chapters 5 and 6.
A general discussion of potential benefits from the control of fine par-
ticle emissions is given in Chapter 7.  Our assessment of the overall
feasibility of emission standards for fine particles and recommendations
for future work are given in Chapters 8 and 9.
                              15

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                                 SECTION  IV
                  ROLE OF FINE PARTICLES IN AIR POLLUTION
INTRODUCTION
Particulate pollutants resulting from man's activity are chemically and
physically a most diverse class of substances.  They are variously de-
scribed as grit, dust, fume, smoke, aerosol or smog.  The meanings gen-
erally given to these terms are listed in Table 5.V  In this report the
term particulate pollutant is used to mean any dispersed matter, solid
or liquid, in which the individual aggregates are larger than single
small molecules (about 0.0002 um in diameter), but smaller than about
500 um.  This is the same definition used in the document, Air Quality
Criteria for Particulate Matter.—/

Particulate pollutants may remain suspended in the atmosphere for times
ranging from a few minutes to many hours.  Particulate removal from the
atmosphere occurs by diffusion, sedimentation, capture by cloud droplets
and scrubbing by precipitation.  In the absence of precipitation, sedi-
mentation dominates and the removal of airborne particles from the
atmosphere depends upon the aerodynamic particle size of the particles.
Figure 1 presents a relationship between particle size (aerodynamic) and
the mean residence time for particles in the atmosphere in the absence
of precipitation.3/  As shown in Figure 1, particles in the range of 10 um
to 1 um have mean residence times of 10-100 hr, while the mean residence
time of submicron particles is on the order of 102-lcPhr.

A profile of the effects of particulate air pollution in the community is
presented in Figure 2.  The effects are all related to particle size.
Comparison of Figures 1 and 2 indicates that with the exception of soiling
or damage of horizontal surfaces, the particles with residence times ex-
ceeding 100 hr (i.e., fine particulates) play the most important role.

The overall impact of fine particulate pollutants, broadly defined as
particles less than 2 um in size, on man's environment is not well known.
                                16

-------
           Table 5.  CLASSIFICATION OF PARTICULATE POLLUTANTS^
                                                 I/
Grit:


Dust:


Fume:

Mist:

Fogs:


Smoke:
Smog:
Soot:
Aerosols:
Coarse particles, greater than 76 um which is the  size  of  the
  opening in the 200 mesh sieve.

Particles smaller than 76 um  (i.e., able to pass through a 200
  mesh sieve) and larger than 1 um.

Solid particles smaller than  1 um.

Liquid particles, generally smaller than 10 um.

Mists are sometimes called fogs when they are sufficiently
  dense to obscure vision.

This is the term used generally to describe the waste products
  from combustion, and may either be fly ash or the products
  of incomplete combustion, or both.  The particles can be
  liquid or solid.

A term--a combination of smoke and fog—used to describe any
  objectionable air pollution.  There are two kinds, known as
  the Los Angeles and the London type.   The Los Angeles smog
  is photo-chemical and comes from motor car exhausts.  The
  London type comes from the incomplete combustion of coal and
  is characterized by its relatively high sulphur dioxide con-
  centration and particle content.

Soot is the aggregated particles of unburned carbon produced
  by incomplete combustion.

Initially this term was used for the fine relatively stable
  aerial suspensions.  In recent years the term has been
  generally applied to all airborne suspensions.
                                  17

-------
? 102  ~
 0)
 0)
 u
 c
 01
 c
 o
 u
   10
   10°
                                                       Limit of Residence Time
                    i   i  i  i i  i i I
.   ..... .1
     1  —
      10-
                                    Particle Size, de (u,m)
•Figure  1.   Relationship between particle mean residence time  and particle

                                       size^/

-------
10
 c
 i
J
                     Atmospheric
                     Electricity
                     Atmospheric
                     Visibility	
                     Condensation
                     Nuclei for Precipitation
                     Soiling Phenomena
                     (Horizontal Surfaces)
Upper Respiratory
Tract Deposition in Man
                     Peripheral Airways and
                     Alveolar Deposition-Man
                     Soiling Phenomena
                     (Vertical Surfaces)
                     Mmospneric
                     Chemistry (Gas-Solid)
                                         Y/////////////A
                                    	w//,
                                                             Particles Comprising//
                                                            /Main Aerosol.Mass
                                           10-
                                     ID'3
io-'
   10'1         10°
Particle Diameter - u.\
                                                                                   10'
102
           Figure 2.   Effects of  particulate atr pollution  in the community as related  to particle  sizeV

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However, evidence  continues  to  point  to  the many negative aspects of fine
particle pollution.   Research on health  effects of  air pollution indicate
links between  fine particulate  pollution and health effects of varying
severity.   In  addition to  particle size,  the chemical composition of par-
ticulates  is an important  factor in determining the effects of this type
of air  pollution.  For example,  the health hazard associated with inhaled
airborne particles depends on:   (1) the  site of deposition in the respi-
ratory  tract,  which  is determined by  particle  size;  and  (2) the effect on
biological tissues at the  deposition  site, which depends on chemical com-
position.   The hazardous pollutant problem (e.g., mercury, lead, cadmium,
vanadium)  is also  directly linked to  fine particle  pollution because many
of the  industrial  processes  that emit hazardous pollutants liberate them
in the  form of micron or submicron particles.  On both a regional and
global  scale>  fine particulate  pollutants play a principal role in the
transport  through  the air  of a  variety of hazardous substances.  It is
emphasized that the  hazards  posed to  human health by trace amounts of
toxic materials in the form  of  fine particulates can be disproportionate
to the  mass involved.

Suspended  fine particles may have considerable influence on the behavior
of the  atmosphere  and thus on human activities.  Fine particles in the
atmosphere absorb  and scatter light,  decrease  visibility, influence solar
radiation, and interfere with astronomical observations.

The  role of fine particles in air pollution  is presented in more detail
in the  following sections.  Health effects will be  discussed first, fol-
lowed by a review  of the effects on the  physical properties of the
atmosphere.

EFFECTS OF FINE PARTICULATES ON HUMAN HEALTH

Humans  as  biological organisms  with varying  degrees of resistance and
adaptive capacity  continuously  struggle  with an essentially hostile en-
vironment. Anything lowering the resistance of man or increasing the
hostility  of the environment, decreases  his  ability to adapt.  A number
of studies have shown that children and  marginal people with poor adap-
tive ability because of serious lung  disease,  heart disease, asthma,
or other serious chronic diseases, have  increased respiratory illness
and  cardiac and respiratory  deaih rates  parallel to the rise in pollution
levels. Thus, at  every level of pollution and not  at some defined thresh-
old, depending on  the adaptive  reserve of individuals, someone becomes
sick and someone's life is shortened.
                                20

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Any attempt to understand the relationship between air pollutants and human
health requires the integration of many diverse factors.  The dynamics of
small particles, respiratory system and lung dynamics, mechanisms of respi-
ratory and lung disease, area of residence (i.e., urban vs rural), occupa-
tion, smoking habits, and age are among the more important elements that
dictate the influence of air pollutants on human health.  An extensive
body of literature exists on the subject, and only a brief review of a
small segment of the literature will be presented, to orient the reader.

Deposition, Retention, and Clearance Processes in the Respiratory System

Laboratory studies of man and other animals show clearly that the deposi-
tion, clearance, and retention of inhaled particles is a very complex
process, which  is only beginning to be understood.  Understanding of these
phenomena requires knowledge of the following:

1.  Mechanisms  and efficiencies of particle deposition in the respiratory
system,

2.  Retention mechanisms,

3.  Clearance mechanisms, and

4.  Secondary relocation to other sites in the body.

The physical forces which operate to bring about aerosol deposition within
the respiratory system vary in magnitude not only with particle size, but
also with the air velocities and times of transit of the air from place to
place within the system and from moment to moment throughout the breathing
cycle.  Three mechanisms are of importance in the deposition of particulate
matter  in  the respiratory tract:

1. Inertial impaction - greatest importance in deposition of large parti-
cles of high density, and at points in the respiratory system where the
direction of flow changes at branching points in the airways,

2.  Gravitational settling  (sedimentation) - most important in the deposi-
tion of large particles or of high-density particles such as dusts of
heavy metals, and

3.  Diffusion  (Brownian motion) - major mechanism for the deposition of
small particles (below 0.1 urn) in the lower pulmonary tract.

The effectiveness with which the deposition forces remove particles from
the air at various sites depends upon the obstruction encountered, changes
                                 21

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in direction of air  flow,  and  the magnitude of particle displacement
necessary to remove  them from  the air  stream.  The anatomical arrangement
and physical dimensions  of the respiratory system, transport mechanisms,
flow rates and gas mixing,  and aerosol particle  size are important factors
that must be considered  in any physical analysis of the deposition of in-
haled aerosols.

The Task Group of Lung Dynamics has  recently developed a model for the
deposition of particles  in the respiratory tract,^J  Findeisen's anatomi-
cal model"/ was chosen as  the  basis  for the Task Group Model.  Calcula-
tions, based on the  model,  of  deposition in respiratory compartments are
shown in Figure 3.   The  curves indicate a relationship between the mass
median aerodynamic diameter and the  gravimetric  fraction of the inhaled
particles which would be deposited in  each anatomical compartment.

Experimental studies of  the deposition of inhaled particulate material may
be divided into two  broad  categories.   The first group deals with the mea-
surement of total deposition in the  respiratory  tract, and the second group
is concerned with regional deposition  within the various areas of the
respiratory tract.   Details of these experiments are given in Ref. 7.
The following points can be made with  respect to the overall retention
characteristics of the respiratory system:Z/

1.  Percentage deposition increases  with aerodynamic particle size from
a minimum value of about 25% at ** 0.5  urn and approaches 100% for particles
> 5 urn.  Particles of different densities and shapes follow the same depo-
sition curve when size is  expressed  in terms of  equivalent diameter of
unit-density spheres.  Particles larger than 10  urn are essentially all
removed in the nasal chamber and therefore  have little probability of
penetrating to the lungs.  Upper respiratory efficiency drops off as size
decreases and becomes essentially  zero at about 1 um.

2.  The efficiency of particle removal is high being essentially 100%
down to around 5 um. Below this size  it falls off to a minimum at about
0.5 iim.  It then increases again as  the force of precipitation by dif-
fusion increases with further  reduction in size.  For particles < 0.1 vim,
the percentage deposited out of the  total respired air approaches, in
value, the fraction  of tidal volume  which reaches the pulmonary air spaces.
This fact suggests that  the absolute efficiency  of alveolar deposition of
these submicron particles  approaches 100%.

3.  Percentage deposition  varies with  breathing  frequency, increasing, for
a heterogeneous aerosol,  in both directions from a minimum level at fre-
quencies of 15-20 cycles/min.   At slower rates,  the probability of


                                22

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                  NASOPHARYNGEAL
            3?&w PULMONARY
            MASS MEDIAN DIAMETER,'MICRON
Figure  3.  Fraction of particles deposited in the three
            respiratory tract compartments as a func-
            tion of particle diameter^/
                      23

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deposition by gravity  settlement  and diffusion  goes up  in proportion to
the increase in  transit  time  of the  dust-laden  air into and out of the
lungs.  With more  rapid  breathing percentage  deposition of the coarser
particles increases  because of the rise  in force  of inertial deposition
with increasing  air  velocity.                                  r

4.  Particles of hygroscopic  materials are removed in higher percentages
than are nonhygroscopic  particles of the same (dry) size because of the
growth  of such particles by water adsorption  from the moist air in the
respiratory  system.

5.  There is reasonably  good  agreement between  the directly measured
values  of overall  deposition  and  the levels predicted from mathematical-
physical equations,  with respect  to  both particle size  and dynamics of
air flow into and  out  of the  respiratory system.

Clearance of Particulate Matter from the Respiratory System

Different clearance  mechanisms operate in the different portions of the
respiratory  tract, so  that the rate  of clearance  of a particle will depend
not only on  its  physical and  chemical properties  such as shape and size,
but also on  the  site of  initial deposition.  The  fast phases of the lung
clearance mechanisms are different in ciliated  and nonciliated regions.
In ciliated  regions, a flow of mucus transports the particles to the
entrance of  the  gastrointestinal  tract,  while in  the nonciliated pulmonary
region, phagocytosis by  macrophages  can  transfer  particles to the ciliated
region. The rate  of clearance is an important  factor in determining toxic
responses, especially  for slow-acting toxicants such as carcinogens.  The
presence of  a nonparticulate  irritant or the  coexistence of a disease
state  in the  lungs may interfere  with the efficiency of clearance mecha-
nisms  and thus prolong the residence time of  particulate material in a
given  area of the  respiratory tract. In addition, since the clearance of
particles from the respiratory system primarily leads to their entrance
into  the gastrointestinal system, organs  remote  from the deposition site
may be  affected.

The Task Group on  Lung Dynamics developed a model for respiratory clearance
and also summarized  experimental  work on clearance.  Details of the model
and the analysis of  experimental  data are presented in  Refs. 2 and 5., and
the reader interested  in a more complete discussion of  respiratory clear-
ance  is directed to  these sources.

Toxicological Studies  of Atmospheric Particulate  Matter

Experimental toxicology  develops  information  on the mode of action of
specific pollutants, on  the relative potency  of pollutants having a similar

                                   24

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mode of action, and on the effect of one pollutant on the magnitude  of
response to another.  If man could be used as the experimental  subject,
experimental toxicology would be the best means of deriving  air  quality
criteria.  However, the impossibility of performing experiments  using
human exposures to varying concentrations of a wide range of compounds
precludes this direct approach.  A limited amount of intentional human
experimentation has been conducted, but most of the data for human toxi-
cology are derived from accidental or occupational exposures.

The use of laboratory animals in toxicological experiments is more straight-
forward, but the obvious anatomical and metabolic differences between ani-
mals and man require the exercise  of caution in applying the results of
animal exposures  to human health criteria.  Furthermore, many   of the
animal experiments have been conducted at exposure concentrations far in
excess of those likely to be found in the atmosphere.8~13/

In spite of these limitations, toxicological studies have shown  that
atmospheric particles may elicit a pathological or physiological response.
Other conclusions from these studies are:

1.  The presence of an inert particle in the respiratory tract may inter-
fere with the clearance of other airborne toxic materials,

2.  Evaluation of irritant particulates on the basis of mass  or  concentra-
tion alone is not sufficient; data on particle size and number averages
per unit volume of carrier gas are needed for adequate interpretation,

3.  Particles below 1 um have a greater irritant potency than larger
.particles, and

4.  A small increase in concentration could produce a greater-than-linear
increase in irritant.response when the particles are < 1 um.

The possible influence of inert particulate matter on the toxicity of ir-
ritant gases has been the subject of considerable speculation and a  limited
amount of experimental work.  Work on the synergistic effects of aerosols
and irritant gases is reported in Refs. 14-27-  Available information in-
dicates that gases and particulates acting together may cause greater damage
than either one acting separately.
                      i
Also, if the particulates and gases are delivered in an alternating  cycle,
the damage is also, potentiated.  This suggests that the defense  evoked by
one of the challenges may impair the protection that the 'lung has against
the other.  These observations, which admittedly have been made  on occasion
                                   25

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with greater concentrations  of pollutants  than normally encountered,  should
at least alert  us  to  the possibility that  a certain ambient  particle  con-
centration might be without  hazard in an otherwise clean environment,  but
harmful if respired  in association with gases commonly found in an urban
environment.

Epidemiological Studies of Atmospheric Particulate Matter

The  ultimate assessment of the impact of air pollution on human health can
come only  from epidemiology.—'  Because particulate matter and gaseous
pollutants  tend to occur together in a polluted atmosphere,  few epidemic-
logic studies have been able adequately to differentiate the effects  of
the  two pollutants.   Because we do not now have a good epidemiological
basis for  stating the influence of particulates, only a brief synopsis
of epidemiological studies of atmosphere particulate matter will be
presented.   References 2 and 28 present an extensive review of epidemiolog-
ical studies, and those seeking more detail are directed to these sources.

Epidemiologic studies of the relationship between pollutant concentrations
and  their effects on health have used indices varying from disturbance of
 lung function to death.  British studies of acute episodes of increased
pollution show excess deaths occurring at smoke levels from 750 ug/nH to
2,000 ug/m3.  High S02 levels are, of course, concurrently present.  The
excesses of mortality are always accompanied by a very large increase in
 illness,  mainly exacerbations of chronic conditions.  Similar, but less
 spectacular, episodes have been reported in New York City..?./

Winkelstein found in Buffalo that increases in the mortality rate were
 significantly linked to higher levels of suspended particulate pollution.29/
His  studies showed that mortality from all causes, from chronic respiratory
diseases,  and from gastric carcinoma increased from the lowest of his five
 levels of pollution  (less than 80 ug/m3) through the three higher ranges,
 after the effects of socioeconomic status had been considered.  Zeid*berg
 found in Nashville significant increases in all respiratory deaths at soil-
 ing  levels over 1.1 cohs annual average.30,3I/  Neither of these studies
 took smoking habits into account and the Nashville study only partially
 allowed for socioeconomic factors.

 Studies of illness in relation to residence in more- and less-polluted
 areas contribute additional information.  Fletcher, et al.,  noted a propor-
 tional decline in the production of morning sputum in chronic bronchitics
 in West London from 1961 to 1966 as smoke pollution in their residence
areas declined from 140 ug/m3 annual mean.r_£/  Douglas and Waller found
an increase in frequency and severity of lower respiratory illness at
                                     26

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smoke and SC>2 levels over 130 ug/m3 annual average.33/  A study of Lunn,
et al. shows similar differences occurring with more morbidity measured
between about 100 ug/m3 and 200 ug/m3 of smoke, and for others between
200 ug/m3 aruj 300 ug/m3 annual average.2z/

Physiologic studies of lung function have also been made in both adults
and children.  On the basis of present limited knowledge it appears that
the alterations found may be both temporary and permanent.  The observa-
tions now available relate to long-term residence in a given area.34;35/
The study reported in Ref. 34 shows reduced pulmonary function in the
children living in areas of high dustfall as compared with those living
in low dustfall areas.  In the Osaka study the dustfall levels were 6.5
gm/m2-month and 13.3 gm/m^-month.3JL/  Douglas and Waller33_/ have shown
that there is a three-fold increase in morbidity from lower chest infec-
tions in infants younger than 2 years in moderate and high pollution
regions, compared to very low pollution regions.

Bates36_/ has recently reviewed advanced concepts of lung function and has
made an attempt to differentiate in a preliminary way the effects that an
inhaled substance may have on the human lung.  Figures 4 to 6 present in
a diagrammatic form Bates' analyses of the effects of different materials
on the major bronchi of the lung, on the terminal bronchioles, and on the
alveoli.

In summary, examination of the studies of the potential effects of air
pollutants on lung functions and available epidemiologic data indicates
that there is an association between air pollution, as measured by both
particulate matter and gaseous pollutants, and health effects of varying
severity.  Increased respiratory disease morbidity is almost certainly
related to air pollution, and fine particulates play an important role
either along or in combination with gaseous pollutants.

MODIFICATION OF PROPERTIES OF THE ATMOSPHERE

The emission of fine particles into the atmosphere can increase the sus-
pended particulate burden, modify the properties of the atmosphere, and,
as a result, influence many facets of human activity.  The suspended
atmospheric particles are of four general types.  The first are the "light
ions" produced in the air by cosmic rays and radioactivity.  They consist
of small aggregates of molecules having dimensions up to a few molecular
diameters.  The second important type of particle consists of the so-called
"aitken nuclei."  These particles range in radius from 2 x 10~7 cm up to
10~4 cm.  They are particularly prevalent near cities and the earth's surface.
                                  27

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           PARTICLES

           2.0-50.0/1
 GAS EXPOSURE

SO2,NO2,O3etc.
                   1 PARALYSIS OF CILiA

                   2 HYPERSECRETION

                   3 MUCUS GLAND HYPERTROPHY
                    AND EXTENSION

                   4 SUSCEPTIBLITY TO INFECTION

                    CHRONIC PRODUCTIVE COUGH
Figure 4.   Effect  of  irritants  in  major  bronchi
           PARTICLES
GAS  EXPOSURE
SO,NO.O3 etc.
                       POTENTIATION IF BOTH
                            PRESENT
                   Loss of Normal Defences
                   Effect on Surfactant
                   Goblet Cell Metaplasia
                   Inflammation and Obliteration
                   Premature Closure
    EFFECTS ON;
        Collateral
          Ventilation
        Gas  Exchange
        Stress of Lung
        Release of Proteo-
          lytic Enzymes
 Figure 5.    Effect  of  irritants  in  terminal bronchioles
   PARTICLES
 0.01/1-0.5/1
                                 GAS EXPOSURE
>k. Jf
POTENTIATION IF BOTH
PRESENT
1
INCREASE OF CELLS AND
MACROPHAGES IN LUNG
\
RELEASE OF PROTEOLYTIC
ENZYME

/


INFECTION

s^ Protection by
.x^ Anti-Proteolytic
S^ Enzymes
(a\~ Antitrypsin etc. )

«
EMPHYSEMA WITH
ALVEOLAR
DESTRUCTION


       Figure  6.   Effect of irritants in alveoli
                                  28

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As a rule of thumb, one anticipates finding about 100,000 of these parti-
cles per cm3 in a large city, about 10,000/cm3 in the country, and about
I,000/cm3 at sea.  The numbers decrease with increasing altitude and only
about 107o of the surface populations are found at an altitude of 7 km.
The fine particle pollution of the air is largely composed of these nuclei.

The third type of atmospheric particle is the cloud droplet having a radius
from 10~4 cm to 5 x 10~3 cm.  Finally, the cloud droplets associate to
form raindrops or snowflakes that fall at velocities dependent upon their
size.  Rain or snow represents the final stage for the removal of atmo-
spheric pollution by natural methods.

The interactions of fine particulate pollutants with atmospheric processes
are reviewed in the following sections.

Visibility

One of the most obvious effects of air pollution  is the reduction  in
visibility which results from the accumulation of particulate matter  in
the atmosphere.  Decreased visibility  interferes with certain human
activities, such as safe operation of  aircraft and automobiles and the
enjoyment of scenic vistas.  Air pollution that reduces visibility, in
addition to endangering the  safety of both air and land travel,  results
in  inconvenience  and  economic loss to  the public, and to  transportation
companies due  to  disruption of  traffic schedules.

Deterioration of visibility caused by suspended particulate matter is the
result of adsorption and scattering of light.   Both  the  brightness of the
viewed object and its visual contrast with the background  are reduced by
attenuation of light due to scattering and absorption.   In addition,  a
further contrast reduction results from scattering of  sunlight into the
observer's line of sight.   Loss  of brightness  and  contrast are responsible
for the subjective impression of impaired visibility.

Studies of the theory of visibility by numerous authors  have led to a
very useful relationship between visual range  and  mass  concentration of
atmospheric particulate matter.   The  visual  range  is defined as the dis-
tance, under daylight conditions,  at  which the apparent  contrast between
object and background is just equal to the threshold contrast of the ob-
server.  The usual assumption of threshold contrast  of 0.02 for the human
eyes leads to expression"
                                L = 3.9/b        ,                    (1)
                                   29

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where  L is  the visual range in meters and b is the extinction coefficient
per meter along the sight path for a black target.

Generally,  the extinction coefficient can be depicted as the sum of several
components:
            b = bscat + bRayleigh + babs-gas + babs-aerosol           (2)
where bscat represents the component due to light scattering by aerosol,
bRayleigh the scattering due to gaseous air (the blue-sky scatter),  and
babs-gas and babs-aerosol represent the absorption due to gases (like  N02)
and particles (such as carbon black), respectively.  Middleton and dthers
have suggested that bscat is dominant especially in situations where the
visual range is somewhat degraded due to haze.39/  Measurements of light
scatter in urban areas tend to support this assumption.

Mass concentration of atmospheric particulate matter has been found to be
approximately proportional to the scattering coefficient, and Char Is on,
et al.,^2/ and Noll, et al.,^1/ have developed a useful  relationship be-
tween visual range and mass concentration of atmospheric particulate
matter.

Combining Eq. (1) with the observation that the mass concentration is  ap-
proximately proportional to "b" results in Eq. (3) .
                                   L = kM'1                          (3)
 Figures 7 and 8 illustrate visibilities calculated using the above  approach
 These and other calculations clearly show that,  with respect to aerosol
 particle size, visibility reduction related to air pollution is caused
'primarily by the 0.1-1.0 um radius particles.

 Most  industrial, combustion, and vehicular sources emit particles  in a
 wide  variety of sizes.   From the preceding discussion,  it is clear that
 the major interest insofar as visibility-reducing particles is  concerned
 centers on those emitted particles in the 0.1-1.0 um radius range.
                                   30

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   80
   70
   60
VI
0>
   50
_i  40
u
o
g
o
2  so
    20
    10
     Calculated Visibilities of
     Ferric Sulfate Aerosol
     Density = 3.09 gm/cm3
     Refractive  Index = 1.8
     Incident Light = 5240 Angstroms
—  Parameter: Concentration in Ambient Air
                               I
                                                I
      0.1
                       0.2                      0.3

                           PARTICLE RADIUS, Microns
0.4
          Figure 7.   Meteorological visibility vs particle^./
                           size, ferric sulfate aerosol
                                              31

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            30 r-
                             Calculated Visibilities of
                             Flyash  Particulates
                             Density =  1.7
                             Refractive  Index = 1.55
                             Incident Light = 5240 Angstroms
         in
         0)
          . 20
                  Parameter: Concentration in  Ambient Air
         CO
LO
NJ
O
g
o
9   10
             o
               0.1
                             0.2
                                     Figure 8.
          0.3
PARTICLE RADIUS, Microns
0.4
0.5
                                         Meteorological visibility vs particle size,
                                                        flyash aerosol

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Solar Radiation

The intensity and spectral distribution of direct  sunlight  and  scattered
daylight, and the variation of intensity with time of day,  season,  latitude,
altitude, and atmospheric conditions are important because they  affect
photosynthesis in plants and the distribution of plants and animals  on
earth, the weathering of natural and manmade materials, climate,  and il-
lumination for human activity.—'

The attenuation of solar radiation through the atmosphere is caused  by a
number of physical factors;43-45/

1.  Rayleigh scattering by air molecules such as N£ and 02, and particles
in size ranges less than the wavelength of solar radiation,

2.  Selective absorption by gaseous constituents of the atmosphere,  and

3.  Scattering and absorption by atmospheric dusts and particulate matter
of a size greater than the wavelength of solar radiation.

Except in cases of heavy particulate pollution of the atmosphere, such as
may occur in large urban centers or heavy industrial areas, it appears
that the effect of turbidity is to scatter radiation out of the direct
solar beam and add an almost equal amount to the diffuse beam arriving
from the rest of the sky by forward-scattering.  In cases of heavy parti-
cle concentrations, however, the loss from the direct solar beam greatly
exceeds the gain in the downward scattered beam, the difference being
lost to backscattering off the top  of the pollution layer, and to ab-
sorption within the polluted layer or column.

Landsberg-t2/ and SteinhauserftZ./ report that cities in general receive
less solar radiation than do their rural environments.  Seasonal, weekly
and daily variations in total solar radiation in urban communities have
also been noted.zZl^2./  These variations appear to be related, in part,
to cycles of industrial and commercial activity.  Measurements at the
Moana Loa Observatory in Hawaii,  which is remote from any local sources
of air pollution, indicate a long-term increase in turbidity or atmo-
spheric dustiness.lP./  McCormick and Ludwig have reported significant
increases in recent years of turbidity over Washington, D.C., and Davos,
Switzerland.  Washington and Davos are probably the only localities with
reliable records over a 50-year span.^P./  Davos is an alpine station far
removed from major pollution sources.  Cobb reports that man-generated
particulate pollution has not yet affected the atmosphere over 90% of the
                                   33

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oceans.—*—   Cobb made  his  conclusion after  comparing  electrical  con-
ductivity readings taken  in the late 1960's  with those taken  early  in
the century.   Exceptions  to the general pattern include  paths of  anthro-
pogenic aerosol  pollution extending from the U.S.  across the  North
Atlantic and  from Japan and Asia across the  North Pacific.  A third path
was found across the  Indian Ocean,  probably  caused by monsoon-carried  dust.
Aerosol concentration is  more varied now than  it was  60  years ago,  accord-
ing to Cobb.   Concentration has doubled over the North Atlantic since  1911
but has remained fairly constant over the South Pacific.  Cobb stressed
his results show only one aspect of man's effect on the  atmosphere,  but
he is confident  that  particulate concentration will decline and its in-
fluence on  climatic  conditions will decrease as regulations to reduce  the
output of particulates are enforced.

Watt has  suggested  that one way to assess the  influence  of air pollution
on atmospheric properties is to find some natural events in the past that
operated  in a manner analogous to modern pollution.-LI/   He analyzed the
changes  in  weather  patterns following the eruptions of the Tambora  and
Krakatau  volcanoes,  and suggests that these  volcanoes had effects similar
to the global increase in atmospheric pollution.

The net  influence of atmospheric turbidity on  surface temperature is un-
certain,  but the emission of long-lived particles may well be leading  to
a decrease  in world  air temperature.54/  As  more is learned aboub the
general  circulation of the atmosphere and the  delicate balance between
incoming  and outgoing radiation, it seems increasingly probable that small
changes  such as those occasioned by increasing particle  loads in  the atmo-
sphere may  produce  very long-term meteorological effects.

Weather Modification

Man's knowledge of  his ability to inadvertently modify his climate  is
still  at  best fragmentary.  Insufficient information is  known about the
long-term build-up  of air pollutants, their effects and  their inter-
relationships.  Substantial evidence of precipitation modification  is
meager but  significant.  An example of increased precipitation from air
pollution appears to exist at La Porte, Indiana, some 30 miles downwind
from  the  heavy industrial complex in Chicago.   Precipitation  and  thunder-
storm activity have increased significantly since 1925,  and precipitation
peaks have  coincided with peaks in steel production in the Chicago  area.—'
               ^i(\ 1
Hobbs, et al.,— have reported measurements of the concentrations  of  cloud
condensation nuclei in Washington State resulting from pulp and paper  mills
and other industrial sources.  Their study of  the precipitation and stream
flow records in Washington State for the past  40 years revealed that in
                                   34

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recent years there have been significant increases in precipitation in
several areas in the vicinity of large industrial sources of cloud-
condensation nuclei.

Excessive dustiness in the atmosphere can also reduce rainfall under  cer-
tain conditions when overseeding occurs.  This happens when many  small
droplets, formed by condensation, do not fall to earth if there is insuf-
ficient moisture available to continue the droplet growth by condensation.
Consequently, what would have fallen as rainfall stays in the form of  clouds.
A case in point of this reduction in rainfall has occurred in the sugar pro-
ducing areas in Queensland, Australia.  During the cane harvesting season,
the common practice is to burn off the cane leaf before cutting and harvest-
ing.  This results in fires over extensive areas and large palls  of smoke.
The fine smoke particles have modified the cloud  formation and hindered
the rainfall process.  A reduction of up to 25% in the rainfall has occurred
downwind of these areas, but there is no such effect in neighboring areas
unaffected by the smoke plume.^Z/  Similar effects have been reported in
Puerto Rico, Africa, and Hawaii.58,597  Schaefer has also reported on ob-
servations of changes in micro-physics of clouds in the vicinity  of large
cities during airplane flights through convective clouds .5_8/  His observa-
tions suggest that such clouds contain an increasing number of cloud  drop-
lets.  Schaefer's investigations of snow and rainstorm patterns in New York
State indicate that submicroscopic particulates from manmade pollution may
be initiating and controlling precipitation in a primary manner,  rather
than being involved in the secondary process wherein precipitation elements
coming from natural mechanisms serve to remove the particles by diffusion,
collision, and similar scavenging processes.

In summary, available data indicate  that man has detectably changed  the
constitution of the atmosphere; in some respects globally, in another at
least on a subcontinental scale, in some cases locally.  At the same  time,
there have been variations of climate.  Our present knowledge of atmo-
spheric processes suggests that these changes are what would be expected to
follow from man's interference with the atmosphere.  But they are also
quite compatible with what we know of the statistics appropriate  to an
atmosphere of undisturbed constitution and they are also compatible with
the possible behavior of a dynamical system as complex as the atmosphere.
                                  35

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                             SECTION V
                    SOURCES OF  FINE  PARTICULATE EMISSIONS

NATURE OF THE PARTICULATE POLLUTION PROBLEM

Atmospheric particulatematter  can be classified  as primary--introduced
into the atmosphere in particulate  form,  or secondary--formed in the atmo-
sphere by chemical  and physical  processes.   Atmospheric particulate matter
originates from natural  causes such as  the  sea,  volcanoes, and the soil
and from man-made sources such as industrial processes and internal com-
bustion engines.  In order to  cast  the  particulate pollution problem in
the proper perspective,  it is  helpful to  identify the relative contribu-
tions of primary particulates  from  natural  and man-made sources.

Tables 6, 7, and 8  summarize estimates  of primary particulate emissions
from both natural and man-made sources.   These estimates were prepared
by MRI as part of the work performed on a systems study of particulate
pollution.60-62/  Specific details  of the procedures used to obtain the
estimates are presented  in Ref. 60.  Estimated emissions from various in-
dustrial operations are  shown  in Table  6.   The emissions were computed in
most cases by means of the following equation:

                              (P)  (ef)   (1 - CcCt)
                                    2,000

where,

          E  is the  emissions rate,  tons/year

         ef  is the  emission factor  (uncontrolled), pounds/ton

          P  is the  production  rate, tons/year

         Cc  is the  average efficiency of  control equipment

         Ct  is the  percentage  of  the production  capacity on which control
              equipment  has been  installed

                                    36

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       Table 6.  MAJOR INDUSTRIAL SOURCES OF PARTICULATE POLLUTION6.0./
                                                                   Emissions
                       Source                                      (tons/year)

 1.  Fuel combustion                                               5,953,000
 2.  Crushed stone, sand and gravel                                4,600,000
 3.  Agricultural operations (grain elevators, feed mills
       and cotton gins)                                            1,817,000
 4.  Iron and steel                                                1,442,000
 5.  Cement                                                          934,000
 6.  Forest products                                                 580,000
 7.  Lime                                                            573,000
 8.  Clay                                                            467,000
 9.  Primary nonferrous (copper, aluminum, zinc and lead)            476,000
10.  Fertilizer and phosphate rock                                   328,000
11.  Asphalt (batch plants and roofing)                              218,000
12.  Ferroalloy                                                      160,000
13.  Iron foundries                                                  143,000
14.  Secondary nonferrous (copper, aluminum, zinc and lead)          127,000
15.  Coal cleaning                                                    94,000
16.  Carbon black                                                     93,000
17-  Petroleum                                                        45,000
18.  Acids (sulfuric and phosphoric)                                  16,000

       Total                                                      18,056,000
                                    37

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      Table 7.  NONINDUSTRIAL  SOURCES OF  PARTICULATE POLLUTION^/
         Source

A.  Natural dusts

B.  Forest fires
      1.  Wildfire
      2.  Controlled  fire
            (a) Slash burning
            (b) Accumulated  litter
      3.  Agricultural burning

C.  Transpor tat ion
      1.  Motor vehicles
            (a) Gasoline
            (b) Diesel
      2.  Aircraft
      3.  Railroads
      4.  Water transport
      5.  Nonhighway  use
            (a) Agriculture
            (b) Commercial
            (c) Construction
            (d) Other

D.  Incineration
      1.  Municipal incineration
      2.  On-site incineration
      3.  Wigwam burners  (excluding
            forest products  disposal)
      4.  Open dump

E.  Other minor sources
      1.  Ruber from  tires
      2.  Cigarette smoke
      3.  Cosmic dust
      4.  Aerosols from spray cans  •
      5.  Ocean salt  spray

          Total
Emissions
(tons/year)
37,000,000

 6,000,000
11,000,000
 2,400,000
   420,000
   260,000
    30,000
   220,000
   150,000

    79,000
    12,000
     3,000
    26,000
    98,000
   185,000

    35,000
   613,000
   300,000
   230,000
    24,000
   390,000
   340,000
                63,000,000
56,400,000
 1,200,000
   931,000
 1,284,000
               122,815,000
                                     38

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Table 8.  ALL MAJOR SOURCES OF PARTICULATE POLLUTION
Source
Natural dusts
Forest fires
Major stationary industrial sources
Transportation
Incineration
Other sources
Total
Emissions
(tons/year)
63,000,000
56,400,000
18,056,000
1,200,000
931,000
1,284,000
140,874,000
Percent by
Weight
44.7
40.1
12.9
0.8
0.7
0.8
100.0
                       39

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Production data for  1968 and  application  of  control information* from 1969-
1970 were used in  the  calculations.   Table 7 lists nonindustrial sources of
particulate pollutants with their  corresponding  estimated emissions, while
Table 8 presents a comparison of .particulate emissions  from  industrial and
nonindustrial sources.

As shown  in Tables 7 and  8,  the largest sources  of particulates are natural
dusts and forest fires.   These sources  account for an estimated 85% of the
national  atmospheric primary  particulate  loading on a mass basis, and are
a substantial portion of  background  levels.   Emissions  from  these sources
are essentially beyond the scope  of  present  air  pollution control methodology.
Furthermore, their effect  on  the  population  is less than for man-made sources
because of the concentration  of the  latter in urban areas.

While the emission figures presented in Table 6  provide some indication of
the relative impact  of individual  industrial operations on the particulate
pollution burden,  total mass  emission data do not clearly portray the really
important and serious aspect  of particulate  air  pollution.   Not reflected
in Table  6  is the  relative contribution that the emissions make to the long-
lived suspended particulate levels in the atmosphere.   As was indicated in
Chapter 2,  it is the long-lived particles (i.e.,  fine particulates) that
contribute  to all  the major adverse  aspects  of particulate air pollution.

PRINCIPAL SOURCES  OF FINE PARTICULATES

As part of the systems study  on particulate  pollution,  MRI estimated the
magnitude of the fine particle burden emanating  from  various particulate
pollutant sources .xL/  In this work, the  fine particle  size  range was de-
fined as  0.01-2 um.   In making the estimates of  fine  particle emissions,
the best  data currently available on particle size distributions before
and after control  devices, fractional efficiency curves for  control devices,
and the degree of  application of control  equipment on specific sources was
used  to estimate the present  level of fine particle emissions from particu-
late  pollution sources.

The method used  to calculate  the quantity of fine particle emissions is
similar to that  used in calculating  total mass emission in Table 6.  The
same  production  figures and emission factors were used. However, to calcu-
late  the  quantity  of fine particles  (< 2  um) emitted  it was  necessary to
use the following  additional  factors:


*  Application of  control is  defined as that fraction of the total produc-
      tion which has  particulate pollution controls.
                                    40

-------
a.  Particle-size distributions for particulates emitted by uncontrolled
sources.

b.  Percent application of control on specific sources,with a breakdown
of this percent application of control into the percent application of
each type of control device.

c.  Fractional efficiency characteristics of each type of control device.

Specific details of the calculations are given in Ref. 61.

Table 9 summarizes the estimates of fine particle emissions on the basis
of mass emitted in specific particle size ranges.  Because of the lack of
adequate data on many specific process sources, the emission figures given
in Table 9 are not complete for some industrial categories.  Also, fine
particle emissions for several sources (e.g., crushed stone operations)
could not be calculated for each size range shown in Table 9, and fine
particle emissions for potentially significant industrial categories,  such
as primary nonferrous metallurgy and clay products, could not be estimated
because of incomplete data.  Fine particle emissions from the industrial
sources listed in Table 9 are estimated to be at least 4 x 1C)6 tons/year.
This represents approximately 20-25% of the total mass emissions (Table 6)
from these sources.  In view of the limitations of available data, the
figure of 4 x 10^ tons/year of fine particulate emissions from industrial
sources probably understates the fine particle burden emanating from those
sources.

To indicate the relative magnitude of the fine particle problem from
stationary sources, fine particle emissions were also estimated for mobile
sources.  Particulate emissions from mobile sources were assumed to be un-
controlled and to consist of all < 2 jam particulates.  Table 10 summarizes
the estimate of fine particle emissions from these sources.  Fine particle
emissions from natural dusts, forest fires, and agricultural burning could
not be estimated because of lack of reliable particle size data..^JV

Summary of Fine Particle Emissions

Fine particle emissions (primary particulates) from man's activity are con-
servatively estimated to be over 5 x 10" tons/year of which about 75% re-
sults from stationary industrial operations. Furthermore, these emissions
compose about 257» of the total mass of particulates emitted from industrial
sources.  Stationary combustion and metallurgical operations account for
about 50% of the quantity of fine particulates emitted from stationary
sources.
                                 41

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                                        Table 9.  FINE PARTICLE EMISSIONS FROM INDUSTRIAL  SOURCES^!/
                                                            (Mass Basis, 103 Tons/Year)
•IS

Source
1. Stationary combustion
A. Coal
1. Electric utility
a. Pulverized
b . Stoker
c . Cyclone

2. Industrial
a. Pulverized
b . Stoker
c. Cyclone

B. Fuel oil
1. Electric utility and
industrial
C. Natural gas and LPG
1. Electric utility and
industrial


Fine Particle Size Ranges (urn)
1-3 0.5-1.0 0.1-0.5 0.05-0.1 0.01-0.05



591.6 178.6 99.2 2.9
21.7 5.7 2.2
48.2 13.9 7.3 0.2
Total from electric utility

15.1 0.5
56.6 7.3 2.1
13.5 6.7 4.1 0.1
Total from industrial coal


126.9


97.2
Total from fuel oil and gas
Total from fuel combustion

Total



872.3
29.6
69.6
971.5

15.6
66.0
24.4
106.0


126.9


97.2
224.1
1,301.6

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Table 9.  (Continued)  FINE PARTICLE EMISSIONS FROM INDUSTRIAL SOURCES^!/
Fine Particle Size Ranges (urn)

2.
3.





4.




5.
6.



7.


Source
Crushed stone
Iron and steel
A. Sinter machines
B. Open hearth furnace
C. Basic oxygen furnace
D. Electric arc furnace

Kraft pulp mills
A. Bark boilers
B. Recovery furnace
C. Lime kiln

Cement plants, rotary kilns
Hot-mix asphalt plants
A. Rotary dryer
B. Vent line

Ferroalloys
A. Electric furnace
B. Blast furnace
1-3
868.0

3.8
60-80
0.9
3.8


49.1
95.3
1.6

130.8

96.4
14.4


18.4
0.8
0.5-1.0


1.2
20-56
18.9
2.5
Total from

11.9
78.0
0.2
Total from
32.7

36.3
1.7
Total from

27.8

0.1-0.5 0.05-0.1


0.6
8.5-234 0.1-22
153.7 1.0
5.2 1.3
iron and steel

6.5 0.3
74.7 1.4

kraft pulp mills
13.5

21.5
0.2
hot-mix asphalt plants

81.1 17.3

0.01-0.05 Total
868.0

5.6
0-3.6 108-376
174.5
1.5 14.3
302.4-570.4

67.8
249.4
1.8
319.0
177.0

154.2
16.3
170.5

7.7 152.3
0.8
                                  Total from ferroalloys
153.1

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               Table 9.  (Concluded)  FINE PARTICLE  EMISSIONS FROM INDUSTRIAL SOURCES6.!/
8.

9.
10.
11.
12.
13.
14.
15.
16.
Source
Lime plants
A. Rotary kilns
B. Crushing and screening

Secondary nonferrous metallurgy
Carbon black
Coal preparation plants, thermal
dryer
•
Petroleum FC.C units
Municipal incinerators
Fertilizer, granulators and dryers
Iron foundries, cupolas
Acids
A. Sulfuric
B. Phosphoric (thermal)

1-3
40.6
25-99

127.0
93.0
63.5
45.0
10.4
7.1
6.8
2.7
1.0
Fine Particle Size Ranges (jim)
0.5-1.0 0.1-0.5 0.05-0.1 0.01-0.05 Total
18.8 23.6 3.0 1.8 87.8
25.0
Total from lime plants 113.0
127.0
93.0
63.5
45.0
6.7 11.5 3.5 4.3 36.4
3.5 3.1 13.7
2.4 3.1 0.4 0.4 13.1
2.7
1.0
Total from acids 3.7
Total from major industrial sources 3,800-4,142
Note:  Potentially significant sources not evaluated because of lack of sufficient data:   (1)  operations re-
         lated to agriculture, (2) primary nonferrous metallurgy, (3) clay products,  (4)  food  processing
         operations, and (5) fiberglass manufacture.

-------
           Table 10.  FINE PARTICLE EMISSIONS FROM MOBILE SOURCES


                                                                    Emissions
              Source                                               (Tons/Year)

1.  Motor vehicles
      a.  Gasoline                                                    420,000
      b.  Diesel                                                      260,000

2.  Aircraft                                                           30,000

3.  Railroads                                                         220,000

4.  Water transport                                                   150,000

5.  Nonhighway use
      a.  Agriculture                                                  79,000
      b.  Commercial                                                 .  12,000
      c.  Construction                                                  3,000
      d.  Other                                                        26.000

              Total                                                 1,200,000
                                     45

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PRIORITY LIST FOR  SOURCES  OF  FINE PARTICLE EMISSIONS

A complete description of  the  importance of a given source of fine partic-
ulate emissions requires not only the quantification of the amount of fine
particulate emitted, but also  the identification of the chemical composi-
tion of the individual particle  size fractions.  Attention must be directed
to the chemical nature of  the  particles as it relates to toxicity or
hazardous aspects.   For example, power plant  flyash produced by the com-
bustion of pulverized coal consists of a diverse mixture of metal oxides
and silica while cement kilns  produce little in the way of potentially
hazardous or toxic  particulates.  Other sources produce different mixtures
of substances.  Incorporation  of considerations of both quantity of fine
particulate emissions and  chemical composition of particles can lead to a
priority ranking of sources of fine particulate emissions.

Data on the chemical composition of various particle size fractions emitted
from industrial sources are sketchy at best.  However, the limited informa-
tion available indicates that  many of the potentially hazardous materials
(e.g., trace metals) are generally in the micron to submicron particle
size range.  While  lack of detailed data hinders the clear-cut identifica-
tion of the most important sources of fine particulate pollution, available
information can be  used to develop a relative priority list of emission
sources.  By using  available  data on the mass of fine particles emitted
by sources, the amount and type  of potentially hazardous pollutant emitted
by sources, and the general location of sources  (i.e., urban or rural), a
general profile of  the "adverse  or negative" characteristics of the partic-
culate pollutants  emitted  by  major industrial sources of fine particles can
be developed.  Table 11 presents such a profile.

The data on the quantity of fine particles emitted  from sources  (column 1,
Table 11) were taken from  Ref. 61, while the information on the amount and
type of potentially hazardous  pollutant emitted was obtained from Ref. 63.
In analyzing the data from Refs. 61 and 63, there appeared to be some dif-
ference in the definition  of  particulate.  Reference 61 considered only
primary particulates with  no  consideration of secondary particulates formed
by condensation or  reaction in the atmosphere.  Reference 63 apparently in-
cludes particulates formed by condensation.

Since some of the  potentially hazardous pollutants may be emitted from a
source as a vapor which subsequently condenses in the atmosphere, some
sources deemed important in Ref. 63 were not considered in Ref. 61.  This
accounts for some  of the information gaps in Table  11.  In addition, the
mass of fine particles emitted from some sources listed in Table 11 could
not be determined  because  of  lack of sufficient data on the particle size
distributions of the emitted  particulates.
                                   46

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                    Table 11.   PROFILE OF THE CHARACTERISTICS OF PARTICULATE POLLUTANTS
                                         EMITTED BY VARIOUS INDUSTRIAL SOURCES
            Industry and/or
                Source	

I.     Stationary combustion
         A.  Coal
           n..  Electric utility,
             a.  Pulverized
                          Mass of Fine
                        Particles Emitted
                         (103 tons/year)
  b.  Stoker
  c.  Cyclone
I.  Industrial
  a.  Pulverized
  b.  Stoker
  c.  Cyclone
3.  Commercial and
      residential
                              872.3
29.6
69.6
15.6
66.0
24.4
              Amount of Potentially
               Hazardous Pollutant
               Emitted (tons/year)
                     51,471
 5,994
 1,776
 3,783
13,237
 1,891
                        657
                       Type of Potentially
                      Hazardous Particulate
                        Pollutant Emitted
                               General Plant
                                  Location
Inorganic/metal oxides,         Urban, rural
  fluorides, polyorganics,
  As, Ba, Be, B, Cr, Cu,
  Pb, Mn, Hg, Ni, Se, Sn,
  V, Zn

As, Ba, Be, B, Cr, Cu,          Urban, rural
  fluorides, Pb, Mn, Hg,
  Ni, POM, Se, Sn, V, Zn

As, Ba, Be, B, Cr, Cu,          Urban, rural
  fluorides, Pb, Mn, Hg,
  Ni, POM, Se, Sn, V, Zn
As, Ba, Be, B, Cr, Cu,          Urban
  fluorides, Pb, Mn, Hg,
  Ni, POM, Se, Sn, V, Zn

As, Ba, Be, B, Cr, Cu,          Urban
  fluorides, Pb, Mn, Hg,
  Ni, POM, Se, Sn, V, Zn

As, Ba, Be, B, Cr, Cu,          Urban
  fluoride, Pb, Mn, Hg,
  Ni, POM, Se, Sn, V, Zn

As, Ba, Be, B, Cr, Cu,          Urban, rural
  fluoride, Pb, Mn, Hg,
  Ni, POM, Se, Sn, V, Zn

-------
                                                                 Table 11 (Continued).  PROFILE OF THE CHARACTERISTICS OF PARTICULATE POLLUTANTS
                                                                                                EMITTED BY VARIOUS INDUSTRIAL SOURCES
00
Mass of Fine Amount of Potentially
Industry and/or Particles Emitted Hazardous Pollutant
Source (103 tons/year) Emitted (tons/year)
B. Fuel oil
1. Electric utility
and industrial 126.9 28,326
2. Commercial and
residential - 44,063
C. Natural gas
1. Electric utility
and industrial 97.2 20,204
2. Commercial and
residential - 10,065
II. Crushed stone 868.0
III. Iron and steel
A. Sinter machines 5.6
B. Open hearth furnace 376.0 68,227
Type of Potentially
Hazardous Particulate
Pollutant Emitted
Inorganic/metal oxides,
polyorganics, As, Ba,
Be, Cr, Cu, Pb, Mn,
Hg, Ni, Se, V, Zn
Ba, Be, Cr, Cu, Pb, Mn,
Hg, Ni, POM, Se, Sn,
V, Zn
.
-
-
Metal oxides, alkalis
Ba, Pb, Mn, Hg, Sn, V,
General Plant
Location
Urban, rural
Urban, rural
Urban, rural
Urban, rural
Predominantly
rural
Urban
Urban
                                                C.  Blast furnace



                                                D.  BOF


                                                E.  Electric arc furnace

                                                F.  Metallurgical coke
175.0
 14.3
 7,215



 2,057


12,508

43,380
  Zn oxides, fluorides,
  POM

As, Cd, Mn, Hg, Ni, V,
  Zn oxides, fluorides,
  POM

Ba, fluorides, Mn, Hg,
  POM, V, Zn

Ba, Mn, Hg, Zn

POM
Urban



Urban


Urban

Urban

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                          Table 11 (Continued).  PROFILE OF THE CHARACTERISTICS OF PARTICULATE POLLUTANTS
                                                         EMITTED BY VARIOUS INDUSTRIAL SOURCES
IV.


V.
VI.
VII.

VIII.
IX.
X.
Industry and/or
Source
Kraft pulp mills
A. Bark boiler
B. Recovery furnace
C. Lime kiln
Cement plants,
rotary kilns
Hot-mix asphalt plants
A. Rotary dryer
Ferroalloys
A. Electric furnace
B. Blast furnace
Lime plants
A. Rotary kilns
Municipal incinerators
Iron foundry cupolas.
Mass of Fine
Particles Emitted
(103 tons/year)
67.8
249.4
1.8
177.0
154.2
152.3
0.8
87.8
36.4
13.1
Amount of Potentially Type of Potentially
Hazardous Pollutant Hazardous Particulate
Emitted (tons/year) Pollutant Emitted
- — f
15 Cr, Hg, POM
-
270 Fluorides
2,800 POM
4,382 Mn, Ni, POM, V, Zn
4,104 Mn, Ni, Zn, 0, POM
-
34,307 As, Cd, Cu, Pb, Hg,
POM, Se, Zn
6,151 As, Ba, Be, Pb, Mn,
General Plant
Location
Urban, rural
Urban, rural
Urban, rural
Primarily
rural
Urban, rural
Urban
Urban
_
Urban
Urban
XI.    Primary copper
         A.  Roasting
         B.  Reverberatory
               furnace
4,373
1,885
                                                                                     Hg,  Ni,  V,  Zn oxides,
                                                                                     POM,  fluorides
As, Cd, Cu, fluoride,
  Pb, Se
As, Cd, Cu, fluoride,
  Pb, Se
Rural
                                                                                                                   Rural

-------
                                   Table 11 (Concluded).  PROFILE OF THE CHARACTERISTICS OF PARTICULATE POLLUTANTS
                                                                  EMITTED BY VARIOUS INDUSTRIAL SOURCES
Ui
O
                     Industry and/or
                         Source	

                  C.  Converters
                  D.  Material handling
                                     Mass of Fine
                                   Particles Emitted
                                    (103 tons/year)
         XII.   Primary zinc
                  A.  Roasting
         B.  Sintering

         C.  Distillation

XIII.  Primary  lead
         A.  Sintering
         B.  Blast furnace

XIV.   Primary  aluminum
         A.  Reduction cells

XV.    Iron ore pellet plant

XVI.   Asphalt  roofing materials

XVII.  Secondary copper

XVIII. Secondary lead

XIX.   Secondary zinc

XX.    Structural clay products
Amount of Potentially
 Hazardous Pollutant
 Emitted (tons/year)

        5,591
        1,235



       34,187


       14,044

        4,676


        1,016

          275

       16,230

       18,200

       23,230

        1,036

        2,020

        3,840

        9,720
   Type  of  Potentially
  Hazardous Particulate
    Pollutant Emitted

As, Cd,  Cu, fluoride,
  Pb,  Se

As, Cd,  Cu,  fluoride,
  Pb,  Se
As, Cd, Cu, fluorides,
  Pb, Se, Zn

Cd, fluorides, Pb, Zn

Cd, fluorides, Pb, Zn


As, Cd, fluorides, Pb,
  Se
As, Cd, fluorides, Pb, Se

Fluorides (gas and solid)

Fluorides

POM

Cd, Cu, Pb, Zn, POM

Pb

Zn

Fluorides
General Plant
   Location

 Rural
                                                                                                                   Rural
                                                                                                                   Urban, rural
                                                                                                                            Urban,  rural

                                                                                                                            Rural

                                                                                                                            Urban

                                                                                                                            Urban

                                                                                                                            Urban

                                                                                                                            Urban

                                                                                                                            Urban,  rural

-------
In developing a priority ranking of the sources presented in Table 11,
equal weight was assigned to each of the adverse facets.  Using this ap-
proach, the priority ranking in Table 12 was developed.  Although quanti-
tative detail is less than desired in Tables 11 and 12, the tables do sug-
gest what should be the objective of initial efforts to control fine
particulate emissions.  The main thrust of initial efforts should be
focused on the reduction of the mass of fine particulate emissions with
emphasis placed on control of those sources which emit potentially
hazardous materials and are located in or near urban areas.  Potential
approaches to the regulation of fine particle emissions are discussed in
the next chapter.
                                      51

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         Table 12.  PRIORITY LIST FOR  SOURCES OF FINE PARTICLE EMISSIONS
Group I        (High priority)

               1.   Stationary combustion  (all fuel types)
                   a.  Electric utility
                   b.  Industrial
               2.   Iron and  steel  plants
                   a.  Open  hearth furnaces
                   b.  EOF furnaces
                   c.  Electric arc furnaces
                   d.  Metallurgical coke ovens
               3.   Municipal incinerators
               4.   Ferroalloy plants
                   a.  Electric furnace
                   b.  Blast furnace
               5.   Primary nonferrous metallurgy
                   a.  Zinc  roasting, sintering and distillation
                   b.  Copper roasting and converting
                   c.  Aluminum reduction cells

Group II       (Medium priority)

               1.   Hot-mix asphalt plant
               2.   Iron foundry cupolas
               3.   Asphalt roofing materials
                   a.  Asphalt blowing
               4.   Secondary copper,  lead and zinc

Group III      (Low priority)

               1.   Iron ore  pellet plants
               2.   Structural clay products
               3.   Cement and lime plants
               4.   Kraft pulp mills
               5.   Crushed stone
                                     52

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                                    SECTION VI
               APPROACHES FOR REGULATING FINE PARTICLE EMISSIONS
INTRODUCTION
The goal(s) of the control program for fine particulates will be the main
factor in the selection of approaches for regulating the emission of fine
particulates.  If the aerosol burden in the urban atmosphere is to be
reduced, a premium must be placed on the collection of particles smaller
than 5 um.  If improved visibility is the goal of fine particulate control
programs, attention must be focused on particle collection in the 0.1-1.0 um
range.  Concern for adverse health effects should direct attention to the
control of the0.01-7um size range, and to potentially hazardous consti-
tuents (e.g., lead, cadmium, vanadium, and particulate polycyclic organic
matter) of the effluent stream.

Two approaches, distinguished by their initial focal point, can be used
to regulate emissions of fine particulates from stationary sources:

1.  Ambient air quality standards expressed in terms of fine particulates,
and

2.  Direct reduction of emissions from specific sources.

The ambient air quality approach requires as an initial step a statement
specifying the desired objective in terms of atmospheric concentration,
e.g., so many micrograms per cubic meter of total particulate plus a
limitation on the contribution to total weight accounted for by particles
of given diameter(s).  The second step requires determination by measure-
ment of existing ambient concentrations of particles of given diameter (s).
From the information developed in these two steps, a ratio can be derived
describing the fraction by which present emissions must be reduced to
achieve the ambient standard.  The final step requires development of
data showing existing rates of emission from sources and the formulation
                                   53

-------
of emission reduction plans derived by  application of the ratio obtained
in Step 3.

The second approach  focuses attention on  the  direct reduction of emissions
from specific  sources, without  initial  recourse  to ambient air quality.
This approach  is based on the premise that, to the extent feasible, fine
particulates should  be prevented from entering the atmosphere without
initial consideration of  the ambient  air  quality.  Measurements of changes
in ambient air quality before and after the initiation of control activi-
ties provide an indication of the overall effectiveness of the control
effort.

Before an approach based  on ambient  air quality  could be utilized effec-
tively, data on (1)  existing ambient  air  quality as a function of particle
diameter(s) and (2)  existing rates of emission must be available from
numerous regions throughout the country.   Acquisition of such a data base
would require  the expenditure of a great  deal of time and money.  A signi-
ficant time lag would also occur before efforts  to control fine particu-
late emissions could commence if this approach were selected.

If it were decided to initiate  efforts  to control fine particulate emis-
sions in the near future, direct reduction of emissions from specific
sources could  be started  immediately.  Although  the existing data base
on emissions of fine particulates from  stationary sources is lacking in
detail and precision, it  could  be used  to formulate initial emission
reduction programs.  As more and improved information on emission rates
becomes available, the emission reduction programs could be refined.

The effectiveness of any  program for  the  control of fine particulate emis-
sions must ultimately be  judged by improvements  in ambient air quality.
Because both atmospheric  conversion  processes (chemical and physical)
and sedimentation contribute to the  fine  particulate burden in the atmos-
phere, it may  be quite difficult to  relate atmospheric fine particulate
levels to control activities on specific  sources.  The City of Los Angeles
is a good example of this situation.  In  Los  Angeles about 35% of the ambient
particulate burden is formed in the  atmosphere from gaseous pollutants
(see Table 13)  .^J In cities like Los  Angeles, a  program based on ambient
air quality might not be  very effective.   Atmospheric processes might
also make interpretation  of the overall effectiveness of direct regula-
tion of sources difficult in some cases.   For example, in Los Angeles
reductions in  emissions of fine particulates  from stationary sources
would not result in  a proportionate  decrease  in  ambient fine particulate
concentration. While the assessment  of the overall effectiveness of direct
regulation of  sources may be difficult  in some cases, the total burden of
                                  54

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          Table 13.  ESTIMATED CONCENTRATIONS OF LOS ANGELES
                          AEROSOL PARTICLES BY SOURCE**!/
                                (Annual Average)
                                                     Mass Concentration
                Source
Natural background
  Primary ............................. 14-26
    Dust rise by wind                               8-20
               Na+                                     3
    Sea salt   cl_                                     3
    Spores, pollen, etc.                r           Unknown
  Secondary ............................  4-7
    Vegetation (organic vapors)                     3- 6
    Biological (soil bacterial action,
      decay of organics) -NH3, NOX, S .  .  .             0.7
                                                                       36
Man-made

Motor vehicles
Organic solvent usage
Petroleum
Aircraft
Combustion of fuels
Other


Reactive hydrocarbon vapors
N03 *
S04


15
6
1.3
4
5
5


11
13.5
14.4
                                                                       39
                 Total Accounted For                                93-108
                   Measured Total                                    119
                              55

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fine particulates entering the atmosphere would nonetheless be reduced by
direct limitation of  source emissions.  In the case of potentially hazard-
ous pollutants, which in many instances are really fine particulates,
direct regulation of  source emissions  is the only viable approach.  The
Environmental Protection Agency has  already set a precedent in this area
by adopting emission  standards for sources of mercury, beryllium and as-
bestos.  The preceding discussion indicates that direct reduction of fine
particulates from specific sources is  the most effective method to insure
reduction of the fine particulate burden emanating from man's activity.

In the development  of programs for the direct reduction of emissions from
specific sources of fine  particulates, a decision must be made regarding
whether to limit regulation efforts  to primary particulates or whether
both primary and secondary particulates emitted from  sources will be
subjected to regulation.  Primary particulates are defined as material
that is emitted from  the  source or its exhaust stack  in a particulate
form.  Secondary particulate  is defined as particulate matter formed
(primarily by physical processes, e.g., condensation) in the atmosphere
from source effluents shortly after  emission from the source or its
exhaust stack.  These secondary particulates are not  the particulates
formed in the atmosphere  from gases  and existing particles.  As noted  in
Chapter 3, some of  the potentially hazardous pollutants may be emitted
from specific sources as  a vapor which subsequently condenses into a fine
particulate in  the  atmosphere shortly after exit from the stack or ex-
haust point.  Although cause-effect  relationships  for health effects as-
sociated with fine  particulate pollutants  are  not quantitative, efforts
to regulate fine  particle emissions  from  stationary sources should be
focused on minimizing the impact  of  fine  particulate  pollutants on human
health.  In general,  this stipulation requires control of both primary
and secondary particulates  in the  nominal  size range  of 0.01-5 um.

The preceding comments serve  to highlight  some of the more important
facts that must be  considered in  the development of effective control
strategies for  fine particulate emissions.  Various approaches that might
be used to regulate fine  particulate emissions from stationary sources
are discussed in  the  following sections of this chapter.

METHODS- FOR REGULATING FINE  PARTICLE EMISSIONS
                                                                i
Because our understanding of the  importance of fine particulate pollution
to man's health and welfare  is in  its infancy, it seems prudent to con-
sider a long-range  regulation strategy based on the adoption and  imple-
mentation of progressively more stringent  regulations for the control of
                                  56

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fine particulates.  Each step toward more effective control of fine
particulates would be based upon improved knowledge of (1) the effects
of fine particulates on human health and welfare; (2) the technical and
economic impact of the more stringent regulations; and (3) the benefits
that would accrue to society from a further decrease in fine particulate
pollution.  Three time-frames that might be considered are:

1.  Regulations that can be proposed and implemented in the near term
(i.e., by 1975).

2.  Regulations that can be proposed and implemented in an intermediate
term (i.e., 1980-1985).
        j
3.  Regulations that can be proposed and implemented in the long term
(i.e., by 1990).

Any method(s)  selected for regulation of fine particulate emissions
should be chosen to facilitate interfacing with existing strategies for
the control of particulate pollutants.  Since the effluent or emission
standard is the backbone of current control programs, interfacing fine
particle control efforts with existing programs would be facilitated by
the use of emission standards as the main tool in the regulation of fine
particulates.  Other methods that could be used to prevent or regulate
fine particle emissions include:  (1) tax incentives; (2) process modi-
fications; (3) substitution of ingredients or fuels; and (4) cessation of
processing operations that emit fine particles.  The last alternative is
deemed untenable except in very special situations.  Each of the other
methods is a viable approach, although methods (2) and (3) are probably
limited in the extent to which they can be used.
           ,                               t
As noted in the preceding paragraphs, a precedent exists for utilizing
emission standards as the main method for control of fine particulate
emissions in the near term.  Current programs for the control of particu-
late pollutants are built around emission standards, and minimum disrupt-
tion in control agency activities would occur if similar methods were
used for fine particulates.  In the intermediate to long term, the un-
availability of sufficiently high efficiency control equipment and adequate
source compliance monitoring methods and/or'instrumentation may limit the
utility of emission standards, especially if fine particulate or specific
components of fine particulate emissions must be controlled to a very high
degree.  Alternative regulatory strategies based on tax Incentives, might
                                     57

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be attractive in  that  event.   Both  positive*  and negative"1" tax incentives
could be considered, but  the  negative  incentive in the form of an effluent
tax is deemed more beneficial.   The negative  tax incentive, in the form
of an emission  or effluent  tax,  has attracted some support recently.  The
proposal for charges on sulfur dioxide emissions is  an example.

BASIS FOR  EMISSION  STANDARDS  FOR FINE  PARTICULATES

Emission standards  for the  control  of  fine  particulates  could be based
on concentration  of  fine  particulates  in an effluent stream, collection
efficiency of control  equipment, plume opacity, mass-emission rate of
fine particulates,  and hazard potential of  the particulates.

Standards  based only on concentration  of fine particulates in an effluent
stream have a very  significant deficiency;  namely, they  generally ignore
the volume of gas emitted from a source.  As  a consequence, such stand-
ards would not  control the  total fine  particulate pollutant discharge
from a specific source unless they  incorporated considerations of the
size of sources along  with  a  specification  of the allowable fine particu-
late grain loading.  An extensive data base relating particle size and
grain loading to  source size  would  need to  be developed  before this
approach could  be implemented.

The requirement of  a specific collection efficiency  in given particle
size ranges,  and the  installation  of   the  best installed  control"*"
device"1""*" on all sources in a  specific  category, are  two  examples of stand-
ards based on the collection  efficiency of  control equipment.  Combined
with a limitation on the  total mass emission  for a specific source, such
an approach has  merit.  An emission standard combining those facets
would limit both  the total  mass emitted as  well as the mass in the fine
particle size range.   The lack of reliable  data  on  the  efficiency  of
control  equipment  as  a function of  particle size  (i.e., fractional
efficiency) might make it difficult to utilize the approach of designat-
ing the collection  efficiency in specific size ranges.   The alternative
of requiring the  installation of the  best  installed control on sources
is somewhat analogous  to  extending  new source performance standards to
all sources in  a  specific categoryi A standard utilizing this approach
*  Positive  tax incentives—include not-only direct  payments  or  subsidies
     but  also  reductions in property taxes,  accelerated depreciation and
     tax  credits.
+  Negative  tax incentives—this category includes effluent charges or
     fees for  the  discharge of specific amounts  of pollutants or other
     taxes on  specific sources of pollution.
++ Best installed  control device is not necessarily  the highest  efficiency
     device  available,  but rather the best that  is generally  being in-
     stalled at present time.

                                  58

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might be expressed in terms of a maximum allowable total mass emission
and a minimum allowable control device collection efficiency.  Since a
standard based on the specification of control device collection effi-
ciency requires the same degree of control for large and small sources,
a distinct possibility of undue regulation of small sources and insuf-
ficient regulation of large sources might occur with this type of regula-
tion.  However, with some adjustment to account for plant size, a standard
based on the installation of the best installed control devices on  all
sources in a specific category is a potential vehicle for the regulation
of fine particulate emissions.  Determination of the effectiveness of such
an emission standard would require extensive source testing.

Because the opacity of a plume is a function of the size of entrained
particulate matter, and particles in the size range 0.1-1.0 um have the
dominant effect on plume opacity characteristics, plume opacity regula-
tions provide a vehicle to control fine particle emissions.  Since  opacity
regulations are currently utilized by many regulatory agencies, no  prob-
lems would be encountered in interfacing with current particulate control
programs.  The trend in opacity regulations is toward 20% opacity*!!/--a
regulation of 10% or 570 opacity could be used as a more stringent opacity
regulation.

Mass-emission regulations provide a direct approach to the control of
fine particle emissions.  Regulations based on mass emissions could be
formulated to control the quantity of material emitted in specific size
ranges, and could be based on either process-weight rate or on potential-
emission rate.  Process weight regulations specify the maximum allowable
discharge rates for particulates in pounds per hour in relation to the
process weight in pounds per hour.  Process weight is defined as the
total weight of all materials introduced into a process, except liquid
or gaseous fuels or combustion air, divided by the time in hours to com-
plete the process.  Process-weight regulations generally are formulated
so that the absolute allowable discharge increases with increasing process
weight.  However, the percentage of process material which is permitted
to be discharged decreases as the process weight increases.

Emission standards can also be formulated to specify maximum allowable
emission rates  (Ib/hr)  of fine particulate as a function of the fine
particulate emission potential of the source  (Ib/hr) .  The potential
emission rate is defined as the total weight rate at which fine particu-
late matter is, or in the absence of an air-cleaning device would be,
emitted from an air contamination source when such source is operated at
its maximum rated capacity.
                                   59

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The potential-emission rate concept appears to be a direct and useful
basis for formulating standards  to control the emission of fine particu-
late pollutants.  This approach  should result in a better understanding
of the main parameters that influence fine particulate emissions from
specific sources.  Once  the potential rate of emission of fine particu-
lates is established for various sources, allowable emission rates can
be set to tailor  the control  of  fine particulate  emissions to any
desired level.

Our analysis has  indicated that  the most promising bases for emission
standards for  fine particulates  are:   (1) plume opacity; (2) minimum
collection efficiency for fine particulates; and (3) potential emission
rate concept.   Each of these  is  discussed in more detail in the follow-
ing sections.

Plume Opacity  Standards

The opacity of a  particulate  emission depends on the mass concentration
of the particles  comprising the  plume,  their size distribution and physi-
cal properties such as density and refractive index.  Other parameters
such as plume  width and  wavelength of  incident  light are also important
in determining opacity.   It is the dependence of plume opacity on mass
concentration  and particle size, especially in  the 0.1-1.0 urn size range,
which makes it possible  to control the  emission of fine particulates by
controlling the opacity  of the exhaust  plume.
                                                    i
As previously  noted, Ref. 65  indicates  that the trend in plume opacity
regulations is toward 20% opacity.   Standards based on 10% or 5% (i.e.,
essentially no visible emission) could  be used  to reduce the emission of
fine particulates.  The  use of opacity  regulations to control fine par-
ticulate emissions involves some subtleties, and care will have to be
taken in order to develop useful regulatory programs.  A brief review of
the mathematical  expressions  used to define plume opacity is given in
Appendix C, and this review delineates  some of  the important implications
regarding the  use of opacity  regulations.

Because of the strong dependence of plume opacity on factors such as the
optical properties of the particulate-matter, each source under scrutiny
must be described in detail before plume opacity has practical meaning.
This fact is illustrated by Figure 9.£§/  Figure 9   presents plume
opacity as a function of particle diameter and  dust loading for particles
with a density of 2 g/cm^ and for 5 ft  dia.. stacks with exit temperatures
of 300°F.
                                  60

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100 r-
 80   -
U
LLJ
Q_
 •v
>-
h-
u
60  -
40   -
20  -
   0.01
                                                     QE = 2  for dp > 0.14
                                                     QE = 3.26(dp)l/4<0.14
                                                     Stack Diameter = 5 FT
                                                     Particle  Density = 2g/cc
                                                     Exit Temperarure = 300° F
                                                        Dust Loading
                                                         .25 Grains/SCF)
                      0.05    0.10             0.50   1.0
                       AVERAGE PARTICLE DIAMETER (MICRONS)

                      Figure 9.   Plume  opacity as a function of particle—'
                                       diameter and dust loading
10.0

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A fairly stringent standard  for grain  loading  is 0.05 grain/scf.   From
Figure  9 it  is noted  that  if the  particulates are large enough that
the average is  greater  than  5 um  or so,  an  opacity requirement of 2070 is
not strict compared  to  the 0.05 grain  loading  requirement.  If the average
particle diameter is 1/2 um  or so,  a 20% opacity requirement would be
more strict.  In order  to accomplish the desired control of fine particu-
lates via the regulation of  plume opacity,  it  may be necessary to develop
regulations that require a different plume  opacity for various sources.

More refined information on  particulate  properties will be required in
order to develop effective strategies  for control of fine particulates
via opacity regulations.  A  more  comprehensive data base will also be
needed  to develop acceptable source compliance monitoring techniques.
Requirements for source monitoring  will  be  discussed further in Chapter 5.

Minimum Collection Efficiency for Fine Particulates

An emission standard which designates  a  minimum collection efficiency
for fine particulates in combination with a limitation of total emission
as a function of source size could  serve as a  vehicle for the control of
fine particulates.   A collection  efficiency standard alone is not a
viable  approach because it would  not directly  limit the total mass of
fine particle emissions.  The minimum  collection efficiency could be
achieved by (1) specifying minimum  collection  efficiency in designated
particle size ranges, or (2)  requiring the  installation of the best
installed control device on  all sources  in  a specific category.

An emission standard incorporating  minimum  control efficiency in specific
particle size ranges could be designed to provide not only control of
fine particulates in general but  also  control  of specific chemical constitu-
ents of the fine particulate stream.   The Bay  Area Air Pollution Control
District (San Francisco, California) has entertained discussions regarding
the feasibility of modification of  their Regulation 2 regarding particulate
emissions to incorporate minimum  collection efficiency in designated par-
ticle size ranges.   The suggested modifications would supplement Regulation
2 with  a new type of performance  standard based on minimum control effi-
ciency  in particle size ranges as follows: 227

                 Efficiency                      Particle
                 (weight 7,)              '       Size Range

                      99                       10 urn or larger
                      97                         3-10 um
                      92                         0-3
                                  62

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The above performance standard is but one of an almost unlimited number
of standards that could be formulated using the basic concept of desig-
nated efficiencies as a function of particle size.  Tailoring of a regu-
lation for a specific source category is an obvious possibility with this
type of standard.  A considerable amount of data on particle size and
other effluent characteristics would have to be developed to show what
collection efficiencies are practical in various size ranges below about
2 um.

An emission standard utilizing the requirement of installation of the
best installed control technology on all sources in a specific category
would in effect specify the minimum allowable collection efficiency on
a total mass basis.  Since the collection efficiency on a total mass
basis is the summation of efficiencies for all particle sizes, control
of particles in specific size ranges would be achieved by this approach.
In terms of existing technology for control systems, this approach would
also represent the current practical limit of an emission standard based
on designation of minimum control efficiency in specific particle size
ranges.  Determination of the effectiveness of a standard requiring the
installation of the best installed  control technology  would require
extensive source-testing in order to develop accurate data on control
device fractional efficiencies for a spectrum of sources of fine particu-
late pollutants.

Mass-Emission Regulations

The use of emission standards which limit the quantity of fine partic-
ulate emitted from specific sources is the most direct approach to
regulating fine particulate emissions.  Process-weight rate,  potential
emission rate,  or parameters that reflect source size (e.g.,  heat input
in 106 Btu/hr)  could form the basis for this type of regulation.   In
the latter category, the New Mexico Environmental Improvement Board has
taken a pioneering role and has adopted a regulation for coal-burning
equipment that is aimed at regulating fine particulate emissions  from
that type of source.  The New Mexico regulation reads as follows:

     "After December 31, 1974, no person owning or operating  coal-
      burning equipment shall permit,  cause, suffer, or allow:

     "1.  Particulate matter emissions to the atmosphere in excess
      of 0.05 Ib/million British thermal units of heat input; or

     "2.  Fine particulate matter emissions of less than 2 um equi-
      valent aerodynamic diameter and unit density to the atmosphere
      in excess of 0.02 Ib/million British thermal units of heat input.
                               63

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     "Fine parttculate matter emissions for this regulation shall be
      collected and measured at  stack conditions and in such a manner
      that no condensation  of gaseous material is included with the
      sample."

Pro cess-weight rate regulations  are currently used as an integral part
of many air pollution control programs.  Historically, process-weight
rate regulations have been  developed from data obtained from well-con-
trolled and well-operated plants.  Source testing data acquired from such
plants form the basis for determining the degree of control that is tech-
nically and economically feasible.  To utilize this type of regulation
to reduce the emission of fine particulates, it will be necessary to have
accurate data regarding:

1.  Quantity of particulate emitted from various well-controlled sources;

2.  Particle size  distribution of  the particulate emitted; and

3.  Fractional efficiency characteristics of various control devices.

Currently available data in the  above areas are inadequate for the formu-
lation of effective emission  standards.

With regard to the regulation of fine particulate emissions, process-
weight rate may not be a good basis for an emissions standard because
the quantity of fine particulate emitted from a source may not be directly
related to process weight.  Available data suggest that factors such as
nature of ingredients, processing  conditions, and equipment and hooding
and ducting configurations  have  a  much stronger influence on fine particu-
late emissions than does the process-weight.

The concept of potential-emission  rate offers an alternate basis for
emission standards to regulate fine particulate pollution.  Regulations
based on this concept establish  emission limits which vary with the pol-
lution potential of the  source,  e.g., limitation of mass rate of emis-
sions in Ib/hr as  a function of  potential-emission rate, also Ib/hr.
This type of regulation  appears  to be adaptable to sources of fine par-
ticulate pollutants.  Three variations of the potential emission rate
concept are depicted in  Figure  10.

1.  Specification  of the minimum efficiency (on a mass basis) of collec-
tion of the potential emission of  less than 2 \ua particulates.  Curves
A, B, C, and D, in Figure 10, represent four of the many collection effi-
ciency regulations that  could be utilized.  Curve C, 99 wt % collection

-------
ON
Ln
                                                                                                                    90wt%(A)
                                                                                                                     95 wt % (B)
                        1,000 —
                                                                                                                       99«t%(C)
                                                                                                                        99.9 «t % (D)
                                                                   100                  1.000

                                                          POTENTIAL EMISSION RATE OF LESS THAN 2 MICRON PARTICULATE (Ib/hi)
                                                                                                           10.000
100.000
                        Figure  10.   Representative  emission standards  based  on potential emission rate

-------
efficiency for less than  2 urn particulate, represents the probable up-
per limit of efficiency for currently available control equipment.  This
variation actually corresponds to  the minimum collection efficiency con-
cept previously discussed  with potential-emission rate as the basis.

2.  Direct limitation of the quantity (i.e., pounds per hour) of less
than 2 jam particulate that can be  emitted from any source without con-
sideration of the emission potential of any specific source.  Curves E
(100 Ib/hr allowable emission rate) and F (10 Ib/hr allowable emission
rate) are representative of this type of regulation.

3.  Regulations based on a sliding scale of allowable emission as a
function of potential emission.  The sliding scale is adjusted to force
sources with large emission potential to use higher efficiency collec-
tion methods than sources  with smaller emission potentials.  Curves G,
H, and I are representative of this form of regulation.

Potential-emission rates of fine particulates for specific sources could
be determined by sampling  the uncontrolled effluent gases, and source
compliance could be determined by  measuring control equipment efficiency.
Alternatively potential-emission rates could be assigned to sources
through use of pre-established emission factors for fine particulates.
Because an emission factor ideally represents the average measured emis-
sion rate from a number of similar installations, the use of such factors
is a logical and equitable substitute for determining potential-emission
rates for each individual  source.   Since currently available data are
inadequate, an extensive data base would need to be developed before this
concept could be implemented.

EMISSION STANDARDS SELECTED FOR EVALUATION

Our analysis of the alternative routes for emission standards for fine
particulates 'led to the following  observations:

1.  The use of standards involving plume opacity is the most practical
means for controlling fine particulate emissions in the near term.
Standards based on plume opacity would require the least amount of addi-
tional data acquisition and they would readily interface with existing
air pollution control programs.

2.  An emission standard based on  the requirement of the installation of
the best installed technology on all sources in a specific category
                                  66

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could be implemented in the intermediate term.  A standard of this type
would represent the attainment of the current practical limit of control
equipment performance.

3.  A mass emission regulation based on the potential emission rate
concept is a very attractive approach for the long term.  A regulation
of this type could be tailored to the control of specific sources or
specific pollutants.

The technical and economic implications of these types of emission
standards are analyzed in Chapters 5, 6, and 7-
                               67

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                            SECTION VII
    TECHNOLOGICAL  IMPLICATIONS  OF  FINE PARTICLE EMISSIONS REGULATIONS

INTRODUCTION

Implementation  of  any  regulation(s)  for  the  control of fine particulate
pollutants  from stationary  sources requires  the availability of technology
in two distinct areas:

1.  Control equipment,  and

2.  Compliance  testing and  monitoring.

In selecting  a  regulation for the  control of fine  particulates, it  is
necessary that  the regulation be realistic in the  sense  that control tech-
nology must be  available to permit the requisite collection of  fine par-
ticulates.  In  addition, methods must be available to ascertain whether
or not specific sources are in compliance with the regulation(s).

REQUIREMENTS  FOR CONTROL EQUIPMENT EFFICIENCY

Regulations to  control the  emission  of fine  particulate  pollutants will
require the use of high-efficiency control equipment.  Depending upon the
type of regulation adopted,  the performance  capability of control systems
may -be stretched to the limit of existing technology.  An analysis of the
collection  efficiency  required  to  meet stringent plume opacity regulations
provides an indication of the level  of performance that will probably be
required.                                ,

The translation of an  opacity regulation into  terms ofL,the overall mass
efficiency  required of control  equipment necessitates the use of a rela-
tionship between plume opacity  and various particulate and source char-
acteristics.  Ensor and Pilat have 'developed a procedure to calculate
plume opacity from plume diameter, particle  size distribution, particle
mass concentration,  average  particle  density,  and particle refractive
                                 68

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index.(Also see Appendix C.)  Equation(4) presents the relationship
developed by these authors to calculate the expected mass concentration
for various values of plume transmittance (or opacity), average particle
density, and plume diameter.
                           W = -K p/L In (I/I0)                      (4)


In Eq.  (4),

       W = Total particulate mass concentration (i.e., grain loading) at
             stack conditions

       p = Average particle density

       L = Diameter of plume

    I/I0 = Light transmittance

         _ Specific particulate volume
             Extinction coefficient

The assumptions and simplifications involved in the derivation of Eq. (4)
are discussed in Ref. 68.  Although Eq. (4) is not exact, it can be
utilized to determine, with sufficient accuracy for the present purpose,
the total particulate mass concentration corresponding to various combina-
tions of p, L, K, and I/IO values.

The parameter K is a function of the particle size distribution, the re-
fractive index of the particulate, and the wavelength of incident light.
Reference 67 presents graphs of K vs the geometric mass mean particle radius
with the geometric standard deviation of the particle size distribution
and the refractive index of the particles as parameters.  A wavelength of
light of 0.55 u was used as an average for visible light.  This is approxi-
mately  the wavelength of maximum sensitivity for the human eye.  Equation
(4), combined with the graphs for the parameter K, and information on ef-
fluent properties from specific sources of particulate pollution presented
in Ref.  62, was used to develop the control efficiency vs plume opacity
data presented' in Table 14.

The selected values of plume opacity (20%, 107o and 570) correspond to
Ringlemann No. 1, No. 1/2, and "no visible emissions."  The total mass ef-
ficiency required for a control device to reduce plume opacity to these
                                  69

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Table 14.  CONTROL DEVICE EFFICIENCY REQUIRED TO ACHIEVE VARIOUS PLUME OPACITY LEVELS


K f L
Source (cm3/m2) (g/cm3) (meters)
Coal-fired 0.64 2.0 2
power plant

5


10


Basic-oxygen 0.20 3.5 2
furnace

5


10


Cement plant — 1.1 3.0 2
rotary kiln

5


10


Asphalt plant— 10 2.6 2
rotary dryer

5


10



Grain Loading at Inlet to
Plume Opacity Control Devices (gi/Bcl)
(I/Ioi 70 Low Average High
20 1.0 3.0 6.0
10
5
20
10
5
20
10
5
20 2.0 5.0 10.0
10
5



20
10
5
20 1.0 6.4 17.0
10
5
20
10
5
20
10
5
20 10.0 30.0 70.0
10
5
20
10
5
20
10
5
W
Grain Loading at Exit
of Control Device
(Rr/scf)
0.09
0.037
0.02
0.036
0.017
0.008
0.018
0.0085
0.004
0.07
0.033
0.016
0.028
0.013
0.006
0.014
0.007
0.003
0.30
0.15
0.069
0.12
0.06
0.0275
0.06
0.03
0.0138
1.70
0.81
0.39
0.68
0.32
0.16
0.34
0.162
0.078
Total Mass
Efficiency Required
for Control Device (%)
Low
Inlet
91.0
96.3
98.0
96.4
98.3
99.2
98.2
99.1
99.6
96.5
98.3
99.2
98.6
99.3
99.7
99.3
99.7
99.9
70.0
85.0
93.0
88.0
94.0
97.0
94.0
97.0
98.7
83.0
91.9
96.1
93.2
96.8
98.4
96.6
98.4
99.2
Average
Inlet
97.0
98.8
99.5
98.8
99.4
99.7
99.5
99.7
99.9
98.6
99.3
99.7
99.4
99.7
99.9
99.7
99.9
99.94
95.5
97.8
99.0
98.1
99.0
99.6
99.1
99.5
99.8
94.3
97.3
98.7
97.7
98.9 •
99.5
98.9
99.5
99.7
High
Inlet
98.5
99.3
99.7
99.4
99.7
99.9
99.7
99.8
99.9
99.3
99.7
99.8
99.7
99.9
99.94
99.9
99.9
99.97
98.2
99.2
99.8
99.0
99.7
99.9
99.7
99.9
99.95
97.6
98.8
99.4
99.0
99.5
99.8
99.5
99.8
99.9

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values is shown in Table 14 for various values of the inlet grain loading
to the control device and plume diameter.  The range of inlet grain load-
ings for specific uncontrolled sources was taken from data in Ref. 68.
The plume diameters were arbitrarily chosen to represent a spectrum of
diameters.

Inspection of the data in Table 14 indicates that a plume opacity limita-
tion of 20% (Ringlemann No. 1), which is the current trend in opacity
regulations, would require an efficiency ranging from 94-99.5% on a total
mass basis for sources with an average inlet grain loading.  That degree
of collection efficiency represents control equipment of medium to high
efficiency.  A plume opacity limitation of 10% would require a collection
efficiency of 97-99.9% for sources with an average inlet grain loading.
If a 5% plume opacity limitation were imposed, sources with an average
inlet grain loading would be required to control emissions to a level of
99-99.9% efficiency.

Compliance with a 10% or 57» plume opacity standard would require the use
of high-efficiency control systems which approach the limits of current
technology.  The capability of current control equipment obviously places
a constraint on the degree of reduction of fine particulate emissions that
can be achieved by any type of emission standard in the near term.  The
status of existing and emerging control technology for fine particulates
is discussed in more detail in the following sections.

CAPABILITY OF CONTROL TECHNOLOGY

The current capability of control equipment to collect fine particulates
is of immediate concern, while the potential of new control methods or
emerging technology is of importance with regard to regulations that might
be devised for the intermediate to long term.   Appendix A presents a de-
tailed review of existing and emerging control  technology,  and only the
major points of the review are presented in the following sections.

Capability of Existing Control Equipment

Four basic types of control devices (electrostatic precipitators, wet
scrubbers, fabric filters, and afterburners) can currently be used to col-
lect fine particulates.  Afterburners have limited utility since the par-
ticulate must be combustible in order to employ this type of control device.
The fabric filter is usually considered to offer the highest collection
efficiency; for the greatest number of sources.  However,  it is not ap-
plicable to some sources of particulate pollutants because of the nature
of the particulate, or the high cost involved in conditioning the gas
stream.
                                  71

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The ability of control devices to collect participate matter, and especially
the fine particles, is commonly expressed in terms of their fractional ef-
ficiency.  MRI has accumulated much of the available data on the fractional
efficiency of control devices.  Analysis of these data (as explained in
Appendix A) has resulted in the generalized fractional efficiency graph
shown in Figure 11.  The curves shown  in Figure 11 indicate the efficiencies
that may be expected for the basic types of control devices as a function
of particle size.  There are, however, several variations in design of
those control devices which is one reason for the broad ranges  in  ef-
ficiency and may be the reason why reported efficiencies for specific de-
vices are not necessarily  in agreement with these curves.

A comparison of the efficiency data presented in Figure 11 and the total
mass efficiency required for control  devices to meet stringent opacity
regulations (10% or 5% opacity, Table 14) shows that only high-efficiency
electrostatic precipitators, Venturi  scrubbers or fabric filters are capable
of meeting the opacity standards.

Achievement of a significant reduction in fine particulate emissions will
require not only the use of high-efficiency control equipment, but also
improvements in the reliability of control equipment.  It is often assumed
that control equipment is  in operation 10070 of the time that a source is
operating.  This is seldom the case,  but data are generally not available
on control equipment operational  availability.  An indication of the po-
tential error in this type of assumption is provided by the results of a
survey reported in Ref. 69 .  In Ref.  69 , Greco and Wynot report the results
of a study dealing with the performance and availability of electrostatic
precipitators of 16 different design  types serving 51 power generating
units of TVA.  The overall weighted average availability was reported to be
92.6% for a 1-year period  of operation.  For most industries the records of
availability have not been reported.

The  availability factor assumes  considerable importance in the control of
fine particulate pollutants.  For  example, an electrostatic precipitator of
99.5% overall mass efficiency which operates only 92.67o of the time a source
operates is really equivalent to  a net efficiency of 92.1%--a reduction of
~- 7.5% in actual collection efficiency.  Reliability will obviously have
to be improved to insure maximum  equipment availability if efforts to con-
trol fine particulates are to be  successful.  More comprehensive maintenance
programs for control equipment will undoubtedly be required.

Another area in which improvements will be necessary in order to achieve
control of fine particulates is the capture efficiency of hooding systems
that are associated with many installations of control devices.  Capture
                                     72

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                       99.99
                                                                                                      i 0.01
co
                        0.01
                          0.01
                                                     FARTICU DIAMETER - MICRONS
                           Figure 11.   Extrapolated  fractional  efficiency of  control  devices

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efficiency of hooding systems that are necessary for many sources such as
metallurgical furnaces  is frequently  estimated to be less than 95%.  If the
control device efficiency is in excess of 997o, the particulate matter which
escapes the hooding system becomes very  significant.

The preceding discussion serves to emphasize  that the control of fine par-
ticulates will require  improvements in all  phases of the technology.  The
major obstacle that will impede control  efforts is the  inherent limitations
in ability of existing  control equipment to collect submicron particles.
Control technology, involving either  improved control devices or particle
conditioning processes, will need to  be  developed if we are to achieve a
significant  reduction  in the emission of fine particulates from station-
ary sources.  Recent work on new control technology is  reviewed in the
next section.

Emerging and New  Control Technology

There are several avenues that might  lead to  improved control of fine
particulates:  (1) development of new or novel particulate control devices;
(2) augumentation of commonly used collection mechanisms by additional
forces which do not approach zero in  the ^  2  urn size range; and (3) utili-
zation of particle conditioning or agglomeration techniques.  The current
status of technology in each of these categories is reviewed briefly in
the following sections.

New or Novel Control Devices - A variety of devices which are claimed to
have high collection efficiencies in  the fine particle  range have been
reported in the technical and patent  literature.ZP_i_Zl/  However, for most
of these devices  the supporting data  for the  claims are often meager,
unavailable, or inconclusive.  Additional testing programs will be required
to determine the  capability of these  devices.

ADTEC system - One of the more promising new  control devices is the ADTEC
system.  The ADTEC system is a wet scrubbing  system that operates on the
conventional Venturi collection mechanism of  inertial impaction, but es-
tablishes the requisite particle-droplet differential velocity by utilizing
waste process heat rather than external  energy.  On the basis of currently
available information,  this system appears  to offer significant improve-
ment in the collection  of fine particles, at  modest energy consumption
rates, where a waste gas is available which contains a  sufficient amount
of thermal energy. Z?_iZ^/

Condensation scrubbers  - Control devices utilizing steam condensation also
appear to offer promise for improved  collection of fine particulates.  The
main areas for utilization of steam condensation appear to be (1) in a
particle conditioning device, and (2) in conjunction with various types of

                              74

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wet scrubbers.  In the former category, a wide variety of condensation
chambers might be designed to achieve growth of particles prior to intro-
duction into a collection device.

Some existing types of wet scrubbers utilize, to some extent, condensa-
tion scrubbing mechanisms and particle growth by steam condensation.  In
a Venturi scrubber, for instance, if the aerosol is saturated in the pres-
sure zone in the Venturi throat, the subsequent expansion (which is sudden
and therefore approximately adiabatic), will cool the aerosol and cause
condensation.  The water tends to condense on the particles and the grown
particles are more readily collected by impaction with the water drop
spray.  If the water drops are colder than the gas, the sweep mechanisms
(i.e., diffusiophoresis and thermophoresis) may also cause the particles
to move toward the water drops.

The main emission sources where the use of condensation mechanisms for
fine particulate removal appear economically attractive are sources that
have wet or saturated gas streams at temperatures on the order of 125°-
175°F or sources with a waste heat stream in which the gas can be saturated
down to 125°-175°F.  Sieve-plate scrubbers may be an attractive configura-
tion that would lend itself to maximization of condensation effects by
utilizing combinations of cold and hot water plates.

Direct steam injection appears to be too expensive if the steam must be
purchased.  If a waste heat stream is available, steam generation from
the waste heat might permit use of a control device employing direct steam
injection.

Charged droplet scrubbers  - The use of charged drops to agglomerate fine
particulates has some potential for transition to commercial equipment.
However, it appears that there is little reason to expect that systems
based on charged drops will represent a breakthrough for collecting sub-
micron particles.  Devices utilizing charged drops may match electro-
static precipitators in performance and may offer advantages in volume
savings over a conventional electrostatic precipitator.  Also, charged
drop scrubbers may be quite attractive for use on sources that emit cor-
rosive and high-moisture content pollutant streams.

Augmentation of Collection Mechanisms - A potentially fruitful avenue to
pursue in order to improve the collection of fine particulates is to aug-
ment commonly used collection mechanisms (e.g., inertia, impaction, inter-
ception) by forces which do not approach zero in the fine particle size
range.  Figure 12 presents the ratio of several forces acting on an aerosol
                                  75

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     10
       8
c
o
 D
6
 O
 0)
&
o
o
    102
     10°
                         •Electrical Force E = 11 Kv/cm
                          and Maximal Surface Change
    10
      r2
    10
      r4
                                      Force 140 dB
                                            Diffusiophoretic
                                            Force Assumes
                                                 107 dynes/cm3
             Thermal Force
             £ = l,000°K/cm
                     I  	I
                                                    I	_J
              10
                ,-2
,0
                          10'
                        Particle Diameter
            Figure 12.  Forces operating on  aerosol  particles
                                   76

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particle to the weight of the particle (gravitational force) for particles
from 0.01-104- um in size.  For particles < 1 ]im the forces shown in Figure
12 are many times greater than gravitational forces.  Thermal, diffusio-
phoretic, electrical and other forces shown in Figure 12 might be used ad-
vantageously for cleaning industrial gas streams containing fine particulates
if devices can be designed and operated with reasonable energy requirements.

Agglomeration of Particles - The agglomeration or coagulation of partic-
ulates could be used as a step in a sequence of operations aimed at con-
trolling the emission of fine particles.   If sufficiently large particles
can be produced, it may be possible to use conventional low-cost techniques
as the final collection step.  Only sonic agglomeration and the agglomera-
tion of charged particles appear attractive.

Coagulation by a sonic field has as its principal advantages its applica-
bility to any aerosol, including those comprised of submicron particles.
The principal disadvantage of sonic coagulation is its relatively high
energy requirements.  A second major disadvantage is the low efficiency of
acoustic coagulators and their inability to handle highly dispersed suspen-
sions.  Even with long residence times, sonic precipitators which incorporate
inertial separators, cannot treat suspensions having particle loadings of
< 0.5-1.0 grains/ft^.  It is therefore necessary to augment highly dis-
persed suspensions with a water mist or other particles to increase the
particle loading and obtain satisfactory separation.

One method of increasing the rate of agglomeration of fine particulates
is to add a bipolar charge, either with or without an externally imposed
field.  To a limited degree, this occurs in a standard electrostatic pre-
cipitator but not sufficiently to permit efficient collection of fine par-
ticulates.  With proper conditions the large electrostatic forces between
particulates can produce a large increase in the rate of agglomeration of
submicron particulates.

The limited theoretical and experimental evidence available indicates that
fine particulates can be coagulated with water mists in a bipolarly charged
mixture on a practical scale.  The resulting agglomerates can then be pre-
cipitated in either a conventional or space-charge electrostatic precipitator.

SUMMARY OF STATUS OF CONTROL TECHNOLOGY

The only conventional control devices capable of significant collection of
fine particulates are high-efficiency electrostatic precipitators, Venturi
scrubbers and fabric filters.  Existing data, as well as theory, on fine
particulate collection efficiency (both on a mass and number basis) of
                                   77

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conventional equipment indicate  that inefficiency in the fine particulate
range is an inherent characteristic of the equipment.  Therefore, definite
constraints will be imposed on the types of emission standards for fine
particulates that can be implemented in the near term.  The inherent limita-
tions of existing control equipment may require that process modifications
or other alternatives be used to meet near-term regulations.

Several physical phenomena exist that suggest possible avenues to improved
fine particulate control.  These include condensation scrubbing, sonic and
charged droplet agglomeration and electrostatics.  In general, their po-
tential for enhancing the fine particulate collection efficiency for con-
ventional control equipment as well as their potential for forming the
basis for a unique collector cannot yet be fully assessed.

REQUIREMENTS FOR COMPLIANCE TESTING AND MONITORING

Emission standards for fine particulates, if they are to be implemented
and enforced, must specify some method(s) whereby the emission of fine
particles can be measured or monitored.  The emission standards selected
for detailed study in this program involve regulation of two characteris-
tics of the effluent stream from a source:   (1) the opacity of the plume;
and (2) the mass of fine particulates emitted.  The method(s) used to
determine compliance with these standards must,' therefore, be able to
accurately measure these characteristics.  Since the ultimate success of
efforts to control fine particulate emissions will be judged, at least in
part, in terms of improvements in ambient air quality, the methods used
to determine rates of emissions from sources should also be compatible
with or relate to methods for determination of particulate concentrations
in the ambient atmosphere.
                   i
A literature review was conducted as part of this program to identify mea-
surement and: monitoring methods that might be useful to determine com-
pliance with emission regulations for fine particles.  The search and
subsequent evaluation activities were directed primarily to methods for
determining plume opacity and manual or continuous methods for determin-
ing the mass concentration of particulates < 3 urn.

Several methods were identified and evaluated.  A listing of the more
promising methods is given in Table 15.  General* comments regarding some
of the major advantages or disadvantages of each method  are included in
Table 15.  In evaluating the methods, cost of the equipment was not an
important criterion, but complexity of the methods was considered to be
important.  The primary consideration, however, was whether the method
                                   78

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  Table 15.  MEASUREMENT AND MONITORING METHODS FOR FINE PARTICIPATES*/
A. .Opacity methods
    Visual
    Transmissometer
B.  Mass emission methods
    Transmissometer
                 Comment

Precision not adequate for 5% and 1070
  opacity regulations.

Recommended method, but not necessarily
  applicable for plumes containing con-
  densed water vapor or for detached
  plumes.  Source and detector must be
  purged with clean air.  Calibration  J
  may be a problem.

                 Comment

Correlation of transmissometer reading
  with concentration is possible, but
  dependent on properties of partic-
  ulate matter.
    Cutoff impactor and filter
    Cutoff cyclone and filter
    Cutoff method and
      piezoelectric crystal
    Cutoff cyclone and beta-tape
Impactors subject to error due to
  pluggage, blowoff, moisture and over-
  loading .

Recommended manual method, but relies
  on single point anisokinetic sample.
  May require use of impingers if ef-
  fluent contains condensible vapors.

Crystal must capture particles and will
  probably require frequent cleaning or
  replacement.  Not applicable for high
  particulate loadings.  Might serve as
  a manual method to eliminate weighing
  of filters.

Offers best possibility of semicon-
  tinuous measurement *
                                 79

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        Table 15.   (Concluded)  MEASUREMENT AND MONITORING METHODS
                            FOR FINE  PARTICULATES
B.  Mass emission methods  (Cone1udedj
    Sonic impingers
    Microscopy
    Light  scattering
             Comment

A simplified manual method, but
  collecting solution must be
  evaporated and weighed.  Might
  possibly be fed continuously to
  Coulter counter.

An accurate method of counting and
  sizing particles, but method is
  tedious and expensive and not
  amenable to continuous monitoring.

Most methods are rather complex.
  They indicate number concentra-
  tion rather than mass concentra-
  tion.
    Electric mobility analyzer
       (Whitby)
    Condensation nucleic counter
    Diffusion batteries  ^

    Lidar

    Holography
Intended for measurement of size
  distribution rather than mass
  concentration.  Development might
  enable use of this method for
  mass concentration.

Similar to light-scattering methods.
  Limited to lower concentrations.
Limited potential.
a/  Compliance monitoring applications only.  Comments not meant to assess
~      suitability of methods for research applications.
                                   80

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was presently developed to the point that it could be used for determining
compliance without serious limitations or disadvantages.  Most of the
methods were judged to have unacceptable limitations.

A number.of other more advanced techniques and methods were also included
in our review.  These techniques include acoustic attenuation, pressure
drop across a nozzle, pressure drop across a filter, unbalance of a
centrifuge, acoustic particle counting, hot-wire anemometry, decrease in
natural frequency of a vibrating band or wire, automatic weighing, tape-
spot photometry, light scattering photometry or nephelometry, lidar,
single- particle light scattering, holography, electrostatic particle
bounce, electrostatic probe-in-nozzle, electrostatic ion capture, and
electrostatic contact charging.  Although some of these techniques may
be useful for other effluent measurements, each has at least one serious
limitation for the monitoring of particulate mass emissions.

A more complete review of most of these methods was conducted by Thermo-
Systems, Inc., under contract from the Environmental Protection Agency.
Their report contains a more complete description of each method and the
advantages and disadvantages of each.l-t'  A summary of this work was also
published in Ref. 75.

The methods selected and recommended for determining compliance with each
type of emission regulation for fine particles selected in Chapter 4 are
presented in the following sections.

Compliance Monitoring Methods for Plume Opacity

Stringent plume opacity regulations will present problems in regard to the
monitoring of sources for compliance with these standards.  The main tech-
nique currently used to determine compliance with opacity standards is to
utilize trained observers.  The "calibrated eyeball" method of judging
densities and opacities of plumes is adequate for the large majority of
situations confronting air pollution control agencies at the present time.
However, visual evaluation of plume opacity will probably not be adequate
to judge compliance with stringent plume opacity regulations (5% or 10%
opacity).

Reproducibility of readings for opacity of plumes is already a problem in
enforcing existing opacity regulations.  Currently,  an observer is required
to reproduce his reading of opacity usually within 10% of actual plume
transmlttance.  The ability of observers to accurately read Ringelmann No. 1
or 20% equivalent opacity has been questioned.Z§/  In response to this ques-
tion, the Bay Area Air Pollution Control District (BAAPCD) has stated that
BAAPCD inspectors can now read Ringelmann No. 1 or equivalent opacity with
an error of ± 1 Ringelmann number .12J  With improved calibration it is believed
                                  81

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that the error can be reduced to ± 1/2  Ringelmann  number.  Thus, aRingelmann
No. 1 (20% opacity) would be read between 1/2  (10%  opacity) and 1-1/2
(30% opacity).  Based on the above comments, an opacity regulation of
20% opacity seems to be the most  stringent regulation that can be en-
forced by use of trained observers.

A trained observer also has difficulty in adequately evaluating a wet
plume or a detached plume.  For an emitted aerosol  that does not change
in the atmosphere except to become diluted with air, relative opacity at
the emission point is a reasonable measure of  the potential effect it will
have on visibility downwind of the source.  But  in  the case of the wet
plume and the detached plume, the apparent opacity  at the emission point
has no relationship whatsoever with the visibility  reduction downwind of
the source.

Many industrial effluents are saturated with moisture at temperatures
above ambient, and in many situations the plume  from such operations will
be highly opaque.  The effluent  from most wet  scrubbers fits in this cate-
gory, and the apparent opacity of the plume bears more relationship to
ambient temperature and humidity  than the amount of pollutant being
emitted to the atmosphere.  Since high-efficiency wet scrubbers are can-
didates for the control of fine  particle  emissions  from many sources, a
problem would exist for a trained observer attempting to judge the com-
pliance of these control systems  with stringent  opacity regulations.

The stack effluent from the burning of high sulfur  fuel oil or high sul-
fur waste gas can very often produce what is known  as a "detached plume"
when the atmosphere is cool and humid.  In this  situation the gases im-
mediately above the emission point may be essentially transparent, but at
some distance downwind of the emission point a plume develops, presumably
from the formation of sulfuric acid droplets produced from mixing cool,
moist air with the 803 in the exhaust gases.

In view of the limitations of the trained observer, instrumental evalua-
tion of plume opacity will undoubtedly be required  if stringent opacity
regulations are imposed.  The best instrumental method currently available
to monitor the opacity of particulate emissions  is  the on-stack transmis-
someter.  Commercial transmissometers with a variety of designs are avail-
                                         *
able for measuring the in-stack  opacity of particulate emissions.  For
these instruments to properly measure the in-stack  opacity and for the
measurement to reflect the opacity of the plume  emitted by the source,
standardization of performance and installation specifications will be
necessary.  EPA has prepared a set of proposed specifications for trans-
missometers and, in addition, has initiated a  program to evaluate the
                                   82

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performance of a commercially available transmissometer as a continuous
monitor of the in-stack opacity, plume opacity and in-stack mass concen-
tration of particulates for several different types of sources.

The Texas Air Control Board has investigated the use of a transmissometer
in over 100 installations in various industrial plants in the State of
Texas.7o?79/  -jhe types of processes investigated include:  (1) alumina
kilns; (b) carbon black furnaces; (c) cement kilns; (d) copper smelters;
(e) fluid catalytic cracking units; (f) glass furnaces; (g) incinerators;
(h) lignite-fired boilers; and (i) instant coffee driers.  Because of the
mostly favorable experience, the State of Texas has amended their regula-
tions to make use of the transmissometer instrument mandatory.  Effective
in December 1973, all industrial processes producing visible emissions
must install a transmissometer instrument on the stack if the total flow
rate is in excess of 100,000 cfm.  Consideration is being given to reduc-
ing this minimum flow rate to 50,000 cfm in order to cover more of the
sources of visible emissions in the State of Texas.

Previous experience has pinpointed some disadvantages in the use of trans-
missometer instruments.  One of the major problems in some applications
occurs in rechecking the zero and span adjustments of the instrument.  How-
ever, recent advances in instrumentation have resulted in the availability
of an instrument with an automatic calibration sequence.Z-L-§2/  Some
problems have also occurred because of dirt in the flue gases depositing
on the optical surfaces of the instrument, giving unrealistically low read-
ings.  If the instrument is readily accessible, cleaning the optical sur-
faces every few hours to insure accurate readings is not an excessive burden
although obviously some labor cost is involved.  However, if the instrument
is mounted several hundred feet up on a stack and is accessible only by an
exposed ladder, frequent cleaning becomes an even greater burden.  This
problem can be reduced by proper design of the installation although it may
never be completely eliminated.  The common practice with a negative pres-
sure stack is to leave a small space between the mating flanges where the
light source is bolted to the pipe which extends through the stack so that
outside air is aspirated into the slot, passes across the optical surface,
and then through the pipe, into the stack, and out the top of the stack.
A similar arrangement is provided on the other side where the bolometer or
other detector is mounted.  With a positive pressure stack, a sparging point
is placed in the flanges and clean air is forced in under pressure to sweep
across the optical surfaces.  Sorae installations of this type have been
quite successful and lens cleaning is only required at very infrequent
intervals, sometimes as long as a month or more.  In other cases, especially
where the particulate matter in the stack is sticky or gummy, these measures
have been only partially successful.  The transmissometer being marketed by
                                    83

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Lear-Siegler, Inc.,  is  equipped with high volume  air  purging attachments
to keep the optical  windows  free  of dirt deposits.  The  purge air  is  sup-
plied by one or  two  blowers  with  filters, depending on pressure conditions
within the stack or  duct.  If  the pressure  is very negative, filters  alone
can be used to clean the  air drawn into the instrument.

As was the case  with direct  visual observation, effluent streams that con-
tain condensed water vapor present operational  difficulties for transmis-
someters.  Experience has shown that these  instruments cannot operate
properly in stacks with an appreciable amount of  condensed water vapor.
Such problems can be avoided by withdrawing a portion of the flue  gas,
passing this stream  through  a  heated chamber to raise the temperature
above the dew point, and  making a measurement in  this chamber, after  which
the sample stream is then returned to  the  stack.ZijJLL/   However, very few
installations of this type have been constructed  and  operated successfully,
and moisture condensation remains a problem in  certain types of industrial
operations.Zz/

Even utilizing variations in transmissometer techniques,  like those described
above, it is still not  possible to representatively measure plume  opacity
in those cases where condensation of hydrocarbons or  other gaseous pollu-
tants occurs beyond  the stack  (i.e., detached plume).  Even  though the
definition of "fine  particulate11  may include these condensing vapors, the
phenomenon occurs in so few  effluent streams and  usually only under such
specific atmospheric conditions that this  situation does not impair the
otherwise wide applicability of the transmissometer method.

In summary, it is our opinion  that the transmissometer has been developed
and tested sufficiently to justify recommending it as a  method that can be
used for monitoring  the opacity of effluent streams in order to determine
compliance with  5% or 10% opacity standards.

Compliance Monitoring Methods  for Mass Emissions

Determination of compliance with an emission standard  based on the utiliza-
tion of best installed  technology or  the  potential-emission rate concept
will require the measurement of the  concentration of  mass of fine  par-
ticulates  emitted for a source.   Because  a measurement of the mass of
fine particulate is  involved in both  cases, one monitoring  procedure  can
probably be developed for use  with either standard.   The specific  require-
ments for  compliance monitoring associated with each  type of standard are
briefly summarized  in the following  paragraphs.

Emission  standards  for fine  particles  based on best  installed  technology
will require a monitoring method which measures the  concentration  (grains/
ft3) of fine particulate  in the inlet  and outlet  of  the  control device.

                                   84

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If the quantity of gas into and out of the control device is significantly
different because of use of dilution air or vaporization of water, etc.,
then it would be necessary to determine efficiency on the basis of pounds
per hour of fine particles at the inlet and the outlet.  This means that
in addition to determining the concentration of fine particles, the gas
flow rate may also have to be determined by a velocity traverse in the in-
let and outlet ducting.  Standards which utilize the concept of potential-
emission rate will require a monitoring method which measures the concen-
tration of fine particulates (grains/ft3) and the total gas flow  (cfm).
Continuous monitoring on both variables would be difficult.

Based on our review of potential methods that might be used in this applica-
tion, we have selected a manual method involving the use of a sampling probe
with a 2 urn cut-off cyclone preceding a filter,  similar to the EPA sampling
train, or an in-stack system as depicted in Figure 13.  This method of de-
termining the concentration of fine particles has the disadvantage of being
a manual method.

This recommended manual method, consisting of a cutoff cyclone followed by
a filter, would need to be modified if "particulates" are defined to in-
clude material that exists as a particle at conditions of standard tempera-
ture and pressure.  The effluent stream may contain condensible vapors
which would not be collected by the filter in the recommended sampling
method if the sampling is conducted at temperatures above standard.   In-
deed, it is desirable to maintain the sampling temperature above the dew
point of the effluent gas stream.  Therefore, when the effluent stream
may contain significant quantities of condensibles,  it will be necessary
to follow the filter with impingers immersed in an ice bath.

A continuous monitoring method would be preferable to a manual method,
but none are available at present that, in our assessment,  would be satis-
factory for monitoring the concentration of fine particles.   The best po-
tential method that might be further developed for this purpose is the
beta-tape device.  Although the beta-tape is a semicontinuous monitoring
method, it does appear to have possibilities for monitoring the fine par-
ticles in a sample stream from a cutoff cyclone  as depicted in Figure 14.2^L/

Several particle collection techniques other than filters can be used with
beta—radiation attenuation.  Among these are impactors and electrostatic
precipitators and possibly thermal precipitators.  Further investigation
is necessary to fully evaluate each collection method for use with the beta
monitor.  Reference 82 reports the results of field and laboratory tests
conducted to evaluate inertial sizing techniques, cascade impactors and
cyclones, for field measurements of control device efficiency as a function
                                     85

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                       Probe

00
ON
                           I
                           S
                                                      Filter
                                     Valve    Flowmeter    Pump
                                       Cutoff

                                       Cyclone
                      Flue Gas
                Figure 13.
Recommended manual method for monitoring compliance of sources

  with fine particle emission regulations

-------
00
                      Probt
                        f
                    Flue Gas
 jr
 Y
Cutoff
Cyclone
                                                                      Output
                                                                      Indicator     Recorder
Geiger-
Muller
Counter
                                                                                   Filter Tape
              Approximately
Beta Source    60 Liters/Minute
                                                              Valve    Flowmeter     Pump
                     Figure 14.   Semicontinuous method  for  monitoring fine particle emissions

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of particle size.  One of the conclusions of  the study was that no single
inertial sizing device was  suitable  for  all the sampling circumstances en-
countered on a wide variety of  stationary emission  sources.  The results
of the work reported  in Ref. 82  suggest  that  it will be necessary to modify
monitoring techniques to suit specific source types.

As noted in Chapter 4, the  State of  New  Mexico has  adopted a fine particle
regulation for coal-burning equipment.   This  regulation limits emission
of < 2 urn particles to 0.02 lb/10^ Btu.  The  following test methods are
recommended by the State of New Mexico.

Method 1 (Manual) - The sample  is first  passed through a cascade impactor
(Andersen type) to remove < 2 ]im particles.   Particulate which escapes the
impactor is collected on the integral filter.

Method 2 (Continuous) - The sample is passed  through the impactor as above,
and particulate which escapes the impactor  is directed to an adhesive-
coated quartz crystal microbalance.

Method 3 - Any method as accurate as Method  1 or 2.

The above Method  1  is similar  to our recommended method except that the
use of a cutoff cyclone  is, we  feel, subject  to  fewer  inaccuracies and is
much more amenable  to continuous sampling.  Method  2 of the New Mexico
Regulation involves  use  of  the  quartz crystal microbalance  (Figure  15).
One possible  problem with the  piezoelectric microbalance  is that particles
must adhere  to  the  surface  strongly enough  to overcome inertial forces of
the vibrating crystal.  Most  testing of this  device has been done on ambient
particles and it  appears  that most particles  smaller than 20 um adhere
well enough  to  be weighted.!^/   This device is relatively new  and untried
in effluent gas  streams  but it  does have the  desirable feature of  high
sensitivity  for direct  sensing  of particulate mass. The  primary problem
with its use  may  be frequent  need to replace  or  clean  the crystal, and
this must be  evaluated  along with testing the applicability on stack ef-
fluents  before  it could  be  recommended for  compliance  testing  or monitor-
ing.  Even  if this  device  is  not applicable for  continuous monitoring,
further  development may  enable its use as. a substitute for  the cutoff
eyelone-filter method,  thereby eliminating  the tedious task of condition-
ing and weighing  of the  filters.
                                                    t
Whether one uses the cutoff cyclone or a cascade impactor for the frac-
tionation of the large and small particles,  it is a requirement  of  both
that a  constant sample flow rate be used.  Because the flow rate  into  the
cutoff  cyclone  (or impactor)  is  fixed, it is difficult to sample  the  stack
                                       88

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  Probe
   (r
   t
Flue Gas
                              Frequency    Oscillator
                  Recorder     Monitor      Circuit
        Particle
        Collection
        Region
Cutoff
Cyclone
       Figure 15.
  Schematic diagram of monitoring
   1 system utilizing quartz
    crystal microbalance
                                89

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gas isokinetically.  However, this may not be necessary because the analyses
are only concerned with the concentration of fine particles in the stack
gas.

Studies of errors in sampling at anisokinetic conditions indicate that it
is rarely  necessary to bother  about isokinetic sampling  for particles
of unit density below about  5 urn diameter.83^86/   Therefore, single
point sampling would be representative.  This conclusion assumes that
problems of air-in-leakage, etc., in stacks which can cause localized
concentration gradients in both the  gases and particulates are negligible.
Unless further experimental study develops evidence to the contrary,
sampling can be conducted anisokinetically at a single point without sig-
nificant error in order to measure fine  particle concentrations by the
methods previously discussed.

The recommended method will determine the concentration of fine particles
and thereby yield the control device fine particle efficiency only if the
effluent flow rate  (SCFM) is the same at the inlet and outlet.  If the
flow rates (SCFM) are significantly  different,  a velocity traverse may
also be necessary.  A velocity traverse  is also a manual method that would
be very difficult to adapt to continuous measurement unless single-point
measurements at the inlet and outlet   were determined to be representative,
and a calibration curve prepared to  enable calculation of total flow based
on velocity at the single point.

If currently available data on particle-size dsitribution of effluents were
used to formulate the fine particle  emission standard, some problems of
equality in enforcement might result during the initial stages of the im-
plementation of a mass emission standard using  the recommended testing
method.  Most of the particle size distribution data currently available,
which would be used to define the potential fine particle emission rate
of sources, has been obtained by a variety of methods, e.g., ASME train-
Bacho sizing, EPA train-Bacho sizing, and cascade impactors.  Measurements
of the mass fraction of fine particles by these methods probably differ
considerably from those which would  be obtained by the cutoff cyclone-
filter method.  Depending upon the extent of discrepancy, it may be neces-
sary to measure fine particles emitted from a source by one of the more
common previously used methods as well as by the cutoff cyclone-filter
method.  When an extensive data base has been developed using the recom-
mended measuring method, it may be appropriate  to modify the emission
standard.
                                      90

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SUMMARY OF RECOMMENDED COMPLIANCE MONITORING METHODS

Presently available methods for determining source compliance are amenable
to use with the three types of emission standards considered for the regu-
lation of fine particulate emissions.  In the case of the opacity stand-
ard, the on-stack transmissometer can be used for continuous monitoring.
For the standard based on best installed technology and the potential
emission-rate, the manual methods of determining fine particle concentra-
tion by cutoff cyclone-filter and total gas flow by velocity traverse can
be used.  It also appears that both of these standards might make use of
beta-tape instruments for continuous monitoring of the concentration of
fine particles, which may be the only measurement necessary for compliance
testing.  Further development of the cutoff cyclone-piezoelectric crystal
method may permit its use as a substitute for the cutoff cyclone-filter
method  to  eliminate filter weighing and provide more immediate results.
                                     91

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            ECONOMIC IMPACT OF FINE PARTICLE EMISSION STANDARDS

INTRODUCTION

Solutions to environmental problems require more than just improved or new
technology.  Economic problems must also be overcome.  The supply of
capital—whether private, corporate or government--is always limited.  It
is, therefore, imperative that the funds that are available are allocated
in a way that will return the greatest benefits per dollar invested.

Adoption of emission standards based on particle size will increase the
capital investment requirements of various industries and raise manufactur-
ing costs by whatever amount is required to operate and maintain the air
pollution control facilities.  In this chapter, estimates of control costs
are presented for selected industrial sources of fine particulates, and a
limited analysis of the economic impact of the control costs on the se-
lected industrial operations is also presented.

The capital and annual costs for control equipment required to meet emis-
sion standards based on particle size were determined using model plants
for the selected industrial operations.  Accurate description of the model
plant for a specific operation requires knowledge of production rates,
emission rates, carrier gas flow rates, effluent particle size distribu-
tion, stack diameter, etc.  Data on the performance capability of control
equipment and the capital and operating costs of control equipment as a
function of collection efficiency and capacity (cfm) are also required.

The following sections of this chapter discuss (1) determination of cost
versus efficiency relationships for control devices, (2) methodology  for
determining costs required for compliance with fine particle emission
standards, (3) potential reduction in fine particle emissions resulting
from implementation of fine particle emission standards, and (4) economic
impact resulting from costs of control equipment required for compliance
with emission standards for fine particles.
                                     93

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DETERMINATION OF COST VS EFFICIENCY RELATIONSHIPS FOR CONTROL DEVICES

During this program, a review  of  the  literature and other available sources
of data on control equipment costs was conducted.  Numerous  installations
of control devices are described  in the  literature and prior EPA studies,
but it is difficult  to obtain  sufficient information to correlate the costs
of individual installations on a  common  basis.

Our analysis of available  information indicated that the most comprehen-
sive analysis of the cost  of control  equipment as a function of capacity
has been presented in the  EPA  publication "Control Techniques for Partic-
ulate Air Pollutants."87/  Figure 16  illustrates typical data from Ref.
87.  The format used in Figure 16 is  not a convenient method of presenta-
tion of data.  Other methods of data  presentation were reviewed, and a
format suggested by Ref. 88 was selected as being the most convenient
for the purposes of the current study.   Reference 88 indicates that for
a given equipment capacity (cfm), equipment costs, either capital or an-
nual ized, plotted as a function of an efficiency factor (E/100-E) yield
useful working relationships for  estimating costs.  The data from Ref. 87
are plotted in Figures 17  and  18  in the  format suggested by  Ref. 88 with
equipment capacities (cfm) as  a parameter.   The data in Ref. 87 (as shown
in Figure 16) present generalized efficiency ranges and only three values
of the nominal efficiency  of each control device can be assigned to the
cost data given in Ref. 87-  It was assumed that a linear relationship
could be used to depict the data  as shown in Figures 17 and  18.

The lines shown in Figures 17  and 18  represent our judgment  of the best
fit of available data for  each equipment capacity (cfm).  In the case of
fabric filters, only one efficiency value is given in Ref. 87 and the re-
lationship of cost to efficiency  is not  known.  It seems probable that
the cost of fabric filters would  increase as the required efficiency is
increased, because the higher  efficiencies  would generally require more
cloth area per cfm (i.e.,  a lower air-to-cloth ratio).  Therefore, we
again assumed that the straight-line  relationship is valid for fabric
filters, and the lines were drawn with an arbitrary slope between that
for electrostatic precipitators (ESP) and wet scrubbers.

It is evident from the above discussion  that the cost vs efficiency re-
lationships (Figures 17 and 18) are based on limited data and that it has
been necessary to make several assumptions  which could lead  to errors in
subsequent calculations.  However, Figures  17 and 18 represent the best
estimations that are possible  based on available information.
                                  94

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           10          50   100          500   1000

           GAS VOLUME THROUGH COLLECTOR, 103 ocfm
Figure 16.  Annualized cost for operation  of high-voltagt
                    electrostatic precipitators
87/
                          95

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         10.0
            50%
                           75%
90%
                                                     95%
                                                                             E
                                                                            99%
               99 5%
                 I
                     99.9%
                       I
                                                                                                  99.99%
                          PARAMETER ON CURVES:  EQUIPMENT CAPACITY IN CFM
VO
        I i.c
                            A FA1MC FILTER
                            O H.ECTROSTATIC PKCIPITATOR
                            D WETSCWMER
          0.1
                      I     I    I
            I      III
I  I  I  I I
I      III
I  I  I  I I
1      I    I   I
                                             10
                                  100
                                   E
                                 100-E
                                                                                                            1.000
                                                                      10.000
                                    Figure  17.    Installed costs for  control equipment

-------
         10.0
            50%
                           75%
                                          90%
                                                     95%
                                                                               E
                                                                             99%
         99.5%
                                99.9%
                                 I
99.99%
                           PARAMETER ON CURVES: EQUIPMENT CAPACITY IN CFM
                            A FABRIC FILTER
                            O ELECTROSTATIC PKCIHTATC*
                            Q WETSCRUHER
VO
          0.1
                                             10
100
 E
                                                                                        J	I	I	I   I  I  I I  I	I      1    I   I   I  I  I I
                                                                                                              1,000
                                                                                                                                              10.000
                                      Figure 18.   Annualized costs for  control  equipment

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METHODOLOGY FOR DETERMINING COSTS REQUIRED FOR COMPLIANCE WITH FINE PARTI-
  CLE EMISSION STANDARDS

The determination of  the  control costs  required  for compliance with various
emission  standards  for  fine particles involves the following major steps:

1.  Development of  model  plants  for  each  industry category.-

2.  Determination of  control-device  performance  required to meet a specific
emission  standard for fine particles.

3.  Determination of  costs for model plant and industry for compliance with
specific  emission standard for fine  particles.

General details involved  in each of  these steps  are discussed in the fol-
lowing subsections.

Development of Model  Plants for Important Industrial Sources of Fine
  Particle Emissions

A review  of the literature and previous EPA  industry studies was conducted
in order  to formulate "model  plants" for  each important source of fine
particle  emissions.   The  objective of this activity was to select an average
or representative size  plant  in terms of  production rate.  Other important
parameters for these  model plants were  carrier gas flow rate and tempera-
ture, emission rate of  particulates, particle size distribution of emitted
particulates, and "best installed control device" (type and efficiency).

In several industries the model  plant consisted  of only one source such
as a coal-fired power plant or a cement kiln.  Other categories were
divided into  two  or three model  plants  because of the  different types of
sources (ferroalloy furnaces).  In still  other cases only one model plant
was selected  but  it consisted of several  different sources and more than
one control device  (primary nonferrous).

It was not possible to  develop model plants  and  carry  out the cost calcula-
tions for all sources because of lack of  information—especially particle
size distribution data.  However,  an attempt was made  to carry out these
calculations  for  the  most important  industrial sources of fine particles
even though it was  necessary  in some cases to make generalizations and
assumptions.
                                    98

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Model plant sizes were selected with the realization that such a generali-
zation does not truly reflect the situation for those plants that are much
smaller or much larger.  However, the primary concern of this study was
the total industry impact so it was felt that use of the model plant was
justified.

Determination of Control Device Performance Requirements

Control equipment costs presented in Figures 17 and 18 are based on the
overall mass efficiency of the control equipment.  In order to utilize these
data to determine costs, the control device performance requirements neces-
sary to achieve a fine particle emission standard must be translated into
overall mass efficiency.  The specific standards that will be considered in
the calculation of costs are: (1) plume opacities  of  10% and  5%, and
(2) utilization of the best installed technology.  Although the potential
emission rate concept offers one of the most direct methods for regulat-
ing fine particle emissions, calculations of control equipment costs were
not performed for this type of regulation because of the need for more
detailed and extensive source testing to determine both potential emis-
sion rates and source compliance requirements.

The techniques used to translate the plume opacity and best installed
technology standards into overall mass efficiency requirements are pre-
sented in the following subsections.

Control Device Performance Requirements for Plume Opacity Standards - An
opacity regulation is perhaps the most difficult to translate into terms
of overall mass efficiency required of control  equipment.  A suitable
relationship between plume opacity and particulate properties and stack
diameter must be used to determine the degree of collection efficiency
required to meet a plume opacity standard.  Ensor and Pilat have recently
developed a procedure for calculating plume opacity from particulate air
pollutant properties.—'   (Also see Chapter 5.)  These authors developed
the following equation to calculate the expected mass concentration for
various values of plume transmittance (or opacity), average particle
density, and plume diameter.

                             W = -K p/L In (I/Io)                     (4)

In Eq. (4),

          W = Total particulate mass concentration of plume (i.e., grain
                loading),

          p = Average particle density,


                                    99

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          L = Diameter of plume,

       I/Io = Light transmittance,

          K _ Specific particulate volume
              Extinction coefficient ratio.

The parameter K is a function of  the particle size distribution, the re-
fractive index of the particulate, and  the wavelength of incident light.
Reference 68 presents graphs of K versus the geometric mass mean particle
radius with the geometric standard deviation of the particle size distribu-
tion and the refractive index of  the particles as parameters.

The grain loading from an uncontrolled  source was determined by using the
effluent flow rate from the model plant, the production rate of the model
plant, and the appropriate emission factor.  Equation (4) was then used
to compute the grain loading of a controlled source corresponding to the
opacity limitation for each model plant.  In some cases the characteris-
tics of the particles (parameters p and K) were not available, and it was
necessary to assume that they were approximately equivalent to other
similar sources for. which the data were available.

When data were available to permit calculation of the outlet grain loading
corresponding to a selected opacity, the efficiency of the control device
required was calculated from Eq.  (5) assuming no dilution of the stack
gases.

       _,,.,...        Inlet Grain  Loading - Outlet Grain Loading      /CN
       Etriciency =  	^	"•      (_j)
                                Inlet Grain Loading

In order to determine, from Figures 17  and 18, the cost of the control
device with the efficiency determined from Eq. (5), it is necessary to
specify the type of control device.  If more than one type of control de-
vice could provide the required efficiency and function on the given
source, the selection of the type of control device was based on knowl-
edge of usual industry practice and lowest cost.
                                 t
Control Device Performance Requirements'for Best Installed Technology
Standard - The emission standard  based  on the installation of best in-
stalled control technology on all plants would require that all sources
in each industrial category be equipped with control equipment that is
at least as efficient as that of  the best control device that has been
installed on each type of plant in recent years.  Our data base was used
to identify this "best installed  control device" (BICD) for each industry
                                  100

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category and its overall efficiency.  This device was not necessarily  the
highest efficiency device available, but rather the best that is generally
being installed in a given industry at the present time.

Costs to Model Plant and Industry for Compliance with Specific Fine  Particle
  Emission Standards

The procedure for determining the costs for compliance with specific fine
particle emission standards is illustrated in detail in Appendix B using
coal-fired power plants as an example.  Only the results of the calcula-
tions will be presented for the various sources in the following subsections,
The annualized costs associated with the control devices were based on
8,000 hr of operation per year.  Not all plants operate that many hours,
and indications of the likely operating hours are given for those industries
which differ significantly from the assumed 8,000 hr/year.

Coal-Fired Power Plants - Table 16 presents the estimated control equip-
ment costs for coal-fired electric utility plants.   An electrostatic
precipitator with an overall mass efficiency of 99% was selected as the
best installed control device (BICD).   The overall collection efficiencies,
computed from Eq. (4) using effluent property data from Refs.  68,60,61
required to achieve the 10 and 5% opacity regulations are 99.66 and 99.83%.
Electrostatic precipitators were chosen as the control devices that would
be used to achieve compliance with the opacity standards.
    •
A comparison of the incremental annualized costs for compliance with the
fine particle regulations is presented in Table 17.   Since  only a small
percentage of electric utility plants  are currently equipped with the BICD,
it was assumed that all existing plants would have to install new control
                         •
devices to meet all the regulations.  The incremental annualized costs
shown in Table 17 for the case where all the electric utility plants are
required to install the BICD are based on the preceding assumption. . The
incremental costs for the opacity regulations represent the difference
between the costs associated with the  opacity regulations and the BICD
regulation.

Estimates of the reduction in fine particle emissions from coal-fired
power plants that would result from installation of control equipment re-
quired for compliance with the emission standards for fine  particles are
also presented in Table 16.   Currently,  fine particle emissions from the
total industry are estimated at 243,000 Ib/hr.  Installation of the best
installed control system on all plants would reduce emissions to 15,000
Ib/hr—a 94% reduction.  Compliance with a 10% opacity regulation would
reduce the emissions to 5,050 Ib/hr (a 97% reduction), while compliance
                                 101.

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Table 16.  CONTROL EQUIPMENT COSTS FOR COAL-FIRED ELECTRIC  UTILITY  PLANTS
I.    Source  description

      Capacity
      Coal burned
                                   Model Plant
400 raw (100% load)
1.2 x 10  tons/year
  at 68.5% load
  factor
                      Industry Total
150,000 raw
258 x 10  tons/year
      Fine particle  emissions
         (a)   Uncontrolled
         (b)   Present

II.   Best installed control
         systemSL'

      Installed  cost
      Annualized cost
      Fine particle  emissions
3,700 lb/hr
                             c/
III.   10% Opacity  regulation-

       Installed cost
       Annualized cost
       Fine particle emissions

IV.    5% Opacity regulation!/

       Installed cost
       Annualized cost
       Fine particle emissions
$1.03 x 106
$0.19 x 106/year
69.1 lb/hr
$1.4 x 106
$0.25 x 106/year
23.5 lb/hr
$1.57 x 106
$0.30 x 106/year
11.7 lb/hr
796,000 lb/hr
243,000 lb/hr
$386 x 10°
$71 x 106/year
15,000 lb/hr
$525 x 106
$94 x 106/year
5,050 lb/hr
$589 x 106
$112 x 106/year
2,510 lb/hr
a/  Quantity emitted depends  on control  device  installed.
b/  Control device required to  meet  standard  is  99% efficient electro-
      static precipitator.
£/  Control device required to  meet  standard  is  99.66% efficient electro-
      static precipitator.
d/  Control device required to  meet  standard  is  99.83% efficient electro-
      static precipitator.
                                102

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             Table 17.  INCREMENTAL ANNUALIZED COSTS FOR COAL-FIRED ELECTRIC UTILITY PLANTS
                                     TO MEET FINE PARTICLE EMISSION STANDARDS
 Emission Standard

All plants install
  best installed con-
  trol device (BICD)

10% Opacity
5% Opacity
      Control System

99% Efficient electrostatic
  precipitator (BICD)
99.66% Efficient electro-
  static precipitator

99.83% Efficient electro-
  static precipitator
                                                                               Incremental Annualized
                                                      Annualized Cost ($/Year)      Cost ($/Year)	
Model Plant  All Plants  Model Plant  All Plants
  190,000    71 x 106
  250,000    94 x 106
  300,000    112 x 106
190,000
 60,000
 50,000
71 x 106
23 x 106
18 x 10(

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with a 5% opacity regulation would further reduce  the emissions to 2,510
Ib/hr (a 99% reduction) .   In making  the  above  estimates of emission reduc-
tions, the control  device  was  assumed  to be  available  and operating at
peak efficiency  at  all  times.

Iron and Steel Plants.  - The costs  for  compliance  with  fine particle emis-
sion regulations were  estimated for  three of the  major sources of partic-
ulate pollutants in iron and steel plants—sinter machines, basic oxygen
furnaces, and electric  arc furnaces.   Open hearth furnaces were not in-
cluded because these furnaces  are  gradually  being phased out  of production.
The cost estimates  for  the three sources are presented separately in the
following sections.

Sinter machine - Estimated control equipment costs for sinter machines are
presented in Table  18.   A  model plant  with a production capacity of 4,000
tons/day (1.46 x 10" tons/year) was  used as  a  basis for the calculations.
Sinter plants in current use in the  industry range in  capacity from 800
to 14,000 tons/day.  For this  source,  10% and  570  opacity regulations would
not require the  installation of control  equipment that is as  efficient as
the best installed  control device  (i.e., a fabric filter system).  Since
only about 19% of the  existing sinter  machines are equipped with fabric
filters and electrostatic  precipitators  are  the prevalent control systems
in use, electrostatic  precipitators  were selected for  compliance with the
opacity standards.

Table 19 gives a comparison of the incremental annualized costs for com-
pliance with the fine  particle regulations.  The  costs given  in Table 19
reflect the fact that  1970  of the existing sinter  machines are already
equipped with fabric filters.

The potential reduction in fine particle emissions resulting  from imple-
mentation of an  emission standard  for  fine particles for all  sinter
machines ranges from 48.5 to 96%.

Basic oxygen furance -  Control equipment costs for basic oxygen furnaces
in iron and steel plants are shown in  Tables 20 and 21.  The  model furnace
selected as the  basis  for  the  estimates  of control costs was  assumed to
have a capacity  of  1 x 10   tons/year or  200  tons/heat.  The costs presented
in Tables 20 and 21 recognize  the  fact that  20% of the existing basic
oxygen furnaces  are already equipped with the  best installed  control device.

Implementation of an emission  regulation for fine particles could result
in a significant reduction in  fine particulate emissions from basic oxygen
furnaces.
                                   104

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    Table  18.  CONTROL EQUIPMENT COSTS FOR SINTER MACHINE  (WINDBOX)
                         (IRON AND STEEL PLANTS)
                                  Model Plant
I.    Source description

      Capacity
      Fine particle emissions
         (a)  Uncontrolled
         (b)  Present

II.   Best installed control
         system^/

      Installed cost
      Annualized cost
      Fine particle emissions

III.  10% Opacity regulation!/
                     t
      Installed cost
      Annualized cost
      Fine particle emissions

IV.   5% Opacity regulation6-/

      Installed cost
      Annualized cost
      Fine particle emissions
4,000 tons/day
116 Ib/hr
   a/
$1 x 106
$227,000/year
1.04 Ib/hr
$770,000
$146,000/year
14.2 Ib/hr
$850,000
$162,000/year
6.9 Ib/hr
                      Industry Total
    <   /•
90 x 10  tons/year

7?150 Ib/hr
1,400 Ib/hr
$49.9 x 10£
$11.3 x 106/year£/
64 Ib/hr
$38.4 x l
7.3 x 106/year£/
722 Ib/hr£/
$42.4 x 10£
$8*1 x 106/year£-/
354 lb/hr£/
aj  Quantity emitted depends on control device installed.
b/  Control device required to meet standard is.a fabric filter.
c_/  Based on fact that approximately .19% of sinter machines are already
      equipped with fabric filter.
d/  Control device selected to meet standard is 98.6% efficient electro-
      static precipitator.
e/  Control device selected to meet standard is 99.4% efficient electro-
      static precipitatqr. .
                                  105

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                Table 19.  INCREMENTAL ANNUALIZED  COSTS  FOR SINTER MACHINES (IRON AND STEEL)
                                       TO MEET  FINE  PARTICLE EMISSION STANDARDS
H
O
    Emission  Standard
     10% Opacity
     5% Opacity
     All  plants  install
       BICD
    Control System

98.6% Efficient electro-
  static precipitator

99.4% Efficient electro-
  static precipitator

Fabric filter
                                                                                    Incremental Annualized
                                                           Annualized Cost ($/Year)        Cost ($/Year)
Model Plant  All Plants  Model Plant  All Plants

  146,000     7.3 x 106    146,000    7.3 x 106
  162,000     8.1 x 106     16,000    0.8 x 106
  227,000    11.3 x 106     65,000    3.2 x 106

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     Table 20.  CONTROL EQUIPMENT COSTS FOR BASIC OXYGEN FURNACES
                       (IRON AND STEEL PLANTS)
                                    Model Plant
                        Industry Total
I.    Source description

      Capacity
      Fine particle emissions
        (a)  Uncontrolled
        (b)  Present

II.   Best installed control
        systemk'

      Installed cost
      Annualized cost
      Fine particle emissions

III.  10% Opacity regulation^/

      Installed cost
      Annualized cost
      Fine particle emissions

IV.   5% Opacity regulation6-/

      Installed cost
      Annualized cost
      Fine particle emissions
1 x 10  tons/year     80 x 10^ tons/year
(200 tons/heat)
10,700 Ib/hr
      a/
$960,000
$163,000/year
32 Ib/hr
$1 x 106
$177,000/year
19 Ib/hr
$960,000!/
$207,000/year
10 Ib/hr
400,000 Ib/hr
 43,600 Ib/hr
$61.5 x
$10.4 x 106/year£/
2,560 Ib/hr
$80 x 106
$14.2 x 106/year
1,540 Ib/hr
$77 x 106
$16.5 x 106/year
800 Ib/hr
a/  Quantity emitted depends on control device installed.
b/  Control device required to meet standard is 99.7% efficiency electro-
      static precipitator.  This is a very high efficiency for an electro-
      static precipitator operating on a source emitting essentially 100%
      < 3 urn particulates, and, in fact, this efficiency is inconsistent
      with fractional efficiency data for electrostatic precipitators.
      However, the particle size distribution at the exit of the furnace
      may not be what the electrostatic precipitator "sees" (i.e., ag-
      glomeration may occur before the particulate reaches the control
      device).
£/  Based on fact that approximately 20% of basic oxygen furnaces are
      already equipped with 99.77. efficiency electrostatic precipitator.
d/  Control device required to meet standard is 99.8% efficiency electro-
      static precipitator.
e/  Control device required to meet standard is 99.91% efficiency fabric
      filter.
f/  Installed cost of 99.91% efficiency fabric filter is the same as for
      99,7% electrostatic precipitator, but annualized cost is higher.
                               107

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                    Table  21.   INCREMENTAL ANNUALIZED COSTS FOR BASIC OXYGEN FURNACES TO MEET FINE
                                                   PARTICLE EMISSION STANDARDS
           Emission Standard

           All  plants  install
             BICD

           10%  Opacity
           5% Opacity
    Control Systems

99.7% Efficient electro-
  static precipitator

99.8% Efficient electro-
  static precipitator

99.91% Efficient fabric
  filter
                                                                                          Incremental Annualized
                                                                 Annualized Cost ($/Year)        Cost ($/Year)
Model Plant  All Plants  Model' Plant  All Plants

  163,000    10.4 x 106    163,000    10.4 x 106
  177,000    14.2 x 106    143,000     4.2 x 106
  207,000    16.5 x 106     30,000     2.3 x 106
O
00

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Installation  of the BICD on all sources could reduce emissions from
43,600 Ib/hr to 2,560 lb/hr--a reduction of 94.5%.  The more stringent
opacity regulations could result in a reduction of 96.5 to 98%.

Electric arc furnaces  -  A model furnace with a capacity of 80 tons/heat
was used as the basis for the estimates of control equipment costs pre-
sented in Tables 22 and 23.  Electric arc furnaces represent a relatively
well controlled source with 65% of existing furnaces already equipped
with fabric filters.  Costs presented in Tables 22 and 23 reflect this
fact.

The costs given in Table 22 show  that the annualized cost associated with
the opacity standards are lower than that for the best installed control
device and reflect the fact that these standards require a control ef-
ficiency that is lower than that of the best installed control system
(i.e., the fabric filter).  However, the installed cost of the control
device selected for the 5% opacity standard is higher than that for the
best installed control system.  It would, therefore, be reasonable to
assume that the higher efficiency best installed control system might be
chosen to meet the 5% opacity standard, but this depends on whether the
choice is made on the basis of installed cost or annualized cost.

The estimated reduction in fine particle emissions that might be achieved
by implementation of fine particle emission standards ranges from 71% for
10% opacity to 82% for the best installed control system.
                                                     i
Cement Plants (Rotary  Kilns)  - In this source category, control equipment
costs for compliance with fine particle emission standards were estimated
only for the rotary kiln—the major emission source in a cement plant.  A
cement plant with a production capacity of 3 x 10° barrels/year was chosen
as the basis for the model plant used to estimate the control equipment
costs.  Cement plants range in size from 1-14 x 10*> barrels/year produc-
tion with approximately 50% of the plants in the capacity range of 2-4 x
10^ barrels/year.

Tables 24 and 25 summarize the estimated costs for compliance with the
fine particle emission standards.  For cement kilns, the opacity regula-
tions are less stringent than the standard requiring the use of the best
installed control device on all sources.  The cost estimates shown in
Tables 24 and 25 reflect the fact that approximately 17% of the cement
kilns are already equipped with the best installed control device—a
fabric filter system.
                                   109

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          Table 22.  CONTROL EQUIPMENT COSTS FOR ELECTRIC ARC
                   FURNACES (IRON AND STEEL PLANTS)
                                    Model Plant
                        Industry Total
I.    Source description

      Capacity
      Production
      Fine particle emissions
        (a)  Uncontrolled
        (b)  Present
80 tons/heat
100,000 tons/year

127 Ib/hr
     a/
10 to 250 tons/heat
21.5 x 106 tons/year

27,400 Ib/hr
 3,600 Ib/hr
II.   Best installed control
        system^'
      Installed cost
      Annualized cost
      Fine particle emissions

III.  10% Opacity^/

      Installed cost
      Annualized cost
      Fine particle emissions

IV.   5% Opacity^/

      Installed cost
      Annualized cost
      Fine particle emissions
$182,000
$41,000/year
3 Ib/hr
$161,000
$28,000/year
8.2 Ib/hr
$204,000
$32,000/year
3.5 Ib/hr
$13.7 x 106£/
$3.1 x 106/year£/
645 Ib/hr
$12.1 x 106£/
$2.1 x 106/ye
1,036 Ib/hr0-/
   .4.x 106-/
$2.4 x 106/year£/
683
a/  Quantity emitted depends  on control  device  installed;
b/  Control device required to  meet  standard is a  fabric filter.
c/  Based on fact that approximately 65% of electric  arc furnaces are
      already equipped with fabric filters'.
d/  Control device selected to  meet  standard is 95.8% efficient electro-
      static precipitator.
e/  Control device selected to  meet  standard is 98.2% efficient electro-
      static precipitator.
                                 110

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          Table 23.  INCREMENTAL ANNUALIZED COSTS FOR ELECTRIC ARC FURNACES TO MEET FINE
                                         PARTICLE EMISSION STANDARDS
Emission Standard

10% Opacity


5% Opacity
                                                  Annualized Cost ($/Year)
                                                         Incremental Annualized
                                                           1  Cost  ($/Year)
   Control System
95.8% Efficient electro- ,   , 28,000
  static precipitator
Model Furnace 'All Furnaces  Model Furnace  All Furnaces

             •   2.1 x 106
98.2% Efficient electro-
  static precipitator
All furnaces install  Fabric filter
  BICD
   32,000
                             41,000
2.4 x 106
                3.1 x 106
28,000


 4,000


 9,000
2.1 x 106


0.3 x 106


0.7 x 106

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   Table 24.  CONTROL EQUIPMENT COSTS FOR CEMENT PLANT ROTARY KILNS
                                    Model Plant
                        Industry Total
I.    Source description

      Capacity
      Production
      Fine particle emissions
        (a)  Uncontrolled
        (b)  Present

II.   Best installed control
        system?-/

      Installed cost
      Annualized cost
      Fine particle emissions

III.  10% Opacity!/

      Installed cost
      Annualized cost
      Fine particle emissions

IV.   5% Opacity^/

      Installed cost
      Annualized cost
      Fine particle emissions
3 x 106 barrels/year  550 x 106 barrels/year
                      400 x 10 *> barrels/year
1,325 Ib/hr
$462,000
$102,000/year
11 Ib/hr
$440,000
$67,000/year
138 Ib/hr
$481,000
$74,000/year
67 Ib/hr
243,000 Ib/hr
 44,300 Ib/hr
$70.3 x 1
$15.5 x 106/year£'
2,000 Ib/hr
$67.5 x
$10.2 x I06/year£/
25,200
$73.2 x 1
$11.2 x HP/year^/
12,200 lb/hr£/
a/  Quantity emitted  depends  on control device installed.
b_/  Control device  required to  meet  standard is a fabric  filter.
£/  Based on fact that  approximately 17% of'kilns are  already equipped
      with fabric filter.
d/  Control device  selected to  meet  standard is 98.7%  efficient electro-
      static precipitator.
e/  Control device  selected to  meet  standard is 99.4%  efficient electro-
      static precipitator.
                                   112

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                    Table 25.   INCREMENTAL ANNUALIZED COSTS FOR CEMENT KILNS TO MEET FINE
                                               PARTICLE EMISSION STANDARDS
                                                                               Incremental Annualized
                                                  Annualized Cost ($/Year)     	Cost ($/Year)  .-•-
    Emission Standard
    10% Opacity
    5% Opacity
    Control System       Model Kiln     All Kilns     Model Kiln    All Kilns
98.7% Efficient electro-   67,000
  static precipitator

99.4% Efficient electro-   74,000
  static precipitator
10.2 x 106      67,000      10.2 x 106
11.2 x 106       7,000      1 x 106
    All kilns install    Fabric filter
      BICD
                          102,000       15.5 x 106      28,000      4.3 x 106
U>

-------
Reduction in fine particle emissions  from all cement kilns that might be
achieved by implementation of fine particle emission standards ranges from
72.5% for 10% opacity to 95.5%  for the best installed control system.

Hot-mix Asphalt Plants  - There  are about 3,000  asphalt paving plants in
the U.S. ranging in capacity from 75  to 300 tons/hr.  A plant with a
capacity of 150 tons/hr was selected  as the basis  for the estimates of
control costs.  Only the rotary dryer which is  the major source of emis-
sions was included in the cost  estimates.

Tables 26 and 27 present the cost estimates for the rotary dryer.  The
opacity regulations are not as  restrictive as the  standard based on the
utilization of the best installed control device—a fabric filter system.
Currently, approximately 1670 of the asphalt dryers are already equipped
with fabric filters.

The installed costs for each standard,  as shown in Table 26, reflect the
fact that the opacity standards are not as restrictive as .the best installed
control system.  However, the annualized costs  for the opacity standards
are higher than that  for the best installed control system.  Therefore,
the choice of control equipment that  might be installed to meet the opacity
standards would depend  on whether selection is  based on installed cost or
annualized cost.

Ferroalloy Furnaces - Three different types of  furnaces are  currently used
to produce ferroalloy materials.  Since the  furnaces are quite different
both with regard to their operation and emissions, individual models were
used for each type of furnace.   Tables  28 to  30 summarize the cost esti-
mates for ferroalloy  furnaces.   Because of  inadequate data on effluent
characteristics  from  the  individual furnaces, it was not possible to de-
termine control equipment requirements  for  opacity regulations.  As a
result, only the costs  associated with  the  standard based on the best
installed control device  are  shown  in Tables  28 to 30.

For the closed electric furnace, available data indicate  that all exist-
ing furnaces are already  equipped with  the best installed control device.
Currently only about 40%  of the hooded  open furnaces are equipped with the
BICD  (fabric filter), and  installation of the BICD on all of this type of
furnace would result  in an  81%  reduction  in fine particle emissions.  Ap-
proximately 20% of existing unhooded  open furnaces are equipped with fabric
filters, and installations  of  this  device on all sources would reduce fine
particle emissions by about 52.5%.
                                   114

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 Table 26. CONTROL EQUIPMENT COSTS FOR HOT-MIX ASPHALT PLANT ROTARY DRYERS
                                     Model Plant
I.    Source description

      Capacity
      Production
      Fine particle emissions
        (a)  Uncontrolled
        (b)  Present

II.   Best installed control
        systemk/

      Installed cost
      Annualized cost
      Fine particle emissions

III.  107o Opacity!/

      Installed cost
      Annualized cost
      Fine particle emissions

IV.   57o Opacity!/

      Installed cost
      Annualized cost
      Fine particle emissions
150 tons/hr
90,000 tons/year
840 Ib/hr
     a/
$53,000
$10,600/year
6.6 Ib/hr
$21,500
$19,800/year
60 Ib/hr
$29,700
$29,700/year
50 Ib/hr
                       Industry Total
700 x 106 tons/year
350 x 106 tons/year

3.26 x 106 Ib/hr
257,000 Ib/hr
$173 x 106£/
$34.6 x 106/year£/
25,600 Ib/hr
$28 x 106®/
$26 x 106/year£/
200,000 Ib/hr£/
$97 x 106&/
$97 x 106/yearfi/
167,000 lb/hr£/
a/  Quantity emitted depends on control device installed.
b_/  Control device required to meet standard is a fabric filter.
£/  Based on fact that approximately 16% of dryers are already equipped
      with fabric filters.
d/  Control device selected to meet standard is 94.870 efficient wet scrubber.
e/  Based on fact that approximately 16% of dryers are already equipped
      with fabric filters and assumption that 507o of the present cyclone
      plus wet scrubber systems will meet 107o opacity standard.
f/  Control device selected to meet standard is 97.47o efficient wet scrubber.
£/  Based on fact that approximately 167o of dryers are already with fabric
      filters and assumption that few of the existing cyclone plus wet
      scrubber systems will meet 570 opacity standard.
                                  115

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              Table 27.  INCREMENTAL ANNUALIZED COSTS FOR HOT-MIX ASPHALT PLANT ROTARY
                                DRYERS TO MEET FINE PARTICLE EMISSION  STANDARDS
Emission Standard
10% Opacity
5% Opacity
  Control System

94*8% Efficient wet
  scrubber

97.4% Efficient wet
  scrubber
All dryers install   Fabric filter
  BICD
Annualized Cost ($/Year)
Model Dryer    All Dryers
  19,800
  29,700
                         10,600
26 x 106
97 x 106
               34.6 x 106
                Incremental Annualized
              	Cost ($/Year)
              Model Dryer    All Dryers
19,800
 9,900
26 x 106
71 x 106

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   Table 28.  CONTROL EQUIPMENT COSTS FOR FERROALLOY FURNACES  (CLOSED
                               ELECTRIC FURNACE)
                                    Model Plantg/
                      Industry Total
I.   Source description

     Capacity

     Fine particle emissions
       (a)  Uncontrolled
       (b)  Present

II.  Best installed control
       system0./

     Installed cost
     Annualized cost
     Fine particle emission
17,000 kw           1,025,000 kw
(13,600 tons/year)  (820,000 tons/year)
1,535 Ib/hr
      b/
92,000 Ib/hr
11,300 lb/hrd/
$15,000
$3,000/year
38 Ib/hr
      d/
11,300 Ib/hr
III. 10% Opacity - Insufficient effluent property data prohibited deter-
                     mination of control efficiency required.

IV.  5% Opacity - Same as 10% opacity.
a/  Operating hours - 8,000 hr/year
b_/  Quantity emitted depends on control device installed.
£/  Control device required to meet standard is a disintegrator.
d_/  MRI survey in 1970 indicated that all plants are already equipped
      with disintegrators.
                                   117

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Table 29.  CONTROL EQUIPMENT  COSTS  FOR FERROALLOY FURNACES  (HOODED OPEN
                                  ELECTRIC FURNACE)
I.   Source description

     Capacity

     Fine particle  emissions
        (a)  Uncontrolled
        (b)  Present

II.  Best installed control
        system?./

     Installed cost
     Annualized  cost
     Fine particle  emissions
                                     Model Plants/
                                                          Industry Total
                                    13,500  kw           1,350,000 kw
                                    (10,800 tons/year)   (i;080,000  tons/year)
                                    1,295  Ib/hr
                                           b/
'-••• 129,500 Ib/hr
   84,100 Ib/hr
                                    $188,000
                                    $42,000/year
                                    158- lb/hr£/
   $11.3 x 106 d/
   $2.5 x lOfy
   15,800 Ib/hrl/
III.  10%  Opacity -  Insufficient effluent property data prohibited deter
                      mination of control efficiency required.

IV.   5% Opacity - Same as 10% opacity.
a/  Operating  hours  - 8,000 hr/year.
b_/
£/
d/
    Quantity  emitted depends on control device installed;1
    Control device required to meet standard is a fabric 'filter.
    Based  on fact  that approximately 40% of hooded electric furnaces are
       already equipped with fabric filter or disintegrator system.
e/  Based  on assumed capture efficiency of hooding system of 90%.
                                   118

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Table 30.  CONTROL EQUIPMENT COSTS FOR FERROALLOY FURNACE  (UNHOODED OPEN
                                      FURNACE)
                                    Model Planta/
                      Industry Total
I.   Source description

     Capacity

     Fine particle emissions
       (a)  Uncontrolled
       (b)  Present

II.  Best installed control
       system?./

     Installed cost
     Aanualized cost
     Fine particle emissions
10,000 kw
(8,000 tons/year)

960 Ib/hr
       b/
750,000 kw
(6 x 105 tons/year)

72,000 Ib/hr
60,800 Ib/hr
$750,000
$168,000/year
384 lb/hr
-------
Rotary Lime Kilns - Rotary  lime kilns range  in  capacity  from 50 to 560
tons/day.  A kiln with a capacity  of 250  tons/day was  selected as the
basis for the estimate of control  costs.   Only  the rotary kiln, which is
considered to be the major  source  of emissions  from  lime plants, was in-
cluded in the cost estimates.

Tables 31 and 32 present the  cost  estimates  for the  rotary kilns.  The
opacity regulations are not as restrictive as the standard based on
utilization of  the best installed  control device--a  fabric filter.

The installed costs for each  standard,  as shown in Table 31, reflect the
fact that the opacity standards are not as restrictive as that of the best
installed control system.   However, the annualized costs for the opacity
standards  are  higher than  that for the best installed  control system.
Therefore, the  choice of control equipment that  might be  installed to meet
the opacity standards would depend on whether selection  is based on in-
stalled cost or annualized  cost.
                                    «

Municipal Incinerators - Individual furnaces used for  municipal incinera-
tion range in size from 15  to 300  tons  per 24 hr.  An  incinerator with a
capacity of 10  tons/hr  (240 tons/24 hr) was  selected as  the basis for the
estimate of control costs.

Tables 33 and 34 present the  cost  estimate for  municipal incineration.
The opacity regulations are not as restrictive  as the  standard based on
the use of the  best installed control device—a 99.0%  efficient electro-
static precipitator.  Few incinerators  in the U.S. are presently equipped
with electrostatic precipitators but  several are installing or planning
to installed them.                                       ,;:

Iron Foundry  (Cupolas) - The  cupola furnaces used in the laron foundry in-
dustry range in size from 1 ton/hr to 40  tons/hr or  larger*  A cupola with
a capacity of 10 tons/hr was  selected as  the basis for the} estimate of
control costs.

Tables 35 and 36 present the  cost  estimates  for the  foundry cupolas.  They
also indicate that the opacity regulations are  not as  stringent as the
standard based  on equipping the foundry with the best  installed control
device (a fabric filter).   However, the annualized costs for opacity stand-
ards are higher than that for the  best  installed system.  Therefore, the
choice of control equipment that might  be installed  to meet the opacity
standards would depend on whether  selection  is  based on  installed cost or
annualized cost.

Primary Aluminum-Electrolytic Cells - It  is  difficult  to characterize the
primary aluminum industry and the  different  sources  and  processes.
                                  120

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      Table  31.   CONTROL  EQUIPMENT  COSTS  FOR  ROTARY  LIME KILNS
I.    Source description

      Capacity         '
      Production
      Fine particle emissions
        (a)  Uncontrolled
        (b)  Present

II.   Best installed control
        sy'stemb/

      Installed cost
      Annualized cost
      Fine particle emissions

III.  10% Opacity regulation!/

      Installed cost
      Annualized cost
      Fine particle emissions

IV.   5% Opacity regulation!/

      Installed cost
      Annualized cost
      Fine particle emissions
                                     Model  Plant
                      Industry Total
250 tons/day        74,400  tons/day
87,500 tons/year    18.5 x  106  tons/year
255 Ib/hr
      a/
$70,000
$14,000/year
4.0 Ib/hr
$42,000
$39,500/year
56 Ib/hr
$58,000
$60,500/year
24 Ib/hr
75,800 Ib/hr
22,000 Ib/hr
$12.6 x 106£/
$2.5 x 106/year£/
1,200 Ib/hr
$7.5 x 10%/
$7.1 x I06/year£/
10,500 lb/hr£/
$10.4 x 106£/
$10.8 x 106/yeare/
4,800 lb/hr£/
£/  Quantity emitte'd depends on control device installed.
b_/  Control device required to meet standard is a fabric filter.
£/  Based on fact that approximately 40% of kiln capacity is already
      equipped with fabric filters.
d/  Control device selected to meet standard is 97.0% efficient wet
      scrubber.
e/  Based on 40% present application of fabric filters and assumption
      that only a few plants are equipped with wet scrubbers that meet
      the required efficiency.                          :
f/  Control device selected to meet standard is 98.7% efficient wet'
      scrubber.
                                 121

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             Table 32.  INCREMENTAL ANNUALIZED COSTS FOR ROTARY LIME KILNS TO MEET FINE
                                        PARTICLE EMISSION STANDARDS
Emission Standard
10% Opacity
5% Opacity
  Control System
All kilns install    Fabric filter
  BICD
97.0% Efficient wet
  scrubber

98.7% Efficient wet
  scrubber
Annualized Cost ($/Year)
Model Plant    All Plants
                         14,000
  39,500
  60,500
               2.5 x 106
7.1 x 106
               Incremental Annualized
              	Cost ($/Year)	
              Model Plant    All Plants
                14,000
25,500
             2.5 x 106
4.6 x 106
10.8 x 106      46,500       8.3 x 106

-------
      Table 33.  CONTROL EQUIPMENT COSTS FOR MUNICIPAL  INCINERATORS
                                    Model Plant
                      Industry Total
I.    Source description

      Capacity
      Production
      Fine particle emissions
        (a)  Uncontrolled
        (b)  Present
II.   Best installed control
        system—'
      Installed cost
      Annualized cost
      Fine particle emissions

III.  10% Opacity regulation!/

      Installed cost
      Annualized cost
      Fine particle emissions

IV.   57o Opacity regulation®/

      Installed cost
      Annualized cost
      Fine particle emissions
10 tons/hr
80,000 tons/year

45.6 Ib/hr
       a/
$170,000
$27,000/year
1.5 Ib/hr
$116,000
$19,500/year
10.3 Ib/hr
$136,000
$23,000/year
5.7 Ib/hr
3,300 tons/hr
18 x H)6 tons/year

15,000 Ib/hr
13,100 Ib/hr
$55.0 x 106£/
$8.9 x 106/year£/
490 Ib/hr
$38.0 x 106£/
$6.4 x 106/year£/
3,400 Ib/hr
$45.0 x 106£/
$7.6 x 106/year£/
1,900 Ib/hr
a/  Quantity emitted depends on control device installed.
b_/  Control device required to meet standard is a 99.07» efficient electro-
      static precipitator.
c_/  Based on fact that few, if any, municipal incinerators are presently
      equipped with electrostatic precipitators.
d/  Control device selected to meet standard is 93.17o efficient electro-
      static precipitator.
e/  Control device selected to meet standard is 96.270 efficient electro-
      static precipitator.
                                 123

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                 Table  34.   INCREMENTAL ANNUALIZED COSTS FOR MUNICIPAL INCINERATORS TO MEET
                                            FINE PARTICLE EMISSION STANDARDS
     Emission Standard
     10% Opacity
     5% Opacity
     All incinerators
       install BICD
   Control System

93.1% Efficient electro-
  static precipitator

96.2% Efficient electro-
  static precipitator

99.0% Efficient electro-
  state precipitator
Annualized Cost ($/Year)
Model Plant   All Plants
              Incremental Annualized
                  Cost ($/Year)	
             Model Plant   All Plants
  19,500      6.4 x 106      19,500      6.4 x 106
  23,000
  27,000
7.6 x 106
8.9 x 106
3,500
7,500
1.2 x 106
2.5 x 106
I-1
to

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         Table 35.  CONTROL EQUIPMENT COSTS FOR IRON FOUNDRY CUPOLAS
I.   Source description

     Capacity
     Production
     Fine particle emissions
        (a)  Uncontrolled
        (b)  Present

II.  Best installed control
        systemk/

     Installed cost
     Annualized cost
     Fine particle emissions

III. 10% Opacity regulation!/

     Installed cost
     Annualized cost
     Fine particle emissions

IV.  5% Opacity regulation^/

     Installed cost
     Annualized cost
     Fine particle emissions
                                       Model Plant
10 tons/hr
10,000 tons/year

17.5 Ib/hr
     a/
$60,400
$12,100/year
0.27 Ib/hr
$27,600
$22,400/year
4.5 Ib/hr
$34,500
$32,800/year
3.0 Ib/hr
                       Indus try  Total
Unknown
13.1 x 106  tons/year

22,900 Ib/hr
13,100 Ib/hr
 $79.1 x  106£/
 $15.8 x  106/year£/
 356  Ib/hr
$36.2 x I06e/
$29.4 x 106/year£/
5,900 Ib/hr
$45.2 x I06e/
$43.0 x 106/yeare/
4,000 Ib/hr
a/  Quantity emitted depends on control device installed.
b_/  Control device required to meet standard is a fabric filter.
£/  Based on the fact that only a small percentage (< 5%) of cupolas are now
      equipped with fabric filters.
d/  Control device selected to meet standard is 94.2% efficient wet scrubber.
e/  Based on information indicating that few plants are equipped with control
      devices that meet the required efficiency.
f/  Control device selected to meet standard is 97.1% efficient wet scrubber.
                                     125

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                   Table  36.   INCREMENTAL ANNUALIZED COSTS FOR IRON FOUNDRY CUPOLAS TO MEET FINE
                                                PARTICLE EMISSION STANDARDS
      Emission Standard
     All cupolas install
       BICD
     10% Opacity
     5% Opacity
  Control System
Fabric filter

94.2% Efficient wet
  scrubber

97.1% Efficient wet
  scrubber
                               Incremental Annualized
 Annualized Cost ($/Year)     	Cost  ($/Year)	
Model Plant    All Plants    Model Plant     All Plants
  12,100
15.8 x 106      12,100        15.8 x 10
                                                                             6
                                                     22,400       29.4 x 106      10,300
                                                     32,800       43.0 x 106       20,700
                                             13.6 x 106
                                             27.2 x 106
to

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However, the electrolytic cells are one of the major particulate sources
within the industry and are the only ones on which enough information was
available to attempt estimation of costs for the emission standards con-
sidered in this program.

Primary aluminum plants may range in size from 150 to 700 tons/day, but
these usually consist of several "potlines" with each potline made up of
several hundred cells.  Information obtained in the study indicated 15
cells might be ducted to the same control device.  Therefore, a 15-cell
potline producing an estimated 3,000 tons/year of aluminum was selected
as the basis for the estimate of control costs.

Table 37 presents the cost estimates for the best installed control sys-
tem.  The Alcoa 398 process was used as the best installed system, and
it was assumed to be equivalent to a fabric filter for cost purposes.  How-
ever, the capture efficiency for the associated hooding systems was as-
sumed to be 95%.

Information was not available on characteristics of the effluent from the
electrolytic cells that would permit estimation of control device effi-
ciencies required to meet the opacity standards.

Primary Copper - In the U.S., 14 smelters represent 98% of the U.S.
capacity and these range in size from 48 tons/day up to 1,000 tons/day.
The configuration of these smelters is quite varied.   A 230 ton/day
smelter was selected as the basis for this study to estimate the partic-
ulate control costs.  Although a significant number of these plants may
have equipped some sources with S02 removal or recovery processes, the
costs of these processes and emissions from them have not been considered.

The 230 ton/day model plant consisted of one roaster, one reverberatory
furnace, and two convertors.  It was assumed that two identical control
devices would be installed to control emission from the above sources and
that the average particle size distribution was 25% < 3 u.

Table 38 presents the cost estimates for the best installed control system-
assumed to be a 99.7% efficient electrostatic precipitator.  It was also
assumed that none of the plants are now equipped with control systems (or
S02 removal processes) that would meet the required efficiency of 99.770.

Information was not available on characteristics of the effluents that
would permit estimation of control device efficiencies required to meet
the opacity standards.
                                  127

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Table 37. CONTROL EQUIPMENT COSTS FOR PRIMARY ALUMINUM-ELECTROLYTIC CELLS
                                    Model Plant
                       Industry Total
I.   Source description
       One potline  (15 cells)

     Production
     Fine particle  emissions
       (a)  Uncontrolled
       (b)  Present

II.  Best installed control
       systemk/

     Installed cost
     Annualized  cost
     Fine particle  emissions
3,000 tons/year     4.0 x 10^ tons/year
29.1 Ib/hr
      a/
$71,200
$16,000/year
1.5 Ib/hr
48,500 Ib/hr
16,200 Ib/hr
$95.0 x
$21.3 x I06/year£/
2,000 Ib/hr
a/  Quantity emitted  depends  on control  device  installed.
b_/  Control device  required to meet standard is the Alcoa  398 control
       system, which was  considered equivalent to a fabric  filter  for
       estimation purposes.
£/  Based on fact that few  plants  ate now equipped with  the  specified con-
       trol device.
d/  Emissions based on estimated capture efficiency of 95%.
                                   128

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      Table 38.  CONTROL EQUIPMENT COSTS FOR PRIMARY COPPER PLANTS
                                  Model Plant
                      Indus try Total
I.  Source Description

    Production
    Fine particle emissions
      (a)  Uncontrolled
      (b)  Present

II. Best installed control
      systemS/

    Installed cost
    Annualized cost
    Fine particle emissions
76,000 tons/year    1.7 x 10° tons/year
1,450 lb/hr£/
      b/
$532,000
$84,000/year
16.7 lb/hra/
32,400 lb/hr£/
7,400 lb/hr£/
$11.9 x
$1.9 x 106/yearl/
374 lb/hr£/
a/  Emissions based on assumption that uncontrolled particle size is 25%
      < 3 11.
b_/  Quantity emitted depends on control device installed.
£/  Control device selected to meet standard is 99.7% efficient electro-
      static precipitator.  S02 removal process costs and emissions have
      not been considered.
d_/  Costs are based on assumption that plants are not now equipped with
      control that would meet the required efficiency (99.7%).
                                   129

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ESTIMATED REDUCTIONS IN FINE PARTICLE EMISSIONS

Implementation of emission standards based on particle size can achieve
significant reductions in the  fine particulate burden entering the atmo-
sphere from stationary sources.  The extent of the reduction depends upon
the type(s) of emission standards that are selected for implementation.
Table 39 presents a summary of estimated reductions in fine particle
emissions from selected industrial sources which might result from the
implementation of the opacity  or BICD emission standards.  The time re-
quired to achieve the installation of requisite control equipment on all
the sources of fine particulate pollutants is difficult to determine.
If one assumes that fine particle emission standards are proposed, adopted,
and implemented in the 1975-1980 period, then it seems reasonable to assume
that total compliance could be achieved by 1985.

The emission figures presented in Table 39 are based on current production
rates.  Production rates have  generally increased for industrial sources
as a function of time.  Changes in production rates must be included in
calculations when an attempt is made to estimate fine particle emission
levels which may result from control efforts in future years.  As a part
of a previous study, MRI made  projections of fine particle emissions using
two different methods.ILL/  Table 40 presents the results of these projec-
tions for the same group of sources listed in Table 39.

The projection of emissions by Method I assumed that there would be no
change in the net control for  a source.  This assumption results in an
increase in emissions in proportion to increases in production capacity.
Production figures were projected by the same methods outlined in Ref. 92
and were used to proportionally increase the current mass of fine particle
emissions.

Method II takes into account the increase in production, but two assump-
tions are also made:

1.  All sources would be controlled by 1980, i.e., application of control
will reach 100% by 1980.

2.  Increased utilization of the most efficient control devices would
continuously increase the efficiency of control on fine particles so
that by the year 2000 it would be equivalent to controlling all sources
with fabric filters.  The fabric filter was selected as a reference
standard of performance because it is one of the most efficient devices
currently available for collecting fine particulates.  It seems realistic
to assume that improvements in the other control devices and possible
                                  130

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                                                      Table 39.  ESTIMATES OF FINE PARTICLE EMISSIONS AS A FUNCTION OF EMISSION STANDARD
LO
Estimated Fine Particle Emissions
Uncontrolled

I.
II.



III.
IV.
V.





VI.
VII.
VIII.
Source
Coal combustion
Iron and steel
A. Sinter machines
B. Basic oxygen furnace
C. Electric arc furnace
Cement plants, rotary kilns
Asphalt plants, dryers
Ferroalloy plants
A. Closed electric furnace
B. Hooded open electric
furnace
C. Unhooded open electric
furnace
Lime plants, rotary kilns
Municipal incinerators
Iron foundry, cupola
Lb/Hr
796,000

7,100
400,000
27,400
243,000
3,260,000

92,000

129,500

72,000
75,800
15,000
22,900
Ton/Year
3,184,000

28,400
1,600,000
109,600
972,000
1,956,000

368,000

518,000

288,000
303,200
37,500
22,900
Present
Lb/Hr
243,000

1,400
43,600
3,600
44,300
257,000

11,300

84,100

60,800
22,000
13, 100
13,100
Ton/Year
972,000

5,600
174,400
14,400
177,200
154,200

45,200

336,400

243,200
88,000
32,800
13,100
BICD Standard^./
Lh/Hr
15,000

64
2,560
645
2,000
25,600

11,300

15,800

28,800
1,200
490
356
Ton/Year
60,000

256
10,240
2,580
8,000
15,360

45,200

63,200

115,200
4,800
1,225
356
10% Opacity Standard 5% Opacity Standard
Lb/Hr
5,050

722
1,540
1,036
25,200
200,000

NCS/

NC

NC
10,500
3,400
5,900
Ton/Year Lb/Hr
20,200 2,510

2,888 354
6,160 800
4,144 683
100,800 12,200
120,000 167,000

NC NC

NC NC

NC NC
42,000 4,800
8,500 1,900
5,900 4,000
Ton/Year
10,040

1,416
3,200
2,732
48,800
100,200

NC

NC

NC
19,200
4,750
4,000
                a/  Not  calculated.
                b_/  BICD-Best installed  control device (not necessarily the highest  efficiency  device  available, but rather  the best that  is generally  being installed
                     at present time).

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Table 40.  PROJECTIONS OF FINE PARTICLE EMISSIONS FROM INDUSTRIAL SOURCES
                                    (106 Tons/Year)
1.


2.

3.
4.
5.
6.
7.
8.
Source ,
Stationary combustion
A. Coal
1. Electric utility
2 . Industrial
Iron and steel
A. Sinter machines
B. Basic oxygen furnace
C. Electric arc furnace
Cement plants, rotary kilns
Hot mix asphalt plants, dryers
Ferroalloy electric furnaces
•Lime plants, rotary kilns
Municipal incinerators
Iron foundries, cupolas
Method

I
II
I
II
I
II
I
II
I
II
I
II
I
II
I
II
I
II
I
II
I
II

1970
1.046
0.976
0.133
0.127
0.006
0.006
0.188
0.177
0.015
6.014
0.188
0.175
0.168
0.158
0.155
0.131
0.103
0.095
0.040
0.037
0.013
0.012

1975
1.201
0.883
0.150
0.111
0.007
0.006
0.293
0.235
0.018
0.010
0.227
0.164
0.205
0.158
0.166
0.074
0.134
0.094
0.051
0.037
0.015
0.010

1980
1.374
0.731
0.170
0.084
0.008
0.005
0.454
0.305
0,021
0.004
0.273
0.140
0.250
0.152
0,180
0.008
0.174
0.086
0.061
0.031
0.016
0.006
Year
1985

1.600
0.653
0.170
0.064
0.009
0.004
0.515
0.277
0.023
0.004
0.319
0.125
0.305
0.141
0.198
0.009
0.189'
0.071
0.071
0.027
0.017
0.005

1990
1.864
0.528
0.170
0.043
0.009
0.003
0.581
0.237
0.026
0.004
r
0.372
0.101
0.375
0.117
0.219
0.010
0.206
0.053
0.081
0.021
0.017
0.003

1995
2.110
0.335
0.166
0.023
0.010
0.002
0.618
0.170
0.029
0.003 .;
0.421
0.062
0.460
0.074
0.241
0.011
0.311
0.044
0.095
0.-014
0.018
0.002

2000

2.388
0.090
0.164
0.002
0.010
0.000
0.654
0.094
0.034
0.003
0.476
0.016
0.563
0.018
0.267
0.012
0.466
0.016
0.109
0.003
0.019
0.003

-------
development of new devices would allow the efficiency of control devices,
in the year 2000, to match the performance capability of the best devices
that are presently available.  Details and examples of the calculations
for both methods are given in Ref. 61.

The two projection methods represent two extremes:  no improvement in con-
trol versus stringent control.  An intermediate position is more probable,
but projection of an intermediate situation requires information regarding
the percent application of each type of control device on specific sources
in the future years.  Of course, this information is not available, and
to project emissions, gross assumptions would have to be made regarding
future equipment utilization.

ECONOMIC IMPACT OF FINE PARTICLE EMISSION STANDARDS ON SELECTED SOURCES

A detailed economic evaluation of the economic impacts of emission stand-
ards involves far more than simply making cost, revenue and capital
projections over a specified time period.  A thorough feasibility analy-
sis must give  careful attention to how all the different parts fit to-
gether and react with each other, in much the same way as a critical
path analysis describes the interactions among all the activities in a
complex  construction project.

Just as in a natural ecosystem,  many of the elements in the economic sys-
tem are closely interrelated, even though—just as in the ecosystem—the
interrelationships may not be instantly obvious,  and even when they are,
they may be hard to express in quantitative or absolute terms.

The accompanying illustration (Figure 19) shows,  in a general sense,  some
of the major microeconomic factors that should be considered in the economic
analysis of the impacts of air quality control programs on a given firm or
industry.

Air[pollution control standards  will primarily influence unit costs.   Unit
costs include both variable and  fixed elements.  The variable costs,  con-
sisting mainly of labor and materials, are related to volume; any change
in volume is accompanied by a proportionate change in the direct costs.
Fixed costs, consisting mainly of capital-related charges and overhead
expenses, are primarily related  to the amount of capital invested in the
operation and remain constant over a wide range of operating conditions.
In total, unit costs generally decline as volume increases, as  the fixed
costs are spread over a broader  base.  The imposition of air pollution
control standards will affect the firm's costs of production by increasing
its capital investment requirements,  and by raising its direct  manufacturing
                                  133

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                         RETURN ON
                         INVESTMENT
Figure-19.
Interrelationships among factors affecting the economics
                 of .a firm
                               134

-------
costs by whatever amount is required to operate and maintain the new air
pollution control facilities.

Figure 20 illustrates a possible structure for analyzing the economic im-
pact of new air pollution control requirements on a  specific firm.  The
specified control efficiency and plant size (as reflected by its prdduc-
tion volume) dictate the size and type of control equipment needed, which
in turn determine the capital and operating costs associated with the
control program.

The total cost of control represents an incremental cost "of production,
which can either be absorbed by the firm or passed cm to its consumers
by means of increased prices. Should prices be increased, however, sales
are likely to decrease; if costs are absorbed, volume may remain constant,
but profit margins will suffer.  Regardless of the economic impact on the
firm, then,-tits way of doing business will be affected.
                                                            t s-'
Table 41 shows an example of the economic impact of air pollution control
requirements on an electric generating plant, as reflected in its costs
of power production.   Again, the control efficiency determines the control
cost, which results in higher costs of energy production, ultimately to
be passed along to the consumer.  As is evident from the control costs
shown in Table 41, control becomes increasingly expensive as the effi-
ciency requirements increase.   This is particularly significant in
certain industries, where any price increase will cause a major decline
in sales, with customers either cutting back on their consumption^ shift-
ing to other producers, or substituting other products.

An in-depth analysis of the economic impact of fine particle emission
standards on individual industry segments was outside the scope of this
study.  The economic impact analysis conducted during this program was
confined to the determination of the increase in production costs for
specific industries.  An example of the procedures used to calculate the
increase in production costs associated with the fine particle emission
standards is presented in the next section.

Example of Calculation of Economic Impact

The financial and operating characteristics of a typical coal-fired steam-
electric generating plant were developed to use as a model for determining
the economic effects of different control strategies for fine particulates.

Based on the compiled statistics of privately owned electric utilities in
the United States, generating costs are equally divided between capital
charges and production expenses, with capital charges averaging 15% of

                                  135

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Specified Control
Control Efficiency Equipment
1
i 1
Capital Operating Control
Requirements Costs Credits
i
i i
Sources of 	 Annual Cost Net Operating
Capital of Capital Cost
1 1


Total Cost Production
of Control Volume
1

Incremental
Unit Cost


	
Absorb Increase
Costs Prices
1
4 * 1
Product Competitive Price Elasticity
Substitution Factors of Demand
1 i '
1
Economic Impact Sales'
on Firm: Volume
• Profit
• Profit Margin
• Return on
Investment
'
Figure 20.  Structure for microeconomic impact analysis
                             136

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           Table 41.  EXAMPLE OF ECONOMIC IMPACT OF AIR POLLUTION CONTROL REQUIREMENTS ON ELECTRIC POWER
                                                     GENERATING COSTS
u>
Control Method
None
Louver
Medium efficiency
cyclone
High efficiency
cyclone
Multiple cyclones
Electrostatic
precipitator
Fabric filter
Fabric filter
Fabric filter
Control
Efficiency
(%)
0
58.6
65.3
84.2
93.8
99.0
99.7
99.8
99.9
Total Annual Cost ($1,
Electric
Production
9,010
9,010
9,010
9,010
9,010
9,010
9,010
9,010
9,010
Pollution
Control
0
100
96
156
168
602
852
1,008
1,190
000)
Total
9,010
9,110
9,106
9,166
9,178
9,612
9,862
10,018
10,200
Net
Cost
(C/kwh)
0.935
0.945
0.945
0.951
0.952
0.997
1.023
1.039
1.058
Incremental
Cost
(C/kwh)
--
0.010
0.000
0.006
0.001
0.045
0.026
0.016
0.019

-------
the utilities net plant investment.  Table 42 summarizes the pertinent
financial characteristics of the 400-MW model steam generating plant burn-
ing 1.2 million tons of coal annually to produce 2.4 billion kilowatt-
hours of electric energy.

As shown in Table 42 the total annual cost of service for this typical
plant comes to $36 million, or $0.015/kwh of net generation, exclusive of
emission control equipment.

Virtually any desired  level of particulate emission control can be achieved
at a price.  Table 43  shows the estimated control costs associated with
various control efficiencies, ranging from the best installed control de-
vice (BICD), an electrostatic precipitator with 99.0% efficiency to 99.9%
efficiency, and including the 10%  opacity level (99.66% collection effi-
ciency) and the 5% opacity level (99.83% efficiency).

Estimated annual control costs vary  from $241,500 at the 99.0% efficiency
level to $465,000 at 99.9% efficiency.  Here, annual charges are estimated
at 15.0% of the total  installed cost of the control equipment, the same
rate applied to the utility's other  plant facilities.  This, it should be
pointed out, is the lowest capital charge rate that would conceivably
apply to the control equipment, and  a rate in the 17 to 20% range is
likely to be applied to this type  of air pollution control equipment.

At control efficiencies in the 99.0  to 99.9% range and with capital charges
computed at 1570 of installed equipment costs, the total impact of air pol-
lution control costs on the net cost of electric generation is almost
negligible, as shown in Table 44.  Here it can be seen that net costs per
kilowatt-hour  ($0.015  without emission controls) increase only to $0.0152
even at the 99.9% control level.   At 10%  opacity,  total control costs
amount to just $0.00013/kwh, and at  5% opacity they increase only to
$0.00016/kwh.

Thus, the net  cost difference between zero control and control at the 5%
opacity (or 99.83% efficiency) level amounts to an increase of 1.3% in
terms of the cost of generating electrical energy under the prescribed con-
ditions.  By way of comparison, O'Connor and Citarella reported that the
total annual cost of particulate air pollution for a 600-MW steam-electric
plant ranges from 0.7  to 2.0% of the total annual cost of power.^-L'

Control Costs  in Selected Industries

The costs of fine particulate control associated with appropriate control
levels—BICD or specified opacity  levels—have been estimated for the in-
dustries representing  the main sources of fine particulate emissions.

                                   138

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      Table 42.  TYPICAL FINANCIAL CHARACTERISTICS OF 400-MW ELECTRIC
                                   GENERATING PLANT^/
Net plant investment at $300/kw                             $120,000,000

Operating revenues at $0.015/kwh                              36,000,000

Operating expenses

  Fuel - 1.2 x 106 tons at $7.00/ton                           8,400,000
  Other production expenses at $0.004/kwh                      9.600,000

    Total operating expenses                                  18,000,000

Capital charges]*/ at 15% of plant investment                  18.000,000

Total cost of service                                       $ 36,000,000
a/  Net annual generation = 2.4 x 10^ kwh; load factor = 68.5%.
b/  Includes depreciation, interest, A&G expenses,  ad valorem and income
      taxes, and return on investment.
                                139

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   Table 43.   ESTIMATED CONTROL COSTS  FOR 400-MW  ELECTRIC GENERATING  PLANT
Installed Cost Annual
Emissions
- . i
Controlled
m

99.00
99.50
99.60
99.66
99.70
99.80
99.83
99.90
Emissions
Uncontrolled
(7.)

1.00
0.50
0.40
0.34
0.30
0.20
0.17
0.10
of Control
Equipment
($)

1,030,000
1,280,000
1,355,000
1,400,000
1,430,000
1,530,000
1,570,000
1,670,000
Operating and
Maintenance Cost
($>

87,000
100,000
105,000
110,000
114,000
132,000
143,000
215,000
Annual
Capital
Charges
($)

154,500
192,000
203,250
210,000
214,500
229,500
235,500
250,500
Total
Annual
Control Cost
' r$)
3
241,500
292,000
308,250
320,000
i. 328, 500
^361-, 500
378,500
465,500
            Table 44.  EFFECT OF CONTROL COSTS ON COST OF ELECTRIC POWER

Emissions
Controlled
(7.)
No control
99. 00*/
99.50
99.60
99,66k/
99.70
99.80
99.83£/
99.90
Total Cost
of Power
Generation
($/Year)
36,000,000
36,000,000
; 36,000,000
36,000,000
36,000,000
36,000,000
36,000,000
36,000,000
36,000,000

Total Annual
Control Cost
($)
0
241,500
292,000
308,250
320,000
328,500
361,500
378,500
465,500

Total Annual
Cost
($)
36,000,000
36,241,500
36,292,000
36,308,250
36,320,000
36,328,500
36,361,500
36,378,500
36,465,500


Cost/kwh
m
0.01500
0.01510
0.01512
0.01513
0.01513
0.01514
0.01515
0.01516
0.01519
a/  BICD.
b/  107. opacity.
£/  57. opacity.
                                     140

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Capital charges have been computed at four different levels, thus encom-
passing the entire range of possibilities for a given plant.  The specific
levels selected represent the  minimum depreciable life established by
the Internal Revenue Service for approved pollution abatement equipment;
the maximum expected useful service life of typical combustion equipment
for which control facilities are required; and two intermediate values,
reflecting the probable economic life ranges of the particulate control
devices being installed.

The four capital charge rates used in converting the installed cost of
particulate control systems to an equivalent annual amount are made up
as follows:
           Straight-Line   Average                          Total Annual
 Economic   Depreciation  Interest     Other Capital      Capital Charge
Life Year     Rate (%)       at  8%   Related Expenses (%)     Rate (%)

    5           20           5              5                   30
   10           10           5              5                   20
   15            7           5              5                   17
   20            5           5              5                   15
The average interest is computed at 8% of the undepreciated account bal-
ance, and, added to the straight-line depreciation rate, constitutes the
"capital recovery rate" used to amortize an investment over a specified
time period.  Other capital-related expenses include insurance costs, ad (
valorem taxes, and administrative expenses.

Total annual costs, including both capital charges and direct operating
expenses, were computed for each model plant, at selected control levels,
for each capital charge rate.  These annual costs were then related to
the model plant's production rate, resulting in a net annual control cost
per unit of production.  This amount, related to the value of the end
product, provides a realistic measure of the economic impact of a given
control strategy under the prescribed conditions.

Table 45 summarizes the estimated total annual control costs for model
plants in selected industries.  Estimated costs are presented for the
BICD, 10% opacity and 5% opacity emission standards.  Table 46 presents
the estimated costs associated with  the BICD standard for both the
model plants and the total industry.
                                 141

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                                                       Table 45.  EFFECT OF CONTROL  CRITERIA ON CONTROL COSTS IN SELECTED INDUSTRIES
to
Source
i'x..
Coal-fired electric plant
Municipal .incinerator
Cement plant (rotary kiln)
Asphalt plant (rotary dryers)
Iron and steel
(a) Basic oxygen furnace
(b) Electric arc furnace
(c) ;. Sintering (i&ndbox)
Lime plant (rotary kiln)
Iron foundry cupola
Control Fine Particle
Criteria Control Efficiency (%)
BICD 98.13 '
19% Opacity ,. 99.36
5% Opacity 99.68
BjgD
107. Opacity
5% Opacity
BICD
10% Opacity
5% Opacity
BICD
10% Opacity
5% Opacity
BICD
10% Opacity
5% Opacity
BICD
10% Opacity
5% Opacity
BICD
10% Opacity
5% Opacity
BICD,
10% Opacity
5% Opacity
BICD
10% Opacity
5% Opacity
96.71
77.41
87.50
99.17
89.58
94.94
99/21
92.86
94.05
99.70
99.82
99.91
97.64
93.54
97.24
99.10
87.76
94.05
" I/.
98.43
78.04
90.59
98.46
74.29
82.86
Model Plant Total Annual Control Cost ($1,000)
Annual Production at Specified Capital Charge Rate
Rate ' 0.15 0.17 0.20 .<*' 0.30
2.4 x 109 kwh ' 241.5
320.0
- 378.5
80,000 tons 35.5
25.3
29.8
3.0 x 10^ bbls 125.1
89.2
98.1
90, 000. tons 13.3
20.9
31.2
1.0 x 106 tons 211.0
227.0
255.0
100,000 tons 50.1
36.1
42.2
1.46 x 106 tons 277.0
184.5
204.5
87,500 tons 17.5
41.6
63.4
10,000 tons 15.1
23.8
34.5
262.1
348.0
409.9
38.9
27.6
32.5
134.3
98.1
107.7
14.3
21.3
31.8
230.2
247.0
2 74'. 2
53.7
39.3
46.3
297.0
199.9
221.5
18.9
42.4
64.6
16.3
24.3
35.2
293.0
390.0
457.0
44.0
31.1
36.6
148.2
111.4
122.1
15.9
22.0
32.7
259.0
277.0
303.0
59.2
44.1
52.4
327.0
223.0
247.0
21.0
43.7
66.3
18.1
25.2
36.3
396.0
530.0
614.0
61.0
42.7
50.2
194.4
155. f
170.2
21.2
24.1
35.6
355.0
377.0
399.0
77.4
60.2
72.8
427.0
300.0
332.0
28.0
47.9
72.1
24.2
27.9
39.7

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                                 Table 46.  TOTAL ANNUAL COST OF ACHIEVING BICDS/-LEVEL CONTROL  OF FINE PARTICULATES  IN  SELECTED  INDUSTRIES
CO
...t-.
Source
Coal-fired electric plant
• f- *- •
Municipal incinerator
Cement plant (rotary kiln)
Model Plant
Production
Rate/Year
2.4 x 109 kwh
80,000 tons
3.0 x 106 bbls
Total Annual Control Cost for
Model Plant at Specified
Capital Charge Rate ($1,000) "
0.15 0.17 0.20 0.30
241.5 262.1 293.0 396.0
35.5 38.9 44.0 61.0
125.1 134.3 148.2 194.4
Total Annual
" Industry
Production
516 x 109 kwh
18 x 106 tons
400 x 106 bbls
-Total Annual Control Cost for
Industry at Specified Capital
Charge Rate ($106)
0.15 0.17 0.20 0.30
51.9 56.4 63.0 85.1
8.0 8.8 9.9 13.7
16.7 17.9 19.8 25.9
Asphalt plant (rotary
  dryers)

Iron and steel
  (a) Basic oxygen furnace

  (b) Electric arc furnace

  (c) Sintering (windbox)

Ferroalloy
  (a) Unheeded open electric
90,000 tons


1.0 x 106 tons

100,000 tons

1.46 x 106 tons
                                                                   13.3
furnace
(b) Hooded open electric
furnace
(c) Closed electric
furnace
Lime plant (rotary kiln)
Iron foundry cupola
8,000 tons
10,800 tons
13,600 tons
87,500 tons
10,000 tons
205.5
51.4
3.8
17.5
15.1
          14.3
15.9
21.2    350 x 106 tons     51.7    55.6    61.8    82.4
211.0    230.2    259.0    355.0    50 x 106 tons      10.6    11.5    13.0    17.8

 50.1     53.7     59.2     77.4    21.5 x 1Q6 tons    10.8    11.5    12.7    16.6

277.0    297.0    327.0    427.0    54 x 106 tons      10.2    11.0    12.1    15.8
                                                                  205.5    220.5    243.0    318.0    600,000 tons
                                                                                                       15.4    16.5    18.2    23.9
                                                                   51.4     55.2     60.8     79.6    1.08 x 106 tons     5.1     5.5     6.1     8.0


                                                                             4.1      4.5      6.0    820,000 tons        0.2     0.2     0.3     0.4

                                                                            18.9     21.0     28.0   , 18.5 x 106 tons     3.7     4.0     4.4     5.9

                                                                            16.3     18.1     24.2    13.1 x 106 tons    19.8    21.4    23.7     31.7
                  a/  See footnote (b), Table 1, for definition of BICD.

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Table 47 summarizes the estimated annual costs of controlling fine partic-
ulate emissions via the BICD standard in selected industries, expressed in
terms of appropriate production units for each industry.  Table 48 presents
the unit values of the output from  selected industries which were used to
develop the data in Table 47.

As is evident from the data in Table 47, the economic impact of .fine par-
ticulate control will vary substantially from industry to industry.  For
example, at the 20% capital charge  rate (reflecting a 10-year equipment
life) applied to BICD-level control of coal-fired electric generating
plants, the $0.00012/kwh cost represents < 1.0% of a typical utility's
total cost of service.  For municipal incinerators, though, control costs
could easily add 8 to 10% to the total waste disposal costs.  Control
costs for cement plants and asphalt plants will fall gnerally in the 1.5
to 4.0% range, while various metallurgical operations in the ferroalloys
industry may require control expenditures ranging anywhere from < 0.5% to
> 20% of the value of their products.
                                  144

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                                       Table 47.   SUMMARY OF FINE PARTICULATE CONTROL COSTS AT BICD-LEVEL CONTROL
                                                                        ($/Unit of Production)
U1
Source
Coal-fired electric plant
Municipal incinerator
Cement plant (rotary kiln)
Asphalt plant (rotary dryers)
Iron and steel
(a) Basic oxygen furnace
(b) Electric arc furnace
(c) Sintering (windbox)
Ferroalloy
(a) Unheeded open electric furnace
(b) Hooded open electric furnace
(c) Closed electric furnace
Lime plant (rotary kiln)
Iron foundry cupola
Primary aluminum (electrolytic cells)
Primary copper
Annual Produc-
tion Rate for
Model Plant
2.4 x 109 kwh
80,000 tons
3.0 x 106 bbls
90,000 tons
1.0 x 10^ tons
100,000 tons
1.46 x 106 tons
8,000 tons
10,800 tons
13,600 tons
87,500 tons
10,000 tons
3,000 tons
76,000 tons
Fine
Particle
Control
Efficiency
98.13
96.71
99.17
99.21
99.70
97.64
99.10
60.00
87.80
97.52
98.43
98.46
94.85
98.85
Capital Charge Rate
0.15
0.00010
0.444
0.042
0.147
0.211
0.501
0.190
25.688
4.759
0.276
0.200
1.512
6.52
1.455
0.17
0.00011
0.486
0.045
0.159
0.230
0.537
0.203
27.563
5.107
0.298
0.216
1.613
6.99
1.595
0.20
0.00012
0.550
0.049
0.177
0.259
0.592
0.224
30.375
5.630
0.331
0.240
1.814
7.71
1.805
0.30
0.00017
0.763
0.065
0.236
0.355
0.774
0.292
39.750
7.370
0.441
0.320
2.418
10.08
2.505

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         Table 48.  UNIT VALUE OF OUTPUT FROM SELECTED INDUSTRIES
         Industry or Product
Electric energy
   Units
Ki lowat t-hour
Municipal refuse incineration    Ton
Cement




Asphalt




Pig iron




Steel




Lime
Barrel




Ton




Ton




Ton




Ton
Unit Cost or Value ($)




         0.015




        10.00




         4.32




        23.50




        78.16




       187.26




        18.00
                                  146

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                                 SECTION
            BENEFIT/COST RELATIONSHIPS FOR FINE PARTICULATE CONTROL

INTRODUCTION

Particulate emissions from a single point source will generally disperse
over a wide area at low concentrations.  The specific area over which the
dispersion occurs will depend on a variety of meteorological and topographi-
cal factors, as will the particulate concentrations experienced at any given
point within the area.

The economic effects of airborne particulate matter are a function of the
particulate concentration, the area over which the dispersion has occurred,
the economic values exposed to various concentrations,  and the rate of
economic loss associated with the interaction between the pollutants and
the economic values.

Five categories of economic loss or economic damage can be attributed to
the presence of air pollutants.  These include effects on:  (1) human health;
(2) animals; (3) vegetation; (4) materials; and (5) aesthetics.  Consider-
able research effort has been devoted to identifying the economic effects
of air pollution in each of these areas, but very little has been accom-
plished in quantifying the effects.  Because of the lack of reliable
quantitative data on effects, only a generalized benefit/cost analysis was
conducted during this program.  The following sections of this chapter
present the methodology utilized for the benefit/cost analysis and the
main results of the analysis.

DETERMINATION OF ECONOMIC DAMAGE ATTRIBUTABLE TO A SPECIFIC SOURCE

The approach used to allocate quantitatively the economic damages attribut-
able to a given emission source is based on the following assumptions:

1.  Potential economic damage is related to the quantity of particles dis-
charged into the atmosphere.
                                 147

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2.  The damage potential is highest near the emission source, decreasing
as the distance from the source increases.

3.  The total economic damage will be the integrated effects of pollutant
concentrations, interaction coefficients, and exposed economic values
throughout the entire dispersion area.

4.  This integrated total economic damage will be the same as if it were
calculated on the basis of an average pollutant concentration, affecting
an average economic value, at an average rate of interaction.

5.  The particulate concentrations at which the economic damage will be
evaluated are 75 ug/m3 and 60 ug/m^.  The former concentrations correspond
to the primary ambient air standard for particulates, while the latter is
the secondary ambient air standard.

6.  A point source having any specified emission rate (Ib/hr) of particu-
lates with an average atmospheric residence time of "t" (hr) will generate
a sufficient quantity of particles to produce a particulate concentration
of 75 and 60 ug/m3 in a given volume of air.

7.  Given the volume of air having a particulate concentration of 75 and
60 ug/m3, and further given the geometric shape of the volume containing
that concentration, the area of influence can be calculated.

8.  Lacking specific meteorological data, a hemisphere provides a reasonable
representation of the atmospheric diffusion of particulate matter from a
stationary point source.

9.  The area of influence is defined as the area over which a single emis-
sion source could cause and sustain a particulate concentration of 75 and
60 ug/m3, assuming uniform dispersion throughout a hemisphere, with the
point source located at its center.

10.  The economic loss factor, or damage intensity rate, is defined as the
total annual economic damage incurred per square mile within the area of
influence that would be experienced as a direct result of continuous ex-
posure of all economic values within the area of influence to a sustained
particulate concentration of 75 and 60 ug/m3.

11.  The total economic damage allocable to a point source is the product
of the area of influence (mile2) and the damage intensity rate ($/mile2).
                                   148

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12.  The economic benefits resulting from pollution control measures rep-
resent, the difference between the total economic damage incurred from an
uncontrolled emission and the total economic damage incurred from the re-
duced level of pollutants discharged from the controlled source.

13.  Economic values and loss factors are assumed to remain constant through-
out the area influenced by a specific pollutant source.  However, the area
of influence decreases as the quantity of particles discharged decreases,
and the total economic losses will decrease in direct proportion to the area
of influence.

14.  The area of influence varies with the 2/3 power of the quantity of
particles discharged.  Thus, an order-of-magnitude increase in particulate
emissions would increase the area of influence, and also the total economic
damage, by IQ0-66?, Or 4.63 times its previous level.  Similarly, a 90%
control efficiency on a particulate source would decrease the area of in-
fluence and total economic loss to 21.4% of its former level.

It must be recognized that the economic losses computed in this manner are
allocated rather than actual; actual losses would be incurred over a much
larger area at a much lower rate.  However, the total economic damage should
be essentially comparable.

Computing the Impact Area

The radius of the hemispheric dispersion model (see Figure 21) is a func-
tion of the emission rate and the residence time in the atmosphere of the
particles emitted.  Equations (6) and (7) present the expressions for the
radius of the hemisphere for ambient concentrations of 75 and 60 ug/m3}
respectively.

                    R = 0.0867 (Et)l/3 for 75 ug/m3                   (6)

                    R = 0.0954 (Et)1/3 for 60 ug/m3                   (7)

where R is the radius in miles, E the emission rate in Ib/hr, and t the
particle residence time in the atmosphere in hours.

The area of influence or impact area for each concentration level is given
by Eq. (8) or Eq. (9).
                                149

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                                   S = Point Source of Pollutant
                                                         t
                                         Emissions
                                   R = Radius of Impact Area

                                   2 = Area pfj Economic Impact ot
                                        Critical Concentration
Figure 21.   Simplified hemispherical pollutant dispersion model
                               150

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                     A = 0.0236 (Et)2/3 for 75 ]ig/m3                  -(8)

                     A = 0.0286 (Et)2/3 for 60 jig/m3                   (9)

where A is the impact area expressed in square miles.

Control Costs

Control costs are known to vary inversely with control efficiency.  The
control cost/control efficiency relationship, furthermore, is believed to
be exponential, in that the control cost per unit of control efficiency in-
creases with increasing control efficiency.  Thus, the cost of achieving
each additional percent of control efficiency costs more than did the  last
percent improvement, and less than the next.

The general cost efficiency relationship for particulate control systems
has this form: '"

                               C = 0.8(1/U)°-3                         (10)

where C is the annualized cost per CFM of control system capacity for achiev-
ing a specified level of control efficiency, with U being the percent  of
total emissions remaining uncontrolled.

Using this equation, a 90% control efficiency would be expected to cost in
the neighborhood of 0.8(1/10)0.3, or $0.40/CFM of capacity.  Similarly, a
99% control efficiency would cost 0.8 (1/1)°-3, or $0.80/CFM; and increas-
ing the efficiency to 99.9% would raise control costs to 0.8(1/0.I)0-3, -.
or $1.60/CFM.

Economic Damage

The economic damage associated with exposure to a 75 or 60 Jig/m3 concentra-
tion of particulate will depend on the specific characteristics of the area
affected, with population density the most important single factor.

The total economic damage to humans, animals, vegetation, materials, and
aesthetics attributable to sustained exposure to atmospheric pollutants
may range from less than $10,000/mile2 in sparsely populated rural areas,
to more than T$l million/mile2 in populous urban and industrial locatipns-.

In densely populated urban areas, effects on human health are by far the
most important; in sparsely populated rural areas, effects on animals  and
                                151

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vegetation are more economically  significant; and  in moderately populated
areas encompassing both  urban  and rural  characteristics, materials and
aesthetics are the chief recipients  of air  pollution damage.

Some effects, then, are  related primarily to  population density, while
others are more dependent on the  characteristics of the- area  exposed  to
the pollutants.  Data  are not  available, however,  to permit accurate
quantification of the  economic effects of air pollution in any specific
category.  The estimates presented here  are based  on a  review of the
literature,  and are intended for  illustrative purposes  only.

Human Health Damage -  The economic effect of  a  75  and 60 jig/m3 fine partic-
ulate concentration on human health  is estimated at $20 and $16/person/year.
These cost figures take  into account premature  death and losses-"incur red as
a result of  air pollution related diseases  such as bronchitis, lung cancer,
respiratory  ailments,  cardiovascular illnesses, and cancer.   Particulate
pollutants are known  to  be a major cause of bronchitis, an important  con-
tributor to  lung cancer  and respiratory  diseases,  and a minor factor  in
cancer and cardiovascular diseases.   The total  economic cost  of these five
diseases is  reported  to  be $13.7  billion annually,-of whicli some 20%  might
be attributed to air  pollutants  of all  types.2£/   Assuming that $1.0  bil-
lion in annual health damage results from  ambient  particulates, the damage
can be estimated at about $5.00-$5.50/year/persoh/20 iig/m3.   A 75 ug/m3
concentration, therefore, would  result  in damage of about  $20/person/year,
while a 60 ug/m^ concentration wo'uld result in  damage of about $16/persori/
year.   •

Animal Health Damage  - Fine particulates at the concentrations considered
here would be expected to cause  little  economic damage  to  animals, even in
predominantly agricultural areas. Cattle population in rural areas may
range from about 200/mile^ when  the  animals are on pasture, to as many as
60,000/mile2 in confined feedlots.  However,  cattle on  feed are generally
kept for no  more than 4  months,  so air  pollutants  at the prescribed level
would have relatively,little impact.

Vegetation Damage - Particulate  pollutants,^except for  specific types (e.g.,
fluorides),  are unlikely to have  any significant impact on agricultural ;i:
crops or otherx vegetation..  In farming  areas,_ the  total va,lue of crops ex-
posed to pollutants would seldom exceed  $100,QOO/mile2,, a,nd .the detrimental
effect of particulates on crop yields would.be  less than 5%.  The-maximum  ....
expected economic loss,  then,  would  be  less than $5,000/mile2 in exclusively
agricultural areas, and  would  -decline with  increasing population as the
value of exposed vegetation decreases.
                                 152

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Materials Damage - Particulate damage to materials is almost entirely in
the form of soiling, and actual economic losses are incurred only when the
frequency (or tost) of cleaning is increased.  Since the value of materials
exposed to damage  (or economic loss) by soiling is closely related to popu-
lation, the resulting damages would be expected to increase with increasing
population density.  It is unlikely that actual losses due to soiling at
the prescribed fine particulate concentrations of 75 and 60 ug/m^ would
amount to more than $10/person/year, and materials damage would more likely
be in the neighborhood of $4/person/year.

Aesthetic Damage - Aesthetic damage is the least quantifiable category of
economic losses suffered as a result of air pollutants, but is probably
second in importance only ,to health effects.  The main aesthetic effect of
particulates in the atmosphere is related to visibility.  Defining the
economic value of various levels of visibility, though, is a perplexing
problem.

There is considerable overlapping between aesthetic and materials damage,
especially in the area of soiling, in that soiling of materials does not
generally cause physical damage to most materials, but does impair human
enjoyment or appreciation of them.  It is this aesthetic effect that pro-
vides the incentive to clean the dirty materials.

Aesthetic damage is related to both population and area; to both the num-
ber of people affected and to the area over which the effects are experi-
enced.  On a per capita basis, then, aesthetic damages will decline as
population density increases, while in total they will rise with increas-
ing population.  For the purposes of this study, aesthetic damages at the
prescribed fine particulate concentration were assumed to range from about
$50/person in sparsely populated areas down to around $8/person in congested
urban areas.

TOTAL ECONOMIC DAMAGES

The preceding discussion presented a methodology for assessing the economic
damage attributable to particulate pollutants emitted from a specific
source.  To apply this procedure to a specific urban^ rural, or mixed loca-
tion with the objective of determining total economic damage from sources
in that area and the relative contribution of each aource, it is necessary
to have^data on factors such as (1) number and type of sources in a specific'
location Ci-e'» emission inventory), rates of emission from specific sources,
and economic values exposed to particulate pollutants.  Detailed analyses
for specific locations were outside the scope of the current program, and
only a generalized analysis of total economic damage as a function oftpopu-
lation densities was performed.
                               153

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Table 49 summarizes the estimated economic damages resulting from fine par-
ticulate emissions for areas exposed to a concentration of 75 ug/m3 with
population densities ranging from 10 to 50,000 persons/mile2.  Here, the
damages have been grouped  into three categories because of the difficulties
in distinguishing between  several closely related areas.  The three cate-
gories are:  (1) human health; (2) animals and vegetation; and (3) mate-
rials and aesthetics.

Total estimated economic damages per square mile resulting from a con-
tinuous ambient fine particulate concentration of 75 ug/m3 are shown in
Table 49 to range from $5,800/mile2 at a population density of 10 people/
mile2, up to $l,602,000/mile2 at a population density of 50,000.  Annual
per capita damages incurred over the same range vary from $580 down to
$32/person

These estimated damages are plotted, both in total and on a per capita
basis, in Figure 22.  Also shown in Figure 22 are population densities
typical of different geographic regions and metropolitan areas, ranging
from less than 12 people/mile2 over the State of Arizona, to some 75,000
people/mile2 in the Manhattan Borough of New York City.  Average popula-
tion density in the Continental United States is 50 people/mile2.

A typical suburban community consisting of single-family residences will
have around 4,000 to 5,000 people/mile2, while central city areas may
run two or three times that density.  Completely rural areas often have
only 20 to 30 inhabitants/mile2-

About 70 to 75% of the total U.S. population lives in urban areas, with the
rest in rural areas.  Applying these percentages to typical combination of
central city, suburbs, and outlying rural areas gives a composite popula-
tion density as follows:

            40% of population at density of 20,000 people/mile2
          + 35% of population at density of 5,000 people/mile2
          + 25% of population at density of 50 people/mile2

         = 100% of population at average density of 196 people/mile2

The economic losses suffered over the U.S. as a result of the particulate
pollutants would be in the $12,000 to $14,000/mile2 range, averaging about
$70/person annually.
                               154

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Table 49.  ESTIMATED DAMAGES RESULTING  FROM FINE PARTICLE POLLUTION AT
                     AN AMBIENT CONCENTRATION  OF 75 ug/m3
Annual Economic Damage
Fine Particulate

Population
Dens ity/mi^
10
20
50
100
200
500
1,000
2,000
5,000
10,000
20,000
50,000

Human
Health
200
400
1,000
2,000
• 4,000
10,000
20,000
40,000
100,000
200,000
400,000
1,000,000

Animals and
Vegetation
5,000
4,600
4,100
3,750
3,450
3,100
2,900
2,700
2,450
2,300
2,150
2,000
0
Attributable to 75 Jig/m
Concentration ($/mi )

Materials and
Aesthetics
600
1,120
2,100
3,900
6,800
14,500
25,000
44,000
92,500
160,000
280,000
600,000

Total
Damage
5,800
6,120
7,200
9,650
14,250
27,600
47,900
86,700
194,950
362,300
682,150
1,602,000
Annual
Per Capita
Damage
580
306
144
97
71
55
48
43
39
36
34
32
                             155

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01
a\
                                                               Okla.
                                                                      P.V., Minneap.
                                                         Brooklyn
                                         N.H.. Ind. Ohio Minn.   City   Dallas  Ks. .
                                       U.S.

                           Ariz. Col. Ks.  Avg.
                   1,000,000
                     100,000
                  a>
            &
                  I
                  8
                  UJ

                  ~s
                  o
                10,000
                       1,000
                      1  1.  1,   t,
                      I     I    I  I I II
                                       Cal.
                                                                    K.C.,
                                                                               Chicago  N.Y.C.
                                                Wash., N.Y.
V
                                N
X
                  Md.  Ct. R.I.  Phoenix Mo.  Seattle D.C.  Cit
                  ili  ii      nil   MIi.i
                  ~l  i  ii mi      I   I  ii i 1111     r~7
                                                                   Manhattan

                                                                   N.Y.C.


                                                                  _J
                                                                                            Jill
                                                                    fnjio.ooo
                                                                                Total Damage

                                                                                  ($/Yr)
                                                                                Per Capita Damage


                                                                                    ($Ar)
                          "I   I   I I  I I I 11	I   I  I  I I  I I 11      I   I   I I  I I I I I	I   I  I  I  I I
                                                                                                1,000
                                                                                                             V
                                                                                                             a>
                                                                         a
                                                                         a
                                                                                                       a.
                                                                                                       a
                                                                                                       U
                                                                  100
                           10
                                                                  10

                                                              100,000
                                       100                1,000              10,000


                                               Population Density - People/Mi*



Figure 22,   Economic damage resulting from continuous  exposure to 75 ug/m^  fine particulate  concentration

-------
Table 50 presents a comparison of the estimated damages resulting from
fine particle pollution at ambient concentrations of 75 and 60 ug/m3.
The damage at 60 ug/m3 is 80% of the estimated damage at 75 ug/m3.

COST/BENEFIT RELATIONSHIPS

Once the control cost/control efficiency relationships have been established
and the economic damage functions defined,  a benefit/cost table can be con-
structed for any given set of conditions.   Then,  from the benefit/cost
table, incremental benefit-cost relationships can be defined.   The point
at which incremental benefits and incremental costs are equal, or where
total economic costs are a minimum, represents the economic optimum con-
trol level.

Ultimately, the information thus developed  will provide a basis for expres-
sing the optimum control efficiency as a function of the economic damage
intensity rate.  For example, a control level of 99.7% might be appropriate
if the damage potential were $1.0 million/mile2,  while a higher efficiency
could be justified in more densely populated areas, and a lower efficiency
could be tolerated in areas less susceptible to economic damage.

Calculation of cost/benefit relationships will be illustrated using a coal-
fired power plant as an example.  Figure 23 illustrates the cost-vs-
efficiency relationships for fine particulate control on a 400-MW coal-
firetf electric generating plant, over the 99.0 to 99.9% control efficiency
range.  As shown in this figure, total annual control costs (with capital
charges included at a 20% annual rate) rise from $148,000 at 90% effi-
ciency, to an estimated $580,000 at 99.9% efficiency.

Table 51 shows the extent of impact of the  remaining fine particulate
emissions from the power plant at various levels of control efficiency,
employing the techniques described earlier  in this chapter.  The eco-
nomic impact area thus calculated describes the extent over which the
prescribed emissions will create and sustain a fine particulate concen-
tration of 75 or 60 ug/m3.  This area of influence (in mile2) multiplied
by the damage incurred per square mile at the specified population density
(from Table 49)  gives the total damage resulting from the specified emis-
sion source.

Tables 52 and 53 bring together the cost of control data from Figure 23
and the damage resulting from the uncontrolled fraction of the fine par-
ticulate emissions at populations densities of from 50 to 500 people/mile2,
thus developing the total economic cost of  fine particulate emissions under
the prescribed conditions.
                                157

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Table 50.  COMPARISON OF ESTIMATED DAMAGES RESULTING FROM FINE PARTICLE
              POLLUTION AT AMBIENT CONCENTRATIONS OF 75 AND 60 jig/m3
                                     ($/mile2)
Population
Density/mi^
10
20
50
100
200
500
1,000
2,000
5,000
10,000
20,000
50,000
Economic
Total
5,800
6,120
7,200
9,650
14,250
27,600
47,900
86,700
194,950
362,300
682,150
1,602,000
q
Damage at 75 Ug/m
Per Capita
580
306
144
97
71
55
48
43
39
36
34
32
Economic
Total
4,640
4,896
5,760
7,720
11,400
22,080
38,320
70,080
155,960
289,840
545,720
1,281,600
q
Damage at 60 ug/m
Per Capita
464
245
115
77
57
44
38
35
31
29
27
26
                                    158

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    0.1
 0.2
 0.4   0.5              1.0       1.5    2.0
       Uncontrolled Fine  Particle  Emissions (%)
_J	1	1	1	L_
3.0
5:0
7.0
ia.o
   99.9
99.8      99.7   99.6  99.5             99.0      98.5   98.0
                          Fine Particle Control Efficiency (%)
                                                97.0
            95.0    93.0
Figure 23.   Fine  particulate control  costs  for 400-MW coal-fired  electric generating  plant
                90.0

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Table 51.  EXTENT OF IMPACT OF UNCONTROLLED FINE PARTICLE EMISSIONS FOR
                           400-MW COAL-FIRED ELECTRIC PLANT
Fine Particle
Control
Efficiency
(%)
90.0
91.0
92.0
93.0
S 94.0
95.0
96.0
97.0
98.0
99.0
99.9
Uncontrolled
Fine Particle
Emissions
(%)
10.0
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.1

Uncontrolled
Emissions
Qb/hr)
370.0
330.0
296.0
259.0
222.0
185.0
148.0
111.0
74.0
37.0
3.7
Fine Particulate
Loading at 100 hr
Residence Time
(lb)
37,000
33,300
29,600
25,900
22,200
18,500
14,800
11,100
7,400
3,700
370
Economic
Impact Area
at 75 ug/m3
(ml2)
26.30
24. 15
22.66
20.73
18.70
16.56
14.27
11.78
8.99
5.66
1.22
Economic
Impact Area
at 60 ug/m3
(mi2)
31.76
29.60
27.37
25.04
22.59
20.01
17.24
14.23
10.86
6.84
1.47

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Table 52.  ECONOMIC COSTS OF CONTROL AND DAMAGE CAUSED BY FINE
               PARTICIPATE EMISSIONS AT VARIOUS POPULATION
                   DENSITIES AND CONTROL EFFICIENCIES
Fine Particle
Control
Efficiency
m
90.0
91.0
92.0
93.0
94.0
95.0
96.0
97.0
98.0
99.0
99.9
Annual
Control
Cost
( $1.000)
148
158
169
181
195
211
230
254
289
349
580
Total Annual Cost ($1,000) at Given Population Density for 75 ug/nr
50/miz , .
Damage
Cost
189.4
173.9
163.2
149.3
134.6
119.2
102.7
84.8
64.7
40.8
8.8
Total
Cost
337.4
331.9
332.2
330.3
329.6
330.2
332.7
338.8
353.7
389.8
588.8
100/miz
Damage
Cost
253.8
233.0
218.7
200.0
180.5
159.8
137.7
113.7
86.8
54.6
11.8
Total
Cost
401.8
319.0
387.7
381.0
375.5
370.8
367.7
367.7
375.8
403.6
591.8
200/miz 500/miz
Damage
Cost
374.8
344.1
322.9
295.4
266.5
236.0
203.3
167.9
128.1
80.7
17.4
Total
Cost
522.8
502.1
491.9
476.4
461.5
447.0
433.3
421.9
417.1
429.7
597.4
Damage
Cost
725.9
666.5
625.4
572.1
516.1
457.1
393.9
325.1
248.1
156.2
33.7
Total
Cost
873.9
824.5
794.4
753.1
711.1
668.1
623.9
579.1
537.1
505.2
613.7

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Table 53.  ECONOMIC COSTS OF CONTROL AND DAMAGE CAUSED BY FINE PARTICULATE
                                    EMISSIONS
Fine Particle
Control
Efficiency
(%)
90.
91.
92.
93.
£ 94.
95.
96.
97.
98.
99.
99.
0
0
0
0
0
0
0
0
0
0
9
Annual
Control
Cost
($1.000)
148
158
169
181
195
211
230
254
289
349
580
o
Total Annual Cost ($1,000) at Given Population Density for 60 ue/nr
50/miz
Damage
Cost
182
170
157
144
130
115
99
82
62
39
8
.9
.5
.7
.2
.1
.3
.3
.0
.6
.4
.5
Total
Cost
330.9
328.5
326.7
325.2
325.1
326.3
329.3
336.0
351.6
388.4
588.5
100/mi2
Damage
Cost
245.2
228.5
211.3
193.3
174.4
154.5
133.1
109.9
83.8
52.8
11.3
Total
Cost
393.2
386.5
380.3
374.3
369.4
365.5
363.1
363.9
372.8
401.8
591.3
200/mi2
Damage
Cost
362.1
337.4
312.0
285.5
257.5
228.1
196.5
162.2
123.8
78.0
16.8
Total
Cost
510.1
495.4
481.0
466.5
452.5
439.1
426.5
416.2
412.8
427.0
596.8
500/mi2
Damage
Cost
701.3
653.6
604.3
552.9
498.8
441.8
380.7
314.2
239.8
151.0
32.5
Total
Cost
849.3
811.6
773.3
733.9
693.8
652.8
634.7
568.2
528.8
500.0
612.5

-------
Here it can be seen that the total economic cost of pollution is, in every
case, high when the control level is low (at 90% in the example); costs
then decrease as controls increase,  until the optimum control level (the
point of minimum total cost) is reached; then increase as the benefits of
control can no longer justify their costs.   These total economic cost-vs-
control efficiency relationships are plotted in Figure 24 for the four dif-
ferent population densities.

As would be expected and is clearly evident in Figure 24, a high popula-
tion density (with its correspondingly high damage cost/mile2) justifies
a higher emission control efficiency than does an area populated at low
density.

In the example, the optimum control efficiency for a population density
of 500/mile2 is 99.1%; for 200/mile2, 97.9%; for 100/mile2, 96.0%; and at
50 people/mile2, 94.0% control is economically justified.  These optimum
control efficiencies are plotted against population densities in Figure
25.

Using this approach—refined, hopefully, with more reliable cost and bene-
fit data—the optimum control efficiency can be readily determined for any
particulate source or combination of sources at any location, employing
local characteristics in the analysis.  The approach should be equally
valid in appraising the economics of control for other air pollutants,
providing the relevant data can be developed.
                                163

-------
        1000
         800
  o
+- o

,92
  —  600
   II
   o o
   ° i j
   ii i \j
    1 &
    S o
   < E
   _ o
    o Q
         400
         200

            0.5
                                              I
                           1.0               2.0        3.0    4.0"   5.0


                               Uncontrolled Fine Particle  Emissions (%)
7.0
                                                                                             500
                                                                                                CN



                                                                                                 I
                                                                                                  0)

                                                                                                  Q.
                                                                                          200 £
                                                                                          100
                                                                                          50
10.0
                c
                0)

                Q


                c
                o
                D
                a.
Figure 24.  Total annual economic costs of fine particulate control at various population densities

-------
                     lOO.Or-
                      98.01
                   £
                   "o
                   £
                   0)
96.01
ui
                    0)
                    c
                    O
                   U

                    E
                      94.01
                   |  92.0|
                   "o.
                   O
                      90.01
                          30
                 50
      i	I

     100                200

Population Density - People/Mi^
500
                           Figure 25.  Optimum fine particle  control level at various population densities

-------
                              SECTION X
    OVERALL FEASIBILITY OF EMISSION  STANDARDS BASED ON PARTICLE SIZE

INTRODUCTION

Our analysis of the  implications  of  emission standards based on particle
size has identified  some technical deficiencies that will limit the type
of standards that  can be proposed and implemented in the near future.
However, because the technical deficiencies relate primarily to the lack
of data on particle  size distributions of effluents and control equipment
fractional efficiency, there  appear  to be no insurmountable technical
obstacles to emission standards based on particle size.
             r
The economic impact  of fine particulate  control was found to vary sub-
stantially from industry to industry.  Estimates of costs associated with
the control of fine  particulates  varied  from less than 1.0% up to 20% of
the value of the product.  The variation in economic impact suggests that
it will probably be  necessary to  consider less restrictive standards for
industries that experience a  significant adverse economic impact.

The types of emission standards that appear feasible based on existing
technical and economic realities  are discussed in more detail in the fol-
lowing section.

FEASIBILITY OF SPECIFIC TYPES OF  STANDARDS

Although our analysis of various  formats for,emission standards based on
particle size was  performed in the context of general regulations that
might be applied uniformally  to all  sources, a more realistic approach
would be to tailor the emission standard to specific sources of fine par-
ticulate pollutants.  Tailoring of standards would permit a greater degree
of flexibility in  an overall  control plan for fine particulates, and would
acknowledge the differences in the importance and difficulty of control
of individual sources.
                              166

-------
The exact format of the emission standard(s) that could be proposed and im-
plemented for specific sources will be limited by:  (1) collection effi-
ciency in fine particle size range of available control equipment, and (2)
availability of source compliance monitoring techniques.  Our conclusions
regarding the overall feasibility of the various formats for emission
standards investigated in this study are presented in the next subsections.

Opacity Regulations

Regulation of plume opacity provides a viable method of reducing the emis-
sion of fine particulates from stationary sources.  Opacity standards ap-
pear to be the easiest to implement of the alternatives analyzed in the
current program.  The data base for determining control equipment perfor-
mance requirements necessary for compliance with opacity standards is more
extensive than that available for other alternative emission standards.

Our analysis of the control equipment efficiency required for compliance
with a 10% or 57, opacity regulation indicated that for most sources the
opacity regulations would not impose collection efficiencies exceeding
existing equipment capability.  Even with allowance for inadequacies in
some of the data used to determine the collection efficiencies needed to
attain 10% and 5% plume opacity for specific sources,  compliance with
stringent opacity regulations would not generally require installation of
control equipment that exceeds the efficiency of the best control device
currently in use on that source.

Commercial transmissometers are available for measuring the in-stack opacity
of particulate emissions.  Although additional field testing needs to be
conducted to define the performance of transmissometers on several different
types of sources, transmissometers provide a suitable, demonstrated tech-
nique for instrumental evaluation of the compliance of a source with opacity
regulations.  With completion of additional field testing,  transmissometers
should rapidly achieve the status of "off the shelf" technology.

Since the opacity standards would generally require the installation of
control equipment that does not exceed the performance capability of the
best available technology, the estimated economic impact of opacity stand-
ards is less severe than that for other alternatives analyzed in this study.
The extent of reduction in the emission of fine particulates is also lowest
of the alternatives studied for the same reason.
                                   167

-------
Regulation Based on Best Installed Control System

An emission regulation which specifies that a  source cannot emit fine par-
ticulate in a quantity exceeding that which would be emitted from the same
source equipped with the best  control device currently being installed on
that source is obviously feasible.  A regulation of this type merely
specifies that ^11 sources must be equipped with the best control system
currently in use for the specific source category.

The major unknown regarding the use of the BICD concept as an emission
standard is the degree of emissions reduction  that can actually be achieved.
As noted in Appendix A, only a limited amount  of reliable data is available
on the fractional efficiency characteristics of control equipment.  In order
to determine the actual collection efficiency  of control equipment in the
fine particle size range, extensive field testing will be required with
reliable sampling techniques.

A standard requiring installation of  the best  control system currently in
use will have nearly the maximum economic impact on industrial sources.
The economic impact analysis presented in Chapter 6 clearly demonstrates
this observation.  Maximum  reduction  in  fine particle emissions would also
be achieved by  such an emission standard.

Mass Emission Regulations

A mass emission standard  specifying the maximum amount of particulate less
than a given particle  size  which  can  be  emitted from a source  is  the most
direct approach to regulating  the emission  of  fine particulates.  An almost
unlimited number of emission standards might be formulated using  restriction
of mass  emissions.

The concept of  potential-emission rate  offers  an  interesting basis  for emis-
sion standards  based  on  particle  size.   Regulations based on this concept
would establish emission limits which vary  with  the pollution  potential  of
the source, e.g.,  limitation of the mass  rate  of  fine particle emissions
in pound per hour  as  a function of  potential-emission rate of  fine  particu-
lates, also in  pound  per hour. Regulations of this  type could be tailored
to control  (1)  specific  sources of  fine  particulate pollutants;  (2) specific
size ranges within the fine particulate  range;'or  (3) specific components
of the fine particulate  stream emitted  by a given source.

In general, mass emission regulations are a feasible vehicle for  reducing
the emission  of fine  particulates,  and  they are  the most flexible of all
the types  of  standards considered in  this  study.   Because of the  inherent
                                   168

-------
flexibility afforded by the use of mass emission rates as a basis for fine
particle emission standards, the extent of reduction in emissions for
specific sources can be carefully selected and the technical and economic
impact can be tailored to fit the realities of a specific industrial cate-
gory.

To obtain maximum utilization of a mass emission regulation,  it will be
necessary to broaden the data base on fine particulate emission rates and
control device fractional efficiency.
                               169

-------
                                SECTION XI
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                                 172

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32.  Fletcher, C. M., B. M. Tinker, I. D. Hill, and F. E.  Speizer,  "A
       Five-Year Prospective Field Study of Chronic Bronchitis,"  preprint
       (presented at the llth Aspen Conference on Research  in Emphysema,
       June 1968).

33.  Douglas, J. W. B., and R. E. Waller, "Air Pollution and Respiratory
       Infection in Children," Brit. J. Prevent. Soc. Med., 2£, 1-8 (1966).

34.  Lunn, J. E., J. Knowelden, and A. J. Handyside, "Patterns of Respi-
       ratory Illness in Sheffield Infant School Children," Brit. J.
       Prevent. Soc. Med., 21, 7-16 (1967).

35.  Watanabe, H., "Air Pollution and Its Health Effects in Osaka,  Japan,"
       preprint (presented at the 58th Annual Meeting, Air Pollution Con-
       trol Association, Toronto, Canada, 20-24 June 1965).

36.  Bates, D. V., "Air Pollutants and the Human Lung," American  Review
       of Respiratory Disease, 10J5, 1-13 (1972).

37.  Connor, W. D., and J. R. Hodkinson, Optical Properties and Visual
       Effects of Smoke Stack Plumes,  PHS Publication No. 999-AP-30,
       Cincinnati, Ohio (1967).

38.  Junge, C. E., Air Chemistry and Radioactivity, Academic Press,  New
       York (1963).

39.  Middleton, W. E. K., Vision Through the Atmosphere, University of
       Toronto Press, Toronto (1952).                :

40.  Charleson, R. J., H. Horvath, and R. F. Pueschel, "The Direct  Mea-
       surement of Atmospheric Light Scattering Coefficient for Studies
       of Visibility and Air Pollution," Atmos. Environ., l_, 469-478
       (1967).

41.  Noll, K. E.j P. K. Mueller, and M. Imada, Atmos. Environ.. 1,  501
       (1967).                                                  ~~
        i
42.  Nicholson, B. R., "Visibility Effects of Various Atmospheric Pollu-
       tants," New .Mexico Environmental Improvement Agency  (1971).

43.  Gates, D. M., "Spectral Distribution of Solar Radiation at the Earth's
       Surface," Science. 151, 523-529 (1966).
                                 173

-------
44.  McCormick, R. A., and D. M. Baulch,  "The  Variation with Height  of
       the Dust Loading Over a  City  as  Determined  from the Atmospheric
       Turbidity," JAPCA, 12, 492-496  (1962).
                                                                   >
45.  Robinson, N., Solar Radiation.  Elsevier,  Amsterdam,  London,  and
       New York (1966).

46.  Landsberg, H., Physical Climatology,  2nd  Edition,  Gray, Dubois,
       Pennsylvania,  317-326 (1958).

47.  Steinhauser,  F., 0. Eckel,  and  F.  Sauberer, "Klima and Bioklima von
       Wien," Wetter  und Leben,  £ (1955).

48.  Meetham, A.  R.,  Atmospheric Pollution;  Its Origins  and Prevention,
       Pergamon Press, New York (1961).

49.  Mateer, C. L., "Note on the Effect of the Weekly Cycle of  Air Pollu-
       tion on Solar  Radiation  at  Toronto," Intern.  J.  Air Water  Pollution,
       4, 52-54 (1961).

50.  Robinson, G.  D., "Long-Term Effects of Air Pollution - A Survey,"
       Center for the Environment  and Man,  Inc., Hartford, Connecticut,
       June 1970.

51.  Cobb, W. E.,  and H. J. Wells, "The Electrical Conductivity of Oceanic
       Air and Its Correlation  to  Global Atmosphere Pollution," Journal  of
       Atmospheric Sciences, 27^  814-819,  August 1970.

52.  Air/Water Pollution Report,  7 May  1973.

53.  Watt, K. E.  F.,  "Tambora and  Krakatau:  Volcanoes and the  Cooling of
       the World," Stanford Research Quarterly, December  1972.

54.  "Restoring the Quality of  Our Environment," report of the  Environ-
       mental Pollution Panel,  President's Science Advisory Committee,
       The White  House, Washington,  D.C.,  111-131, November 1965.

55.  Changnon, S.  A., "The LaPorte Weather Anomaly—Fact  or Fiction,"
       Bulletin of American Meteorological Society.  49^ (1), 4-11  (1968).

56.  Hobbs, P. V., et al., "Cloud  Condensation Nuclei from Industrial
       Sources and Their Apparent  Influence on Precipitation in
       Washington State," Journal  of Atmospheric Sciences. 27_,  81-89
       (1970).
                                 174

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57-  Aynsley, E., "How Air Pollution Alters Weather," New Scientist,
       66-67, 9 October 1969.

58.  Schaefer, V. J., "The Inadvertent Modification of the Atmosphere by
       Air Pollution," Bulletin of American Meteorological Society, 50^
       (4), 199-206 (1969).

59.  Warner, J., "A Reduction in Rainfall Associated with Smoke from Sugar
       Cane Fires - An Inadvertent Weather Modification," J. Applied
       Meteorology, 7, 247-251 (1968).

60.  "Particulate Pollutant Systems Study, Volume I - Mass Emissions,"
       Midwest Research Institute, EPA Contract No. CPA 22-69-104,
       1 May 1971.

61.  "Particulate Pollutant Systems Study, Volume II - Fine Particle Emis-
       sions," Midwest Research Institute, EPA Contract No. CPA 22-69-104,
       1 August 1971.

62.  "Particulate Pollutant Systems Study, Volume III - Handbook of Emis-
       sion Properties," Midwest Research Institute, EPA Contract No. CPA
       22-69-104, 1 May 1971.

63.  Goldberg, A. J., "A Survey of Emissions and Control for Hazardous and
       Other Pollutants," EPA/OR&D internal report, November 1972.

64.  Hidy, G. M., and S. K. Friedlander, "The Nature of the Los Angeles
       Aerosol," Proceedings of the Second International Clean Air Congress,
       H. M. England and W. B. Beery, Editors, Academic Press, New York
       (1971).

65.  Duncan, L. J., "Analysis of Final State Implementation Plans—Rules
       and Regulations," The Mitre Corporation Report MTR-6172, Rev. 1,
       July 1972.

66.  Feldman, P. L., and D. W. Coy, "Comparison of Computed and Measured
       Opacities:  Lignite-Fired Boilers," Research Cottrell, Bound Brook,
       New Jersey.

67.  Callaghan, D. J., "Detailed Background Information for Modification
       of Regulation 2 Regarding Particulate Emissions," (BAACD internal
       memo).
                               175

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68.  Ensor, D. S., and M. J. Pilat, "Calculations  of  Smoke  Plume Opacity
       from Particulate Air Pollutant  Properties," J. Air Poll. Control
       Assoc.. 2U No. 8, 496-501  (1971).

69.  Greco, J., and W. A. Wynot,  "1971 Operating and  Maintenance Problems
       Encountered with Electrostatic  Precipitators," American  Power Conf.
       Proc.. 33, 345-353.

70.  "Scurbbing System Removes  Submicron Particulates,"  Chem. Eng.,
       20  September 1971.

71.  Teller, A. J., "A Fresh Look at the Technology of Particulate Re-
       moval Via  Scrubbing," Eng.  Mining J.,  April 1971.

72.  "A New Process for Cleaning  and Pumping  Industrial  Gases—The Aero-
       netics System," U. S. Patent No.  3,613,333.

73.  Private Communication, Mr. H. E.  Gardenier, Vice President, Aero-
       netics, Inc.,  September  1972.

74.  Sem,  G. J.,  et al., "State of the Art:   1971-Instrumentation for
       Measurement of Particulate Emissions from Combustion Sources,"
       Thermo-Systems, Inc., EPA  Contract CPA 70-23,  July 1972.

75.  Sem,  G. J.,  et al., "Monitoring Particulate Emissions," Chem. Eng.
       Prog., 67_9 No. 10, October 1971.

76.  Presentation to  Bay Area Air Pollution Control District Advisory
       Council by Bay Area League of Industrial Association, Inc.,
       September  1970.

77.  Internal Memo of Chief Administrative Officer, Bay  Area Air Pollution
       Control District, 22 July  1970.

78.  Texas Air Control Board, "Instrumental Method for Measurement of
       Transmittance," 14 September 1972.

79.  McKee, H. C., "Instrumental  Method  Proves Superior  for Control of
       Visible Emissions," paper  73-245, presented at the 66th  Annual APCA
       Meeting, Chicago, Illinois, 24-28 June 1973.

80.  Bentner, H.  P.,  "Measurement of Opacity  and Particulate Emissions
       with the Lear  Siegler On-Stack  Transmissometer,"  paper 73-169, pre-
       sented at  the  66th Annual  APCA  Meeting, Chicago,  Illinois, 24-28
       June 1973.

                                   176

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81.  Yocom, J. E., "Problems in Judging Plume Opacity—A Simple Device
       for Measuring Opacity of Wet Plumes," J. Air Poll. Control Assoc.,
       13;(1), 36-39 (1963).

82.  Bird, A. N., J. D. McCain, and D. B. Harris, "Particulate Sizing
       Techniques for Control Device Evaluation," paper 73-282, pre-
       sented at 66th Annual APCA Meeting, Chicago, Illinois, 24-28 June
       1973.

83.  Dorman, R. G., "Dust Sampling," Filtration and Separation, November-
       December 1968.

84.  Badzioch, S., "Correction for Anisokinetic Sampling of Gas-Borne
       Dust Particles," J. Inst. Fuel. March 1960.

85.  Logan, T. J., et al., "Experimental Investigation of Isokinetic and
       Anisokinetic Sampling of Particulates in Stack Gases," paper pre-
       sented at the 65th Annual Meeting of the AICHE, New York, November
       1972.

86.  Jackson, M. L., "Particle-Molecule Collection by Sonic Flow Im-
       pingers," paper presented at the 65th Annual Meeting of the Air
       Pollution Control Association, Miami Beach, Florida, June 1972.

87.  Control Techniques for Particulate Air Pollutants, U.S. Department
       of Health, Education, and Welfare, Washington, D.C.  (1969).

88.  Sargent, Gordon D., "Dust Collection Equipment," Chemical Engineering,
       January 1969.

89.  O'Connor, J. R., and J. F. Citarella, "An Air Pollution Control Cost
       Study of the Steam-Electric Power Generating Industry," APCA
       Journal, 20(s), 283-288 (1970).
                               177

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                             SECTION XII
                           GLOSSARY OF TERMS

   A = Area

   b = Extinction coefficient

   c = Annualized cost

  Cc = Average efficiency of control equipment

  Ct =' Percentage of the production capacity on which control  equip-
         ment has been installed

   E = Emission rate, tons/year

  ef = Emission factor (uncontrolled), pounds/ton

g(r) = Mass distribution function

   I = Intensity Of transmitted light

  I0 = Intensity of incident light

     _ Specific particulate volume
         Extinction coefficient

   L = Visual range

   M = Mass concentration

   m = Refractive index of the particles relative to air

n(r) = Size frequency distribution, number of particles  of radius  r
         per volume per Ar

   P = The production rate, tons/year
                               178

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) = Particle light extinction efficiency factor, the total light
      flux scattered and absorbed by a particle divided by the
      light flux incident on the particle

r = Particle radius

t = Time

R = Radius

T = Plume transmittance

W = Mass concentration of particles in exhaust stream

a = Size parameter, 2nr/X

X = Wavelength of light

p = Particle density
                                 179

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                            SECTION  XIII
                             APPENDICES
                   CONTROL TECHNOLOGY FOR FINE PARTICLES
INTRODUCTION
The technology applicable to the control of fine particles is the same as
for any participate emissions, but with interest centered on the higher
efficiency equipment.  Currently available devices include electrostatic
precipitators, wet scrubbers, fabric filters and afterburners.  New con-
trol devices are under development with the aim of removal of fine parti-
cles at lower cost or more efficiently.  Characteristics of both the
conventional devices and some new devices and control concepts are de-
scribed in the following sections of this appendix.

CURRENTLY AVAILABLE CONTROL TECHNOLOGY

The control devices currently available for controlling fine particle
emissions are generally the same as those usually considered for control-
ling total particulate emissions, that is, electrostatic precipitators,
fabric filters, scrubbers and afterburners.  However, to date there has
been little incentive for manufacturers to investigate the ability of
their equipment to remove fine particles.

Currently, control equipment is rated mainly by one parameter, namely,
overall mass efficiency.  Specification of control equipment efficiency
by overall performance is inadequate with respect to fine particle emis-
sions.  Penetration (i.e., 1-mass efficiency) in specific size ranges is
a more revealing term for rating control equipment performance.  Correla-
tions of penetration vs particle size are called "fractional efficiency
curves."  Table A-l presents typical data on average collection effi-
ciencies for various particle sizes and various particulate control
equipment.!./

Midwest Research Institute, under contract from EPA, has been conduct-
ing several studies involving the control of fine particulate emissions
                         180

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     Table A-l.  AVERAGE COLLECTION EFFICIENCIES FOR VARIOUS PARTICLE SIZES
                           AND VARIOUS PARTICIPATE CONTROL EQUIPMENT*/
Efficiency. %, in Micron Ranee
Type Collector
Baffled settling chamber
Simple cyclone
Long -cone cyclone
Multiple cyclone
Overall
58.6
65.3
84.2
74.2
0-5
7.5
12
40
25
5-10
22
33
79
54
10-20
43
57
92
74
20-44
80
82
95
95
X.M.
90
91
97
98
 (12-in. diameter)

Multiple cyclone               93.8       63       95       98         99.5      100
 (6-in. diameter)

Irrigated long-cone            91.0       63       93       96         98.5      100
  cyclone

Electrostatic precipitator

Irrigated electrostatic
  precipitator

Spray tower

Self-induced spray
  scrubber

Disintegrator scrubber

Venturi scrubber

Wet impingement scrubber

Baghouse
97.0
99.0
94.5
93.6
98.5
99.5
97.9
99.7
72
97
90
85
93
99
96
99.5
94.5
99
96
96
98
99.5
98.5
100
97
99.5
98
98
99
100
99
100
99.5
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
a/  Data based on standard silica dust with the following particle distribution:

               Particle Size Range Microns           Percent by Weight

                           0-5                              20
                           5-10                             10
                          10-20                             15
                          20-44                             20
                           > 44                             35
                                         181

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from stationary sources.  A part of  this effort has involved the evaluation
of information that  is  available on  the fractional efficiency measurements
of different control devices.2/  Our analysis  indicated that a major por-
tion (over 957o) of the  data currently available on the particle size of
particulates emitted from industrial sources has been obtained by sampling
and particle sizing  techniques that  are not suitable for the particle size
range < 2 u.  As a result, only a meager quantity of accurate data is avail-
able on particle size in the < 2 u size range for effluents  from uncontrolled
or controlled sources.   As a result,  the ability of control devices to col-
lect the < 2 u particles is ill-defined.

Figures A-l to A-4 illustrate some of the available fractional efficiency
data.2_/  Log-probability coordinates were used in order to magnify the ef-
ficiency relationship for the smaller particles.  All available information
relating to specific type of device,  overall efficiency, operating condi-
tions  (such as pressure drop or water rate, etc.), and sampling and analy-
sis techniques are included.  Figure A-l illustrates data  for electrostatic
precipitators, while Figure A-2 presents fabric filter fractional efficiency.
Wet scrubber characteristics are given in Figures A-3 and  A-4.  The data for
each type of device varied over a wide range,  but this variation is not
surprising considering  the variations in types and design  of devices, test-
ing procedures, operating conditions and particle size analysis techniques.

Since the data for each type of device did vary over a wide range, the
curves were examined with the objective of drawing general curves that
would represent low, medium, and high overall  efficiencies for each type
of device.  The data for each type of control  device were  carefully as-
sessed to determine  the general fractional efficiency curves shown in
Figure A-5.2/

Performance Capabilities of Current  Equipment

The fractional efficiency curves described in  the preceding section show
that even though the control devices can achieve overall mass efficiencies
in excess of 99%, their ability to remove fine particles is often sig-
nificantly less.

Variations in the usual control equipment designs may increase the cap-
abilities of these devices.  One such variation is the wet electrostatic
precipitator in which water removes  the collected material and often makes
possible the use of electrostatic precipitation on sources where it would
otherwise not be suitable.  Preconditioning of effluent and injection of
NHq or other gases has  also been used to change the resistivity of the
dust to permit better collection in  electrostatic precipitators.
                               182

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            99.99
00

CO
                                                                                                               ELECTROSTATIC PKCIPITATOSS .
                                                                                                                                        u
                                                                                                                                        O
                                                                                                                                        o
                                                                                                                                        u
                                                                                                     10.0
                                                                                                                                 100.0
                                                                  MRTlClf DIAMtm - MICKONS
                              Figure A-l.   Fractional  efficiency data for  electrostatic precipitators

-------
                   Symbol Identification for Figure A-l







D  Stairmand, Dry ESP




    Stairmand, irrigated ESP




    Well Conditioned Dust, Particle Sizing by Electron Microscope




K  Wet ESP, High Resistivity Dust, Particle  Sizing by Electron Microscope




O  No  Information Except 99.9 % Efficient




£3  No  Information Except 99.9 % Efficient




V  P'lot Scale ESP on Coal-Fired Boiler; Gas Velocity 2.62 Ft/Sec




A  "Typical" Curve
                                    184

-------
00

tn
            99.9°







            99.9


            99.£






            99.0 -








            95.0




            90.0
                                                                 1 - 1
                                                                                                  1 - \
I  I  | [
          O
             50.0
             20.0
-I	1	1	T



 FABRIC FIITE"
                                        0.05


                                        0.1


                                        0.2



                                        0.5


                                        1.0


                                        2.0




                                        5.0




                                        1C.O




                                       20.C #.



                                           Z


                                           O
                                                                                                                                                     50.0
                                           O
                                           *-
                                           u
                                           tJ

                                           6
                                           u
                                                                                                                                                     90.0




                                                                                                                                                     95.0








                                                                                                                                                     99.0







                                                                                                                                                     99.8


                                                                                                                                                     99.9







                                                                                                                                      -I	1	1—L_L_LJ99.99
                                                                                                                                                    100
                                                                          PARIICU  DIAMETER - MOONS
                                         Figure  A-2.   Fractional  efficiency data  for fabric  filters

-------
           Symbol Identification for Figure A-2







    35 Shakes, Precoated, Monodisperse Aerosol, 1-4 In. A




    Loaded, Precoated, Monodisperse Aerosol, 1-4 In. AP




1C  No Information Except 99.9 + % Efficient.




£3  No Information Except 99.9 + % Efficient
    Data Using Cascade Impactor, Shake Type Collector, Very Low AP




    Data Using Cascade Impactor, Ultrajet Type Collector,  10-12 In. A P
                                  186

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                99.99-
00
                 0.01
                   0.01
                                                                                                                               SCRUBBERS
                                                                                                                     10.0
                                                                                                                                                        0.05
                                                                                                                                                        0.!
                                                                                                                                                        C.?

                                                                                                                                                        0.5
                                                                                                                                                        1.0
                                                                                                                                                        2.0

                                                                                                                                                        S.O

                                                                                                                                                       10.0

                                                                                                                                                       20.0
                                                                                                                                                       90.0

                                                                                                                                                       95.0


                                                                                                                                                       99.0
                                                                                                                                                       99.8
                                                                                                                                                       99.9
-g_l_U99.99
     100.0
                                                                                                                                                            u
                                                                                                                                                       50.0  ~
                                                                                                                                                            4W
                                                                                                                                                           O
                                                                                                                                                           0
                                                                                                                                                           a
                                                                             PARTICLE DIAMETER • MICRONS
                                              Figure  A-3.    Fractional  efficiency data  for wet  scrubbers

-------
            Symbol Identification for Figure A-3


    Stairmand, Gravity Spray Tower, Less Than 1 In. AP

    Stairmand, Impingement Scrubber

    Stairmand, Orifice Scrubber

    Stairmand, Venturi Scrubber

    Spray Tower, Soluble Dust (Na^/SO^), Optical Counter,  Liquid Flowrates
       Approximately 0.03 Ft^/Mirx

LJ  Venturi Scrubber "Typical" Curve

t3  Venturi Scrubber,  H3PO4 Plant Mist, Approximately 30 In. Ap
                               188

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          99.95
00
ID
                                                                                                                   I	1	1	L_l_L_U99.99
                                                                                                    10.0
                                                                 PAITIClf OIAMITEI • MICHONS
                                                                                                                                 100.0
                                   Figure A-4.   Fractional  efficiency  data  for wet  scrubbers

-------
                 Symbol Identification for Figure A-4
LJ   Data Using Cascade Impactor

W   4-6 In. H2O AP, 4 gpm/1,000 cfm

Q   4-6 In. H2O Ap, 3.3 gpm/1,000 cfm

     4-6 In. H2O Ap, 3.0 gpm/1,000 cfm
£3   Perforated Plate Scrubber, 3 Plates, 2,750 cfm, Vane Separator, Water Recycled,
        12 In. AP

     Perforated Plate Scrubber, 3 Plates, 2,750 cfm, Venturi Separator, Water Recycled,
        12 In. A,P

     Perforated Plate Scrubber, 3 Plates, 2,750 cfm, Venturi Separator, Fresh Water,
        12 In. AP

     Asphalt Plant,  Wet Scrubber, Low Ap

     Venturi Scrubber (1967), Throat Velocity 17,800 Ft/Min

     Orifice Scrubber (1967), 6 In. AP

O   Wet Centrifugal Scrubber (1967),  3.5 In. AP

O   Venturi Scrubber, 30 In. AP, H3PO4 Mist

A   Stairmand, Spray Tower, 1  In. AP, 18 Gal/1, OQO cf.

     Stairmand, Venturi Scrubber, 6 In. Throat, 3,500 cfm Gas
                               190

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99.99
                                                                               0.01
           i     I	1—i—i—r—n
                              fAHTICU DIAMETER - MICRONS
                                                                              99.99
       Figure A-5.   Extrapolated fractional efficiency of  control  devices
                                        191

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One of the largest users of electrostatic precipitators has been the coal-
fired power plants.  Electrostatic precipitators in this service process
very large volumes of flue gases at temperatures usually in the range of
300-600°F.  Design efficiencies may be as high as 99.7% but the particle
size of the flyash emissions is comparatively large.

Wet scrubbers are in wide use  in many types of sources and there have been
a multitude of variations in design.  These devices have generally not been
used for controlling sources containing a large percentage of fine parti-
cles except for higher pressure drop Venturi scrubbers.  Venturi scrubbers
are capable of high overall mass efficiencies (> 997o) even on sources con-
taining a higher percent of fumes such as basic oxygen furnaces in the
steel industry.  More recently, variation in scrubber design for pressure
drops on the order of 4-10 in. of H20 have shown high efficiencies.  Ex-
amples of this are the marble  bed scrubber and the turbulent contact ab-
sorber.  These types of  scrubbers have undergone increased development in
connection with S02 removal processes for power plants, etc.

Fabric filters are usually considered as the highest efficiency device and
have been demonstrated to have efficiencies in excess of 99.9%.  Variations
in design of fabric filters include  fabric material and cleaning method.
The cleaning method may  also permit variations in air to cloth ratio which
range from as low as 2 cfm/ft^ up to 25 cfm/ft2.

For many sources, as the applied control device efficiencies are increased,
the emissions during periods when the control devices are out of operation
or when their operation  is impaired become quite significant.  Reliability
and maintenance requirements are briefly reviewed in the next section.

Maintenance and Reliability Requirements of Current Equipment with Regard
  to Control of Fine Particles

Increasingly stringent emission  regulations will make it imperative  that
control devices installed operate reliably.  As a first requirement, the
control device and all associated equipment must be properly designed with
the proper materials of  construction and adequate instrumentation to shut
the system down or bypass the  control device in case of upsets.  This is
necessary to prote'ct the control equipment; and prevent long and costly
downtimes for repairs.

Assuming that the equipment has been properly designed and proper materials
of construction used, regular  maintenance and inspection schedules must be
followed in order to avoid unscheduled downtime for repairs and to prevent
deterioration in the operating efficiency of the system.  Because the fine
                                 192

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particle fraction of any effluent stream is the most difficult to collect,
it is this portion of the effluent which will most likely escape collection
if the equipment is not kept at its peak operating efficiency.

Each type of control device has its own characteristic problem areas that
most frequently occur, leading to decreased efficiency and lowering reli-
ability, if regular maintenance is not practiced.  In the case of electro-
static precipitators the most frequently reported problem is breakage of
electrode wires which takes that associated section of the precipitator
out of operation.  This may cause only a small decrease in efficiency but
the problem usually cannot be repaired without shutting down all or a "Large
part of the precipitator.  References 3 and 4 report the results on a study
of the reliability of electrostatic precipitators of various design types
serving 51 power generating units of TVA.  Figure A-6 indicates the items
that contributed to the average unavailability of nine classes of electro-
static precipitators on the TVA system over a recent year's operation._L'
Reference 3 reported that the overall weighted average availability was
92.6% for a 1-year period of operation.

Wet scrubbers are especially susceptible to corrosion and buildup problems.
Corrosion problems are best controlled by choice of construction materials
and inspection and repair during regular shutdowns.  Buildups of particu-
late matter or other solids from the scrubbing solution are a problem that
may be more difficult to control than corrosion.  Both problems of corro-
sion and buildup will result in decreased efficiency of particulate removal,
with the finer particles being the ones most likely to escape collection.

Operational reliability of fabric fibers is related to prevention of over-
heating or condensation.  Any malfunction that causes either situation can
quickly ruin the entire set of bags in a fabric filter unit.  This not only
requires costly replacement of the fabric but also takes the control device
out of service until new fabric can be obtained and installed.
                                                                       i
Another problem, one that may be difficult to detect, is small holes inj the
bags.  This can occur because of abrasive particulate  matter, but it is
also often due to improper installation and tensioning of the bags.  This
latter problem is preventable if regular and proper maintenance inspection
and repairs are carried out.

Few people would question the merits of a good maintenance program, but the
press of plant operations often cause such programs to be passed over.   It
is often the nonproduction equipment, such as pollution control devices,
that are neglected.  Increasingly stringent regulations and monitoring ef-
forts along with required incident reports and penalties are being implemented.
                               193

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 23
 22
 21
 20/7
   /
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                                                     UNKNOWN
           \

           V

        \  N
                                3  Z
                                         ^
                                         v  \
                                         s  \
                                            \
                                                 \  0
                                                 \  V
          A
                 PRECIPITATOR
        B     C     D    E     F
H
 Figure  A-6.   Electrostatic  precipitator  unavailability
                            194

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The incident reports and penalties should help to promote regular mainte-
nance programs to keep the installed equipment operating at its peak with
resultant improvement in collection—especially of the fine particle frac-
tions.

NEW OR EMERGING CONTROL TECHNOLOGY

There are several possible avenues that might lead to improved control of
fine particulates.  The more promising approaches can be grouped into three
broad categories:   (1) development of new or novel particulate control de-
vices; (2) augmentation of commonly used collection mechanisms by additional
forces that do not  approach zero in the ^ 2 ji size range; and (3) particle
agglomeration techniques.

Recent developments in each area are briefly summarized in the following
sections.

New Control Devices

A variety of devices which are claimed to have high collection efficiencies
in the fine particle range have been reported in the literature.  Table A-2
presents a list of  many of the devices recently reported in the literature.
For most of these devices supporting data for the claims of high efficiency
are meager, unavailable, or inconclusive.  Extensive testing programs will
be required to determine the full potential of these devices.

One of the more promising new control devices is the ADTEC system.  The
ADTEC system is a wet scrubbing system that operates on the conventional
Venturi collection  mechanism of inertial impaction, but establishes the
requisite particle-droplet differential velocity by utilizing waste process
heat rather than external energy.  On the basis of currently available in-
formation, this system appears to offer significant improvement in the col-
lection of fine particles, at modest energy consumption rates, where a
waste gas is available which contains a sufficient amount of thermal
energy. SiZ./

Control devices utilizing steam condensation also appear to offer promise
for improved collection of fine particulates.  Condensation phenomena are
already utilized in many types of wet scrubbers in that the effluent gas
is contacted with water spray resulting in cooling and saturation of the
gas stream.  However, the efficiency of these devices for removing fine
particles is not especially high unless considerable mechanical energy is
dissipated during the condensation, such as that which occurs in a Venturi
scrubber.
                                    195

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         Table A-2.  NEW CONTROL DEVICES FOR PARTICULATE POLLUTANTS
   Control Devices
Manufacturer(s) or Investigator(s)
ADTEC-wet scrubber
Aerodynamic immaculator
  (wet scrubber)

PENTAPURETM IMPINGER
Nucleation scrubber
Condensation  Scrubber
Granular bed  filters
Fluid beds
Charged droplet  scrubber
 Space charge  precipitator

 Pulsed  precipitator
Electret  filters
  Aronetics, Inc.
  Tullahoma, Tennessee

  Lone Star Steel Company
  Lone Star, Texas

  Purity Corporation
  Elk Grove Village, Illinois

  Teller Environmental Systems, Inc.
  New York, New York

  Oak Ridge National Laboratory,
    APT, Inc.
  University of Melbourne

  Rex-Chainbelt, Inc., Ducon Company
  Carnegie-Mellon University, City
    University of New York

  University of Idaho,
  Oregon State University

  TRW, Inc.
  University of Washington,-MIT

  University of California

  Belco Pollution Control

  Battelie Northwest
                                 196

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The experimental work of Schauerl/ has demonstrated that condensation ac-
complished by the use of a diverging nozzle system can produce very high
removal efficiency, but this requires excessive quantities of steam.
Lancasters1 work2/ indicates that condensation phenomena offer a potential
means of improving the operational efficiency of existing wet scrubber
units but the technique of direct steam injection is inefficient and could
only be considered in situations where low pressure waste steam was avail-
able.

The inefficient usage of steam appears to be due primarily to inadequate
distribution of the steam between potential condensation nuclei.  If the
efficiency of steam usage can be increased by the design of special con-
densation scrubbers which adequately distribute the condensed steam among
aerosol particles, the system could be competitive with conventional
scrubbers in normal applications.  For the removal of ultrafine particles,
the condensation scrubber may prove to be superior.

Augmentation of Collecting Mechanisms

Theoretically, improvements in the control of fine particles might result
from better exploitation of particle collection mechanisms (e.g., dif-
fusiophonesis, thermophoresis).   Such phenomena might be used advantage-
ously for collection of fine particles if devices can be designed to
utilize them without unreasonable high energy requirements.

A brief presentation of some of the theoretical aspects and experimental
results for these mechanisms is given in the succeeding sections.  A more
in-depth analysis of these mechanisms, with emphasis on wet scrubber tech-
nology, has been carried out by Calvert, et al.10-12/ among others.  Equa-
tions presented and developed by Calvert plus the many important references,
will be of interest to those who may want to continue investigations in
this area.

Thermophoretic Forces - Exploitation of thermal forces to improve the col-
lection of fine particles might be accomplished in one of two ways:  (1)
design and construction of cleaners based entirely on particle deposition
by thermal forces; and (2) use of thermal forces as a contributing mecha-
nism in existing dust collectors.

From the standpoint of the collection efficiency of fine particulates,
thermal precipitators appear quite promising.  However, consideration of
                                 197

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the energy requirements presents a different picture.  The power required
for thermal precipitation would be at least an order of magnitude greater
than that required for most other air cleaners.  If waste thermal energy
is available from the gas stream that is being cleaned, then a thermal
precipitator is more attractive from an external energy consumption stand-
point. '       l

The deposition of particles from a hot gas in a cooled, packed bed is an
instance in which thermal forces may improve collection efficiency.  Ex-
periments have shown that when a packed bed is initially cold, particle
collection is more nearly complete.  Theoretical calculations indicate
that, since the passages in a bed are narrow, a temperature difference of
50°C might give rise to a temperature gradient of 1000°C/cm in the pass-
ages.  Calculations show that this could result in the deposition of 98.8%
of the 0.1 u particles in a 9-in. deep bed.il/

Diffusiophoretic Forces - Diffusiophoresis might be a useful mechanism to
exploit in conjunction  with other mechanisms  for  the removal of small
particulates from gas streams.  Diffusiophoresis has the following ad-
vantages:

1.  The fundamental mechanisms is independent of particle size and becomes
more important compared to other removal mechanisms for particles below
2 u.

2.  The particulate removal efficiency that can be expected depends on
operating conditions and equipment design but  can  theoretically reach
100%.  In a more practical situation, theory indicates that diffusio-
phoresis might account for more than 30% of the total collection effi-
ciency.

To exploit the mechanism of diffusiophoresis, the collecting device must
be designed such that one component in the gas phase is diffusing toward
a collecting surface.  The most practical case would be the diffusion of
water vapor toward a surface.
                                  198

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Agglomeration of Particles

The agglomeration or coagulation of particulates could be used as a step
in a sequence of operations aimed at controlling the emission of fine
particles.  If sufficiently large particles can be produced,  it may be
possible to use conventional low-cost techniques as the final collection
step.  The movement of particles toward one -another may be brought about
solely by Brownian motion, but usually other influences play a major role,
e.g., turbulence of the fluid, gravitational forces, electrostatic forces,
and sonic forces.

The following sections discuss the nature of particle agglomeration with
and without the use of external forces, and indicate possible avenues
that might be utilized to enhance the control of fine particles.

Agglomeration in Absence of External Forces - When the movement of parti-
cles, leading to contact and agglomeration, can be accomplished only by
Brownian movement  (diffusion), the process  is called thermal coagulation.

The major disadvantage of thermal agglomeration is the long time required
to grow particles.  The only variables which can be used to control
particle-particle  collision rate are temperature, gas composition and
the particle concentration.  The temperature and suspending gas composi-
tion do not appear to be useful variables.

The possibility of influencing the coagulation rate of particles suspended
in air by introducing a second gas or vapor has been explored in several
experimental programs, and the only clear-cut results seem to be those in
which the added vapor in  some way affects the shape of the particles, or
in which vapor is  actually being transferred between the vapor phase and
the particles so that appreciable gaseous diffusion occurs (i.e., dif-
fusiophoresis).

Onercould conceivably change  the particle distribution and concentration
by seeding  the particle suspension with large particulates to act as
"agglomeration sites," but this does not appear very useful based on ex-
perimental  studies.  Thus, thermal agglomeration is  not a viable approach
to augmenting the  ability  of  control systems to control fine particulate
emissions.
                                  199

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Turbulent Agglomeration - Turbulence  increases the relative velocities
among particulates which in turn  increases  the chance of particulate col-
lision.  Theoretical studies on the coagulation  of aerosols in turbulent
flow have been conducted by Levich,!!/ East and  Marshall,JA/ Tunitskii,I-L/
Obukhov and Yaglon,lJI/ and Beal.il/

Experimental study of the rate of agglomeration  in the presence of tur-
bulence is difficult because turbulence also accelerates the deposition
of particles on walls.  The rate of deposition increases with particle
size so that the assessment of the course of agglomeration from the in-
crease in mean particle size in complicated.  Experiments by Yoder and
Silverman are the only results that are subject  to any rigorous analy-
sis.—'  These investigators performed experiments to obtain data on the
deposition and agglomeration of particles in turbulent air flow.   In
their experimental design, deposition and agglomeration were occurring
simultaneously, and their basic problem was to separate the two effects.
They did this by measuring both the total number concentration and the
fraction of particles which had agglomerated at  the inlet and outlet of
their test section.  By applying theoretical concepts, they could then
infer the separate effects of both deposition and agglomeration from the
measured parameters.  They did not, however, make any direct observation
of either phenomenon.

Figures A-7, A-8, and A-9 present some of the results of Seal's theoreti-
cal calculations.  As shown in Figure A-7,  the "exact" solution of the
diffusion equation is asymptotic to the solutions based on either Brownian
motion or turbulent diffusion alone and does not differ very much from a
simple sum of these solutions.  Figure A-8  presents the normalized co-
agulation constant, K = ffo , as a function  of particle diameter,  while
Figure A-9 illustrates the variation  of the agglomeration rate constant
(Kno) as a function of particle size  for a  constant mass concentration
of 10-8 g/cm3.

Beal's analysis has several limitations.  Only the steady-state solution
of the diffusion equation was obtained, only interactions among particles
of equal size were considered, and all particles were assumed to stick
together on impact.  The last assumption is the  most tenuous.

Figures A-7 and A-8 indicate that turbulence does not significantly en-
hance agglomeration for particles less than 0.2  u in diameter, but can
increase the coagulation constant of  0.5 u  particles by about a factor of
10 and 1 u particles by a factor of 1Q2.  The energy expended to accom-
plish this increase is about 2.7 x 107 dyne-cm-sec"1 or 0.004 hp/g.


                                 200

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                           I  I I i I I !l|
                       FLUID Alft
                       PIPE OlA.VLTER-IOCM
                       TEV,PEI
-------
                   I  I I I IIIJ   I  I I I I 11>l   I  I I I 11 III
              ; FLUID «AIR
              -_ PIPE DIAMETER -10 CM
              I TEMPERATURE • 20* C
              - PARTICLE DENSITY • 1.0 GM/CC
                CONCENTRATION • ICT« GM/CC
                	I I  I i ii nl   I  I I I I i II|	I  I I I 11 III   I  I  I I I
              I0'2 2    9   10"'  2    9   10°  2    9  10'  2     9
                              PARTICLE DIAMETER, pm
Figure  A-9.   Agglomeration  rate  constants for various
                particle diameters  and  fluid velocities
                                202

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This is the equivalent to about 40 hp/1,000 ft3.  If this energy is ex-
pended over a period of 1 min, a 0.5 u particle could be grown to about
2-3 u.  This is an extremely high energy consumption, and, therefore,
turbulent agglomeration does not appear attractive for general use.

Agglomeration in Sonic Fields - Several different effects are responsible
for the enhanced agglomeration rate due to sonic forces including (1) col-
lection of the particles at the antinodes in the sonic standing wave  (due
to radiation pressure), (2) hydrodynamic forces between the particles, and
(3) additional collisions due to the different vibrational amplitudes of
different sized particles.

The relative importance of the three mechanisms cited above has not been
determined.  In fact, there is no assurance that other mechanisms are not
important.  It is, therefore, not possible to construct a theoretical
model.

However, previous theoretical studies have developed equations which ex-
press the functional dependence of the three mechanisms.^./  From a
theoretical standpoint, all three mechanisms show a strong dependence on
the radii of the particles, with the forces due to radiation pressure and
hydrodynamics increasing with increasing particle size and the relative
vibrational amplitudes decreasing with increasing particle size.  There
is also a strong frequency dependence in all the mechanisms and particle
agglomeration becomes negligible at low frequencies.  There is, therefore,
an optimum frequency for acoustic agglomeration which varies with particle
size.

Coagulation by a sonic field has as its principal advantage its applic-
ability to any aerosol, including those comprised of submicron particles.
The principal disadvantage of sonic coagulation is its moderately high
energy requirements.  A second major disadvantage is the low efficiency
of acoustic coagulators and their inability to handle highly dispersed
suspensions.  Even with long residence times, sonic agglomerators which
incorporate inertial separators for particle collection, cannot treat
suspensions having particle loadings of < 0.5 to 1.0 grains/ft3,  it is,
therefore, necessary to augment highly dispersed suspensions with a water
mist or other particles to increase the particle loading and obtain satis-
factory separation.

Water augmentation appears necessary to obtain the removal of a large
fraction of the particulates.  If a pound of water per 1,000 cfm is used,
one would expect an increase in the power requirements of up to 1 hp/1,000
                               203

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cfm, depending on the device used  to  introduce  the water and  the mean
droplet size.  The minimum energy  requirements  would then be  5.5 to  10
hp/1,000 cfm.  Whether this is competitive with other devices capable of
removing fine particles remains  to be seen.

Agglomeration of Charged  Particles -  One method of increasing the rate of
agglomeration of fine particulates is to add  a  bipolar  charge,  either with
or without an externally  imposed field.  To a limited degree, this occurs
in a standard electrostatic precipitator but  not  sufficiently to permit
efficient collection of fine particulates.  With  proper conditions the
large electrostatic forces between particulates can produce a large  in-
crease in the rate of agglomeration of submicron  particulates.

Space-charge precipitation is a  method of removing particulates from gas
streams based on the migration of  charged particles in  their  own space-
charge fields.  However,  particulate  gas systems  are usually not suffi-
ciently concentrated to provide  adequate fields.  It is, therefore,
necessary to add a cloud  of charged drops in  order to produce fields
which will remove the particles.

Basically, a space-charge precipitator consists of two  parts:   (1) a
short section where both  the particles and the  added drops are  charged
by high voltage coronas;  and  (2) a section of grounded  tubes  or plates
on which the particles and drops are  collected.   In the collecting sec-
tion, the drops and particles migrate to the  surfaces,  where  they coalesce
and  flow from the prec.ipitator as  a slurry.

Both theoretical and limited experimental studies on space-charge pre-
cipitation have been conducted at  the University  of California.19-21/
While the experiments may not accurately model  a  practical system, the
calculations and experiments done  to  date indicate that space-charge
precipitation may be a viable approach to the collection of particulates.
Energy requirements for a space-charge precipitator are relatively.un-i
certain.  Calculations performed by investigators at the University  of
California indicate a total energy requirement  of about 0.5 hp/1,000 cfm
of gas;  Based on a preliminary  cost   estimate^  space-charge  precipita-
tion appears to be economically  competitive with  conventional electro-
static precipitation.  Additional  testing with  a  pilot-scale model on an
actual industrial source  will be needed to allow  precise analysis of the
potential of full-scale units.
                                 204

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                               REFERENCES

1.  McGraw, M. J., and R. L. Duprey, "Compilation of Air Pollutant Emis-
      sion Factors," Environmental Protection Agency, Research Triangle
      Park, North Carolina, April 1971.

2.  "Participate Pollutants System Study, Volume II - Fine Particle Emis-
      sions," Midwest Research Institute, EPA Contract No. CPA-22-69-104,
      August 1971.

3.  Greco, J., and W. A. Wynot, "1971 Operating and Maintenance Problems
      Encountered with Electrostatic Precipitators," Am. Power Conf. Proc.,
      33i:345-353.

4.  Greco, J., "Electrostatic Precipitators - An Operator's View," Proceed-
      ings of Design. Operation and Maintenance of High Efficiency Particu-
      late Control Equipment Specialty Conference, St. Louis, Missouri,
      March 1973.

5.  Shannon, L. J., et al., "Research and Development Program for Control
      of Fire Particulate Emissions," Interim Report No. 1, EPA Project
      No. R-801615, Midwest Research Institute, November 1972.

6.  A New Process1 for Cleaning and Pumping Industrial Gases - The Aeronetics
      System, U.S. Patent No. 3,613,333.

7.  Private Communication, Mr. H. E. Gardenier, Vice President, Aeronetics,
      Inc., September 1972.

8.  Schauer, P. J., Ind. Eng. Chem., 43jl532 (1951).

9.  Lancaster, B. W., and W. Strauss, "A Study of Steam Injection Into Wet
      Scrubbers," Ind. Eng. Chem. Fundamentals. ^.£:362-369, No. 3 (1971).
                               205

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10.  Calvert, S., et al.,  Scrubber Handbook  (Contract  No.  CPA-70-95)  APT,
       Inc., Riverside, California, August 1972.

11.  Goldshmid, J. Jr., D. Leith, and S.  Calvert,  "Flux Force Scrubbers—An
       Engineering Analysis,"  presented  at 164th  ACS National  Meeting,
       New York, New York, 27  August  1972.

12.  Strauss, W., Industrial Gas  Cleaning, Oxford,  Pergamon Press,  Limited
       (1966).

13.  Levich, V., Dokl. Akad. Nauk.. SSSR, 99:809  (1954a).
                                                                't.
14.  East, T. W. R., and J. S. Marshall, Q.  Journal R. Met. Soc..  80j26
       (1954).

15.  Tunitsky, N. N., Zh. Fiz. Khim..  20:1136 (1946).

16.  Obukhov, A., and A. Yaglon,  Prikl.  Mat.  Mekh., 15:1  (1951).

17.  Beal, S. K., "Turbulent Agglomeration of Suspensions," Aerosol Science,
       .3:113-125 (1972).

18.  Yoder,  J. D., and L.  Silverman,  "Influence of  Turbulence  on Aerosol
       Agglomeration and Deposition in a Pipe," Paper  No.  67-33, 60th
       Annual Air Pollution Control Association Meeting,  Cleveland, Ohio,
       13 June 1967.

19.  Faith,  L. E., S. N. Buktany, D.  N.  Hanson, and C. R.  Wilke, Ind.  Engr.
       Chem. Fundamentals, 6:519  (1967).

20.  Kostow, Lloyd P., "Design and  Testing of Space-Charge Precipitators,"
       M. S. Thesis, University of  California,  Berkeley,  California,
       6 March 1972.

21.  Webber, M.  E., "Experimental Studies on Space-Charge  Precipitation,"
       M. S. Thesis, University of California,  Berkeley,  California,
       5 September 1969.
                               206

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                               APPENDIX B

              EXAMPLE OF PROCEDURE FOR DETERMINING CONTROL
       COSTS FOR COMPLIANCE WITH FINE PARTICLE EMISSION STANDARDS

INTRODUCTION

The determination of the control costs required for compliance with
various fine particle emission standards involves the following major
steps:

1.  Development of model plant for each industry category.

2.  Determination of control-device performance required to meet a
specific fine particle emission standard.

3.  Determination of costs for model plant and industry for compliance
with specific fine particle emission standard.

Individual steps in the procedure will be illustrated in the following
sections using the coal-fired power plant category as an example.

SPECIFICATION OF CHARACTERISTICS OF MODEL PLANT

1.  Boiler type:  pulverized coal fired.

2.  Boiler capacity:  400 MW (existing boiler range from < 25 MW up to
1,000 MW or more).

3.  Coal usage rate:  assume boiler operates at 100% capacity at all times,
Reference 1 states that a 400-MW plant would consume 150 tons/day.

4.  Gas flow rate:  Ref. 2 gives the following relation between boiler
capacity and gas flow rate:

                          1 MW = 2,800 acfm2-/
                               207

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Reference 3 indicates that a 400-MW plant would have a gas flow rate of

800,000 scfm.  Assuming that the exit gas temperature is 300°F,2/ the gas

flow rate given by Ref. 2 can be converted to scfm as follows:
                  (2,800 *£*)  (400 MW)  (-) = 765,000 scfm          (1)
                         MW             760



Since the gas flow rate from Refs. 2 and 3 are in good agreement, the figure

of 2,800 acfm/MW will be used  in subsequent calculations.


5.  Stack diameter:  assume that the exit velocity of stack gas is 4,000

ft/min.
                    Cross-sectional area of stack = Gas Flow Rate
                                                    Exit Velocity
                               acfm
                    = r^soo) ~Mi"ir4oo MWI
                           4,000 ft/min               '               ( )


                    = 280 ft2
                     Stack diamter =   4 Area)
                                         rr  /                         (3)
                                      i"(4) (280)1

                                      L  TT   J
                                   = 18.9 ft = 5.76 meters
 CONTROL DEVICE PERFORMANCE REQUIRED TO MEET PLUME  OPACITY REGULATION


 Equation (4)  was used to calculate the allowable outlet  grain  loading for

 a  specific plume opacity.
                           W = -K p/L In |-                            (4)
                                         Io


 The  efficiency of the control device was then determined  from Eq.  (5).
                                    208

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     Efficiency  =   Inlet Grain Loading - Outlet Grain Loading
                                 Inlet Grain Loading
The inlet grain loading to the control device for the model plant was cal-
culated from the relation:
Inlet Grain Loading =  (Emission Factor) (Coal Usage Rate)
                                Gas Flow Rate
                       (l90 	1*	r)    (l50 £2S^°al)   (y.OOO SSia)
                       \    ton of coal/    \       hr  /   \	l£_/
                                    min              6
                                 60 —     1.12 x 10b
                                    hr                 nun
                         . 97 grain \   /460 + 300
                              acf )   \460 +  60 <
                     =  4.34 grains/scf
The allowable grain loading at the outlet of the control device for plume
opacities of 5% and 10% and the corresponding required control device ef-
ficiency are given in Table B-l.
       Table B-l.  SUMMARY OF CONTROL EQUIPMENT PERFORMANCE REQUIRED
                           TO MEET PLUME OPACITY REGULATIONS
                              (Coal-Fired Power Plant)
                                                            Overall Mass
                               Outlet Grain Loading        Efficiency of
Plume Opacity Permitted            (grain/scf)	        Control Device

          10%                        0.0149                    99.66

           5%                        0.00728                   99.83
                                209

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The main type of control device currently installed on coal-fired power
plants to control particulate emissions is the electrostatic precipitator.
The cost of an electrostatic precipitator for the model plant was deter-
mined from Figures 17 and/or 18, Chapter 6, and the cost for the total in-
dustry was determined using the following equation:
Total Cost = (Total Industry Production CaPacitv\     Lt fm Model plant\ (?)
             \ Model Plant Production Capacity  ]     \                 /
Table B-2  summarizes  the  calculation  of  the  annualized costs required to
meet a 107» or  570  plume opacity  standard.

CONTROL  SYSTEM CORRESPONDING  TO BEST  INSTALLED  CONTROL DEVICE

Electrostatic  precipitators are the most efficient particulate control de-
vices currently being installed on coal-fired power plants.  Reference 2 in-
dicates  that the  average  design efficiency of electrostatic precipitators
installed  on power  plants in  the 1970-1971 period was 997o  (overall mass
efficiency) .   The cost of this  control device was determined from Figures
17 and/or  18,  Chapter 6.

COMPARISON OF  CONTROL EQUIPMENT COSTS

Table B-3  presents  a  comparison of the control  costs required for compliance
with the two fine particle emission standards.
                                    210

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          Table B-2.  ANNUALIZED COSTS FOR POWER PLANTS TO MEET 10% AND  5%  PLUME  OPACITY STANDARD


  Opacity          Control                          	Annualized  Cost	
  Standard      Device Required                     Model Plant                           All  Plants

10% Opacity  99.66% Electrostatic  (a) $0.22/cfm/year                        /i50^000_JlW\  ($2>5 x 105/year)  =
               precipitator                                                  *           '    $94 x 10^/year
                                   (b) ($0.22/cfm/year) (1.12 x 106 cfm) =
                                         $2.5 x 105/year

 5% Opacity  99.83% Electrostatic  (a) $0.27/cfm/year                        ^150,000 MW\ ($3>0 x io5/year)  =
               precipitator                                                  \    40° m  I    $112  x 106/year
                                   (b) ($0.27/cfm/year) (1.12 x 106 cfm) =
                                         $3.0 x 105/year

-------
NJ
H1
NJ
                    Table B-3.   ANNUALIZED COSTS FOR POWER PLANTS TO MEET 10% AND 5% PLUME OPACITY AND
                                                   BEST INSTALLED CONTROL STANDARD
        Emission Regulation

        Best installed control
          device

        107. Opacity
        57, Opacity
  Control System

99% Electrostatic
  precipitator

99.66% Electrostatic
  precipitator

99.83% Electrostatic
  precipitator
                                                           Annualized  Cost  ($/Year)
                                                        Incremental Annualized
                                                             Cost  ($/Year)
Model Plant    All Plants     Model Plant    All Plants
  190,000
  250,000
  300,000
 71 x 106
 94 x 106
112 x 106
 60,000
110,000
23 x 106
41 x 106

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                               REFERENCES

1.  "Control of Air Pollution from Electric Power Generators—A State-of-
      the-Art Review," Research Cottrell, Inc., June 1969.

2.  "Particulate Pollutant Systems Study, Volume III - Handbook of Emis-
      sion Properties," Midwest Research Institute, EPA Contract No. CPA-
      22-69-104, 1 May 1971.

3.  Anonymous, "Basic Technology," Chemical Engineering-Deskbook Issue,
      p. 172, 27 April 1970.
                                    213

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                                APPENDIX C

                               PLUME OPACITY

The opacity  of  a  plume is  defined as one minus the transmittance of the
plume, i.e.,

                        Plume Opacity = 1 - Transmittance              (1)

Plume transmittance  can be calculated from Eq. (2) :ii?_/


                                     r2
           T =  I^ =  exp [- TT L    /     QE(Q',m)r2n(r)dr]              (2)

                                 rl

where,

          or  = Size parameter,  2nr/X,

          r  = Particle radius,
                                 i
          A.  = Wavelength of light,

          m  = Refractive index of the particles relative to air,..,-,

       n(r)  = Size frequency distribution,  number of particles of radius r
                per  volume per Ar,

    QE(o-,m)  = Particle light extinction efficiency factor,  the total light
                flux scattered and absorbed by a particle divided by the
                light flux incident on the particle,

          L  = Plume  width,
                                       214

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          I = Intensity of transmitted light, and

         I0 = Intensity of incident light.
The light extinction efficiency factor Qjr for spheres, ellipsoids and
cylinders can be computed using the Mie equations. ft/  For pure scatterers
with typical refractive indices, Qg can vary from near zero for very small
particles, to about four when the particle diameter is near the wavelength
of light, and approaches a theoretical limit of two for very large parti-
cles.  For spherical particles,
where,

          W = Mass concentration of particles in exhaust stream,

          p = Particle density, and

       g(r) = Mass distribution function.

Substitution of Eq.  (3) into  (2) yields:
             /^
[ - 3/4 ^  J     ^ g(r)dr
                T = exp [ - 3/4                g(r)dr]                  (4)

                                   *1

By suitable rearrangements of the preceding equations, Pilat and Ensor?./
have developed  a simplified equation to calculate the expected mass  con-
centration for  various values of plume transmittance  (or opacity) , average
particle density, and plume diameter.

                          W =  -K p/L In (I/I0)                          (5)

where,

                           _  Specific particulate volume
                                Extinction coefficient
                                    215

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The parameter K is dimensionally  similar  to  the volume  surface characteris-
tic size described by Herdan  (1960).I/  K is primarily  a  function of the
particle size distribution, refractive  index, and  to a  lesser degree, the
wavelength of light.

Equation (A) can be used to obtain  an understanding of  the dependence of
opacity on various parameters,  and thereby, some important implications
regarding the use of opacity  as an  indicator of fine particulate emission.
The effect of mass concentration, path  length, and particle density on the
transmittance can be evaluated directly from Eq.  (4).
If p is defined as WL/p, and I1 is 3/4   /   (-:£)  g(r)dr,  then Eq.  (4) becomes
/*
                            T =  exp  (-pi')                              (6)
For a constant  I1,  a  change  in (3  from g^  to  $2  results  in  a change  in trans-
mittance given  by:
                           T2  -  T                                      (7)
Thus, the percentage  change  in transmittance  caused  by a  change  in W, L,
or p depends  on  the initial  transmittance  level.   For  example, a doubling
of W or of L  or  a halving  of p will  result in an  80% reduction of trans-
mittance of TI = 0.2  or  a  20% reduction if TI = 0.8.1/

The optical properties of  particles  are described by the  refractive  index,
which is a complex number, m = n^-in£.   The real  part, n^,  describes the
light-scattering properties  and the  imaginary part,  n£, describes the light
absorption of the particulate material. The  refractive index has a  strong
influence on  the evaluation  of Qg  and,  hence,  on  the transmittance.

Figure C-l shows percent opacity plotted against-the mass median radius
for a hypothetical case.  Four curves  are  plotted, each for a different
value of m from  1.33  to  3.0  with n£  assumed equal to zero.   Thus, the
effect of the real part  of the refractive  index on opacity  is illustrated.
The lower value  of m  = 1.33  represents  water  droplets  in  air.  The m =
1.5 curve approximates the inorganic components of fly ash.  The  higher
valjues of m are  typical  of iron oxide,  for  example.!/
                                   216

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   100 r-
a.
o
                                         Geometric Standard Deviation of Particle

                                         Size Distribution, (7=2
                                0.1                        1.0


                         MASS GEOMETRIC MEAN RADIUS RGW (MICRONS)
                  Figure C-l.
Effect  of real  part of  refractive index on

   opacity particle-size relationship!./
                                              217

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It is important to note that all of the curves show a maximum opacity in
the 0.1-0.3 Jim range, the opacities falling off rapidly on either side of
the maximum.  About 1 um the curves merge and opacity is independent of
the refractive indices.  For finer particles, the higher values of re-
fractive index result in higher opacities.  A plume composed of iron
oxide particles will, therefore, transmit less light than a fly ash plume
of identical characteristics.  For the case where the plumes have identi-
cal characteristics, different levels of plume opacity would, in fact,
represent the same level of fine particulate emissions to the atmosphere.

Figure C-2 illustrates the effect of the imaginary part of the refractive
index, i.e., light absorption, on opacity.  The four curves plotted rep-
resent refractive indices all with n^ = 1.5 but with n£ varying from
0 to 0.9.  The effect is significant.  For mass median radius less than
0.5 um, light absorption by fine particles plays a dominant role in de-
termining opacity.  In fact, for the higher values of n2, the calculated
opacities become virtually independent of particle size.  This has impor-
tant implications in the use of opacity as an emission indicator.  High
opacities could be measured in a plume composed of very fine absorbing
particles whereas an identical plume of nonabsorbing particles might go
unnoticed.!./

Particle size distribution also exerts a strong influence on plume opacity
because of the fact that particles in different size ranges contribute un-
equally to the overall opacity.  For nonabsorbing particles, a given mass
of particles less than 0.1 jam contributes less and less to opacity as the
particle size decreases.  Above 1 um the same is true as size increases.
As a result, particulates which are monodisperse or nearly so, should be
expected to yield opacities which show a greater dependence on particle
size than more polydisperse distributions.±J

Figures C-3 and C-4 show the composite effects of some of the main param-
eters on the plume opacity as expressed in terms of the parameter K, de-
veloped by Pilat and Ensox.—'  Figure C-3 shows the functional dependence
of K on size distribution parameters for a black aerosol, while Figure C-4
depicts the same relationships for a white aerosol.—'
                                    218

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  loo  r-
   10  h
u
2
o
»—
  1.0  h-
                                    Geometric Standard Deviation of Particle
                                    Size Distribution , O" = 2
                                              WL//) =
  0.1
                                 1
     0.01
       0.1                        1.0
MASS GEOMETRIC MEAN RADIUS, RGW (MICRONS)
                                                                                     10
                Figure C-2.
      Effect  of imaginary part of refractive index
       on opacity particle-size relationship^-'
                                                  219

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                       10'
                      I
                      u
                      JO
                       10
                       10
                           Geometric standard deviation,
                                 Refractive index= 1.96 0.66 i
                                 Wave length of light=550 nm
                           •2
                         10 '"   10"  .10°     lo1    102
                          Geometric mass mean radius, r8W (microns)

                                                                   i
Figure  C-3.   Parameter K as  a function of  log-normal size

       distribution  parameters for black aerosol—'
                              Geometric standard deviation
                                              i
                                              1
                                Refractive index =1.50
                                Wave length of light=550 nm
                         10'"   10"'    10°    10l     102

                         Geometric mass mean radius, r-gw (microns)
 Figure  C-4.
        distribution  parameters for a
Parameter K as  a function of  the  log-normal size

                            white  aerosol-!/
                                     220

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                                  REFERENCES

  1.   Feldman, P. L., and  D.  W.  Coy, "Comparison of Computed  and Measured
        Opacities:  Lignite-Fired Boilers," Research Cottrell,  Bound Brook,
        New Jersey.

  2.   Ensor, D. S., and M.  J. Pilat, "Calculation of Smoke Plume Opacity
        from Particulate Air  Pollutant Properties," Journal of Air Pollu-
        tion Control Association. 21:496-501, No. 8  (1971).

  3.   Hardan, G., Small Particle Statistics. Butterworths, London (I960).
*US. GOVERNMENT PRINTING OFFICE: 1974 546-318/337 1-3       221

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 SELECTED WATER
 RESOURCES ABSTRACTS
 INPUT TRANSACTION FORM
                     1. Report No.
                                         w
Feasibility of Emission Standards Based on Particle Size
L.J. Shannon,  P.G. Forman, W. Park
Midwest Research Institute
425 Volker Blvd.
Kansas City,  Missouri  64110
 12. if-Sponsoring Organization Environmental Protection Aeencv
   -»:  i>                                          -o   j
     .L.r         *'
                       Environmental Protection Agency Report
                       Number EPA-600/5-74-007, March 1974.
                                         5.  R  ortD;
                                         e.
                                         5.  PF • f ormir,  Orgar Won
                                         68-01-0428
                                         13.  TypeofRepoi ^
                                            Period Covered
                                             Final
 lo.
The technical and economic feasibility of particulate emission  standards based on
particle  size was assessed in this  program.  Specific attention was focused on
standards to regulate the emission  of fine particulates—particulates below 2 u in
size.  The program was divided  into four major areas of effort:

1.  Analysis of approaches for  regulating fine particle emissions from stationary
    sources.

2.  Definition of technological and economic requirements necessary for imple-
    mentation of emission standards.

3.  Identification of benefits  that would accru if control  procedures for -fine
    particulates can be implemented.

4.  Assessment of overall feasibility of implementation of  fine particle emission
    standards.
 17a. Descriptors

 Particulates; Emission Standards
 17b. Identifiers
 I7c. COW P.P. field & Gro-jp
  18  •}
19.  Sr-urity Class.
    (Report)

20.  Security Class.
    
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