POLLUTANT  SYSTEM  STUDY.
VOLUME  II.   FINE PARTICLE  EMISSIONS

L.  J.  Shannon,  et  al

Midwest Research Institute
Kansas  City,  Missouri

1 August  1971
     NATIONAL TECHNICAL INFORMATION SERVICE
                                          Distributed .., 'to foster, serve
                                             and promote the nation's
                                                economic development
                                                   and technological
                                                      advancement.'
                                          U.S. DEPARTMENT OF COMMERCE

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UNITED STATES


GOVERNMENT                    EPA/OAP SSPCP LIBRARY

PROPERTY                        m w  C'lAPEL HILL  ST

This took is the property of                ~ .nL.'rtM
the United States Government               UUK'"iA1VI
National Air Pollution Control Administration

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                                   PREFACE
          Thl.i3  report, wur.  prepared for  ]>'P\/KK() under Contract No.
CPA-'^2-6y-lC4,  which wau monitored by Mr.  Don  K.  I-'eLton and  Mr.  Koberl
Lorentz.
                                                                  t

          The work was conducted in the Environmental Sciences Section of
the Physical Sciences Division.

          The report was written by Dr.  L.  J.  Shannon and Mr.  P.  G.  Gorman
with the assistance of Miss M. Reichel.

          Dr. Seymour Calvert and Mr. Paul L.  Magill,  consultants to MRI,
made valuable contributions to this document.
Approved for:

MIDWEST RESEARCH INSTITUTE
H. M. Hubbard, Director
Physical Sciences Division
1 August 1971
                                     iii

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                            TABLE OF  CONTENTS
 1.   Summary.
     1.1  Data Acquisition and Analysis	   1
     1.2  Fine-Particle Emissions (1969-1970)  	   2
     1.3  Projections of Fine-Particle Emissions,  	   9
     1.4  Literature Surveys	12
         1.4.1  Particulate Sampling and Sizing	15
         1.4.2  Adverse Effects of Particulates on Human Health. .  .  15
         1.4.3  Modification of the Atmosphere by Particulates ...  17

2.   Introduction	19

3.   Definitions of Important Terms 	  21

     3.1  Fine Particulate and Particle Size	21
     3.2  Process Emissions  	  22
     3.3  Fractional Efficiency of Control Equipment	22
     3.4  Penetration	22

4.   Data Acquisition	23

5.   Particle-Size Distribution Data	25

     5.1  General Features of Available Data	25
     5.2  Methods of Data Presentation	26

6.   Fractional Efficiency of Control Equipment 	  37

     6.1  Acquisition and Review of Data	37
     6.2  Data Analysis	38
    6.3  Extrapolation of Fractional Efficiency Data for
           Control Devices 	  58

7.  Current Level of Pine Particulate Emissions (1969-1970)	61

    7.1  Limited Check of the Validity of Particle Size and
           Fractional Efficiency Data Extrapolation	61
    7.2  Fine-Particle Emissions from Specific Stationary Sources.  .  64
         7.2.1  Stationary Combustion Sources	67
         7.2.2  Crushed Stone Operations 	  72
         7.2.3  Iron and Steel Plants	72
         7.2.4  Forest Products Industry 	  82

                                   iv

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                      TABLE OF CONTENTS  (Continued)
          7.2.5   Cement  Plants	89
          7.2.6   Hot-Mix Asphalt  Paving Plants	91
          7.2.7   Ferroalloy  Plants	95
          7.2.8   Lime Plants	95
          7.2.9   Secondary Nonferrous Metallurgy	107
          7.2.10  Carbon  Black  	 107
          7.2.11  Coal Preparation Plants	107
          7.2.12  Petroleum Refineries  	 109
          7.2.13  Fertilizer  and Phosphate Rock	109
          7.2.14  Iron Foundries	109
          7.2.15  Acids	115
          7.2.16  Primary Nonferrous Metallurgy	113
          7.2.17  Clay Products	116
          7.2.18  Operations  Related to Agriculture	116
          7.2.19  Municipal Incineration  	 116
    7.3   Fine-Particle  Emissions from Mobile and Miscellaneous
           Sources	116
          7.3.1   Mobile  Sources	116
          7.3.2   Miscellaneous Sources	116

8.  Projections  of Fine-Particulate Emissions to the Year 2000  .  .  . 119

    8.1   Mass Basis	119
    8.2   Number  Basis	123

9.  Conclusions  and Recommendations	147

    9.1   Conclusions	147
    9.2   Research Recommendations	148

References	151

Appendix A - Particulate Sampling and Sizing 	 157

Appendix B - Adverse Effects of Particulates on Human Health .... 181

Appendix C - Modification of the Atmosphere by Particulate
               Pollution	205

Appendix D - Data Sources	217

Appendix E - Calculations of Fine-Particle Emissions 	 221

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                     TABLE OF CONTENTS  (Continued) •

                            LIST OF FIGURES

I.  General

Figure                            Title

  1        Histogram Representing a Particle-Size Distribution. . .   27
  2        Typical Cumulative Percentage Curve for a Particle-
             Size Distribution	   28
  3        Cumulative Percentage Curve for Particle Size Distri-
             bution of Fly Ash	   29
  4        Log Normal Curve for Fly Ash Particle-Size Distri-  .
             bution	   30


II.  Specific

     A.  Fractional Efficiency of Control Equipment

  8        Fractional Efficiency Data for Electrostatic
             Precipitators	   41
  9        Fractional Efficiency Data for Fabric Filters	   43
 10        Fractional Efficiency Data for Wet Scrubbers 	   45
 11        Fractional Efficiency Data for Wet Scrubbers 	   47
 12        Fractional Efficiency Data for Cyclones	   49
 13        Fractional Efficiency Data for Cyclones	   51
 14        Fractional Efficiency Data for Cyclones	   53
 15        Fractional Efficiency Data for Cyclones	   55
 16        Fractional Efficiency Data for Cyclones	   57
 17        Extrapolated Fractional Efficiency of Control Devices.  .   59

     B.  Industry Sources                                .

          1.   Asphalt,  Hot-Mix Plants

 35        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Hot-Mix Asphalt Plant Dryers (Banco
             data)	    96
 36        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Hot-Mix Asphalt Plant Vent  Lines
             (Bahco data) 	    97
 59        Projections  of Fine-Particle Emissions  from Hot-Mix
             Asphalt Plant Dryers 	   135
                                   VI

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                      TABLE OF CONTENTS (Continued)

                       LIST OF FIGURES (Continued)

          2.  Cement Plants

Figure                            Title

  7        Extrapolated Particle-Size Distribution of Particu-
             lates Emitted from Cement Kiln Controlled by
             Electrostatic Precipitator	35
 33        Particle-Size Distributions of Particulates Emitted
             from Uncontrolled Cement Kilns	92
 34        Particle-Size Distributions of Particulates Emitted
             from Cement Kilns Controlled by Electrostatic
             Precipitators 	   93
 58        Projections of Fine-Particle Emissions from Cement
             Plant Rotary Kilns	134

          3.  Coal Preparation Plants

 43        Particle-Size Analysis for Particulates Emitted from
             Coal Thermal Dryers	108
 62        Projections of Fine-Particle Emissions-from Coal
             Preparation Plant Thermal Dryers	138

          4.  Crushed Stone Operations

 24        Particle-Size Distribution of Particulates  Emitted from
             Uncontrolled Crushed Stone Operations (Bahco  data).  .  .   74
 50        Projections of Fine-Particle Emission from  Crushed
             Stone Operations	126

          5.  Ferroalloy Plants

 37        Particle-Size Distributions of Particulates Emitted
             from Uncontrolled Ferroalloy Electric Furnaces
             (optical technique)  . •	98
 60        Projections of Fine-Particle Emissions  from Ferroalloy
             Electric Furnaces 	  136

          6.   Fertilizer Manufacture

 45        Particle-Size Distribution of Particulates  Emitted from
             Uncontrolled Fertilizer  Dryers (Bahco  data) 	  Ill
 64        Projections  of Fine-Particle  Emissions  from Fertilizer
             Granulators  and Dryers	140

                                   vii

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                      TABLE OF CONTENTS (Continued)

                       LIST OF FIGURES (Continued)

          V.  Iron .and otc'.-l Planir;

Figure                            Title

 25        Particle-Size Distribution by Weight of Sintering
             Machine Dust	 .   77
 26        Particle-Size Distribution of Particulates Emitted
             from Uncontrolled Open Hearth Furnaces	78
 27        Particle-Size Distribution of Particulates Emitted
             from Uncontrolled Basic Oxygen Furnaces 	   80
 28        Particle-Size Distribution of Particulates Emitted
             from Uncontrolled Electric Arc Furnaces 	   83
 51        Projections of Fine-Particle Emissions from Sinter
             Machines	127
 52        Projections of Fine-Particle Emissions from Open
             Hearth Furnaces 	  128
 53        Projections of Fine-Particle Emissions from Basic
             Oxygen Furnaces	1L'9
 54        Projections of Fine-Particle Emissions from Electric
             Arc Furnaces.	130

          8.   Iron Foundries

 46        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Iron Foundry Cupolas (Bahco data)	115
 65        Projections of Fine-Particle Emissions from Iron
             Foundry Cupolas 	  141

          9.   Kraft Pulp Mills

  6        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Recovery Furnace, Kraft Pulp Mill.  .  .  . .   33
 29        Particle-Size Distribution for Particulates Emitted
             from Uncontrolled Pulp Mill Bark Boilers (Bahco  data) .   86
 30        Particle-Size Distribution for Particulates Emitted
             from Uncontrolled Pulp Mill Recovery Furnaces	87
 31        Fractional Efficiency of an Electrostatic Precipitator
             Operating on a Kraft Mill Recovery Furnace	88
 32        Particle-Size Distribution of Particulates Emitted
             from Uncontrolled -Pulp Mill Lime Kilns	30
 55        Projections of Fine-Particle Emissions from Kraft  Pulp
             Mill Bark Boilers	131

                                   viii

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                      TABLE OF CONTENTS (Continued)

                       LIST OF FIGURES (Continued)

Figure          .                  Title

 56        Projections of Fine-Particle Emissions from Kraft Pulp
             Mill Recovery Furnaces	132
 57        Projections of Fine-Particle Emissions from Kraft Pulp
             Mill Lime Kilns	133

          10.  Lime Plants

 38        Particle-Size Distributions of Particulates Emitted
             from Uncontrolled Rotary Limestone Kilns	102
 39        Particle-Size Distributions of Particulates Emitted
             from Controlled Limestone Kilns	103
 40        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Lime and Limestone Screenhouse (Bahco
             data)	104
 41        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Lime and Limestone Hammermills (Bahco
             data)	105
 42        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Lime and Limestone Raymond Mills (Bahco
             data)	106
 61        Projections of Fine-Particle Emissions from Lime Plant
             Rotary Kilns	137

          11.  Municipal Incinerators

 47        Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Municipal Incinerators  (Bahco data).  .  .  . 118
 63        Projections of Fine-Particle Emissions from Municipal
             Incineration	139

          12.  Petroleum Refineries

 44        Particle-Size Distribution of Particulates Emitted from
             Petroleum FCC Units  (cyclone  inlet,  Bahco data)  .... 110
                                   IX

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                      TABLE OF CONTENTS  (Continued)

                       LIST OF FIGURES (Concluded)

          13.  Stationary Combustion

Figure                            Title                              Page

   5       Particle-Size Distributions of Particulates Emitted
             from Uncontrolled Power Plants (pulverized coal-
             fired boilers)	32
  18       Particle-Size Distributions of Particulates Emitted
             from Uncontrolled Power Plants (pulverized coal-
             fired boilers)	63
  19       Particle-Size Distributions of Particulates Emitted
             from Electric Utility Power plants Controlled by
             Electrostatic Precipitators 	  65
  20       Particle-Size Distributions of Particulates Emitted
             from Uncontrolled Power Plants (pulverized coal-
             fired boilers)	69
  21       Particle-Size Distributions of Particulates Emitted
             from Uncontrolled Power Plants (cyclone coal-fired
             boilers)	70
  22       Particle-Size Distribution of Particulates Emitted from
             Uncontrolled Power Plants (stoker coal-fired boilers)  .  71
  23       Particle Size Distributions of Particulates Emitted
             from Uncontrolled Industrial Power Plants (coal-fired).  73
  48       Projections of Fine-Particle Emissions from Electric
             Utility Coal-Fired Power Plants 	 124
  49       Projections of Fine-Particle Emissions from Industrial
             Coal-Fired Power Plants 	 125


                             LIST OF TABLES

I.   General

Table                             Title

  1        Fine-Particle Emission from Industrial Sources	   4
  2        Fine Particle Emissions from Industrial Sources 	   6
  3        Priority Ranking of Industrial Sources of Fine-
             Particulate Pollutants	   9
  4        Fine-Particle Emissions from Mobile Sources 	  10
  5        Fine-Particle Emissions from Miscellaneous Sources.  ...  10
  6        Projections of Fine-Particle Emissions from Industrial
             Sources	13

                                   x

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                      TABLE 01'' CONTENTS (Continued)

                         LIST OF TABLES (Continued)

Table                             Title

  7        Projections of Fine Particle Emissions from Industrial
             Sources	14


II.  Industry Sources

          1.  Asphalt, Hot-Mix Plants

 12        Summary of Fine-Particle Emissions from Hot-Mix
             Asphalt Plants	94
 18        Projections oJ' Fine-Particle Kmir;ruonE i'or Acphalt
             Dryers	11!)
 19        Calculation of Average Efficiency of Control for Fine
             Particles from Asphalt Dryers 	 120
 20        Calculation of Average Efficiency of Control on Fine
             Particles for Fabric Filter on Asphalt Dryer	121
 21        Values Used in Calculation of Projected Fine-Particle
             Emissions for Asphalt Dryers	 . 122
 22        Projections of Fine-Particle Emissions for Asphalt
             Dryers	122
 23        Projection of Fine-Particle Emission, on a Number. Basis,
             for Asphalt Dryers	142
 24        Calculation of the Average Diameter of Fine Particles
             from Asphalt Dryers in 1968	143
 25        Calculation of the Average Diameter of Fine Particles
             from Asphalt Dryers in the Year 2000	144
 26        Compilation of Data to Be Used in Projection of Number
             of Fine Particles Emitted from Asphalt Dryers 	 146
 27        Projection of Fine-Particle Emissions on a Number Basis
             for Asphalt Dryers	146

          2.   Cement Plants

 11        Summary of Fine-Particle Emissions from Rotary Cement •
             Kilns	91

          3.   Ferroalloy Plants

 15         Summary of Fine-Particle Emissions from Ferroalloy
             Plants	99

                                   xi

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                      TABLE OF CONTENTS (Concluded)

                       LIST OF TABLES (Concluded)

          4.  Fertilizer Plants

Table                 ,            Title

 15        Summary of Fine-Particle Emissions from Fertilizer
             Granulators and Dryers	112

          5.  Iron and Steel Plants

  9        Summary of Fine-Particle Emissions from Iron and Steel
             Plants	    76

          6.  Iron Foundries

 16        Summary of Fine-Particle Emissions from Iron Foundry
             Cupolas	114

          7.  Kraft Pulp Mills

 10        Summary of Fine-Particle Emissions from Kraft Pulp Mills.    84

          8.  Lime Plants

 14        Summary of Fine Particle Emissions from Lime Plants  .  .  .   100

          9.  Municipal Incinerators

 17        Summary of Fine-Particle Emissions from Municipal
             Incinerators	117

          10.  Stationary Combustion Sources

  8        Summary of Fine-Particle Emissions from Stationary Fuel
             Combustion Sources	    68
                                   xii

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 1.   Summary

          Midwest  Research Institute, under  contract  from  the Air Pollution
 Control  Office,  Environmental Protection Agency, conducted a program to
 quantify fine-particle  emissions  (0.01-2 p,)  from particulate pollution
 sources.  The primary objective was  to use the best data currently avail-
 able (i.e., 1969-1970)  on  particle-size distributions of particulates from
 uncontrolled and controlled sources,  fractional efficiency curves for specific
 control  devices, and  the degree of application of control  equipment  on spe-
 cific  sources to estimate  the  mass  and  number of  fine particles  emitted
 from particulate pollution sources.   Secondary objectives  were the assess-
 ment of  (l) the  applicability of  standard sampling and particle  sizing meth-
 ods  to the  fine  particle regime,  and (2) the  current  understanding of the
 adverse  effects  of fine particulate  pollutants.

     1.1 Data Acquisition and Analysis

          The MRI  data  bank and data acquisition activities conducted during
 the  study provided- information on particle-size distributions and fractional
 efficiency  characteristics.  Particle-size data were  found to be quite exten-
 sive for some sources,  but rather meager for  other sources.  Coal-fired power
 plants,  cement kilns, lime kilns, and foundries are in the former category,
 while  sources in primary and secondary nonferrous metallurgy, iron and
 steel, and pulp  and paper  industries  fall in  the latter category.

          Another  facet of the particle-size  distribution  data is that a
 significant portion,  approximately 85%, was obtained  from  uncontrolled
 sources.  The lack of particle-size  data from controlled sources clearly
 indicates that neither  control equipment manufacturers nor air pollution
 control  agencies have placed any  significant  emphasis on the particle size
 of pollutants emitted from control equipment.  The main thrust of air pol-
 lution control to  date  has been toward control on a mass basis, with no
 concern  given to the  size  and number  of particles emitted  from the control
 equipment.

          Analysis  of the  particle-size distribution data  indicated that
 a major portion  (over 95$)  had been  obtained by sampling and sizing pro-
 cedures  that are not  suitable for the particle size range  < 2 p,.  As a re-
 sult,  only a meager quantity of accurate data is available on particle size,
 in the < 2 |i size  range, for effluents from either controlled or uncontrolled
 sources.

          Evaluation of fractional efficiency information  for control de-
vices revealed that limited data are available, and an assessment of the
reliability of much which is available is hampered by lack of specifics
pertaining to source sampling,  particle sizing, and source operating methods.

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In many cases the reported fractional efficiency curves were only identi-
fied as "typical" for a certain type of device with no other information,
comment, or reference.  Also, fractional efficiency data pertaining to a
specific control device on a upeolfic industrial source are very limited.
However, in general, the fractional efficiency data did reflect the expected
efficiency characteristics of specific types of control devices.  That is,
multiclones showed a higher efficiency curve than cyclones, and Venturi
scrubbers exhibited a higher efficiency than low-pressure drop scrubbers.
Detailed discussions of fractional efficiency and particle size data are
presented in Sections 5 and 6, pages 25 and 37.

     1.2  Fine-Particle Emissions  (1969-1970)

          The method used to calculate the mass and number of fine particles
emitted from a source utilized:
          1.  Production figures and emission factors reported in Volume I.

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

          3.  Percent application of control on specific sources, with a
breakdown of this percent application of control into the percent appli-
cation of each type of control device.

          4.  Fractional efficiency characteristics of each type of con-
trol device.
          To calculate the number of particles emitted in each particle-
size range, the following assumptions were made:

          1.  The particles are all spherical in shape, and

          2.  The density of the particles is independent of particle size,

With these assumptions the equation relating mass and number emissions is

                                              .)
                                                    N
y
where
          (Mass) 3 _j  = mass emitted in particle-size range between
                        diameter d  and d?

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                    P  = particle  density

               (i       = particle  diameter midpoint between d, and
                Di. p.                                        I

                   N    number of pnrticlou <;mli-t
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                                                             TABLE 1
                                         FINE-PARTICLE EMISSION FROM INDUSTRIAL SOURCES
               Source

1.  Stationary Combustion
        A.  Coal
            .1.  KJcctrir; Utility
                a.   l"ulverizcd
                b.   Stoki.-r
                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
    Crushed Stone

    Iron and Steel
        A.  Sinter Machines
        B.  Open Hearth Furnace*
        C.  Basic Oxygen  Furnace*
        D.  Electric  Arc  Furnace
4.  Kraft Pulp Mills
        A.  Bark Boilers
        B.  Recovery  Furnace**
        C.  Lime Kiln
5.  Cement Plants, Rotary Kilns

6.  Hot-Mix Asphalt  Plants
        A.  Rotary Dryer
        B.  Ventline
7.  Ferroalloys
        A.  Electric  Furnace
        B.  Blast Furnace
8.  Lime Plants
        A.  Rotary Kilns
        B.  Crushing and Screening***

1-3
UH.6
i'1.7
46.2
15.1
56.6
13.5
126.9
97.2
740.4
3.8
60-80
0.9
3.8

49.1
95.3
1.6
130.8
96.4
14.4

18.4
0.8
40.6
25-99
(Mass Basis, 10^ Ions/Year)
Fine Particle Size Ranges (Microns)
0.5-1.0 0.1-0.5 0.05-0.1 0.01-0.05 Total
I70.fi 99.2 2.:* 872. Z
!>.7 2.2 29.',
13.9 7.3 0.2 69.6
Total from El-;ctrio Utility 971.5
0.5 It,. 6
7.3 2.1 66
6.7 4.1 0.1 24.4
Total from Industrial Coal 106
126.9
97.2
Total from Fuel Oil and Gas 224.1
Total from Fuel Combustion 1,501.6
92.9 34.7 868
1.2 0.6 S.e
1-0-56 8.5-254 0.1-22 0-3.fi 108-376
10.9 153.7 , 1.0 174.!)
2.5 5.2 1.3 l.r, 14.3
Total from Iron and Steel 302.4-570.4
11.9 6.5 0.3 67.8
78 74.7 1.4 249.4
0.2 1.8
Total from Kraft Pulp Mills 319
32.7 15.5 177
36.3 21.5 154.2
1.7 0.2 16. S
Total from Hot-Mix Asphalt Plants 170.5
27.8 81.1 17.3 7.7 152.3
0.8 '
Total from Ferroalloys 153.1
18.8 23.6 3.0 1.8 87.8
25
Reliability
Rt-ting+
j
3
3
3
3
3
5
1
1
ft
•r

3
3
4
2
3
3

3
3
's
4
                                                               Total from Lime Plants
                                                                                                    113

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                Source
10.  Carbon Black

11.  Coal Preparation Plants, Thermal
       Dryer

12.  Fbtroll-urn FCC Units

IS.  Municipal Incinerators

14.  Fertilizer, Granulators and Dryers

15.  Iron Foundri'-a, Cupolas

16.  Acids
         A.  Sulfarie
         B.  Phosphoric (thermal)
                                           1-3
     Secondary Nonferrous Metallurgy****   127
                                            93
                                                       TABLE 1 (Concluded)

                                                     Fine Particle Size Ranges  (Microns)
                                                    0.5-1.0    0.1-0.5
63.5
45
10.4 6.7
7.1 3.5
6.6 2.4
2.7
1.0


11.5
3.1
3.1


                                                                           0.05-0.1
                                                                                       0.01-0.OS
3.5
0.4
            4.3
            0.4
                                                       Total from Acids

                                                       Total from Major Industrial Sources
                       Total

                        127

                         93
Reliability
  Rating*

    5

    3
63.5
45
36.4
13.7
13.1
2.7
1.0
3.7
3.800-4.066
4
4
2
3
2
4
4


 *     See Section 7.2.3 for discussion of calculations.
 **    See Section 7.2.4 for discussion of calculations.
 ***   See Section 7.2.8 for discussion of calculations.
 ****  See Section 7.2.9 for discussion of calculations.
 +     Reliability rating is indicative of the relative reliability of the emission quantities.  Ratings range
         from 1 to 5 with 1 being the most reliable.

 Note:  Potentially significant sources .not evaluated because of lack of sufficient data:  (l) operations related to
          agriculture, (2) primary nonferrous metallurgy, (3) clay products, (4) food processing operations, and
          (5) fiberglass manufacture.

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-------
On a mass basis, stationary combustion, crushed stone, iron and steel,
and kraft pulp mills are significant industrial sources of fine-particle
pollutants.

          Table 1 also includes an indication of the  reliability of
emission quantities presented in Tables 1 and 2.  The reliability was
determined from an evaluation of data on (l) mass emission factors; (2)
overall efficiency of control equipment; (3) extent of application of
control; (4) fractional efficiency for control devices; (5) particle-size
distribution; and (6) production figures.  The evaluation considered the
quantity of data available, a comparison of data from different information
sources, and the souree of the data.  Ratings range from 1 to 5 with 1
being the most reliable.

          As shown in Table 2, metallurgical furnaces and municipal
incinerators are significant sources of fine-particle pollutants on a
number basis.  In view of the many assumptions involved in the calculations,
the individual emission quantities given in Tables 1 and 2 are considered
to be only a "first-cut" estimate.

          Differences were found in the estimated fine-particle and total
mass emissions from some sources that emit mainly micron or submicron
particulates.  In these cases, the estimated fine-particle emissions exceeded
the total mass emissions.  Section 7.2 presents these results in detail.

          Table 3 presents a source priority ranking, based on the mass
and number of fine  particles emitted, of the industrial sources for which
adequate information was available to estimate emissions.  The priority
ranking indicates those sources where initial efforts should be focused
to control the emission of fine-particulate pollutants.  In our opinion,
improved control of fine-particle emissions from the high priority sources
would result in a significant reduction in the mass and/or number of fine
particulates emitted from stationary sources.

-------
                                   TABLE 3

                  PRIORITY RANKING OF INDUSTRIAL SOURCES OF
                         FINF.-PARTTCULATE POLLUTANT::

                   1.  Fcrronltoy Furnaces

                   2.  Steel-Making Furnaces

                   3.  Coal-Fired Power Plants

                   4.  Lime Kilns

                   5.  Kraft Pulp Mill Recovery Furnaces

                   6.  Municipal Incinerators

                   7.  Iron Foundry Cupolas

                   8.  Crushed "tone Plants

                   9. . Hot-Mix Ar.phalt PI ante

                  10.  Cement Kiln;;
          To indicate the relative magnitude of the fine particulate problem
from stationary sources, fine-particle emissions were also estimated for
mobile and miscellaneous sources.  Particulate emissions from mobile sources
were assumed to be uncontrolled and to consist of all < 2 p, particulates.
Table 4 summarizes the estimate of fine-particle emissions from these sources,
Table 5 presents an estimate of fine-particle emissions from miscellaneous
sources for which adequate particle size data were available.  Fine-particle
emissions from natural dusts, forest fires, and agricultural burning could
not be estimated because of lack of reliable particle size data.

     1.3  Projections of Fine-Particle Emissions

          Projections were made of fine-particle mass and number emissions
through the year 2000 for some of the sources listed in Tables 1 and 2.
Because of incomplete data it was not possible to project the emissions of
primary and secondary nonferrous metallurgy, petroleum, acids, and carbon
black mar ofacturing operations.

          1.3.1  Mass basis;  Two methods were used to project the mass of
fine particles emitted in future years.

-------
                         TABLE 4
       FINE-PARTICLE EMISSIONS FROM MOBILE  SOURCES


1.


2.
3.
4.
5.





Sourer;
Motor Vehicles
a. Gasoline
b. Diesel
Aircraft
Railroads
Water Transport
Nonhighway Use
a. Agriculture
b. Commercial
c. Construction
d. Other
l'jmi;;.f: ion::
( torm/yij or )

420,000
260,000
30,000
220,000
150,000

79,000
12,000
3,000
26,000
                              Total
 1,200,000
                         TABLE 5
   FINE-PARTICLE EMISSIONS FROM MISCELLANEOUS SOURCES
      Source

1.  Rubber from tires

2.  Cigarette smoke

3.  Ocean salt spray

4.  Aerosol from spray cans
                                Total
 Emissions
(tons/year)

   300,000

   230,000

   340,000

   590,000

 1,260,000
                         10

-------
          Method  1  - The  projection of  emissions by Method 1 assumec that
there will be no  change in  bhe  net control for a source.  Thi:; a,'jRumptIon
To::u3l-o in an increase  In curd,".;;ion:; in  proport.ion to  ine.reanen in production
capacity.  Production i'iyurcs were projected by the same methods outlined
in Volume li/ and were used to  proportionally increase the current ma.",s of
fine-particle emissions.

          Method  2  - The  projection of  emissions by Method 2 takes into
account the increases in  production but two assumptions are also made:

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

          2.  Increased utilization of  the most efficient control devices
will continuously increase the  efficiency of control on fine particles so
that by the year  2000 it  will be equivalent to controlling all sources with
baghouses.  The fabric filter was selected as a reference standard of
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 development of new
devices would allow the efficiency of control devices, in the year 2000,
to match the performance  capabi]ity of  the best devices that are presently
available.

          No attempt was  made to account for any changes in particle size
distributions of  emitted  particulates that might result from process modi-
fications in future years.

          The two projection methods represent two extremes:  no improve-
ment in control versus stringent control.  An intermediate position is
more probable, but  projection of an intermediate situation requires in-
formation 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.   Projections involving
gross assumptions of future equipment utilization were not deemed valu-
able.

          Table 6 summarizes the projections of fine-particle emissions
on a mass basis.  Details of the calculation procedures are given in Sec-
tion 8.1, pages 119 to 123.   Fine-particle emissions for the sources
listed in Table 6 can be reduced from 3.5 x 106  tons/year (1968 emission
level)  to 3.5 x 105 tons/year by the year 2000 if the  efficiency of control
                                   11

-------
on all these sources in the year 2000 is equivalent to the performance of
the best device currently available (i.e., baghouse).  The projections
also show that, even if stringent control is achieved in the year 2000,
coal-fired power plants, basic oxygen furnaces, and kraft-pulp-mill re-
covery furnaces will each emit over 50,000 tons/year of < 2 p, partic-
ulate.

          1.3.2  Number basis;  The number of fine particles emitted by
stationary sources to the year 2000 were projected by two methods that are
extensions of the techniques used to project mass emissions.  The first
method assumes no change in net control which means that the emissions on
a number basis, as they were on a mass basis, are directly proportional to
future production capacities.  Method 2 utilizes the mass emissions pro-
jected by the second technique discussed in Section 1.3.1 and an assump-
tion regarding the average diameter of fine particles emitted from sources
in the future.  The average diameter of the particles emitted in 1968
could be computed from the mass emissions versus particle size data given
in Table 1.  However, some method had to be devised to determine an aver-
age diameter for the years between 1968 and 2000.  This was accomplished by
computing an average diameter for the fine particles emitted in the year
2000 when all sources were assumed to be controlled by baghouses or their
equivalent.  The average fine-particle diameters for the intervening years
between 1968 and 2000 were taken from a straight line interpolation be-
tween the average size of the fine particles emitted in 1968 and in 2000.
The sequence of calculation steps for Method 2 is presented in detail in
Section 8.2, page 123.

          Table 7 presents a summary of the projections of fine-particle
emissions on a number basis.  The projections show that ferroalloy elec-
tric furnaces, rotary lime kilns in lime plants, municipal incinerators,
coal-fired power plants, and steel-making furnaces (EOF and electric arc)
will be significant sources of fine-particle pollutants, on a number basis,
even in the year 2000.

     1.4  Literature Surveys

          Literature surveys were conducted in the areas of source samp-
ling techniques for fine particles, particle size measuring methods, and
adverse effects of fine particulate pollutants.   Information from the
literature surveys, coupled with data from personal contacts with univer-
sity and APCO research groups, testing laboratories, and consultants, was
used to prepare summaries of the state of knowledge in each area.   These
                                    12

-------
                            TABLE  h





PKOJECTIOHS OF FINE-PARTICLE EMISSIONS FROM  INDUSTRIAL SOURCES
JjOlil
I.

II.
III.



IV.


V.
VI.
VII.
Vti
Stationary Combustion
A. Coal
1. Electric Utility
?. Industrial
Crushed Stone
Iron and Ut<>el
A. ;!intr.r Mi^hui.':.
M. O)vn Hearth Furnocr
C. Basic Oxygen Furnace
D. Electric Arc Furnace
Kraft Pulp Mills
A. Bark Boilers
B. Recovery Furnace
C. Lime Kilns
Cement Plants, Rotary
Kilns
Hot Mix A.'.phnlL PJunts,
Dryers
Ferroalloy Electric
Furnaces
VIII. Lime Plants, Rotary
Kilns
IX.
X.
XI.
XII.

Coal Preparation Plants,
dermal Dryer
Municipal Ireinerators
Fertilizer, Granulators,
and Dryers
Iror Foundries, Cupolas
Totals
Method
I
II
I
II
I
II
1
II
1
II
I
II
I
II
I
11
I
II
I
II
I
II
I
31
I
II
I
II
I
II
I
II
I
II
I
II
I
II
(Mass
1970
1.046
0.976
0.133
0.127
1.067
1.046
0.006
O.OOf,
.;•(>'.,
0 . l.Mi
0.166
0.074
0.134
0.094
0.086
C.061
0.051
0.037
0.016
0.012
0.015
0.010
4.61
3.51
1980
1.374
0.731
0.170
0.084
1.814
1.137
0.000
iJ.i-iOo
'J.IC'I
0.040
0.454
0,305
0.021
0.004
0.109
0.063
0.372
0.268
O.OO3
0.002
0.273
0.140
O.J'M)
O.IK'
0.180
0.008
0.174
0.086
0.105
0.047
0.061
0.031
0.017
0.010
0.016
0.006
5.57
3.12
1985
1.600
0.653
0.170
0.064
2.300
1.090
0.009
0.004
0.098
0.018
0.515
0 .277
0.023
0.004
0.115
0.051
0.407
0.208
0.003
•0.001
0.319
0.125
0.30.')
<;. M)
0.198
0.009
0.189
0.071
0.124
0.043
0.071
0.027
0.013
0.008
0.017
0.005
6.48
2.8
1930
1.364
0.528
C . 170
0.043
2.934
0.933
f'.ooa
0.003
0.0.', C
0.006
0.581
0.237
0.026
0.004
0.123
0.037
0.446
0.163
0.003
0.001
0.372
0.101
0.3V.S
0.117
0.219
0.010
0.206
0.053
0.145
0.037
0.081
0.021
0.021
0.006
0.017
0.003
8.45
2.3
1995
2.110
0.335
0.166
0.023
3.715
0.606
0.010
ii.UX-
0.001
0.000
0.616
0.170
0.029
0.003
0.142
0.022
0.514
0.116
0.004
0.001
0.421
0.062
0.460
0.074
0.241
0.011
0.311
0.044
0.166
0.025
C.095
0.014
0.023
0.004
0.018
0.002
9.04
1.51
2000
1.586
0.030
0.164
0.002
4.713
0.033
0 . 010
0.000
0.000
0 . 000
0.654
0.094
0.034
0.003
0.165
0.002
0.594
0.051
0.004
0.000
0.476
0.016
0.563
0.018
0.267
0.012
0.466
0.016
0.190
0.011
0.109
0.003
0.025
0.001
0.019
0.003
10.84
0.355
                            13

-------
                            TABLE 7





PROJECTIONS OF FINE-PARTICLE EMISSIONS FROM INDUSTRIAL SOURCES
(Number Basis, 1Q23 particles/Year)
Source Muthod
1.

II.
Ill



IV.


V.
VI.
VII
;U.fitionary Oombuntlon
A. To ii.l
1 . Klfctrlr Utility
2. Industrial
Crushed Stone
Iron and Steel
A. Sinter Machines
B. Open Hearth Furnaces
C. Basic Oxygen Furnaces
D. Electric Arc Furnaces
Krnft Pulp mils
A. Rnrk Boilers
B. Recovery Furnaces
C. Lime Kilns
Cement Plant Rotary Kilns
Hot-Mix Asphalt Plants, Dryers
Ferroalloy Electric Furnaces
VIII. Lime Plants, Rotary Kilns
EC.
X.
XI.
XII

Coal Preparation Plants, Thermal
Dryers
Municipal Incinerators
Fertilizer, Granulators, and
Dryers
Iron Foundries, Cupolas
Totals
1
31
I
II
I
II
I
II
I
II
I
II
I
II
1
II
1
II
I
II
I
II
I
II
I
III
I
II
I
II
I
II
I
II
I
II
I
II
1970
:M .:',
IM .0
7.66
7.60
14. S
14.2
0..172
0.152
663
633
42.3
40.5
280
257
/.[>
'/.'.<
17
46
0.005
0.005
3.8
3.7
6.5
6.2
1,940
1,720
538
530
0.004
1,260
1,180
1.14
1.08
100
96
5,006
4,637
197E
1011. ',
11 / . 1
0.64
7.65
18.8
18.2
0.224
0.165
449
275
65.9
53.8
330
198
3.0
fi.:o
S.'j
49
0.006
0.005
4.6
4.2
8.0
6.4
2,070
1,140
699
601
0.005
1,610
1,320
.1.25
1.00
110
88
5,548
3,868
19flO
r.'.i.'i
Ki.7,
9.81
6.98
24.6
23.6
0.291
0.171
302
84
101.9
69.8
390
89
11.0
8.6
65
54
0.007
0.006
5.5
4.0
9.7
6.3
2,240
140
911
616
Year
1985
.M4.;'
nn.B
9.81
5.79
31.2
27.5
0.316
0.148
174
40
115.6
63.4
427
89
11.7
7.7
72
44
0.008
0.005
6.5
4.1
11.9
6.1
2,470
150
989
564
0.007 0.008
Not Calculated
1,940
1,130
1.36
0.85
121
62
6,258
2,385
2,250
1,060 .
1.48
0.74
127
57
6,342
2,208

1990
IfVl.l
HO.Z
'J.&1
4.33
39.8
29.1
0.346
0.121
101
19
130.5
54.2
469
90
IP. 6
fi.4
79
37
0.008
0.004
7.6
3.7
14.6
5.2
2,740
170
1,080
484
0.009
2,570
890
1.62
0.59
132
50
7,556
1,924

1935
:•><,.'.
','/.'•
'.1.V,'
2.45
50.3
23.7
0.521
0.076
1.0
0.0
136.8
38.9
540
93
14.5
4.Z
'
0.1G
63.9
1.6
0.782
0.015
0.0
0.0
147.0
21.5
624
89
lf,.H
(i . '','/
10!j
13
0.011
0.001
9.7
0.8
21.9
0.9
3,320
210
2,440
192
0.012
3,480
140
1.94
0.07
145
6
10,600
693

-------
summaries are presented  i.n  Append leer, A, is, and C.  The highlight:; of the
appendices are presented in the  following  sections.

          1.4.1  Partlculate  sampling and  sizing;  Standard collecting
techniques are inadequate for collecting particulate pollutants for ac-
curate particle  size determinations, particularly for particles 1 ji or
smaller.  Cyclone  separators  tend to break up aggregates and friable par-
ticles, stainless  steel  or  alundum thimbles do not quantitatively capture
the submicron particles,  and  small particles may penetrate deeply into the
body of a fiber  filtering medium before they are captured and then cannot
be removed for subsequent analyses.

          A sampling device which collects submicron particles and causes
neither formation  nor breakup of aggregates is necessary if accurate par-
ticle size information is to  be  obtained.  Cascade impactors, thermal
pi-ecipitator!L;; and small electrostatic precipitators are devices currently
available that come eloLie to  mooting l,hese requirements, and are clearly
superior to the  standard :;amplinp; trains.  A cascade impactor -which can
be inserted inside a duct Li;  the most versatile of these devices.  Stain-
less steel cascade impactors  are now available which permit "in-stack"
collection of submicron  particles.

          If a standard  sampling train is used to collect particulates
for subsequent particle  sizing,  failure to disperse the particles ade-
quately as discrete particles will be a major source of error.  The use
of cascade impactcrs, thermal precipitators, or electrostatic precipitat-
ors as sampling  devices  minimizes' the redispersion problem because opti-
cal sizing techniques are generally used in conjunction with these de-
vices.

          The Bahco Micro-Particle Classifier has been used extensively
for routine particle size measurements, and a major portion of the data
currently available on the  particle size of particulates emitted from
industrial sources has been obtained by using this device.   The range of
applicable particle diameter  for the Bahco instrument is 6 to 60 (j,.  As
a result of the  extensive use of the Bahco method, only a meager quantity
of accurate data is available on the particle size of particulate pollu-
tants in the < 2 |j, size  range.

          1.4.2  Adverse effects of particulates on human health;  The ad-
verse effects caused by particulate pollutants on human health are, for
the most part, related to injury to the surfaces of the respiratory sys-
tem.   Particulate material  in the respiratory tract may produce injury
                                    15

-------
itself, or it may act in conjunction with gasee, altering their tiiter. or
their modes of action.  A combination of particulars and gaues may pro-
duce an effect that, lu greater Lh/in the uum of the cffecto cauued by eit,hor
individually (i.e., uynerglotle effect).

          Laboratory studies of man and other animals show that the deposi-
tion, clearance, and retention of inhaled particles is a very complex pro-
cess, which is only beginning to be understood.  Particles cleared from the
respiratory tract may exert effects elsewhere.  Available data from labora-
tory experiments do not provide suitable quantitative relationships for
establishing air quality criteria for particulates.  These studies do, how-
ever, provide valuable information on some of the bio-environmental rela-
tionships that may be involved in the effects of particulate air pollution
on human health.

          Toxicological studies on animals have shown that:

          1.  Particulate matter may exert a toxic effect via one or more
of three mechanisms:

               (a)  The particle may be intrinsically toxic because of ite
inherent chemical and/or physical characteristics.

               (b)  The particle may interfere with one or more of the
clearance mechanisms in the respiratory tract.

               (c)  The particle may act as a carrier of an adsorbed toxic
substance.

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

          3.  The toxicological importance to mankind of submicron particles
cannot be overemphasized.

          4.  Particles below 1 p. may have a greater irritant potency than
larger particles.

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

          6.  All particulate matter does not potentiate the response to
irritant gases.
                                      16

-------
           7.   Both solubility of sulfur dioxide in a droplet and catalytic
 oxidation to sulfuric acid play a role in the potentiation of sulfur dioxide
 by certain particulate matter.

           'Lno  .•jna.lyHe.'j oi' numerous epidemiologic»l studies eJenrJy indicate
 an assoriation bo two en air pollution,  or>  measured by parti cuJ uto  mutter
 accompanied by sulfur dioxide,  and health effects of varying soverity.   This
 association is most firm for the  short-term air pollution episodes.   The
 studies concerned  with increased  mortality also show increased morbidity.

           The  association between long-term residence in a polluted  area
 and chronic disease morbidity and mortality is  somewhat more conjectural.
 However,  in the absence of other  explanations,  the findings of increased
 morbidity and  of increased death  rates for selected causes, independent of
 economic  status, must still be  considered consequential.

           Information is lacking  regarding the  mechanisms involved in the
 enhancement of viral  virulence  by specific air  pollutants.  Specific  methods
 by which  air pollutants can synergistically affect viral infections  are
 unknown.   It is possible that fine particulate  matter may act  as  carriers
 for certain virus  agents.

           1.4.3 Modification of  the  atmosphere by particulates;   Suspended
 fine particles may have considerable  influence  on the behavior of the
 atmosphere  and thus on human activities.   They  can act as condensation  or
 freezing  nuclei and therby modify weather patterns.   They absorb  and scatter
 light  and decrease visibility.  Fine particles  in the atmosphere  may also
 influence  solar radiation and interfere with astronomical observations.

           Visibility  reduction  related to air pollution is caused primarily
 by the 0.1  to  1.0  p, radius particles in the atmosphere.   The visibility
 problem associated with particulate air pollution can be  divided  into
 specific  smoke  plumes  and well-aged aerosols.   The visual appearance  of
 smoke plumes and visual obscuration by smoke  plumes  are  closely related to
 the amount  of  light the  plumes  scatter in the direction of the viewer from
 their surroundings  and the  sun.   Consequently,  evaluation of plumes by  a
 visual effect  is more  difficult for nonblack plumes  than  for black plumes,
 and depends on plume  illuminating and  viewing conditions.   Because of this,
 nonblack plumes  could  be  evaluated differently  when  viewed on  different days
 or viewed from different directions,though their  aerosol  content  has  not
 changed.  Furthermore,  the  size of particles  and  mass  per  unit time emitted
 from the stack, and not  the  appearance  or optical properties of the plume,
 are more inportant  to  the  eventual air  composition,  even  though appearance
may be aesthetically objectionable.
                                     17

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          Recent advances in our knowledge of the size distributions and
optical properties of well-aged atmospheric aerosols have resulted  in a
clearer description of visibility reduction by such aerosols.   Theoretical
and experimental utiuMos of weJI-nfred  aoroHoJo huvo ohown Mini:

          1.  A^rosola :in the lowenl rutfJon of the atmosphere (tropespher<-),
whether over urban areas or not, tend  to have similar size distributions.

          2.  A narrow range of particle sizes, usually from 0.1 to 1.0 \i
radius, controls the extinction coefficient and thereby visibility.

          3.  The mass concentration of a well-aged aerosol is  approximately
proportional to the light scattering coefficients for atmospheric aerosols
originating naturally or as the result of man's activity.

          The increased emission of fine particles into the atmosphere may
cause changes in the delicate heat balance of the earth-atmosphere  system,
thus altering worldwide climatic conditions.  Comparisons at different sites
over the world covering periods of up  to 50 years suggest that  a general
worldwide rise in turbidity may be taking place.  This may well be  indicative
of a gradual buildup of worldwide background levels of suspended particulater,.
The net influence of atmospheric turbidity on surface temperature is uncertain,
but the emission of long-lived particles may well be leading to a decrease
in world air temperature.  As more is  learned about 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 atmosphere may produce very
long-term meteorological effects.

          Suspended particulate matter may alter weather patterns.  There is
evidence that some of the particles introduced into the atmosphere by man's
activities  can act as nuclei in processes which affect the formation of
clouds and precipitation.  Investigations of snow and rainstorm patterns
indicate that submicroscopic particulates from man-made pollution may be
initiating and controlling precipitation in a primary manner, rather than
being involved in the secondary process wherein precipitation elements
coming from natural mechanisms serve to remove the particles by diffusion,
collision, and similar scavenging processes.
                                    18

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2.  Introduction

          Much of today's atmospheric pollution is smoke and dust of such
a size that it falls out or is washed out of the atmosphere within a day or
so.  A certain portion of the pollution is, however, composed of particles
a micron or smaller in diameter.  These particles may exist in the atmosphere
for long periods of time.  The presence in the air of submicron particles
of various chemical compositions from man-made sources is of increasing
interest to many governmental and scientific groups.  The interests of
these groups range from upper-atmosphere physics and air pollution control
engineering to the protection of human health.

          Fine participates emitted from man's activity contribute signifi-
cantly to all the major adverse aspects of air pollution.  Fine particles
can initiate or contribute to problems related to human health, atmospheric
physical properties, and/or economics.  The effects of particulate matter
on human health are, for the most part, related to injury to the surfaces
of the respiratory cystem.  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.  Particle size, together with specific
gravity and chemical nature, largely determine:  (l) where particles are
deposited in the respiratory system, (2) the fate of the particles after
deposition, and (3) to a considerable extent their physiological action.
Particulate material i.n the respiratory tract may produce injury itself, or
it may act in conjunction with gases, altering their sites or their modes
of action.  A combination of particulates and gases may produce an effect
that is greater than the sum of the effects caused by either individually
(i.e., synergistic effects).

          Fine particulate pollutants also affect the physical properties
of the atmosphere.  The chemical and physical properties of the atmosphere
affected include:  its electrical properties; its ability to transmit radi-
ant energy; its ability to convert water vapor to fog, cloud, rain, and snow;
its ability to damage and to soil surfaces.  Concern with atmospheric trans-
mission of radiant energy encompasses the entire electromagnetic spectrum,
but of particular concern is the infrared region, as it affects the terres-
trial 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.

          The overall impact of fine particulate pollutants, as well as air
contaminants in general, on the aggregate of living things in nature is
nearly a • otal mystery.  In any ecosystem, the inhabitants exist in a com-
plex state of interaction among themselves and with the inanimate phases of
the environment.   This interaction is affected by climate and by chemical

                                    19

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and physical inputs to the system.  As man has become more knowledgeable in
these areas, he has also become increasingly aware of the importance to his
well being of the action of fine particles.  Not only do they affect his
own body in a multitude of ways, but they can have extremely important
effects on the plants and animals that constitute his food supply.  While
our present understanding of this interaction does not permit a quantitative
assessment of the overall influence of fine particulates, information is
being accumulated which points to many negative features of fine-particulate
air pollution.

          The particulate pollutant systems study conducted at MRI under
AFCO sponsorship had as an overall objective the delineation of deficiencies
in our knowledge regarding the nature and magnitude of particulate pollutant
emissions from stationary sources.  During the course of the first year's
activity, it became apparent that two of the major unknown areas were the
mass and size ranges of fine particles emitted from particulate pollu-
tion sources.  This first year pinpointed deficiencies in our knowledge with
respect to important sources of fine particles, actual particle-size range
emitted, and the collection efficiency of control equipment in the small-
particle size range.

          The present study was initiated to bring into focus the current
status of what is known about the fine-particle burden emanating from various
particulate pollution sources.  The primary objective was to use the best
data currently available on particle-size distributions from uncontrolled
and controlled sources, control equipment fractional efficiency curves,* and
the degree of application of control equipment on specific sources to esti-
mate the present level of fine-particle emissions from particulate pollution
sources.  Secondary objectives were the assessment of (1) the applicability
of standard source sampling and particle sizing methods to the fine-particle
regime, and (2) the current understanding of the adverse effects of emitted-
fine particulate. matter.

          The major tasks of this program are discussed in the following sec-
tions:  (l) data acquisition and analysis (Sections 4 and 5); (2) literature
surveys on source sampling methods, particle size measuring techniques, and
adverse effects of particulate pollution (Appendices A, B, and c); (3) prep-
aration of summary reports on the literature surveys (Appendices A, B, and
C); (4) evaluation of methods of graphical representation of particle-size
distribution and control equipment fractional efficiency data (Sections 5
and 6); (5) calculations of weight, number and size ranges of fine particu-
lates emitted from specific sources (Section 7); and (6) projection of fine-
particle emissions through the year 2000 (Section 8).  Important conclusions
are listed in Section 9, and Appendices on source sampling methods, particle
size measuring techniques, and adverse effects of particulate pollution, data
sources, and emission calculations conclude the report.
*  See Section 3, page 21, for definition.
                                      20

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3.  Definitions of Important Terms

          Several terms, which may not be familiar to the reader, are used
in this report.  For ease of reading the report, these terms are defined in
this section.

     3.1  Fine Parti oulate and Particle Si
          The terms "participate" and  "particle oize" are ambiguous unless
they are carefully defined.  Therefore, prior to initiating the study of fine-
particulate emissions, it was necessary to select a definition of a particu-
late, particle size, and the particle-size range of interest to the program.
The principal objective in this study was the estimation of the level of
fine-particle emissions from man-made sources.  Furthermore, attention was
to be focused on primary particulates , and not on secondary particulates
formed by subsequent reaction of source effluents in the atmosphere.

          The following definition was adopted for the purposes of this
study:

          "Fine particulate matter is a material that exists as a
          solid or liquid in the operating environment of the source
          and is in the size range of 0.01 to 2 (j, in diameter."

          The operating environment Includes the process equipment and itn
exhaust stack or pipe.  The definition of particle size ia unique only 1'or
spherical particles.  For all other cases, the particle size will be depen-
dent upon the experimental method used.  Since in this program emissions
were to be estimated from available particle-size distribution data, the
particle size is defined by the experimental method utilized to obtain the
particle size.

          The lower size limit of 0.01 ^ was selected from considerations
of potential adverse effects of particulates on human health.  A review of
the literature on health effects and discussions with prominent researchers
in the field indicated that a lower limit of 0.01 p, would be reasonable for
the purposes of this program (see Appendix B).  Selection of the upper size
limit of 2 M. was based on a review of literature information relating to the
influence of particulates on the modification of the atmosphere.  Visibility
reduction is primarily caused by the 0.1 to 1 (j, radius particles and, in
addition, reduction in solar radiation and weather modification are caused
by 0.05 to 1 M- radius particles (see Appendix c).  A secondary factor in
establishing the 2 (X upper limit is the decrease in control-equipment effi-
ciency for < 2 (j, diameter material.
                                    21

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     3.2  Process Emissions

          Process emissions arc do 11 nod as cm.iun.lonc before and uputream of
any control devices.

     3.3  Fractional Efficiency of Control Equipment

          The fractional efficiency (on a mass basis) of a control device
is defined as the efficiency of removal of specific sizes of particles.
For example, if a stream contains 10 Ib. of 1-p, particulate, and a control
device removes 9 It. of this material, the fractional efficiency of the
device at 1 ^ is 90$..

     3.4  Penetration

          Penetration of a specific particle size through a control device
is defined as
                          [pL    i -
                          I ^             x

where

            [p] d  = penetration at diameter  d-^

                ,  = fractional efficiency of control device at particle
                      size of  dn
                                    22

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4.  Data Acquisition

          Information on particle-size distributions of effluents from
particulate pollution sources and fractional efficiency curves for
control equipment applied to these emission sources was obtained from the
MRI data banki/and data-acquisition activities conducted during the study.
The data bank includes about 3,000 technical articles and reports; 500
stack sampling tests from air pollution control agencies; telephone and
personal interview reports from 350-400 industrial, testing laboratory,
and control device manufacturer contacts; and communiques from consultants
and academic people.  This data bank was searched for all pertinent data
on particle-size distributions and fractional efficiency curves.

          Acquisition of additional particle-size data was an integral
phase of the program, and efforts were focused on control device manufacturers,
source sampling organizations, and university research groups.  We contacted
numerous potential data sources, and believe that all significant sources
of particle-size data have been exhausted.  A complete list of contacts
made during the program is given in Appendix D.

          The second part of the information-acquisition activity was
directed to a literature survey in the areas of source sampling techniques
for fine particles, fine particle size measuring methods, and adverse effects
of emitted fine particulates.  Information from these surveys, coupled with
data from personal contacts with university groups, testing laboratories,
APCO research groups, and consultants, was used to prepare summaries of
the state of knowledge in each area.  These summaries are presented in
Appendices A, B, and C.
                                   23

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5.  Particle-Size Distribution Data

     5.1. General Features of Available Data

          A major portion (over 95$) of the data currently available on
the size of particulates emitted from industrial sources has been obtained
by using standard source sampling procedures and the Banco Micro-Particle
Classifier.  The Coulter Counter, Whitby centrifuge/MSA Sedimentation, and
microscopic techniques have also been used for particle sizing.  Cascade
impactors, electrostatic precipitators, and thermal precipitators have been
used to a limited extent in source sampling, and a small quantity of particle-
size data vas obtained from investigators using this equipment.  A complete
list of industrial organizations and research groups that provided particle-
size data is given in Appendix D.

          In general, the exact source sampling techniques used to obtain
the particulates for subsequent sizing have not been defined.  In some
cases, the thimble size used in the sampling train vas indicated.  Requests
to provide detailed information on this point were made to the groups ^
supplying data, but their general response vas that the collection of such
information vould require an extensive reviev of their files, and we decided
that the time and money required for them to perform such a reviev were
prohibitive for this program.  Telephone conversations with knowledgeable
individuals in the various organizations did indicate that sampling techniques
were "standard".

          Particle-size data vere found to be extensive for some sources,
but rather meager for other sources.   Coal-fired power plants, cement
kilns, lime kilns, and foundries are in the former category, vhile sources
in the primary and secondary nonferrous metallurgy, iron and steel, and
pulp and paper industries fall in the latter category.   This nonuniformity
in the availability of data made it impossible to provide more than a
general indication of the mass of fine particles emitted from some
sources.

          Another facet of the particle-size distribution data collected
during the program is that a significant  portion,  approximately 85$,  vas
obtained from uncontrolled sources.   The  lack of particle-size data from
controlled sources clearly indicates  that neither control equipment
manufacturers nor air pollution control agencies have placed any significant
emphasis on the particle size of pollutants emitted from control equipment.
The main thrust of air pollution control  to date has  been tovard control
on a mass basis,  vith no concern given to the size and  number of particles
emitted from the control equipment.   Failure to collect fine particles
constitutes the most  severe deficiency of current  control equipment because

                                   25

                                                 PRECEDING WF. HJW

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the fine particles emitted contribute significantly to all the major
adverse aspects of air pollution (see Appendices B and C).

          The lack of particle-size distribution data following control
equipment and the lack of measurement of total efficiency vhere outlet
size data are available made it difficult to check calculations of fine-
particle emissions.  For those sources where adequate particle-size
distribution data for controlled sources were available, these outlet dis-
tributions vere used to check emission calculations performed using size
distributions for uncontrolled sources and generalized fractional efficiency
curves.  Sections 6 and 7 discuss these subjects in more detail.

     5.2  Methods of Data Presentation

          Particle-size data can be expressed in tabular or graphical
form.  Presentation of size data in tabular form is more precise as well
as more general.  Measurements are expressed explicitly in this format.
The table can present either particle size versus cumulative frequency
greater (or less) than specific sizes, or particle-size range versus
weight or number frequency within the range.  The choice between number-
size and weight-size is dictated by method of measurement, i.e., whether
the data were collected by counting particles or by weighing.

          For purposes of Illustrating data, there are a number of reasons
why representing particle-size distributions graphically is preferable
to tabular presentation.  One of these is that graphs present the data in
such a form that one may learn at a glance something of the deviation
of the data, their skewness, and the location of the mode.  Another reason
is that graphs are much more concise than long tables of measurements.
At the same time, they present more complete information than can be
indicated by one or two of the usual averages and some measure of the
deviation.  A third reason for preparing graphs is that they can often be
used to obtain numerical values for certain properties of the distribution.
Examples are estimates of the arithmetic mean from plots of normally
distributed particle sizes, and estimates of the geometric mean from plots
of log-normal distributed particle sizes.  Still another purpose for
plotting particle-size data is to obtain a basis for interpolation or
extrapolation of the data.  This last reason is quite important for the
current study because very few particle-size data are available in the
size range of interest (0.01-2^).
                                    26

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          Several methods are available for graphical depiction of particle
size data.  Histograms, frequency distribution curves (continuous  histogram),
and cumulative distribution curves are frequently used to present  particle-
size data.  Figure 1 illustrates a histogram and frequency distribution
curve, while Figure 2 presents a cumulative percentage curve.   The cumula-
tive percentage curve is suitable for both equidistant and nonequidistant
class intervals of particle size.  However, the frequency distribution curve
is best suited for the graphical presentation of data classified by an equi-
distant scale.  A frequency distribution with a nonequidistant scale,  while
theoretically possible, would give a distorted picture of the  distribution.
Such a distortion would necessitate additional inspection of the numerical
table of data, and defeat the basic idea of graphical representation.   For
these reasons, cumulative curves are used extensively in preference to fre-
quency curves.
                40r
           u
           z
           LU
           o
V                                             FREQUENCY
                                             DISTRIBUTION

                10 -
                      1    2    345678
                           PARTICLE DIAMETER, MICRON
         Figure 1 - Histogram Representing a Particle-Size  Distribution
                                   27

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              lOOr
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80
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                           2468
                             PARTICLE DIAMETER,  MICRON
                                                  10
     Figure 2 - typical Cumulative Percentage Curve for a Particle-Size
                                     Distribution
          The utility of cumulative curves can be enhanced by plotting data
in such a manner that a linear curve results.  Plotting for a linear curve
can be done only under the assumption that the distribution obeys one of
the standard laws, e.g., normal or log-normal law.  If the distribution
obeys the normal law, a linear relationship can be obtained by plotting the
data on probability paper.  If the distribution follows the log-normal law,
a linear curve can be obtained by plotting the data on log probability
paper.  Materials exhibiting a normal distribution of particle size are
relatively rare.  On the other hand, particle-size distributions of many
particulate systems follow the log-normal law.i§/  Although it is common to
find the experimental points at the upper and lower extremes of the distri-
bution deviating from a linear curve, the log normal method of plotting and
representing particle-size data is useful and convenient.  It also permits
interpolation between points as well as limited extrapolation beyond the
experimental range covered.  Figure 3 shows a cumulative curve for a fly
ash, and Figure 4 presents the same data on log probability coordinates.
                                     28

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          As noted in Section 5.1, nearly all the particle-size data avail-
able for use in estimating fine-particle emissions were obtained by using
the Bahco Micro-Particle  Classifier.  The lower range of applicable particle
diameter for the Bahco instrument is generally quoted as 1-5 p, (Appendix A,
Section 3.1-1).  Since the particle size range of interest to the program
is 0.01-2 |i, it was necessary to select a method of data presentation that
would facilitate extrapolation of the particle-size data.

          Extrapolation would clearly be enhanced by using a presentation
method that resulted in a linear curve.  Consideration of the plus and minus
aspects of the available  graphical methods indicated that the log-normal
distribution was the best method available.  The bat;ic limitations of the
method have not been ignored in its selection, but there does not appear
to be any better method of presentation that will facilitate the extrapola-
tion.  Also, the log-normal distribution was found to be useful in repre-
senting fractional efficiency curves for control devices (see Section 6).

          Although available particle-size data were obtained primarily by
the Bahco method, attempts were made to compare size distributions by vari-
ous measuring techniques  whenever possible.  Particle-size distributions of
particulates emitted from coal-fired power plants have been measured by sev-
eral methods.  Figure 5 illustrates a comparison of size distributions
obtained by Coulter Counter, optical methods (regular and electron micro-
scope), and the Bahco classifier.  The Coulter Counter data represent the
arithmetic mean of 18 individual analyses, while the optical data are the
arithmetic mean of LO individual analyses.  The arithmetic curve for the
Bahco data was obtained from over 300 individual analyses.  Since the stack
sampling techniques used  to obtain the samples for subsequent sizing are
not known in detail, only very general comments will be given on the dif-
ferences in the size distributions.  The differences in the Coulter Counter
and Bahco distributions may be a result of the fact that the Bahco classi-
fier subjects the ash to  much higher attrition than the Coulter Counter, and
probably breaks up most of the agglomerates.  The electron microscope is a
more exact method of sizing particles, especially in the smaller size range.
The increase in percentage of smaller particles shown by the optical data
is explainable in terms of the differences among the different methods.

          Figure 6 illustrates the variation in particle-size distribution
that can result from the  use of different source sampling devices.  Particle-
size data are shown for the effluent from a kraft pulp mill recovery furnace.
The data were obtained by using a stainless steel cascade impactor,f/ cap-
able of in-stack sampling, and a small electrostatic precipitator (optical
sizing).3/  NO specific comments can be made about the difference in size
distributions because only a limited number of samples were taken from two
separate furnaces, and the operating characteristics of the furnaces are
not defined in sufficient detail.

                                    31

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    100.0
                               D  UNCONTROLLED POWER PLANTS,
                                  PULVERIZED UNITS, EXTREMES
                                  OF BAHCO DATA

                               A UNCONTROLLED POWER PLANTS,
                                  PULVERIZED UNITS, ARITHMETIC
                                  MEAN OF BAHCO DATA

                               O COULTER COUNTER, ARITHMETIC
                                  MEAN

                               •  OPTICAL,  ARITHMETIC MEAN
    0.01
      0.01  0.1  0.51
 5  10        50        90 95    99
WEIGHT % LESS THAN STATED SIZE
99.9  99.99
Figure 5 - Particle-Size Distributions of Particulates Emitted from Uncontrolled
                       Power  Plants (pulverized coal-fired boilers)
                                      32

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         Because particle-size data are generally not available in the
0.01-2 |i size range, extrapolation of available data to this size range
was necessary.  Admittedly, justification of such an extrapolation is
tenuous.  However, there is little recourse if some estimation of the
mass of fine particles emitted in various size ranges is to be attempted.
Figure 7 illustrates a typical linear extrapolation of particle-size data
plotted on log probability coordinates.  A limited check of the validity
of the particle size extrapolation procedure is presented in Section 7.1.
                                   34

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 6.  Fractional Efficiency of Control Equipment

          Calculation  of the quantity of fine particulate  emitted from
 controlled  sourcec  requires  information relating  to  the collection effi-
 ciency  of control equipment'  for  each particle size or  ul-/,o range.  Graphs
 depicting this relationship  are  commonly referred to as "fractional effi-
 ciency  curves." During  the  program, available data on  fractional efficiency
 characteristics of  control equipment were collected  and reviewed.  The
 pertinent aspects of this activity  are discussed  in  the following sections.

     6.1  Acquisition  and Review of Data

          Using the library  of articles and reports  collected for the
 Particulate Pollutant  System Study,  all of those  related to control
 equipment were scanned to retrieve  any that contained  information on
 fractional  efficiency.   Special  attention was paid to  those containing
 data for particle sizes  below 5  jj,.

          Our  retrieval  of fractional efficiency  information revealed
 that limited data are  available, and that the reliability  of much which
 are available  is hampered by lack of specifice pertaining  to sampling,
 and analysis techniques  and  operating conditions.  Many of the data
 were determined for pilot sca]e  units, and tests  were  most often con-
 ducted  using specific  test dusts or monodisperse  aerosols.  In many
 cases the published curves were  only identified as "typical" for a cer-
 tain type device with  no other information or references.

          Many of the  available  fractional efficiency  curves are plotted
 on linear coordinate paper and do not have sufficient  detail to be use-
 ful in  the  fine-particle range (0.01-2 p,).  This  was expected since the
 more common sampling and analysis techniques are  not accurate much below
 5 |j,.  Also, until recently there has been limited interest or need to
 give much consideration  to the particles below 5  n as  they relate to
 overall efficiency  of  control equipment.

          Many of the curves published in the literature are those orig-
 inated by Stairmand.^/   The fractional efficiency curves prepared by
 Stairmand refer to particles of  density 2.7 g/cm3 and are, in most cases,
 the result of prolonged  tests on full-size plants.£/  It is assumed that
 sedimentation apparatus  was used to carry out the particle-size analysis ..§/

          The review of  available fractional efficiency curves indicated
that a statement of the  overall efficiency of the device is often not
included on the graph or in the text.  Overall efficiency could not be
reported for those units tested using monodisperse aerosols,  but it could
                                         Preceding page blank

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be reported when other methods were used or where in-plant tests were
conducted.

          In some cases the overall efficiency of the device has been
included with the fractional efficiency curve, but some discrepancies
were noted.  For instance, the overall efficiency was 99.5$, whereas
the fractional efficiency curve never exceeded 95$.  This relationship,
of course, is an impossibility which raises doubt as to the validity
of the information.

          The fractional efficiency data for each type of control de-
vice varied over a wide range since the overall efficiency and design
of these devices vary over a wide range.  However, the shape of the
fractional efficiency curves was similar for each type of device except
for fabric filters.  Peterson and Whitby reported that the fractional
efficiency of a fabric collector goes through a minimum at about 0.3 (j,
with increasing efficiency above and below 0.3 H.2/  Their conclusion
was based on fractional efficiency measurements using monodisperse
aerosols.  However, such results may not be applicable to industrial
fabric filters and reverse-jet filters, and the efficiency of these de-
vices does not depend on particle size.§jL§/

          Recent data taken on a felt bag fabric filter using a cascade
impactor shows minimum efficiency (about 96$) occurring at 0.1-0.2 \i>
but there is no indication of increasing efficiency when the particle
size decreases to 0.1 M>.10/  More experimental data will be necessary
to resolve the fractional-efficiency characteristics of industrial fabric
filters in the fine-particle range.

     6.2  Data Analysis

          Available fractional efficiency data apply to specific indus-
try sources in only a few cases.  Therefore, the data  were separated
on the basis of control devices (i.e., cyclones, electrostatic pre-
cipitators, wet scrubbers, and fabric filters).  The fractional-efficiency
data for each control device category were plotted on log-probability
paper to magnify the efficiency relationship for the smaller particles
and to assess the possibility of extrapolation down to 0.01 M-«  Log
probability coordinates were chosen on the basis that a linear relation-
ship had been previously reported by other investigators.7,11,12/  Ref-
erence 13 indicates that a linear correlation can also be obtained for
certain types of cyclones by using semi-log coordinates.  Notation of
all available information relating to specific type of device, overall
                                  38

-------
efficiency, operating conditions (such as pressure drop or water rate,
etc.), and sampling and analysis techniques vere included on the log
probability plots.

          Figure 8 illusl.rater, data for electrontatic precipitators,
while Figure 9 presents fubric filter fractional efficiency.  Wet ocrubber
characteristics are given in Figures 10 and 11.  Fractional efficiency
characteristics of cyclones are presented in Figures 12 to 16.
                                  39

-------
                        Symbol Identification for Figure .8






D  Stairmand, Dry ESP*/




•  Stairmand, Irrigated ESpl/




W  Well Conditioned Dust, Particle Sizing by Electron Microscope^/




ft  Wet ESP, High Resistivity Dust, Particle Sizing by Electron Microscope^




O  No Information Except 99.9 % Efficient??/




$3  No Information Except 99.9 % Efficient^/




^  Pilot Scale ESP on Coal-Fired Boiler; Gas Velocity 2.62 Ft/Sec




A  "Typical" Curved/
                                       40

-------
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o    o  o  o  o
    % 'ADN3IDUJ3 NOUDTIICD



2     s         a
                                                                                   s »
 8;
 * o.
TS
                                                                                                         CO
                                        % 'NOUV!H3N3d
                                                     41

-------
                       Symbol Identification for Figure 9






O  Stairmand^/




A  35 Shakes, Precoated, Monodisperse Aerosol, 1-4 In. Ap2}/




A  Loaded,  Precoated, Monodisperse Aerosol,  1-4 In. AP^I/




H  No Information Except 99.9 + % Efficient^/




S3  No Information Except 99.9 + % Efficient^




D  24/




^  Data Using Cascade Impactor,Shake Type Collector, Very Low APJ5/




O  Data Using Cascade Impactor, Ultrajet Type Collector, 10-12 In. A P
                                     42

-------
O     O  —      o  o d   o  —'   «i
          % 'ADN3OUJ1 NOIOJ11O3
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     s     a          a               si   &
                                                                                  K       £
                                                             g    O   10     f*  —  O   O O  o
                                           % '

-------
                    Symbol Identification for Figure 10


    Stairmand, Gravity Spray Tower,  Less Than  1 In.

    Stairmand, impingement Scrubber^/

    Stairmand, Orifice ScrubberZ/

^  Stairmand, Venturi Scrubber^/

0  Spray Tower, Soluble Dust (Na^SO^), Optical Counter,  Liquid Flowrates
       Approximately 0.03 Ft3/Mir2§/

D  Venturi Scrubber "Typical"  Curved/

S3  Venturi Scrubber,  H3PO4 Plant Mist, Approximately 30 M
                                   44

-------
                                     % 'A3NiDIJJ3 NOUDJ110D
o    o ~  o*   •n  o  o

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                                                                                                          8'
                                                                                                          3
                                                                                                          t)0
                                        % '
                                                 45

-------
                      Symbol Identification for Figure 1 1


LJ  Data Using Cascade Impactor33/

W  4-6 In. H2O AP, 4 gpm/1,000 cfm3*/

O  4-6 In. H2O Ap, 3.3 gpm/1,000 cfm34/

O  4-6 In. H2O Ap, 3.0 gpm/1,000 cfm34/

t$  Perforated Plate Scrubber, 3 Plates, 2,750 cfm,  Vane Separator, Water Recycled,
        12 In. AP19/

•  Perforated Plate Scrubber, 3 Plates, 2,750 cfm,  Venturi Separator, Water Recycled,
        12 In. A|PK}/

V  Perforated Plate Scrubber, 3 Plates, 2,750 cfm,  Venturi Separator, Fresh Water,
        12 In. APIS/
     Asphalt Plant, Wet Scrubber, Low

d   Venturi Scrubber (1967),  Throat Velocity 17,800 Ft/Min3£/

^   Orifice Scrubber (1967),  6 In. AP36/

O   Wet Centrifugal Scrubber (1967), 3.5 In. AP36/

O   Venturi Scrubber, 30 In.  AP,  H3PO4 Mist3-7/

A   Stairmand, Spray Tower,  1  In. Ap, 18  Gal/1,000 cf4/

£k   Stairmand, Venturi Scrubber, 6 In. Throat, 3,500 cfm Gas4/
                                    46

-------
                                                                  CO

                                                                  fc

                                                                  0)



                                                                 I

                                                                  fc
                                                                  O
                                                                 03


                                                                 -P

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                     J	1	1   I   I	L-JLO	J

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    8          82


'NOUV!U3N3d
                                                     o o

                                             GO    o
        47

-------
                     Symbol Identification for Figure 12






C\  "Typical" Curve, High Efficiency Cyclone^/




A  "Typical" Curve, Multiclone39/




O  High Draft Loss Cyclone, 2.5 In.  AP40/




$J  Medium Draft Loss Cyclone, 0.4 In. AP40/




O  Low Draft Loss Cyclone, 0.2 In. Ap40/




^  Medium Efficiency, 2 In. A Pil/




D  High Efficiency, 3-4 In. AP4-!/




H  "Typical" Curve, 4 In. AP, "High Efficiency - Small Diameter Cyclone"4.?/




0  "Typical" Curve, 2 In. AP, "High Efficiency - Small Diameter Cyclone"42/




V  "Typical" Curve, 1  In. AP, "High Efficiency - Small Diameter Cyclone"4?/
                                   48

-------
% 'XDN3IDUJ3
                                                                   0
                                                                   a
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                                                                          !n
                                                                          O
                                                                          0)
                                                                          •s
 O
 C
 (U
•H
 O
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-------
                      Symbol Identification for Figure  13
Q   Fly Ash, 6 In. Dia., 2.5 In.



O   Fly Ash, 10 In.  Dia., 2.5 In. A




J   Fly Ash, 10 In.  Dia., 2.5 In. A




D   12 In. Dia., 610 cfm, 7 In.




*   5 In. Dia., 65 cfm, 4 In.




•   5 In. Dia., 85 cfm, 4 In.




A   20 In. Dia., 2,500 cfm, 4 In.




S3   Asphalt Pit., Overall Efficiency 94.7%45/




^   "Typical" Cyclone^/




O   "Typical" Scroll Type Mechanical Collectors^




+   "Typical" High Capacity
                                    50

-------
% 'ADN3OHJ3 NOIID3TIOD


 o

A.
                                                                  CO
                                                                  o
                                                                 H


                                                                 g
                                                                  a
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                                                                 W
                                                                  §
                                                                 •H
                                                                 •P
                                                                  O
                                                                 H
                                                                  bO
    % 'NOIiVili3N3d
                51

-------
                      Symbol  Identification for Figure 14






D  "Typical" Cyclone Collector, 3 In. Ap£/




V  Fertilizer Plant, Dry Cyclone, Design Efficiency Curve4§/




O  "Typical" Curved/
                                    52

-------
                               % '
                                             NOUD3TIOD
i  r i  —r~r
                                   i   i   i   i   i    i
                                                                   _i_  I	1 _1_ I  I
                                                                          SI
                                                                          U
     ft     ft
o    o

8    8
o     o   o     o  o  m   r* — <3    o
g     o   
-------
                     Symbol Identification for Figure  15


It   Srairmand, Medium Efficiency High Throughput Cyclone, 4 Ft. Dia.4r

Q   Srairmand, High Efficiency (Long Cone) Cyclone4/

A   Stairmand, Multiple Cyclone^/

O   "Typical" Curve, Medium Efficiency Cyclone^Q/

£   "Typical" Curve, High Efficiency Cyclone^

^   Mesh Impingement Separator^]/

O   Centrifugal Separator:!!/

V   Cement Plant,  12 Unit Multiclone,  4 Ft. Dia. Each,  3.5 In. Ap,
       75,OOOcfmat450°F^

•   "Typical" Efficiency Curve for Tubular Dust Collector^/

O   Fly Ash, 4 In.  Ap54/
                                    54

-------
% 'ADN3OIJJ3
                                                                     3
                                                                     u
                                                                            to

                                                                            1
                                                                           rH
                                                                            O
                                                                            4)
                                                                            •H
                                                                            O
                                                                            •H
                                                                            <«H
                                                                            
-------
                      Symbol Identification for Figure 16






O  "Typical" Efficiency for Multiclone on Rock Dust,  1 In.




^  "Typical" Efficiency for Multiclone on Rock Dust,  2 In.




A  "Typical" Efficiency for Multiclone on Rock Dust,  3 In.




S3  "Typical" Efficiency for Multiclone on Rock Dust,  4 In.




D  "Typical" Efficiency for Multiclone on Rock Dust,  6 In.
                                     56

-------
O     O  ~-(  CM   tf)  O
o     o  Q  o   o  <~
                                                                    8   g        &
                                                                    y    ^     If
     y
     5
     2
                                               -I	1	1	1	L.
                                                                   J	1_
                                                                                 J—L
                                                                                     I	1''
                                                                                     
-------
          The data spread for each type of device varied over a wide range,
but this variation is not surprising when one considers the wide variation
in types and design of devices  (such as pilot unit versus full-scale unit),
testing procedures, operating conditions and analysis techniques.  However,
the data did, in most cases, reflect the expected efficiency characteristics
of specific types of devices.   That is, multiclones showed a higher efficiency
curve than cyclones, and Venturi scrubbers showed a higher efficiency than
low pressure drop scrubbers.

     6.3  Extrapolation of Fractional Efficiency Data for Control Devices

          Examination of the data for cyclones verified the predominance of
a straight-line relationship of efficiency to particle size.  This relation-
ship is especially frequent when the particle size decreases below 10 p,.  A
straight-line relationship also appears to exist for scrubbers and electro-
static precipitators for particle sizes below 3 p,.  There are limited data
regarding fractional efficiency of fabric filters, but part of these data,
including those which were taken using cascade impactors, also indicate a
straight-line relationship for  particle sizes below about 0.5 p..

          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
control device.  The data for each type of control device and the informa-
tion regarding specific types of devices, operating conditions, and testing
procedures were carefully assessed to determine the general fractional effi-
ciency curves for each type of  control device which best represents low,
medium, and high overall efficiencies.  The resulting general fractional
efficiency curves were then extrapolated to the size range of interest to
this program, i.e., 0.01-2^,.   Figure 17 presents the extrapolated general
fractional efficiency curves.   Only one curve has been drawn for fabric fil-
ters, due to limited data, and  it was extrapolated as a straight line from
below about 0.5 p,.  The linear  relationships for electrostatic precipitators
and wet scrubbers should not be considered valid above 3 p,.  These general
fractional efficiency curves for each type of device represent the results
of the evaluation of available  fractional efficiency data, and they will
subsequently be used in calculating the quantity of fine particulates emitted
from controlled industrial sources.
                                    58

-------
99.99
                                                                                  0.01
            I     I    I  I  I l" l"l
                 ,^




      icFiltw
0.01
  0.01
                              PARTICLE DIAMETER - MICRONS
                                                                                  .99
     Figure 17  - Extrapolated Fractional Efficiency of Control  Devices
                                        59

-------
7.  Current Level  of Fine  Particulate Emissions  (1969-1970)

          The procedure  used  to  calculate the current level  (1969-1970) of
fine particulate emissions is similar to that used in calculating total mass
emissions.i/  The  same 1968 production  figures and emission  factors are used.
However, to calculate quantities emitted within  given size ranges, it is
necessary to have  the following  additional information:

          a.  Particle-size distribution for particulates emitted by the
uncontrolled source  (measured or extrapolated).

          b.  Percent application  of control, with a breakdown of this per-
cent application of  control into the percent application  of each type of
control device  (i.e., cyclones,  scrubbers, electrostatic precipitators,
and fabric filters),

          c.  Fractional efficiency characteristics of each  of these control
devices (measured  or extrapolated).

          Since, in  general,  particle-size distributions from uncontrolled
sources and fractional efficiency  curves are not available in the 0.01-.2|j,
range, it was necessary  to extrapolate  available data to this size range
(see Sections 5 and  6).

          An alternate calculation method was employed as a  cross check for
some sources.  For controlled sources,  overall control equipment efficiency
and particle size  distributions  at the  exit of each type of  control device
can be used to calculate fine particle  emissions.  This method does not
require use of control equipment fractional efficiency.  However, as noted
in Section 5.1, particle size distribution data  for controlled sources are
inadequate.  As a  result,  utilization of the alternate procedure was restricted
to those source categories  where sufficient size distribution data for con-
trolled sources were available.

     7.1  Limited  Check  of the Validity of Particle Size and Fractional
            Efficiency Data Extrapolation

          Because  neither  particle size distribution data nor fractional
efficiency curves  for control devices were available in the  0.01-2 p size
range, extrapolation of  available  data to this size range was necessary.
Admittedly, such extrapolation casts doubt on the meaning and validity of
the results of the fine  particle emission calculations.  The only satisfac-
tory way to check  the accuracy of  such extrapolations would be to measure
the requisite data in the  appropriate size range and compare them with the
extrapolated values.  Since no experimental work could be performed in the
current program, other methods of providing a check on the extrapolations
were sought.
                                   61                    ..   ,
                                          Preceding page blank

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           In general, it was difficult to check the validity of the extrapo-
 lation technique because of inadequate sampling of fine particulates emitted
 from both uncontrolled and controlled sources.  However, it was possible to
 perform a limited check on the technique by using data obtained by Bush on
 particle size distributions before and after an electrostatic precipitator
 operating on a pulverized coal-fired power plant.ii/  Three items were used
 in performing the check:

           1.  Particle size distributions from uncontrolled power plants
 with pulverized coal-fired boilers (Banco data, standard sampling methods).

           2.  Data obtained by Bush on particle size distributions before
 and after an electrostatic precipitator operating on a pulverized coal-fired
 unit.  A thermal precipitator was used as the sampling device, and an elec-
 tron microscope was used for particle sizing.i^

           3.  The fractional efficiency curve for a medium efficiency elec-
 trostatic precipitator is shown in Figure 17.

           Figure 18 summarizes the size distribution data for particulates
 emitted from uncontrolled units.   The three curves on the left-hand side of
 Figure  18 are the complete size distributions as determined by Banco methods
 (extreme and arithmetic average).   The curves are the composite of over 300
 individual size distributions for pulverized coal-fired power plants.   The
 solid lines on the left-hand curves connect the actual measured size dis-
 tributions,  while the dashed lines are the linear extrapolation of the data
 down to the submicron range.   Bush's  data are given by the  circles on the
 curve to the extreme  right.   In Bush's sampling arrangement,  the inlet to
 the  thermal precipitator was  arranged so that particles above 5 p, diameter
 did  not enter the precipitator.   For  the purposes of comparison,  the < 5 p,
 data from the Bahco analysis  were  plotted on the same basis as the Bush
 data.   The curve  depicted by  the  solid squares and triangles  illustrates
 the  Bahco data in that form.

           A  comparison between the <  5 p, curve for the Bahco  data,  and
 Bush's  data  shows that the Bahco data are biased toward the large particle
 sizes.   This  is not surprising because of the  inherent limitations  of  the
 Bahco device  and  the  standard sampling techniques  in the <  5 (j,  size  range
 (see  Appendix A).  The thermal precipitator,  on the  other hand, is highly
 efficient in that size range.  It  deposits virtually all particles  of most
 materials from 5 p, down to 0.01 ^.  In addition, Bush used an electron micro-
 scope for the particle sizing.  In view  of the  superior  techniques utilized
by Bush,  the  agreement between the  two sets  of data  is  considered quite
 good.
                                    62

-------
   100.0
    10.0
  u
   a
   u
    0.0
      0.01
5  10          50          90  95



    WEIGHT % LESS THAN STATED SIZE
                                                                   99.9  99.99
Figure  18 - Particle-Size Distributions  of Particulates Emitted from

             Uncontrolled Power Plants  (pulverized coal-fired boilers)
                                      63

-------
         Figure 19  illustrates  a comparison of particle size distributions
of particles emitted from units controlled by electrostatic precipitators.
Three size distributions are shown:

         1.  Outlet size distribution as measured by Bush.ii/

         2.  Outlet distribution calculated from the extrapolated arithmetic
mean of the Bahco inlet data in Figure 18 and the fractional efficiency
curve.

         3.  Outlet distribution calculated from Bush's inlet data in
Figure 18 and the fractional efficiency curve.

         The comparison shows very good agreement, considering the differences
in sampling techniques, particle-sizing methods, and the assumptions involved
in extrapolation procedures.  The correspondence between the particle-size
distribution as measured by Bush and that calculated from the extrapolated
arithmetic mean curve of the Bahco inlet data and the extrapolated frac-
tional-efficiency curve is particularly good.  While this is only a limited
check (i.e., one source and one control device) of the extrapolation
technique, it does  provide some confidence in the use of the method for
other sources.

     7.2  Fine-Particle Emissions from Specific Stationary Sources

         As discussed in Section 7, the method selected for calculating
the mass of fine particles emitted utilizes particle-size distributions
for particulates emitted from uncontrolled sources, percent application of
each type of control device on the source, and fractional efficiency char-
acteristics of each of the control devices.  It was assumed that control
equipment is in operation 100# of the time that a source is operating.
This is, of course, not the case, but data are not available on control
equipment operational efficiency.

         The sequence of steps comprising the calculation is:

         1.  Calculate process emissions using production figures and
emission factors given in Volume I.
                                   64

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^L

o
                                                                                                                 8:
                                                                                                                 8:
                                                                                                                   H
  o
_o

c
                                                                                                                        p.

                                                                                                                        OJ
                                                                                                                        o
          o
         •H
          M  03
         -P  f-!
          o  o
          Q}  -p
         rH  OS
         W  -P
             •H
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          O  -H
          *H  O
         Vi  
H

0)
                                       SNOHDIW - U3i3WVia  riDUHVd
                                                      65

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          2.  Calculate procesa  omission  into  controlled  plant;:  and uncon-
trolled plants based  on overall  percent application of control data reported
in Volume I.

          3.  Extrapolate process  emission particle-size  distribution data
down to 0.01 p. (or to 0.01 wt. %) .  Determine  percentage  of  emissions within
size ranges 1-3 (j,, 0.5-1.0 p,, 0.1-0.5 jj,,  0.05-0.1 ^ and 0.01-0.05 y,.

          4.  Calculate process  emissions into each major type of control
device employed on the source using the data on percent application of con-
trol for each of these devices given in Ref . 1.

          5.  For each type  of control device  refer to appropriate  fractional
efficiency curve (Figure 17) to  determine average fractional efficiency for
each particle-size range.

          6.  Compute emissions  within each particle-size range  for uncon-
trolled plants using  process emissions (Step 2), and particle-size  distri-
bution percentages (Step 3).

          7.  Compute emissions  within each particle-size range  for each
type of control device using process emissions (Step 2),  particle-size dis-
tribution percentages (Step 3),  and average fractional efficiencies (Step 5).

          To calculate the number  of particles emitted in each particle-size
range, the following  two assumptions were made;

          1.  The particles are  all spherical  in shape, and

          2.  The density of the particles is  independent of particle size.

With these assumptions the equation relating mass and  number emissions is
                       (Mass)d1-d2 =     6      N

where

          (Mass),   -,  = mass emitted in particle-size range between
                 1  2     diameter  d-^  and  &Q

                    p = particle density

                d     = particle diameter midpoint between  d-^  and  dg

                    N = number of particles emitted with average diameter
                          ^m.p.
                                    66

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          The  fine particla  emissions  for  stationary  sources for which ade-
 quate information was  available  are presented in Tables 1 and 2, pages 4 to 7 ,
 Summary  comments  on Tables 1 and 2 are given on pages 2  to  9  .  More
 details  of the calculations  for  individual sourcec are presented in the fol-
 lowing sections.  The  source categories are presented in the same sequence
 as the sources are listed in Table 1.

          7.2.1   Stationary  combustion sources;

           7.2.1.1 Electric  utilities--coal-fired  boilers;   Fine-particle
 emissions from electric utility coal-fired boilers are summarized in  Table
 8.  Total emission of particulates < 2 p, is estimated to be  971,500 tons/
 year, which is about  31$ of  the total mass emissions  for these  boilers as
 reported in Table 4.1-1, Volume I.   Fine-particle  emissions  for pulverized
 coal-fired boilers are presented in  more  detail  in Tables E-74  to E-79,
 pages 303 to 308 . Emmissions for stoker  coal-fired boilers  are shown in
 Tables E-80 to E-84,  pages  309  to 313 , while  those for cyclone coal-fired
 boilers  are summarized in Tables E-85 to  E-89, pages  314 to 318.

               Particle-size distributions  for the various uncontrolled
 boilers  are  presented  in Figures 20, 21, and 22.  The data for pulverized
 coal-fired boilers in  Figure 20  represent  size distributions from more than
 300 individual boilers.  Figure  21 represents data from seven cyclone coal-
 fired boilers, while Figure  22 summarizes  particle-size distributions
 obtained from  nine stoker coal-fired boilers.  Percent application of con-
 trol and the percent controlled  by different control  devices was obtained
 from Section 5.1, Volume I.

               7.2.1.2   Electric utilities—oil and gas-fired boilers;
Accurate  size  data were  not  available  for the particulates emitted from oil
 and gas-fired  boilers, either for electric  utility or industrial units.  The
meager data  available indicated  that emitted particulates were generally
 90 wt. %  less  than 2 y,.  Available information also indicates that these
units are nearly all uncontrolled.  Tables E-105 and  E-106 present details
 of an estimate of the fine-particle emissions from both electric utility
and industrial units.   Emissions are estimated to be  about 224,000 tons/year.

               7.2.1.3   Industrial power plants—coal-fired boilers;  Details
 of the calculations of fine-particle emissions from pulverized coal-fired
industrial power plants  are  summarized in Tables  E-90 to E-94, pages 319 to 323,
for stoker coal-fired boilers in Tables E-95 to E-99,  pages  324 to 328, and
for cyclone coal-fired boilers in Tables E-100 to E-104, pages  329 to 333.
Emissions of fine particulate are estimated to be 106,000 tons/year,  which
represents about 4$ of the total mass emissions for these boilers  as reported
in Table 4.1-1, Volume I.
                                    67

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                                                TAH1J5  'i

              SUMMARY OF FINE-PARTICLE EMISSIONS  FROM STATIONARY  FUEL C'MBUCTION SOURCES

Source
A. Mass Basis
Stationary Fuel Combustion
A. Coal
1. Electric Utility
a. Pulverized
b . Stoker
c . Cyclone
2. Industrial
a. Pulverized
b. Stoker
c . Cyclone

1-3




591,600
21,700
48,200

15,100
56,600
13,500
Fine
0.5-1.0




178,600
5,700
13,900

500
7,300
6,700
Particle Size Range:; (^L)
0.1-0.5 0.05-0.1
Tons/Year



99,200 2,900
2,200
7,300 200

—
2,100
4,100 100

0.01-0.05 Total




372, •'OO
29,600
69,600

15,600
66,000
24,400
     B.  Fuel Oil
         1.  Electric Utility
               and Industrial

     C.  Natural Gas and LPG
         1.  Electric Utility
               and Industrial

                     Total
126,900
              212,700
114,900
3,200
                                        126,900
                                                                      97,200
1,301,600
B.  Number Basis

     A.  Coal
         1.  Electric Utility
             a.  Pulverized
             b.  Stoker
             c.  Cyclone

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

     B.  ?uel Oil
         1.  Electric Utility
               and Industrial

     C.  Natural Gas
         1.  Electric Utility
               and Industrial

                     Total
                         Particles/Year
5.1 x 102S    29.5 x 1022   250 x 1Q22   480 X 1022
0.2 x 1022    0.9 x 1022    5.6 x 1022
0.42 x 1022   2.3 x 1022    18.5 x 1022  83 x 1022
0.3 x 1022    0.08 x 1022
0.5 x 1022    1.2 x 1022    5.6 x 1022
0.12 x 1022   1.1 x 1022    10.4 x 1022  42 x 1022
1.1 x 1022
0.85 x 1022
8.6 x 1022    35.1 x 1022   290.1 X 1022 605 x 1022
                                      765 x 1022
                                      6.7 x 1022
                                      104 x 1022
                                      0.38 x 1022
                                      7.3 x 1022
                                      53.6 x 1022
                                      1.1 x 1022
                                      0.85 x 1022

                                      939 x 1022
                                                          68

-------
         100.0
          0.01
           0.01
0.1   0.5 1
                               5   10          SO           90  95

                                    WEIGHT % tfSS THAN STATED SIZE
                                                                          99.9   99.99
Figure  20 - Particle-Size  Distributions of Particiilates  Emitted  from. Uncontrolled
                          Power Plants  (pulverized coal-fired boilers)
                                             69

-------
      100.00
      10.00 -
       1.00 -
    •a
    u

    fc
       0.10
       0.01
                                                              A Cyclop* find Electric Utility Boile




                                                                Arithmetic M«on
         0.01    0.1    0.5  1
                               5   10            »            90  95



                                    WEIGHT % LESS THAN STATED SIZE
99.9   99.99
Figure 21  - Particle-Size Distributions of  Particulates  Emitted from Uncontrolled


                             Power Plants  (cyclone coal-fired boilers)


                                               70

-------
        10.00
     5
     6
     S   1.00
     o
     3
     y
         0.10
         0.01
                         ,	,
                                                                1	r
          0.01    0.1   0.5 1
                                                i
                                                            A Stoker Fired Electric Utility Boiler
                                                               Cyclone Inlet
                                                            O Arithmetic Meon
                                5   10            50           90   95
                                      WEIGHT % LESS THAN STATED SIZE
                                                                      99     99.9   99.99
Figure 22 -  Particle-Size Distribution of  Particulates Emitted, from Uncontrolled
                              Power Plants  (stoker coal-fired boilers)
                                            71

-------
               Available particle-size distribution data are presented in
Figure 23.i^/  The particle-size measuring method used to obtain the size
distributions is not known.  The percent application of control and the per-
cent controlled by different control devices was obtained from Section 5.1.2,
Volume I.

               7.2.1.4  Industrial power plants—oil- and gas-fired boilers:
Fine-particle emissions from these boilers were combined with those of elec-
tric utility oil- and gas-fired boilers.

               7.2.1,5  Commercial and residential furnaces;  Data are not
available on the particle-size distribution of emissions from these sources
and no estimate of fine-particle emissions was made for these sources.

          7.2.2  Crushed stone operations;  Meager particle-size data are
available for crushed stone operations.  The limited particle-size data for
crushing and conveying are shown in Figure 24.  The arithmetic mean of these
data indicates that 15 wt. % is < 2 p,.  If this percentage is assumed appli-
cable to all crushed stone operations, the fine-particle emissions may be
grossly estimated as follows:
            (681,000,000 tons/year)(!7 lb/ton)(l ton/2,000 Ib.)

            = 5,788,000 tons/year (uncontrolled emissions)


If 15# is < 2 n, then


               fine-particle emissions = (5.788 x 106)(0.15)

                                       = 868,000 tons/year (< 2
          Although some plants do employ control equipment, it is believed
that the net control is low (20$), and disregarding control equipment utili-
zation is not deemed serious in view of the gross estimate of particle size.

          The number of particles emitted that are < 2 y, in diameter is
estimated to be 19 x 1022 particles/year.

          7.2.3  Iron and steel plants;  The major sources of particulate
air pollution in iron and steel plants are:  sintering machines, coke-oven
plants, blast-furnace operations, steel-making furnaces, and materials
handling operations.  Fine-particle emissions were estimated only for

                                    72

-------
  inn.on
   in.no -
|
o
a
    I.op
   0.01
                                                          Traveling Grate


                                                        O Spreader Stoker


                                                        A Underfeed Srokei


                                                          Pulverized Coal


                                                        O Cyclone Furnace
     0.01
           O.I    0.5 1
                              10            50           90

                               WEIGHT % l£SS THAN STATED SIZE
99
       99.9   99.99
Figure  23 -  Particle-Size  Distributions  of  Particulates Emitted from
                    Uncontrolled  Industrial  Power Plants  (coal-fired)
                                    73

-------
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-------
sintering machines and steel-making furnaces because of lack of particle-
size distribution data for the other sources.  Table 9 summarizes the
estimates that were made for this industry.  The emission calculations for
sinter machines and steelnmaking furnaces are reviewed in the following
sections.

               7.2.3.1  Sinter machines:  Details of the calculation of
fine-particle emissions from sinter machines are presented in Tables E-40
to E-43, pages 269to272.  The 5,600 tons/year listed in Table 9 is about
5% of the total mass emissions for these machines (Table 4.1-1, Volume l).

               Particle-size distributions for uncontrolled and controlled
sinter machines are illustrated in Figure 25.  Information on percentage
application of control was obtained from the telephone survey reported in
Section 5.4, Volume I.

               Fine-particle emissions from sinter machines controlled by
cyclones were calculated using particle-size distributions from both uncon-
trolled and controlled units.  Utilizing particle-size distributions from
uncontrolled sinter machines and the high efficiency cyclone curve in
Figure 17, emissions were estimated to be 5,100 tons/year.  This compares
with 9,200 tons/year obtained using particle-size distributions from con-
trolled units, and the assumption that cyclones used on the sinter machines
have an overall efficiency of
               7.2.3.2  Open hearth furnaces;  Estimates of the fine-particle
emissions from open hearth furnaces proved to be difficult because data on
particle-size distributions from uncontrolled or controlled furnaces are
almost nonexistent.  Furthermore, there are inconsistencies in the available
information.  Another complication is that the mass rate of emissions, and
the particle size of the emitted material changes during the furnace cycle.

               Figure 26 illustrates both of these aspects of available
particle-size data.  The two curves in the upper left represent data from
a furnace utilizing an oxygen lance.i§/  The sampling method and particle
sizing method are not known.  The data in the lower right of Figure 26 were
obtained by using two sampling trains:

               1.  Glass cloth thimble ahead of a Whatman paper thimble, and

               2.  A thermal precipitator.

Particle sizing was accomplished by optical techniques.   The samples were
collected between charging periods and early in the melting period.
                                    75

-------
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                77

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       100
       10
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      0.1
                                                                       I      I
                                                 COMPOSITE FOR HEAT
                                                         ,O
                                                       . UME (OIL
                                              a
                                        \SAMPUNG AND SIZING
                                        J METHODS UNKNOWN
                                            SAMPUNG METHOD
                                            ABSOLUTE FILTER AND THERMAL PRECIPITATOR


                                            SIZING
                                            OPTICAL (VISUAL AND ELECTRON MICROSCOPE)

                                          A EXTREMES
                                          O ARITHMETIC MEAN
      O.OlL__L
I    II    III
                          J	I
                                      I
       0.01    O.I   0.5  1      5   10            SO            90   95

                                     WT. % LESS THAN STATED SIZE
                                             99      99.9    99.99
Figure 26  - Particle-Size Distribution of Particulates  Emitted  from
                            Uncontrolled  Open  Hearth  Furnaces
                                           78

-------
               Fine particle emissions  for open hearth furnaces were calcu-
lated using both sets of data in Figure 26.  Tables E-36 to E-39, pages 265
to 268 , summarize the calculations.  Emissions are estimated to be 375,900
tons/year, using the particle size data in the lower right of Figure 26.
This quantity exceeds the 337,000 tons/year reported as the total mass
emissions from these furnaces (Table 4.1-1, Volume I).

               If the"composite" particle-size distribution (upper left) in
Figure 26 is used for the calculations, the emissions are estimated to be
108,200 tons/year.

               The discrepancy in the emission figures.indicates that:

               1.  The particle-size distributions are erroneous, or

               2.  The overall efficiency of the electrostatic precipitators
and/or the degree of application of control reported in Section 5.4, Volume I,
is too high.

               Additional field testing of open-hearth furnaces and asso-
ciated control equipment will be necessary to pinpoint the exact cause of
the above inconsistency.

               7.2.3.3  Basic oxygen furnaces;  Calculations of fine-particle
emissions from basic oxygen furnaces were also hampered by a discrepancy in
the reported particle-size distributions for basic oxygen furnace dust.
Reports have been made of 95$ < 1 (j, as well as 99$ < 0.2 p,.  Available par-
ticle size data are presented in Figure 27.  The curve with the triangle
symbols was used for the emission calculations.

               Tables E-26 to E-29, pages 255  to  258, summarize the calcula-
tion of emissions.  Emissions are estimated to exceed 174,000 tons/year.
This quantity is nearly 20 times as high as that reported for total mass
emissions from basic oxygen furnaces in Table 4.1-1, Volume I.  This discrep-
ancy results primarily from the calculation of fine-particle emissions from
EOF units controlled with Venturi scrubbers (Table E-29, page 258).

               The emissions from EOF units that are controlled with Venturi
scrubbers were computed using the particle-size distribution for uncontrolled
furnaces (Figure 27), and the fractional efficiency curve for a Venturi
scrubber (Figure 17).  Since all available information indicates that the
particulate emitted from these furnaces is nearly all  micron or submicron
in size, the large difference in the computed emissions appears to result
from the fractional efficiency values for the Venturi scrubber given in
Figure 17.  The fractional efficiency curve for a Venturi scrubber indicates
a collection efficiency of 92$ for 1-p, particles, 88$ for 0.5-p, particles,

                                    79

-------
    100,
    10
a

u
   0.1
   0.01
         I I I
                                                     O EXTREMES
                                                     A ARITHMETIC MEAN
                         II   I   I  I  I  I  I  I    II    II    II
    0.01    0.1   0.5
                         5  10           50           90   95     9V     99.»   99.99

                              WEIGHT % LESS THAN STATED SIZE
Figure  27 - Particle-Size Distribution  of Particulates Emitted from
                         Uncontrolled Basic Oxygen Furnaces
                                       80

-------
and 22% for 0.1-p, particles,  Tho particle--.".Jz'- distribution for ba.^Jc
oxygen furnace dust (Figure 27) shows 94$ < 1 p and 58$ < 0.5 (j,.  Comparing
this particle-size distribution with the respective Venturi scrubber
efficiencies indicates that the overall efficiency for a Venturi scrubber
would be less than 88$ on a typical basic oxygen furnace.  This value of
overall efficiency for a Venturi scrubber on EOF emissions seems quite low,
particularly in view of field tests on Venturi scrubbers operating on
EOF units that indicate 96-99$ overall efficiency.0§j£L/

          Difficulties in sampling the outlet of Venturi scrubbers on
basic oxygen furnaces may have led to erroneous conclusions regarding the
overall efficiency.  The exact sampling procedures used in the field tests
were not defined.  As discussed in Appendix A, standard sampling techniques
are not adequate for sampling submicron particulates.  If standard sampling
trains were employed, it is possible that a significant portion of the par-
ticulate leaving the scrubber was not collected.  Failure to collect part
of the material leaving the scrubber would result in the calculation of
a higher than actual efficiency for the control device.

          An effort was made to check the fractional efficiency curve for
the Venturi scrubber by calculating theoretical particle penetration from
information given in Reference 19.  Assuming a liquid-to-gas ratio of
8 gal/mcf and a pressure drop of at least 40 in. HgO, theoretical efficiencies
of about 90$ for 0.5-|o, particles, and 95$ for 1 p. particles we re determined.
These theoretical collection efficiencies compare quite well with the values,
indicated by the fractional efficiency curve of Figure 17.  Different as-
sumptions of pressure drop and liquid/gas ratio would, of course, alter
the theoretical efficiencies.

          Comparison of the fractional efficiency curve in Figure 17 with
the theoretical and measured overall efficiencies does not resolve the
large difference in the calculated emissions.  This raises the possibility
that the particle-size distributions for basic oxygen furnace dust are
not correct.  Meager data are available on the particle-size of EOF dust.
Only two particle-size distributions were found during the program (Figure 27),
Therefore, it is possible that the data shown in Figure 27 are not repre-
sentative of EOF dust.  However, telephone contacts with knowledgeable
people in the iron and steel industry, indicated that primary EOF dust
(i.e., unagglomerated) is predominantly submicron in size.58»59/
                                    81

-------
           It  is also possible  that the particle size which a control device
 "sees"  is  not the  same  as  that reported  in Figure 27.  As noted in the pre-
 ceding paragraph,  the data in  Figure 27  are assumed to represent primary
 particulates.  BOF dust is mainly red iron oxide which has a high tendency
 to agglomerate.  If the dust is transported through a hooding and ducting
 system before it enters a  control device, considerable agglomeration may
 occur.   In this event,  the particles would be larger than shown in Figure
 27, and the efficiency ,of  a control device would be correspondingly higher.
 Also the fractional efficiency curve for a Venturi scrubber shown in Figure
 17 was not obtained for a  scrubber collecting basic oxygen furnace dust,
 but rather for a dust that had low agglomeration tendencies.  In passage
 through a  scrubber*BOF  dust may agglomerate more than a dust of lower agglom-
 eration  tendency.  Therefore,  the scrubber might exhibit a high efficiency
 because  of the agglomeration characteristics of BOF dust.

           All of the above factors probably contribute to the differences
 between  the calculated  total and fine-particle mass emissions.  This case
 clearly indicates  the many pitfalls involved in calculating fine-particle
 emissions  from generalized fractional efficiency curves, extrapolated par-
 ticle size data, and inadequate information on particulate sampling proce-
 dures.   Resolution of the  difference can be accomplished only by careful
 field testing of Venturi scrubbers on basic oxygen furnaces.

               7.2.3.4   Electric arc furnaces;  Limited particle-size data
 are available for  the electric arc furnaces.  As was the case with the other
 steel^maklng  furnaces,  there is also considerable spread between individual
 particle-size distributions.  Figure 28 presents the available particle-
 size data.  The arithmetic mean curve was used for the calculation of emis-
 sions which are summarized in Tables E-30 to E-35, pages 259 to 264.   Fine-
 particle emissions are  estimated at 14,300  tons/year, which is nearly 80$
 of the total mass  emission (18,000 tons/year) reported in Table 4.1-1,
 Volume I.

           7.2.4  Forest products industry:  The forest products industry
 encompasses forestry, sawmill, plywood, particleboard, hardboard, and pulp
 mill operations.  Only in  the kraft pulp mill operations were sufficient
 particle-size and application-of-control data available to permit an esti-
 mate of  the fine-particle  emissions.  Fine-particle emissions from kraft
pulp mills are given in  Table 10.  Individual sources in the kraft pulp
mills are  discussed in the  following sections.
                                     82

-------
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                                                      A EXTREMES

                                                      O ARITHMETIC M£AN
                                 I   I  I  I   I  I   I	|    |   I   I     I
                0.5
                         5  10           50           90  95



                              WEIGHT % LESS THAN STATED SIZE
                                                             99
99.9   99.99
  Figure 28  - Particle-Size  Distribution of  Particulates Emitted from

                         Uncontrolled  Electric  Arc Furnaces
                                         83

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               7.2.4.1  Bark boilers:  Many of the pulp mills utilize wood
wastes as feed to the boiler plants.  Reported particle-size distributions
for particulate effluents from five separate uncontrolled bark boilers are
presented in Figure 29.  Tables E-50 to E-53, pages  279  to  282,  summarize
fine-particle emission calculations for the bark boilers.  Emissions are
estimated at 67,800 tons/year, or nearly 83$ of the total mass emissions
(82,000 tons/year) reported in Table 4.1-1, Volume I.  Since cyclones are the
main control device used on these boilers, emissions from controlled units
would be mostly in the smaller particle-size ranges which is in general
agreement with the estimate.

               7.2.4.2  Recovery furnaces;  The recovery furnace is the
major source of particulate emissions in kraft pulp mills.  Because of the
extreme fineness, hygroscopic nature, and impaction characteristics of
recovery furnace dust, it is difficult to collect a sample for size analy-
sis.  Available particle-size distribution data are presented in Figure 30.
A small electrostatic precipitatorf-P/ and a cascade impactor^/ were used
for sampling.  Particle sizing was performed with an electron microscope.

               Most kraft pulp mills now use electrostatic precipitators to
control emissions from recovery furnaces.  In some cases, it has been noted
that the particle collection efficiency of the electrostatic precipitator
decreases for particles above 1.5-2.0 g, in diameter.  Figure 31 illustrates
collection efficiency as a function of particle size for a precipitator
exhibiting such a decrease in efficiency with increasing particle size.-/
One reason for this occurrence is that electrostatic forces can coagulate
small particles into large agglomerates.  The giant particles can be re-
introduced into the gas stream, and may or may not be recollected by down-
stream collection electrodes.  This phenomenon of particle growth and sub-
sequent reentrainment in the gas flow is dependent upon the physical char-
acter of the particulates.  The physical characteristics of particulate
emissions appear to be strongly dependent upon the flue gas temperature.
In some furnaces, the dust is light and easily handled and transported in
flue systems, while in other furnaces the dust is a sticky or heavy material
which tends to build up in flue systems.

               The extent to which the phenomenon depicted in Figure 31
occurs in recovery furnaces is not known and it was assumed negligible in
the calculations of fine-particle emissions from these furnaces.
                                     85

-------
    100
     10
    0.1
   0.01
             I  I   I  I   I
I     I   I  I  I   I  I   I     I
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                                           O   A
                                                      A EXTREMES
                                                      O ARITHMETIC MEAN
           I  I  I   1  I   I    I    I    II
               III
   I	II
     0.01     0.1    0.5 1
                           5  10            SO           90   95

                                 WEIGHT % LESS THAN STATED SIZE
                                    99
                                           99.9  99.99
Figure 29 -  Particle-Size Distribution for  Particulates Emitted from
                 Uncontrolled  Pulp Mill Bark  Boilers .(Banco data)
                                      86

-------
8
I
5
3
u
                                                O CASCADE IMPACTOR
                                                   ELECTRICAL PRECIPITATOR
                                                    SAMPLING, OPTICAL SIZING
                                                   ARITHMETIC MEAN
   O.QII	I  I  I   I   I   I    I   I
     0.01   O.I   0.5    1    5   10           50           90  95      99     99.9   99.99

                                WEIGHT % LESS THAN STATED SIZE


    Figure 30 - Particle-Size Distribution  for  Particulates  Emitted from
                          Uncontrolled Pulp Mill Recovery Furnaces
                                         87

-------
     100
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      92
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      84
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I   I  1  I  I
                                       1    I   I   I  I   TTJ
               A OVERALL MASS

                 EFFICIENCY
           I   111!
                     I
I     I    I   I   I  I  I  I
       0.5
                    2               5


               PARTICLE DIAMETER, MICRON
                    10
20
Figure 31 - Fractional Efficiency of an Electrostatic Freeipitator Operating

                         on a Kraft Mill Recovery Furnace£/
                                  88

-------
                Tables E-54 to  E-57  summarize the estimates  of emissions from
recovery furnaces.  As  shown in Table E-57, using the  fractional efficiency
curve  (Figure 17) for a medium efficiency electrostatic precipitator results
in fine-particle emissions (234,500 tons/year) which exceed the total mass
emissions  (164,000 tons/year)  listed in Table 4.1-1, Volume I.  Using the
fractional efficiency for  a high efficiency electrostatic precipitator
(Figure 17), emissions  of  32,400 tons/year of fine particulate are calculated.

               Available information on the performance characteristics of
electrostatic precipitators  on recovery furnaces indicates  that overall
efficiency probably does not exceed 95-97$ (i.e., medium efficiency).  This
fact tends to support the  use  of the fractional efficiency  curve for a
medium efficiency precipitator to calculate fine-particle emissions.

                Because  of  the  variable character of the emitted particulate
and observed decrease in equipment  efficiency with increasing size, the dis-
crepancy in emission figures cannot be resolved at this time.  Additional
field testing of electrostatic precipitators on recovery furnaces will be
necessary.

                7.2.4.3  Lime kilns;  Data on particle-size  distributions
from either uncontrolled or  controlled pulp mill lime  kilns are nearly non-
existent.  Figure 32 illustrates  the only particle-size distribution that
was found  during the study.iZ/  The sampling technique used to obtain the
material for subsequent particle  sizing was not mentioned in Ref. 17.  Micro-
scopic techniques were  used  for the determination of the size distribution.
Since an adequate number of  particle-size distributions were not available,
only a gross estimate of fine-particle emissions from  lime  kilns in pulp
mills was  made.

               Tables E-58 to  E-61,  pages 287 to 290, summarize the calcula-
tion of fine-particle emissions  for the lime kilns.  Fine-particle emissions
total only 1,800 tons/year,  which is about 5.5$ of the total mass emissions
reported in Table 4.1-1, Volume  I.

           7.2.5  Cement plants:  In the cement plant source category, calcu-
lations of fine-particle emissions  could be performed  only  for the rotary
kilns.  Calculations of emissions from dryers, grinders, and other miscel-
laneous sources could not be done with any reliability because of lack of
information on emission factors, particle-size distributions,  and applica-
tion of control.

          Table  11 summarizes fine-particle emissions for rotary cement
kilns.  Production and emission factor data were taken from Section 4.6,
Volume I.  The  overall  percent of application of control and the percent
controlled by different control devices was obtained from a telephone
survey as  reported in Volume I.

                                     89

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      0.01    0.1    0.5  1
                  5   10             50             90   95



                         WEIGHT % LESS THAN STATED SIZE
                                                                     T—T
I  I
                            99
                   99.9    99.99
           Figure  32 - Particle-Size Distribution of Particulates  Emitted from

                                   Uncontrolled Pulp Mill Lime Kilns
                                            90

-------
                                TABLE  11

      SUMMARY OF FINE-PARTICLE EMISSIONS FRCM ROTARY  CEMENT KILNS


                   	Particle Size Ranges  (p,)	
                   1-5        0.5-1.0      0.1-0.5  0.05-0.1   0.01-0.05  Total

A.  Mass Basis     ___	Tons/Year	

                130,800     32,700       13,500                  '        177,000

B.  Humber        	Particles/Year	| ^

                9.7 X 1021  46.4 x 1021  3 X 1023                       3.5 x Id2*'
          In making these estimates the arithmetic mean  (extrapolated to
the lower particle sizes) of the particle-size distribution data for uncon-
trolled sources (Figure 33) was used.  The data in Figure 33 represent the
composite of size distributions obtained from 42 individual kilns.  Figure
34 presents particle-size data for particulates emitted  from controlled
kilns.  Details of the calculation of the fine particle  emissions are given
in Tables E-ll to E-17, pages 240 to 246.

          7.2.6  Hot-mix asphalt paving plants;  Asphalt is a raw material
for several industries.  Two of the more important with  regard to air pol-
lution are hot-mix asphalt paving plants and asphalt-roofing manufacturing
facilities.  Particle-size distribution and degree of application of con-
trol information were not available for the asphalt-roofing manufacturing
operations.  As a result, fine-particle emissions were determined only for
the hot-mix asphalt paving plants.

          The major source of dust in hot-mix asphalt paving plants is. the
rotary dryer.  However, while dust from the rotary dryer is the greatest
source, dust emitted from the vibrating screens, bucket elevator, storage
bins, and weight hopper is also significant.  In some plants, the dryer dust
problem is handled separately from the other sources.  However, the trend
is to combine both dryer and vent line sources (fugitive sources) together
with a single collector fan system.

          Fine-particle emissions were estimated for both the rotary dryer
and the vent line sources as shown in Table 12.  Calculations are summarized
in Tables E-l to E-10, pages 230 to 239.  Emissions are estimated at 170,500
tons/year.  This represents 85% of the total mass emission reported in

                                    91

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                                                            A Uncontrolled Cmwrt Kilm

                                                              Extremes of Bohco Dote



                                                            Q Geometric Meen



                                                            O Arithmetic Mean
     0.01     O.I   0.5  1
5   10             50             90  95



    WEIGHT % LESS THAN STATED SIZE
                                                                       99
                                                                               99.9   99.99
  Figure 33 -  Particle-Size  Distributions  of  Particulates Emitted from

                               Uncontrolled Cement Kilns
                                         92

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Table 4.1-1, Volume I.  Particle-size distributions for uncontrolled rotary
dryers and vent lines are presented  in Figures 35 and 36.  The particle-size
data in Figure 35 were  obtained from 20 individual dryers, while  those  in
Figure 36 were obtained from  only two different vent lines.

          7.2.7  Ferroalloy plants;  The production of ferroalloys has  many
dust or fume producing  steps.  Materials handling, crushing  and grinding
operations generate coarse dust, while the pyrometallurgical steps release
metallic fumes.  Particle-size data  were available only for  the pyrometallur-
gical operations, and as a consequence, fine-particle emissions were esti-
mated only for these operations.

          Figure 37 presents  available data on the particle-size  distribu-
tions of fume emitted from uncontrolled ferroalloy electric  furnaces.   The
data in Figure 37 were  obtained for  a furnace producing FeSi (50$), and. are
assumed to be representative  for all ferroalloys produced in electric fur-
naces.  Particle-size distributions  from electric furnaces producing a  vari-
ety of ferroalloy materials range from 0.05-1.0 p (Table 17-4, Ref. 18),
and, on this basis, the above assumption is justified.

          Table 13 presents the estimates of emissions from  ferroalloy  pro-
duction.  Tables E-18 to E-21, pages 247 to 250, summarize calculations  of
fine-particle emissions from  ferroalloy electric furnaces.   Emissions are
estimated to be 152,300 tons/year, which is approximately equal to the
150,000 tons/year reported for total mass emissions from these furnaces in
Table 4.1-1, Volume I.

          Emissions from ferroalloy  blast furnaces were assumed to be negli-
gible except for fugitive sources.   About 80$ of the dust from ferroalloy
blast furnaces is < 1 y,.i§/   If the  total mass emissions of  1,000 tons/year
listed in Table 4.1-1,  Volume I, are assumed to be from fugitive  sources, then
about 800 tons/year of  fine particulate are jemitted from the blast furnace.

          7.2.8  Lime plants;  The major particulate emission source in
lime plants is the rotary calcining  kiln.  Secondary sources include mate-
rials handling, crushing, and screening operations.  Table 14 summarizes
fine-particle emissions from  lime plants.  Individual sources are discussed
in the following sections.

               7.2.8.1  Rotary kilns:  Calculations of the estimates of
fine-particle emissions from rotary  kilns are presented in Tables E-62 to
E-67, pages 291 to 296.  Emissions are estimated to be 87,800 tons/year,
which is about 30$ of the total mass emission reported for this source in
Table 4.1-1, Volume I.
                                    95

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    100
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                                                            I    I
                                                     O ARITHMniC MEAN
                                                     O GEOMETRIC MEAN
                                                     A EXTREMES
              I  I  I
                              J	I
                                                                II     II
     0.01    0.01   0.5 1
                           5   10            50            90  95
                                WEIGHT % LESS THAN STATED SIZE
                                                                         99.9   99.99
      Figure  35 - Pazfticle-Size Distribution of Particulates Bnitted from
                   Uncontrolled Hot-Mix Asphalt Plant  Dryers  (Banco data)
                                          96

-------
     100
u
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                                                    I   I    r
                                                     A  EXTREMES
                                                     O  ARITHMETIC MEAN
            III   II   I
I     I   I   I  I   I   I   I
                                                                I	I
      0.01    0.1   0.5  1       5   10            50             90  95

                                   WEIGHT % LESS THAN STATED SIZE
                                      99
                                             99.9   99.99
         Figure 36 - Particle-Size Distribution  of Particulates Emitted from
                           Uncontrolled Hot-Mix Asphalt Plant Vent  lines
                                          (Banco data)
                                            97

-------
    100
    10
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   0.01
                                              I   I
                                            THREE REPORTED SIZE DISTRIBUTIONS
                                            fOR FERROALLOY-ELECTRIC FURNACE
                                I  I  I  I   I  J
                                                    II   II
    0 01
           O.I   0.5
5  10           SO           90  95

    WEIGHT % LESS THAN STATED SIZE
                                                             99
                                                                    99.9   99.99
   Figure 37 -  Particle-Size  Distributions  of Particulates Emitted from
                       Uncontrolled Ferroalloy Electric FurnacesSQ/
                                   (optical technique)
                                       98

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               Particle-size distribution data  for  uncontrolled kilns  are
shown in Figure 30.  The data  in Figure 38 were obtained  from 19  individual
kilns.  Information on percentage application of control  was  obtained  from
the telephone survey reported  in Section 5.7, Volume  I.

               The fine-particle emissions for  rotary kilns controlled by
cyclones and wet scrubbers were  also determined by  using  particle-size dis-
tributions obtained from controlled rotary kilns (Figure  39).  In Figure 39
the cyclone curve is the arithmetic average of  13 individual  size analyses
on different units, while the  rotoclone, wet scrubber, and bypass stack
curves represent only a single particle size analysis for each device.  The
cyclone outlet size distribution curve shows that 58  wt.  % is  < 3 p,  .
Assuming an overall efficiency of 70% for cyclones  on rotary  lime kilns,
fine-particle emissions are estimated at
           (261,OCX) tons/year)(l-0.70)(0.58) = 45,400 tons/year
< 3 y,.  This compares with 32,300 tons/year calculated from data in Figure
38 and the fractional efficiency curve for a medium-efficiency cyclone.

               The wet scrubber outlet size distribution shows 67$ < 3 p,.
Assuming an overall efficiency of 90$ for scrubbers on rotary lime kilns,
fine-particle emissions are estimated at
           (449,000 tons/year)(1-0.90)(0.67) = 30,100 tons/year
< 3 ii.  This compares with 25,900 tons/year calculated from data in Figure
38 and the fractional efficiency curve for a medium-efficiency wet scrubber.

               Particle-size distribution data were not available for ver-
tical lime kilns, and no estimate of fine-particle emissions was made for
these units.  However, total emissions from these kilns are only 4,000
tons/year (Table 4.1-1, Volume l), and exclusion of fine-particle emissions
from these kilns is justified.

               7.2.8.2 . Crushing and screening;  Gross estimates were made
of the fine-particle emissions from the crushing and screening operations
in lime plants by utilizing the particle-size data shown in Figures 40, 41
and 42.  The size distributions for the screenhouse, hammermill and raymond
mill indicate 46 wt. $, 30 wt. %, and 36 wt. $ < 3 p,.  The average is 37
wt. % < 3 y,.  Total process emissions for the crushing and screening
                                    101

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operations are 336-,000  tons/year  (Table 4.8-1, Volume  I).   If the net
control is 20$, the  emissions < 3  p, are estimated to be
            (.v>36,000 tons/year)(1-0.20)(0.37) •= 99,000 tons/year
However, this number may be erroneous because the limited information on
control procedures for these  sources obtained during the survey of the lime
industry indicated that many  of these sources are controlled with fabric
filters.  Therefore, net control of these sources may be closer to 80$ and
the fine-partiele emissions about 25,000 tons/year.

          7.2.9  Secondary nonferrous metallurgy;  Particle-size distribu-
tions from either uncontrolled or controlled sources are meager for all pro-
cesses in secondary nonferrous metallurgy.  Information on degree of appli-
cation of control js also meager for all sources.  Available particle-size
data for all the specific sources listed under the secondary nonferrous
metallurgy category in Table  4.1-1, Volume I, indicate that uncontrolled
sources emit nearly 100$ < 2  p,.i§/  Therefore, a gross estimate of fine-
particle emissions from secondary nonferrous metallurgical operations is
127,000 tons/year.  The number of particles emitted that are < 2 y, in
diameter is estimated to be 7.85 x 1021 particles/year.

          7.2.10  Carbon black:  The particle size of carbon black particles
is 0.01-0.4 p, in diameter.16/ Therefore, the total mass emissions (93,000
tons/year) listed in Table 4.1-1, Volume I, are also the fine-particle
emissions.  The number of particles emitted that are < 2 p, in diameter
is estimated to be 1 x 10^2 particles/year.

          7.2.11  Coal preparation plants:  Thermal dryers are the only
particulate emission source in coal preparation plants for which adequate
data were available to permit an estimate of fine-particle emissions.  The
fine-particle emissions from  thermal dryers were calculated using an emis-
sions factor of 12 Ib/ton following the primary cyclones, and available
extent of control information.i/  Information on control of thermal dryers
indicates that all plants are equipped with primary cyclones, and that 85$
of the production is also equipped with wet scrubbers following the primary
cyclones.  The available particle-size data for thermal dryer effluents
shown in Figure 43 indicate that the particles exiting the primary cyclone
average about 40$ < 3 (j,.

          Using the emission  factor of 12 Ib/ton, the total particulate
emitted from the primary cyclones was calculated to be 438,000 tons/year.
Since 15$ of the production is not equipped with additional control devices,
the total emissions from these units were calculated to be 65,700 tons/year
with 40$ of the quantity, or  26,300 tons/year, being < 3 p,.
                                    107

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        to
        §60
          40
           20
                                                  9
                                     '<&£* OUTLET FROM
VT C?
                                              MAIN CYCLONE
           0.01  0.2    2       20   50    80      96   99.8  99.99
                      % LESS THAN STATED SIZE (WT. %)
Figure 43 - Particle-Size Analysis for Particulates Emitted from Coal
                              Thermal Dryersi§/
          The remaining 85$ of the production, which accounts  for 372,300
tons/year emissions from the primary cyclones, is controlled with wet
scrubbers.  Assuming that the wet scrubbers are "medium" efficiency scrub-
bers, and that the penetration for < 3 p, particles was 25%,  fine-particle
emissions were calculated to be 37,200 tons/year.  Therefore,  the total
fine-particle emissions from thermal dryers are:
   Plants controlled with cyclones               =  26,300 tons/year < 3 p,
   Plants controlled with cyclones and scrubbers =  57,200 tons/year < 5 p,

                   Total fine-particle emissions =  63,500 tons/year < 3 y,


The 63,500 tons/year represent 67.5$ of the total mass  emission for thermal.
dryers reported in Table 4.1-1, Volume I.

          The number of particles emitted that are  < 3  p,  in diameter  is
estimated to be 3.9 x 1021 particles/year.
                                   108

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           7.2.12  Petroleum refineries;   Catalyst regenerators,  boilers,
 process  heaters, decoking operations,  and incinerators are sources of par-
 ticulate pollution.   Meager particle-size data exist for all uncontrolled
 sources, and only an estimate of fine-particle emissions from catalyst
 regenerators was made.

           Figure 44  summarizes available particle-size distribution data
 from eight uncontrolled FCC units.   In order to use this particle-size
 data to  calculate fine-particle emissions, it is necessary to know the
 quantity entering the cyclones.  The total mass emissions of 45,000 tons/
 year from FCC units  (Table 4.1-1, Volume I) was calculated on the basis of
 an  emission factor for  controlled FCC  units.   Assuming that all  FCC units
 are equipped with 80$ efficiency cyclones, the quantity of particulate
 material entering the cyclones is 225,000 tons/year.

           Using the  inlet rate of 225,000 tons/year,  the particle-size data
 in  Figure 44, and the fractional efficiency curve for a high efficiency
 cyclone  (Figure 17),  fine-particle  emissions  were calculated to  be 56,600
 tons/year.   This figure exceeds the total mass emission of 45,000 tons/year.
 However, in view of  the assumptions in the calculations,  the difference in
 the emissions is not  considered significant,  and fine-particle emissions
 are assumed to equal  the total mass emissions of 45,000 tons/year.

           The number  of particles emitted that are < 2 p,  in diameter is
 estimated to be 3.7 x 1021 particles/year.

           7.2.13  Fertilizer and phosphate rock;   Particulate emissions
 from the processing of  phosphate rock  and from fertilizer manufacturing
 originate from dryers,  roasters,  digesters, granulators,  and coolers.
 Particle-size distributions were obtained only for granulators and dryers
 used in  the manufacture of phosphate fertilizers.   Figure 45 presents  the
 particle-size data for  these sources.  The data were  obtained from eight
 individual fertilizer plants.

          Because  of  the lack of adequate particle-size distribution data
 for the  other sources,  estimates  of fine-particle  emissions  were made  only
 for the  granulators and dryers.   Fine-particle  emissions  from the granu-
 lators and  dryers  are estimated to  be  13,700  tons/year as  shown in  Table 15.
 Details  of  the  calculations  are given  in  Tables E-22 to E-25, pages  251 to
 254.   This  represents  about 8$ of  the total mass  emissions  reported for
 these sources in Table  4.1-1,  Volume I.

          7.2.14  Iron  foundries:   The iron melting process  in foundries is
 the principal source of  particulate emissions.  Cupola, electric arc, elec-
 tric induction,  and reverberatory air furnaces are used to obtain the molten
metal.   Secondary  sources of particulates include materials handling, cast-
 ing shakeout systems, buffing and grinding operations, and core ovens.
                                    109

-------
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                                                              99
                                                                    99.9   99.99
Figure 44  - Particle-Size Distribution of Particulates Emitted from
                 Petroleum FCC Units (cyclone  inlet, Banco data)
                                         110

-------
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 Figure 45 - Particle-Size Distribution of  Particulates  Emitted from
                     Uncontrolled Fertilizer Dryers  (Banco  data)
                                      111

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Particle-size distributions,  emission factors,  and degree of application of
control  information were available only for the cupola furnaces,  and esti-
mates of. fine-particle emissions  were confined  to that source.

          Table  16  summarises Cine-particle cmluuiona  from cupola.';.   Uota'drj
of the calculations are given in  Tab lee E-44 to E-49,  pages 273 to WV.  The
13,100 tons/year of fine particulate  matter comprises  approximately  12.5$
of the total mass emission from these furnaces  (Table  4.1-1,  Volume  I).
Available particle-size data  for  uncontrolled cupolas  are presented  in
Figure 46.  The  data  in Figure 46 were obtained from 25 individual cupola

          7.2.15 Acids;

               7.2.15.1  .Sulfuric acid;  Chamber plants are uncontrolled,
and the  particles emitted from these  plants are typically 90-96$  < 3 jj,.*y
Total mass emissions  from chamber plants are only 2,000 tons/year..   Fine-
particle emissions  are estimated  to be 5% of this total, or 100 tons/year.

               The  available  particle-size data for effluents from contact
plants show that 65 wt.  $ are < 3 y,.   Since the control devices normally
remove mostly larger  particles, it is estimated that at least 65  wt.  % of
the total emissions of 4,000  tons/year, or 2,600 tons/year, are < 3  p,.

               Fine-particle  emissions from spent acid concentrators were
not estimated because of inadequate particle-size data.   The  number  of par-
ticles emitted from sulfuric  acid plants that are < 3  p, in diameter  is
estimated to be  3.4 * 1020 particles/year.

               7.2.15.2  Phosphoric acid—thermal process;  Particle-size
data for thermal-process phosphoric acid plants indicate that particulate
effluents are 50 wt.  % < 1.6  p,.   The  only estimate of  fine-particle  emis-
sions that can be made is that at least 50$ of  the total emissions of
2,000 tons/year,  or 1,000 tons/year,  are < 1.6  p,.

               The  number of  particles emitted  that are < 3 p, in  diameter
is estimated to  be  1.2 x 10^ particles/year.

          7.2.16  Frimary nonferrous  metallurgy;   No estimate was made for
fine-particle emissions from  primary  nonferrous metallurgy sources.   Very little
particle-size data  are available  for  the many varied sources  within  each of
the primary nonferrous groups.  These sources range from copper reverbera-
tory furnaces (51$  <  37 p,) to zinc sintering machines  (100$ < 10  p,).   The
variability of the  operations and the inadequate  particle-size data  do not
permit even a generalization  as to percent  < 2  p,.

          Furthermore,  the extent of  control information for  the  many pri-
mary nonferrous operations has only fair reliability,  and this would fur-
ther decrease the accuracy of any estimation of fine-particle emissions.
                                    113

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    Figure 46  - Particle-Size Distribution  of Particulates Emitted from

                      Uncontrolled Iron Foundry Cupolas (Banco data)
                                        115

-------
          7.2.17  Clay products;  No calculations for fine-particle emissions
from clay product manufacturing could br> made because of inadequate particle-
size and .'ipplicntlon-of-control data J'or all iiourcoo.

          7.2.18  Operations related to agriculture;  No estimates of fine-
particle emissions were made for this category because of lack of particle-
size distribution data for nearly all individual sources.

          7.2.19  Municipal incineration;  Municipal incineration is not
strictly an industrial source of particulate air pollutants, but it produces
significant quantities of fine-particle emissions and has been included in
Tables 1 and 2.

          Estimates of fine-particle emissions from municipal incineration
are presented in Table 17.  Fine-particle emissions are estimated to be
36,400 tons/year, which is about 37$ of the total mass emissions reported
for this source in Table 4.1-2, Volume' I.  Details of calculation of fine-
particle emissions are given in Tables E-68 to E-73, pages ?97 to 302.

          Particle-size distribution data for uncontrolled incinerators are
shown in Figure 47.  The data in Figure 47 were taken from Ref. 18.

          Before calculating fine-particle emissions it was necessary first
to calculate total mass emissions, before any control devices.  This was
computed to be 240,000 tons/year based on incineration of about 20 x 10
tons/year of waste^l/  and an emission factor of 24 Ib/ton reported in a
study conducted by A. D. Little for APCO.^2/  This same study also provided
the information on percent application of control.

     7.3  Fine-Particle Emissions from Mobile and Miscellaneous Sources

          To indicate the relative magnitude of the fine particulate prob-
lem from stationary sources, fine-particle emissions were also estimated
for mobile and miscellaneous sources.

          7.3.1  Mobile sources;  Particulate emissions from mobile sources
were assumed to be uncontrolled and to consist of all < 2 p, particulate.
Table 4, page 10,  summarizes the estimate of fine-particle emissions from
these sources.

          7.3.2  Miscellaneous sources;  Table 5, page 10, presents an
estimate of fine-particle emissions from miscellaneous sources for which
adequate particle size data were available.  Fine-particle emissions from
natural dusts, forest fires, and agricultural burning could not be esti-
mated because of lack of reliable particle size data.
                                    116

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  Figure 47 -  Particle-Size Distribution of Particulates Emitted from


                   'Uncontrolled  Municipal Incinerators  (Banco data)
                                     118

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8.  Projections of Fine-Particulate Emissions to the Year 2000

     8.1  Mass Basis

          Projections of fine-particle emissions through the year 2000 were
performed for those sources for which adequate particle-size distribution
data and information on application of control devices were available.  Two
projection methods were used which are similar to Method 1 and Method 5
previously described in Volume I.  The first method reflects no change in
control,while the other method reflects establishment of controls on all
sources by 1980 and an increasing use of the most efficient control devices.

          Method 1 - The projection of emissions by Method 1 assumes that
there will be no change in the net control for a source.  This means that
the emissions increase in proportion to increases in production capacity.
Production figures were projected by the same methods outlined in Volume I,
and were used to proportionally increase the current mass of fine-
particle emissions.  An example of the calculation method is given in Table
18.
                                 TABLE 18
        PROJECTIONS OP FINE-PARTICLE EMISSIONS FOR ASPHALT DRYERS
Year

1968
1970
1975
1980
1985
1990
1995
2000

Production
106 Tons/Year
251
274
333
406
498
610
747
915
(Method 1)
Production
Ratio
1.00
1.09
1.33
1.62
1.98
2.43
2.98
3.65

Fine Particle Emissions
(tons /year)
154,200
168,100
205,100
249,800
305,300
374,700
459,500
562,800
          Method 2 - The projection of emissions by Method 2 also takes
into account the increases in production, but two assumptions are also made:

          1.  All sources will be controlled by 1980; i.e., application of
control will reach 100$ by 1980.
                                   119

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           2.   Increased utilization of the most efficient control devices
 will continuously increase the efficiency of control on fine particles so
 that by the year 2000 it will be equivalent to controlling all sources with
 baghouses.

          The  fabric  filter was  selected  as  a  reference  standard  of per-
 formance because it is  one of the most  efficient devices  available today
 for  collecting fine particulates.   It  seems  realistic to  assume that
 improvements in the other control devices and  possible  development of  new
 devices would  allow the efficiency  of  control,  in the year 2000,  to match
 the  performance capability of the best  devices  that  are presently available.

          The  calculation of  projected fine-particle emissions by Method  2
 uses the present average efficiency of control on fine  particles  as a  start-
 ing  point.  Therefore,  the first step  in  this  method is the  back  calcula-
 tion of the average efficiency of control on fine particles  as shown in the
 example for asphalt dryers, Table 19.
                                TABLE 19

               CALCULATION OF AVERAGE EFFICIENCY  OF  CONTROL
                 FOR FINE PARTICLES FROM ASPHALT MYERS
                                (Method  2)

 1968  Total  Production                             = 251 x 10^ tons/year
 Emission Factor                                   = 32 Ib/ton
 Process Emissions                                 = 15.5$ < 3 p,
 Fine  Particle  Emissions                           = 154,200 tons/year
 Application of Control                            = 99$
 Calculation of Average Efficiency of Control for Fine Particles  (x):

             (251 x 106)f gooo J(15.5$)(1 - 0.99x) = 154,200

                                        1 - 0.99x = 0.248

                                            0.99x = 0.752

                                                 x = 0.76

Average Efficiency of Control for Fine
  Particles  from Asphalt Dryers                   = 76$
                                    120

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          The  second  step in the  calculations  is  to determine the efficiency
of control on  fine particles using  a baghouse.  This is  based on the particle-
size distribution of  the  process  emissions  and the  fractional efficiency
curve for a fabric filter as shown  in Table 20.   The value  computed is
assumed to represent  the  efficiency of control for  the source in the year
2000.  The efficiency of  control  for the  intervening years  is increased
linearly from  the present value to  the efficiency calculated for the year
2000.
                                 TABLE  20

           CALCULATION  OF AVERAGE EFFICIENCY  OF CONTROL ON FINE
               PARTICLES FOR FABRIC FILTER  ON ASPHALT DRYER

Basis:  100 Ib. of process emission

        15.5$ < 3 (j,

Fine Particle Process Emission  - 15.5  Ib.

  Size                              Fabric  Filter            Fine Particle
Range (p.)            #             Penetration (%)       .      Emission

  1-3              12.6                  0.5                     0.06

0.5-1.0             2.18                 1.8                     0.04

0.1-0.5             0.71                 3.3                     0.02

                                                                 0.12

Average Efficiency of Fabric Filter on Fine Particles =      "   — = 99.2$
                                                            -LO • O
          Method 2 also assumes that the application of control increases
linearly to 100$ by 1980, as shown in Table 21.  Table 21 also summarizes
the variables used to calculate the projected emissions of fine particles
for asphalt dryers.  The calculation of the projected fine-particle emis-
sions for asphalt dryers is illustrated in Table 22.
                                    121

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                                TABLE 21

         VALUES USED IN CALCULATION OF PROJECTED FIKE-PARTICLE
                     EMISSIONS FOR ASPHALT DRYERS
                               (Method 2)

At Present, Application of Control = 99$
Efficiency of Control on Fine Particles = 76%

           Production        Application of       Fine-Particle Efficiency
Year       (tons/year)         Control (%)             of Control

1968       251 X 106             99                       76
1970       274 x 106             99.1                     77.5
1975       333 X 106             99.6                     81.2
1980       406 x 106            100                       84.9
1985       498 x 106            100                       88.6
1990       610 X 106            100                       92.3
1995       747 X 106            100                       96.0
2000       915 X 106            100                       99.2
                                TABLE 22

       PROJECTIONS OF FINE-PARTICLE EMISSIONS FOR ASPHALT DRYERS
                                (Method 2)

Year                                     Calculation

1968   (251 x 106)(-~-)(0.155)[l  - (0.99)(0.76)] = 154,200 tons/year
                  \ 2000/

1970  (274 x 106)(-^-)(0.155)[l - (0.991)(0.775)] = 157,600 tons/year
                 \ 2000/
1975  (333 x 106)(-^-Vo.l55)[l - (0.996)(0.812)] = 157,700 tons/year
                 »2000/

1980          (406 x ,106)( -2=-) (0.155) (1 - 0.849) = 152,000 tons /year
                         \2000'

1985          (498 x 106)(-^-)(0.155)(l - 0.886) = 140,800 tons/year
                         \cOOO/

1990          (610 x 106)(-^-)(0.155)(l - 0.923) = 116,500 tons/year

1995          (747 x j!06)(-^-Vo.l55)(l - 0.960) = 74,100 tons/year
                         V 2000/

2000          (915 x 3.06)(-^-)(0.155)(l - 0.992) = 18,200 tons/year
                         »2000'
                                    122

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          Table 6, p. 13, and Figures 48 to 65 summarize the projections
of fine-particle emissions on a mass basis.  Fine-particle emissions for
the sources listed in Table 6 can be reduced from 3.5 x 106 tons/year  (1968
emission level) to 3.5 x 105 tons/year by the year 2000 if the efficiency
of control on all these sources in the year 2000 is equivalent to perfor-
mance of the best device currently available (i.e., baghouse).  The projec-
tions also show that, even if stringent control is achieved in the year
2000, coal-fired power plants, basic oxygen furnaces, and kraft pulp mill
recovery furnaces will each emit over 50,000 tons/year of < 2 p, particulate.

          The calculation methods described above involve many assumptions
and the two projection methods represent two extremes; that is, no improve-
ment in control versus increasingly stringent controls.  However, even with
the assumptions involved, the calculation methods must be based on knowledge
of the particle-size distribution for the specific uncontrolled source and
on information regarding the percent application of each type of control
device on the specific source.  Without this information, it is very diffi-
cult to estimate, with any reliability, the present level of fine-particle
emissions, and any attempt to make projections of these emissions wouM be
of little value.  For this reason, projections of fine-particle emissions
were made only for those sources for which adequate particle size dis-
tribution data and percent of application of each major type of control
device were available.

     8.2  Number Basis
          The number of fine particles emitted to the year 2000 by sta-
tionary sources was projected by two methods that are extensions of the
techniques used to project mass emissions.  The first method assumes no
change in the net control from 1968 to 2000 which means that the number
emissions, as were the mass emissions, are directly proportional to the
projected production capacities.  Method 2 utilizes the mass emissions pro-
jected by the second technique discussed in Section 8.1 and an assumption
regarding the average diameter of fine particles emitted from sources in
future years.  The two methods are discussed in more detail in the follow-
ing paragraphs.

          Method 1 - This method is the same as Method 1 for the projection
of mass emissions.  Therefore, the number of particles emitted increases in
direct proportion to increases in production capacity.  Projected produc-
tion figures, reported in Ref. 1, were used to proportionally increase the
current number of fine particle emissions (Table 2).   An example of the
calculation method is given in Table 23.
                                   123

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    2.0
    1.5
I
O
i  i.o
a
u
    0.5
         I    I
                         COAL-FIRED ELECTRIC UTILITY
                                                      2.38 IN YEAR 2000
                A  METHOD 1

                O  METHOD 2
            _L
       1968  1970
1975
1980
 1985


YEAR
1990
1995
2000
     Figure 48 -  Projections of  Fine-Particle Emissions from Electric Utility

                                     Coal-Fired Power Plants
                                        124

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   0.20
   0.15
i   o.i
Of
<
Q.
UJ
   0.05
      oU
                               COAL-FIRED INDUSTRIAL POWER
               A METHOD 1
               O METHOD 2
1968  1970       1975
                               1980
 1985
YEAR
1990       1995
2000
     Figure  49 - Projections  of Fine-Particle Emissions from Industrial
                                   Coal-Fired Power  Plants
                                      125

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in
o
g.
\7t
a
u
          I    I
               Crushed Stone
               A Method 1
               O Method 2
                        _L
                                  I
                                  I
        (968 1970
1975
1980
1990
1995*
                                         196S
                                        YEAR
Figure  50 - Projections of Pine-Particle Emission from Crushed  Stone
                                      Operations
2000
                                         126

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0.010
0.009 \-
             Iron and Steel
             Sinter Plants
            A Method 1
            O Method 2
0.001 I-
    1968 1970
    Figure 51 - Projections  of Fine-Particle Emissions  from Sinter
                         Machines (iron and  steel plants)
                                                                          2000
                                    127

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     0.4
     0.3
O
z
2    0.2
10
to
a
y
a:
     0.1
          I    I
                                Iron and Steel
                                Open Hearth
               A Method 1
               O Method 2
         I	I
       1968 1970


       Figure  52
   1975
1980
  1985
YEAR
1990
1995
2000
Projections of Fine-Particle Emissions from Open
    Hearth Furnaces  (iron and steel plants)
                                        128

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<
*
I/)
o
a
o
I
               Iron and Steel
               Basic Oxygen Furnaces
                A Method 1
                O Method 2
                                                                             2000
                    Projections  of Fine-Particle Emissions from Basic
                       Oxygen  Furnaces (iron  and steel plants)
                                        129

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0.04
     —   Iron and Steel
         Electric Arc Furnaces
            A Method 1
            O Method 2
                                                                         2000
                Projections  of Fine-Particle  Emissions from Electric
                      Arc Furnaces (iron and  steel plants)
                                    130

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0.20
          A Method 1
          O Method 2
                                                                     2000
                Projections of Fine-Particle Emissions from Kraft
                             Pulp  Mill Bark Boilers
                                   131

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     0.8
O
O
y
     0.6
0.4
     0.2
          I    I
               Pulp Mills
               Recovery Furnaces
      0  I	I
                A  Method 1
                O  Method 2
        1968 1970


        Figure  56
                  1975
1980
  1985
YEAR
1990
1995
2000
                Projections of Fine-Particle Emissions from Kraft
                            Pulp Mill Recovery Furnaces
                                          132

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   0.004
   0.003
LA.
<



I
0
*/»
z
O 0.002
y
>—
<
Q_
LU
Z
   0.001
                Pulp Mills
                Lime Kilns
                A  Method 1
                O  Method 2
          I	I
        1968  1970
1975
1980
  1985
YEAR
1990
                                                                            0.0043
1995
                                                        2000
         Figure  57 - Projections of  Fine-Particle Emissions from Kraft
                                       Pulp Mill  Lime Kilns
                                          133

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   0.40
   0.30
UJ



in



O
z


§  0.20
y



I
a.
   0.10
                             .    I          T


                              CEMENT KILNS
                                0.476 IN YEAR 2000


                                 /
               A METHOD 1

               O METHOD 2
       1968  T970
1975
1980
 1985


YEAR
1990
1995
2000
      Figure 58 - Projections of Fine-Particle Emissions from Cement Plant

                                          Rotary Kilns
                                        134

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    0.40
    0.30
1  o.»
 £

 UJ

 SJ
 U
    0.10
                       I          I


                        ASPHALT DRYERS
                              0.562 IN YEAR 2000
                A  METHOD 1

                O  METHOD 2
             I
        1968 1970
1975
1980
 1985

YEAR
1990
1995
2000
        Figure  59 - Projections  of Fine-Particle Emissions from Hot-Mix

                                        Asphalt  Plant Dryers
                                          135

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   0,40
   0.30
IU
£  0.20
(/>
2
o
   0.10
                                      FERROALLOY
               A METHOD 1
               O METHOD 2
       1968 1970
1975
1980
 1985
YEAR
1990
1995
2000
     Figure 60 - Projections of Fine-Particle Emissions from Ferroalloy
                                     Electric  Furnaces
                                       136

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   0.40
    0.30
ee.
in


O
i  0.20
in

5
UJ



y

ee
<
Q.

LU
z
   0.10
                                        LIME KILNS
                                                              0.466 IN YEAR 2000
                A  METHOD 1

                O  METHOD 2
       1968  1970
1975
1980
 1985

YEAR
1990
1995
2000
        Figure 61 - Projections of Fine-Particle  Emissions  from Lime  Plant

                                           Rotary  Kilns
                                        -137

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   0.20
   0.15
Of
UJ
I/I
o
z
o
sa  o.io
to
5
UJ
y
P
CK
   0.05
               A METHOD 1
               O METHOD 2
                                            I
                                       COAL DRYERS
       1968  1970
1975
1980
 1985
YEAR
1990
1995
2000
     Figure  62 - Projections qf Fine-Particle Emissions from Coal Preparation
                                   Plant Thermal Dryers
                                          138

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0.10
           Municipal Incineration
            A Method 1
            O Method 2
                                                                         2000
                 Projections of Fine-Particle  Emissions from Municipal
                                     Incineration
                                     139

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    0.04
    0.03
I
o
z
O  0.02
a
    0.01
                Fertilizer
                Gronulators and Dryers
                A Method 1
                O Method 2
          I	I
  I
                        I
             I
        1968 1970

        Figure 64
1975
1980
1990
1995
                         1985
                       YEAR
Projections of Fine-Particle  Emissions  from Fertilizer
                Granulators and Dryers
2000
                                          140

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  0.020
  0.015
vf


o
1
   o.io
y



I
o.

UJ

Z
  0.005

                                 T          I          T



                                     IRON FOUNDRIES
               A METHOD 1

               O METHOD 2
       1968  1970
                     1975
1980
 1985


YEAR
1990
1995
2000
       Figure 65  -  Projections of Fine-Particle  Emissions from Iron Foundry

                                            Cupolas
                                         141

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                                 TABLE 23

         PROJECTION OF FINE PARTICLE EMISSION, ON A NUMbER BASIS,
                           FOR ASPHALT DRYERS
                               (Method 1)

                   Production Ratio               Number of Fine Particles
Year               (from Table 20 )                    Emitted per Year

1968                    1.00                             6.0 x 1023
                                                        (from Table 2)
1970                    1.09                             6.5 x 1023
1975                    1.33                             8.0 x 1023
1980                    1.62                             9.7 x 1023
1985                    1.98                             11.9 x 1023
1990                    2.43                             14.6 x 1023
1995                    2.98                             17.9 x 1023
2000                    3.65                             21.9 x 1023
          Method 2 - Method 2 employs:

          1.  The mass emissions projected by the second technique presented
in Section 8.1, and

          2.  The average diameter of fine particles emitted from sources
in future years.

          The average diameter of the particles emitted in 1968 could be
computed from the mass emissions vs. particle size data given in Table 1.
However, some method had to be devised to determine an average diameter
for the years between 1968 and 2000.  This was accomplished by computing an
average diameter for the fine particles emitted in the year 2000 when all
sources were assumed to be controlled by baghouses or their equivalent.
The average fine-particle diameter for the intervening years between 1968
and 2000  was taken from a straight-line interpolation between the average
size of the fine particles emitted in 1968 and in 2000.

          The sequence of steps involved in projecting the number of fine
particles emitted from asphalt dryers in future years by Method 2 is
described below and is illustrated in Tables 24-27.

               Step 1 - Calculate the average diameter of the fine particles
emitted in 1968 (see Table 24).
                                    142

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                                  TABLE 24

           CALCULATION OF THE AVERAGE DIAMETER OF FENE PARTICLES
                        FROM ASPHALT DRYERS IN 1968
                                 (Method 2)

 Fine  Particle  Emissions = 154,200 tons/year  (from Table l)

 Number  of Fine Particles Emitted = 6.0 x 1023 particles/year  (from Table 2)
                     5/(l7.5 x 105)(mass  emission tons/year)
                p ~  t\l(density g/cm3)(number emissions)
                     5/(l7.5 x 105)(154.2 x 105)
                    N    (2.6*)(6.0 x 1023)
             dmp =  /y/171 x 10"15
             dmp = 5.55 x 10"5  cm.
*  Density values were taken  from Ref.  18.
               Step 2 - Calculate the average diameter of the fine par-
ticles emitted in the year 2000.  Calculation is based on the projected
mass emission for the year 2000  (Method 2, Section 8.1) and on the assump-
tion that all sources will be controlled with baghouses or the equivalent
in the year 2000.

               The size distribution of the particulates escaping the bag-
house was computed using the size distribution of the particles emitted
from the uncontrolled source and the fractional efficiency curve for a
fabric filter (Figure 17).  For most sources, this had already been done
in conjunction with computing the mass emissions of fine particles.  The
size distribution of the particles emitted from the baghouse and the pro-
jected total mass emissions of fine particles for the year 2000 are then
used to calculate the mass emission of fine particles within each size
range.  The mass emission within each size range is in turn used to calcu-
late the number of particles emitted within each size range.  Knowing the
total mass and total number of fine particles emitted, the average diameter
can be calculated.  Table 25 presents an example calculation.
                                   143

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                                TABLE 25



         CALCULATION OF THE AVERAGE DIAMETER OF FIME PARTICLES

                  FROM ASPHALT DRYERS IN THE YEAR 2000

                               (Method 2}



A.  Calculate Mass Emissions Within Each Size Range

            (~\ f\C.

I-3 H     /* 'TTT? = 50$ x 18,200 tons/year = 9,100 tons /year
          \                  it
          (from Table 20)    \ (from Table 22)


0.5-1 (j,       ' , = 33$ x 18,200 tons/year = 6,000 tons/year
0.1-0.5 „   %g • 17* » 18,200 tons/year -
B.  Calculate Number of Particles Eknitted Within. Each Size Range
1-3 „       N = (17.5 x 105 g/ton)(9.1 x 105 tons/year) = y<6 x 1Q20 particles/ye

                       (2.6 g/cm3)(2 x 10'4cm.)3
                                  ,
                  (2.6)(0.75 x 10"4)-
0.5-1,
0.1-0.5 ,   N =    ..1xlCa ?64>Q x 1Q20

                 (2.6)(0.30 x 10'4)3


          EN = 866 x 1020 particles/year




C.  Calculate Average Diameter of Fine Particles
                 3/ (17.3 x 105 g/ton)(!8.2 x 105 tons/year)
          dmp = ^ /		
                    (2.6 g/cm3)(0.866 x 1023 particles/year)
          dmp = 5.19 x 10   cm.
                                      144

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               Step  3  -  The  data to be  used in projecting the number of fine
particles emitted  by asphalt dryers are compiled as i;hown in Table P6.  Th<
averaKQ particle diejnotera for the yuarn butwcen IWi and POOO were ubtalno't
by straight-line intcrp<».!atl<>n boLwcori  the  avur/igc  dltunoter \'nr the yuur
1968 and the year  2000 as  discussed in  Stops 1 and  c'.   The macs emission
of fine particles  was  taken  from previous projection of these emissions
(Method 2, Section 8.1).

               Step  4  -  The  data compiled in Step 3 are used to calculate
the number of fine particles emitted, up to year 2000,  as shown in Table 27.

               Table 7, page 14,  summarizes the results of the projections
of fine-particle emissions on a number  basis.   The  projections show that
ferroalloy electric  furnaces,  rotary lime kilns in  lime plants, municipal
incinerators, coal-fired power plants,  and  steel making furnaces (EOF and
electric arc) will be  significant sources of fine-particle pollutants, on
a number basis, even with  stringent  control in the  year 2000.
                                    145

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                                TABLE 26



       COMPILATION OF DATA TO BE USED IN  PROJECTION  OF  NUMBER OF

               FINE PARTICLES EMITTED FRCM ASPHALT DRYERS

                                (Method 2)



       Average Diameter of Fine-Particle    Fine-Particle  Mass Emissions

Year   	Emissions (dmp)	(tons/year)(from Table 25)
1968
1970
1975
1980
1985
1990
1995
2000

5.55 x 10~5 cm,
5.53 x 10~5
5.47 x 10~5
5.42 x lO-5
5.36 x 10-5
5.30 x 10-5
5.25 x 10-5
5.19 x 10-5 cm.

(from Table 24)






(from Table 25)
TABLE 27
PROJECTION OF FINE-PARTICLE EMISSIONS ON A
154,200
157,600
157,700
152,000
140,800
116,500
74,100
18,200

NUMBER BASIS FOR ASPHALT DRYERS
                                (Method 2)


                                                        No.  of Fine  Particles

Year           (Refer to Table  26)                        Emitted Per Year



1968                                                    =  6.0 x 1023 (from Table 2)


1Q,n    TT   (17t3 x 1C)5 g Aon) (157. 6 x 103 tons/year)   _          23
J»y ' U    JN ~              ty            tr      'Z.           ~*  O • t X J.U
                (2.6 g/W)(5.53 x 10"° cm.)


            (17.3 x 105)(l57.-7  x 103)                             a*
1975    N = * - ^ - r-= — L                   =  6.4 x 1023

               (2.6)(5.47 x Kfbr


            (17.5 x 105)(152.0  x 103)
1980    N = - - " - =-= — *•                   =  6.3 x
               (2.6)(5.42 x 10~b)5


1985    N = (17.5 X 105)(140.8  x 103)                   =  ^ x

               (2.6)(5.36 x 10'5)5


1990    N = (I?-3 x 105)(116.5  x 103)                   „  ^ x

               (2.6)(5.30 x 10-5)3



1995    N -
               (2.6)(5.25 x 10-5)3



2000    y.(l7.5xlo5)(lB.2xlQ3)                   =  0.87 x 1023

               (2. 6) (5. 19 x 10-5 )3


                                    146

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 9.   Conclusions  and Recommendations

      9.1  Conclusions

           1.   An accurate assessment  of the  mass of fine particles
 emitted from specific  sources  was  precluded  because  neither particle  size
 distribution data nor  fractional efficiency  curves for  control devices were
 available  in the 0.01-2  p, size range.   The lack of particle size data for
 effluents  from controlled sources  indicates  that neither control equipment
 manufacturers nor air  pollution control agencies have placed any emphasis
 on the  particle  size of  material emitted from control equipment.

           2.   Fine-particle  emissions  from industrial sources  of particu-
 late  pollution are estimated to be at  least  4 x 10°  tons/year.  This  rep-
 resents approximately  20-25$ of the total mass emissions for these sources.

           3.   Major industrial sources of fine particles, based on mass
 and number emitted,  include:   (a)  ferroalloy furnaces,  (b)  steelmaking
 furnaces,  (c) electric utility power plants,  (d) lime kilns,  (e) kraft pulp
 mill  recovery furnaces,  (f)  municipal  incinerators,  and (g)  iron foundries.
                       *
           4.   Discrepancies  exist  in the fine-particle  and  total mass emis-
 sions from some  sources  that emit  mainly micron or submicron particulates
 (e.g.,  basic  oxygen furnaces and kraft pulp mill recovery furnaces).  Analy-
 sis of  the possible  causes of  these discrepancies led to observation that
 erroneous  conclusions  may have been reached regarding the high  overall mass
 efficiency of control  equipment on these sources.

           5.   Currently,  control equipment is  rated by  one  parameter, namely,
 overall mass  efficiency.  Specification of control equipment efficiency by
 overall performance  is inadequate  with respect  to small particles.  Penetra-
 tion  (i.e.', 1-mass efficiency)  in  specific size ranges  is a more revealing
 term  for rating  control  equipment  performance.

           6.   There  is considerable doubt that  present  air pollution control
 procedures, which are based on overall percentage reduction in emissions
 (tons/year),  actually  achieve  the  desired reduction in  suspended particulate
matter  in  the  community  air.

           7.   Fractional efficiency characteristics of control devices
have not been  accurately determined, and, as a result,  the ability of con-
trol devices to  collect < 2 y, particles  is ill-defined.

           8.  A major portion  (over 95$) of the data currently available  on
the particle size of particulates emitted from industrial sources  has been
 obtained by sampling and particle sizing techniques that are not suitable

                                    147

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 for  the particle  size  range  < 2 ^.   As  a result,  only a meager, quantity  of
 accurate data  is  available on particle  size  in the < 2  y,  size  range for
 effluents  from uncontrolled  or controlled sources.

           9.   Fine particulates emitted from man's activity contribute
 significantly  to  all the major adverse  aspects of air pollution.  Fine par-
 ticles can initiate  or contribute to problems related to  human health,
 atmospheric physical properties, and/or material  degradation.   The chemical
 and  physical properties of the atmosphere affected include:  its electrical
 properties; its ability to transmit  radiant  energy;  its ability to convert
 water vapor to fog,  cloud, rain, and snow; its ability to damage and to
 soil surfaces.

           10.   The effects of particulate matter  on  human health are, for
 the  most part,  related to injury to  the surfaces  of  the respiratory system.

           11.   A  combination of particulates and  gases  may produce an effect
 on human health that is greater than the sum of the  effects caused by either
 individually (i.e.,  synergistic effects).

     9.2   Research Recommendations
          1.  Source sampling with more advanced instrumentation (e.g.,
cascade impactors, thermal precipitators, and electrostatic precipitators)
must be done to define the effectiveness of control equipment for the col-
lection of particulate pollutants.  Standard sampling techniques are inade-
quate for collecting and sizing particles, particularly for particles 1 (j,
or smaller.  The program should involve actual field testing, and attention
should be directed to the determination of the particle-size distribution
before and after control equipment and the.fractional efficiency of specific
control devices on specific sources.

          2.  Current.control devices do not adequately collect fine par-
ticles.  Therefore, research programs should be initiated to study methods
for the collection of fine particulates.  Research should be directed to
these main areas:  (a) improvement of existing control equipment via better
design,  (b) development of new and/or novel devices for controlling fine
particles, and (c)\agglomeration mechanisms of fine particles.  Research
on the agglomeration mechanisms should improve existing collector perfor-
mance and may lead to new collector devices.

          3.  Current' capability to monitor, sample, and size effluents
from particulate pollution sources is inadequate.  Research should be
initiated to improve this capability.  Optical techniques for monitoring fine
particle emissions should be pursued.  Simple, yet reliable stack sampling
methods need to be developed.  A collection mechanism which collects

                                   148

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submicron particles and  causes neither a formation nor a break-up of aggre-
gates is necessary if  accurate particle size information is to be obtained.

          4.  Research should be directed to defining the relationships
between total suspended  particulate in the air and specific sources of
particulate pollution.   Information is needed to help identify the origins
of suspended particles in the air and to assess the contribution of various
sources to the total particulate burden in the atmosphere.  Investigations
should focus on material that leaves the source as a particulate (i.e.,
primary particulate),  and source effluents that form particulates after
leaving the source (i.e., secondary particulates).  Reduction of total sus-
pended particulate matter may require control at the source of effluents
that form secondary particulates.

          5.  Epidemiological and laboratory studies of the effects of
particulate pollutants on humans, including experiments on animals, should
be carefully coordinated and selectively accelerated.  Attention should be
focused on synergistic effects produced by gases in combination with par-
ticulates.

          6.  Information on chemical composition of particulate pollutants
as a function of particle size should be obtained to assist in defining
potential health hazards of particulate pollutants.  Attention should be
focused on potentially harmful metals.

          7.  Material damage caused by fine particulate pollutants should
be assessed more closely.

          8.  The influence of suspended-particulate matter on the behavior
of the atmosphere should be defined in more detail.  Attention should be
focused on their effect  on solar radiation and weather modification.

          9.  Since the major adverse effects of particulate pollutants on
human health and welfare are associated with micron and submicron.particles,
the technical and economic feasibility of establishing national emission
standards based on particle size should be investigated.  Performance or
emission standards based on  particle size should be studied because there
is great doubt that present procedures which are based on overall percent-
age reduction in emissions (tons/year) actually achieve the desired reduc-
tion in suspended particulate matter in the community air.   If a performance
standard based on particle size were adopted, accurate data expressing
control equipment efficiency over the various particle size ranges  will be
necessary.  Simple, accurate, and reliable methods for testing the  perfor-
mance of various control devices in the fine-particle range will also be
needed.   These test procedures will be needed to confirm compliance of
installed equipment with regulations as well as to provide  a means  of

                                   149

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comparing performance capabilities of various devices on a single source.
Research recommendations 1 and 3 would provide input to this area.  More
stringent regulations will produce substantial costs in design, engineering,
and testing.  Data on those costs will need to be accumulated.  Also more
analytical data on the.dependence of control equipment performance on source
operating variables and effluent characteristics will need to be developed,
industry by industry.
                                    150

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                                REFERENCES
 1.  Pa'rticulate Pollutant System Study, Volume I, NAPCA Contract CPA 22-
       69-104, Midwest Research Institute, 1 May 1971.

 2.  Bosch, J. C., "Size Distributions of Aerosols Emitted from a Kraft Mill
       Recovery Furnace," M. S. Thesis, University of Washington, 1969.

 3.  "A Manual of Electrostatic Precipitator Technology," Southern Research
       Institute, pp. 418-73, August 1970.

 4.  Stairmand, C. J., "The Design and Performance of Modern Gas-Cleaning
       Equipment," Journal of the Institute of Fuel, 58-81, February 1956.

 5.  Sargent, G. D., "Dust Collection Equipment," Chemical Engineering, 130-
       50, January 27, 1969.

 6.  Stairmand, C. J., "The Design and Performance of Cyclone Separators,"
       Trans. Inst. Chem. Engrs., 29, 356-83 (1951).
 7.  Peterson, C. M., and K. T. Whitby, "Fractional Efficiency Characteristics
       of Unit Type Collectors," ASHRAE Journal Reprint, May 1965.

 8.  Caplan, K. J., "Collection Efficiency of Reverse-Jet Filters and Cloth
       Arresters," Report prepared for National Center for Air Pollution
       Control, September 1968.

 9.  Venturini, J. L., "Operating Experience with a Large Baghouse in the
       Electric Arc Furnace Steelmaking Shop at Bethlehem Steel Corporation's
       Los Angeles Plant," presented-at 63rd Annual Air Pollution Control
       Association Meeting, June 1970.

10.  Colley, D. G., "Stack Sampling Yields Fractional Efficiencies for Dust
       Collectors," presented at Air Pollution Control Conference, Purdue
       University, October 1970.

11.  Valentin, F. H. H., "The Design and Performance of Cyclone Separators,"
       The South African Industrial Chemist, 27-35, February 1958.

12.  Pinchak, A. C., "A Review of the State of the Art of Cyclone Type
       Separators," Clearinghouse, U.S. Department of Conmerce, March 1967.

13.  Gallaer, C. A,, and J. W.  Schindeler, "Mechanical Dust Collectors,"
       Journal of the Air Pollution Control Association, ,^5(12), 574-79.
                                     151

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14.  Bush, A. F., and E.  S.  C.  Bouler,  "Electron Microscopy Studies  of  a
       Coal-Fired Steam-Electric Generating  Stack Discharge," University
       of California, December  1965.

15.  "Louisville Air Pollution  Study,"  Report  for USDHEW, Robert A.  Taft
       Sanitary Engineering  Center, Cincinnati, Ohio  (1961).

16.  Herdan, G., Small  Particle Statistics,  London, Butterworths (1960).

17.  Collins, T. T., Jr.,  "Pilot Plant  Study of a Multiclone Unit Operating
       on Stack Gases from a Lime  Kiln," TAPPI, March 1948.

18.  Particulate Pollutant System  Study, Volume III,  NAPCA  Contract  CPA
       22-69-104, Midwest Research Institute,  1 Hey 1971.

19.  Stern, A. C., Air  Pollution,  Vol.  3, pp.  488-489, New York, Academic
       Press (1968).

20.  Op cit., Ref. 3.

21.  Bay Area Air Pollution  Control District Library, Accession No.  8317.

22.  Sommerlad, Robert  S., "Fabric Filtration  - State  of the Art,"
       Livingston, New  Jersey,  Foster Wheeler  Corporation, March 6,  1967.

23.  Gosselin, A. E., and  L. W. Lemon,  "Bag  Filterhouse Pilot Installation
       on a Coal-Fired  Boiler - Preliminary  Report and Objectives,"  Pro-
       ceedings of the American Power Conference, Vol. 28 (1966).

24.  Pilpel, N., "Industrial Gas Cleaning,"  Brit. Chemical Engr., 542-550,
       August 1960.

25.  Watkins, E. R., and  K.  Darby, "The Application of Electrostatic Pre-
       cipitation to the  Control of Fume in  the Steel  Industry," Scrap  Iron
       and Steel Inst., pp.  24-37.

26.  Little, A., "Practical Aspects of Electrostatic Precipitator Operation-
       Experiments on a Pilot Plant," Trans. Inst. Chem. Engrs.,^34, 259-68
       (1956).

27.  Engelbrecht, Heinz L.,  "Electrostatic Precipitators in Thermal Power
       Stations Using Low Grade Coal,"  Proceedings of the 28th American Power
       Conference, April 1966.

28.  Tuhs, Wolfgang, "Manufacture of Aerosols  and Separation of Ultrafine
       Dusts in Spray Washers," Staub, 29, 43-48, February 1969.
                                ™-~-••"—~  •»•>•»

                                     152

-------
29.  Button, P.,  "Air Pollution in Petroleum Refining," Chem.  Proc. Engr.,
       96-100, February 1968.

30.  "Atmospheric Emissions from Thcrmal-Proceea  Phucphoric Acid Manu-
       facture,"  Public Health Service Report, October 1968.

31.  "Nationwide  Inventory of Air Pollutant Emissions - 1966," USDHEW NAPCA
       Pub. No. AP-73, August 1970.

32.  Niessen, Walter R., and Adel F. Sarofim, "The Emission and Control of
       Air Pollutants from the Incineration of Municipal Solid Waste,"
       Proceedings of the Second International Clean Air Congress, December
       1970.

33.  Horauth, Helmuth, and August T. Rossano, "Technique for Measuring Dust
       Collector Efficiency as a Function of Particle Size," Proceedings of
       the 62nd Meeting of the Air Pollution Control Association, June 1969.

34.  Kalika, Peter W., "How Water Recirculation and Steam Plumes Influence
       Scrubber Design," Chem. Engr., 133-138, July 1969.

35.  Schell, T. W., "Cyclone/Scrubber System Quickly Eliminates Dust Prob-
       lem," Rock Products, 66-68, July 1968.

36.  Dickie, Lou, "All About Wet Collectors," Air Engineering, 24-27,
       February 1967.

37.  Brink, J. A., and C. E. Contant, "Experiments on an Industrial Venturi
       Scrubber," 132nd Meeting, American Chemical Society, New York, New
       York, September 1957.

38.  Training Program - National Center for Air Pollution Control.

39.  Turner, B., "Grit Emissions," BAAPCD Library, Accession No. 9775.

40.  National Coal Association, "Modern Dust Collection for Coal-Fired
       Industrial Boilers," NCA Fuel Engineering Data, Washington, -D. C.

41.  Hodason, John, "The Selection of Industrial Dust Collection Plant,"
       Proceedings of Clean Air Conference (1965).

42.  Yocom, J.  E., and D.  H. Wheeler, "How to Get the Most from Air-Pollution
       Control Systems," Chem. Eng.,  127-136,  June 1963.
                                    153

-------
 43.  Burdock,  J.  L.,  "Present Applications  of Mechanical Collectors  to
       Boilers,"  Proceedings of the  62nd Meeting  of  the  Air Pollution
       Control Association, June 1969.

 44.  Op cit.,  Ref. 12.

 45.  Mau, G. A.,  "The Elimination of Dust from Asphalt Plants," Air  Repair,
       102-104, November  1953.

 46.  Gallaer,  C.  A.,  "Economics  of Ply Ash  Collection,"  Buell Engineering
       Company, New York, New York.

 47.  Air Engineering, 28-38, September 1964.

 48.  Sachsel,  G.  T., J. E. Yocom and T. A.  Retzke, "Fume Control in  a
       Fertilizer Plant - A Case  History,"  JAPCA, 6, 214-217, February 1957.

 49.  Dohrman,  H.  C.,  "Particle  Size  Analysis of Fly Ash," Buell Engineering
       Company, Lebanon, Pennsylvania.

 50.  Op cit.,  Sutton.

 51.  Newmann,  E.  P., C. R. Sederberg, and A. A. Fowle, "Design, Application,
       Performance and Limitations of Sonic Type Flocculators and Collectors,"
       Ultrasonic Corporation, Cambridge, Massachusetts.

 52.  Burke, E., "Dust Arrestment  in  the Cement Industry," Chem. and  Ind.,
       1312-1319, October 1955.

 53.  Peterson, A. A., "Fly Ash Collection for Small Plants," Meeting of the
       American Society of Mechanical Engineers, Washington, D. C., April
       1950.

54.  Larcombe, H. L.  M., "Centrifugal Dust Collectors," The Mining Magazine,
       137-148, September 1947.

55.  Penick, Walter L., and Howard W. Lange, "Fifty Years of Dust and Fume
       Collection in the Mining Industry," Proceedings of the Ninth  Pacific
       Northwest Industrial Dust Waste Conference, April 1959.
                                   154

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56.  Henschen, H. C., "Wet vs. Dry Gas Cleaning in the Steel Industry,"
       Journal APCA, 18, 538-342, 1968.

57.  Wellet, H. P., and D. E. Pike, "The Venturi Scrubber for Cleaning
       Oxygen Steel Process Gases," Iron and Steel Engineer, pp. 126-131,
       July 1961.

58.  Private communication, Mr. Al Brandt, Bethlehem Steel Corporation,
       January 1971.

59.  Private communication, Mr. Jack Smith, Kaiser Steel Company, January
       1971.

60.  Person, R. A., "Control of Emissions from Ferroalloy Furnace Process-
       ing," Union Carbide Corporation, Niagara Falls, New York, 1969.
                                    155

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           APPENDIX A





PARTICULATE SAMPLING AND SIZING
               157
Preceding page blank

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Summary

          Standard stationary source sampling techniques are inadequate
for collecting particles for accurate particle size determinations, par-
ticularly for particles 1 ^  or smaller.  Cyclone separators tend to breafc
up aggregates and friable particles, stainless steel or  alundum  thimbles
do not quantitatively capture the submicron particles, and small particles
may penetrate deeply into the body of a fiber filtering medium before they
are captured and then cannot be removed for subsequent analyses.

          A sampling device which collects submicron particles and causes
neither formation nor breakup of aggregates is necessary if accurate parti-
cle size information is to be obtained.  Cascade impactors, thermal pre-
cipitators, and small electrostatic precipitators are devices that come
close to meeting these requirements, and are clearly superior to  the standard
sampling trains.  A cascade impactor which can be inserted inside a duct is
the most versatile of these devices.  Stainless steel cascade impactors are
now available which permit "in-stack" collection of submicron particles.

          The Bahco Micro-Particle Classifier has been used extensively for
routine particle size measurements, and 95$ of the data currently available
on the particle size of particulates emitted from industrial sources have
been obtained by using this device'.  The range of applicable particle di-
ameter for the Bahco instrument is 5 to 60 p.  As a result of the extensive
use of the Bahco method, only a meager quantity of accurate data  is avail-
able on particle size in the < 2 g, size range.
                                   158

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 1.   Introduction

           Measurements of the  chemical and physics] properties of particu-
 late pollutants  omitted  from flpeciflc oources generally require a sample to
 be  collected,  i.e., the  purtlcuiatuE must be suparatod uut, from the ^ua
 stream in which  they  exist.  The process of sampling may change the physi-
 cal properties of the individual particles and the size distribution of
 the particles.   Following collection of the particulate, the desired physi-
 cal and chemical measurements  can be performed.  Particulate pollutants,
 however,  are not all  alike and can be of different shapes and compositions.
 The variability  in particulate properties has led to the development of
 numerous  methods for  the measurement of specific properties, such as par-
 ticle size.

           The  selection  of the method for determining the particle size
 or  particle-size distribution  of a given material is generally based on
 (l)  the particle-size range, (2) the form in which results are desired
 (i.e.,  number-or-weight  size curves), (3) application of the results, and
 (4)  accuracy required.   Different methods of determining the particle size
 may give  quite different results, and the method used to prepare the sam-
 ples for  analysis can alco be  a rloddlnp; factor in what the analysis actu-
 ally measures.

           The  limiting aspects of sampling methods and particle size analy-
 sis  techniques assume added importance for the determination of the quan-
 tity of fine particulate emitted from specific sources. -The applicability
 of  standard sampling  techniques and routine particle-sizing methods to the
 micron-or-less size regime is  questionable.  A discussion of conventional
 source  sampling  and particle-sizing methods and their ability to collect
 and  measure fine  particles is  presented in'the following sections.
2.  Source Sampling Methods

          The accurate collection of a representative sample from a flow-
ing gas stream containing particulate matter is by no means a simple matter.
In general, a representative sample can only be withdrawn from a flow if
the probe through which it passes does not disturb the streamline pattern.
Therefore, an ideal probe samples isokinetically and has infinitely thin
walls.  Both of these conditions are difficult to achieve in practice, and
the problem is one of determining how far from the ideals one can depart
and still obtain representative samples.

          At the extremes of particle size, representative samples can be
obtained despite disturbances caused by the presence of the probe and an
anisokinetic sampling.  Very small particles have low inertia and follow

                                    159

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 deflections  of the  streamlines with  insignificant Departure, and particle
 and gas  are  drawn into the  probe  in  the correct proportions.
          At tho other  extreme, vcr.y Juj-tfn partjcloa, with rolat.lv<:.Ty hlph
 inertia,  enter the probe  in straight trajectories independent of the stream-
 line  deflection, and the  correct flow rate of particles is measured.  When
 particles are about 10  |j,, and the sampling velocity is lower than the velocity
 in the  duct, some of the  gases will be deflected around the probe.  However,
 some  of the particles,  because of their inertia, will enter the probe and
 the sample will be biased toward the large particles.  Conversely, if the
 sampling  velocity is greater than the dust velocity, the sample will be
 biased  toward the smaller particles.

          An approximate guide to indicate when careful sampling is neces-
 sary  can  be obtained by using the dimensionless inertia parameter,  ^ .
 This  parameter, which is  frequently used in deposition studies, is the ratio
 between the stopping distance of the particle and the diameter of the probe.
 The stopping distance,  defined by Equation 1, is the distance the particle
 will  travel when projected horizontally into a still atmosphere with velocity
 U  .
                       Stopping Distance = £E-	                       (l)
                                            18 n

where     ^  = viscosity of gas

          Pp = density of particle

           d = diameter of particle

           U = stream velocity

           C = Cunningham correction factor

Theoretical and experimental studies have shown that if  |  exceeds 50,
the particles are not affected by the streamline deflection, and if  if  is
less than 0.05 the particles follow the streamline closely.!/  Thus, iso-
kinetic sampling is required if

                                 Pdd2UC
                         0.05  < —	  < 50
                                 18 ^P


where  Dp = probe diameter.

                                    160

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          A  number of devices have been designed which nearly achieve iso-
 kinetic  sampling.   These  devices  either use a null-type sampling probe, or
 measure  the  velocity of the gas stream with a pitot tube as near to the
 probe as possible  without interfering with the gas flow, and then adjusting
 the  sampling velocity.?.;.5/ Since the velocity in a stack generally varies
 with distance  from the wall, accurate sampling also requires the accumula-
 tion of  samples  from several different positions (i.e.,'traverse of the
 stack).

     2.1 Sample Collectors

          The  usual method for collecting the particles from the gas-streem
 sampled  by the probe is to draw the entire stream through a filter which
 is often in  the  form of a thimble.  A small cyclone separator is also use'-
 in series with filters in some cases.  Wet scrubbers have also been used
 in conjunction with cyclones.—/

          The  standard collecting techniques are probably inadequate for
 collecting particles for  accurate size determinations, particularly for
 particles in the micron or less size range.  The cyclone separators will
 tend to  break  up aggregates and friable particles; stainless steel or
 alundum  thimbles probably do not  capture all or any of the submicron par-
 ticles;  and  small  particles may penetrate deep into the body of a fiber
 filtering medium before they are  stopped.  Particles which penetrate into
 the  filters  cannot be removed or  observed microscopically.  Another source
 of error in  sampling aerosols for subsequent particle size analysis is lead-
 ing  the  aerosol  through a long and/or tortuous path before the particles
 are  removed.  The  danger  from this procedure is that particles are caught
 on the walls of  the  tubing, particularly near bends.  Preferential trapping
 of certain particle  sizes can produce serious errors in the particle size
 determinations.

          A  collection mechanism which collects submicron particles and
 causes neither a formation nor a break-up of aggregates  is necessary if
 accurate  size  information is to be obtained.  Small electrostatic precipi-
 tators, thermal  precipitators, and cascade impactors are devices that come
 close to meeting these  requirements.

     2.2  Collector-Measuring Devices

          2.2.1  Impaction devices;  Impactor sampling devices are based on
the fact than an aerosol particle suspended in a  fluid stream tends to move
in a straight line because of its inertia  when the  fluid  flows around an
obstacle.  The larger particles, because  of their greater  mass, will have
sufficient momentum to continue to move toward the object  and impact  on  the
surface.   At the same time, particle motion relative to  the  gas stream is

                                   161

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 slowed by fluid resistance, and some particles may fail to reach the col-
 lector surface before they are carried past the sampler due to deflection
 in the fluid flow field.  Impactors will provide meaningful results only
 under isokinetic sampling conditions.

          Cascade impactors, constructed of stainless steel, are beginning
 to be used for "in-stack" source testing.  Cascade impactors consist of a
 series of stages containing jets and collector plates.  The jets in each
 stage through which the aerosol is drawn become progressively smaller.  The
 particles are classified by inertial impaction according to their mass;
 the larger (heavier) ones are collected on the plate opposite the first
 stage, and the smallest (lightest) on the plate opposite the last stage.
 Figure A-l illustrates a schematic of a source test cascade impactor ..ii/

          The classification of particle size produced by impactors has
 certain advantages for microscopic determinations of size distributions
when there is a large variation in particle size.  Furthermore, this clas-
 sification provides a technique for obtaining mass distribution curves,
 normally in the size range 0.3 to 60 jj,.  The impactor is calibrated to de-
 termine the smallest particles collected at each stage or, preferably, the
 sir.e of particles which are sufficiently small that they are collected with
 only 50$ efficiency at each stage.  Size calibration is dependent upon the
 specific gas velocity through the instrument.  Following calibration, the
 dust whose particle-size distribution is to be determined is then collected
 with the impactor.  The weight of material collected at each stage is de-
 termined and the results are plotted as cumulative weight-distribution
 curves.,!/

          Impactors are capable of very high collection efficiency under
 rigid, experimental conditions.  An efficiency of 100$ for particles as
 small as 0.6 p, has been obtained.^/  A commercial stainless steel eight-
 stage, multi-jet impactor for "in situ" stack sampling has recently become
 available, and is reported to be capable of sizing particles down to 0.1 ^.S/

          Particle-size distributions determined by cascade impactors may
 be distorted by particle bounce, surface overloading (i.e., particle build-
 up and blow-off) and wall losses.  Wall losses can be minimized by good
 impactor design and proper operation.  Particle bounce may be reduced by
using a viscous surface coating on the collector plates.

          2.2.2  Thermal precipitators;  Thermal precipitators have been
used for many years in England and South Africa for ambient sampling.  Ther-
mal precipitators have also been used to a limited extent for stack sam-
pling in this ftnnnt.ry.6-8/  The thermal precipitator makes use of a radiom-
eter force produced by a thermal gradient between two different surfaces.
Direct measurements of collection efficiency indicate that thermal precipitators

                                   162

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       IMPACTOR STAGE
         77A    77A
    \V\\\\\\\\
     \\\\\\\\V\
           IMPACTOR PLATE
                                          O-RINGS
SPACING STUDS
LOCATED AT EQUAL
INTERVALS ABOUT
CIRCUMFERENCE
Figure A-l - Schematic of Source Test Cascade Impactor^/
                     163

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Deposit virtually all particles of most materials from 5 down to 0.01 ^
and possibly smaller.  Ficure A-2 illustrates the narnpling head of ,-A z^w.w:
thermal precipitator .£/

          hy 'iQjxjsitjrip; hhu pM.r-1/ic los on an electron microscope grid, t,hc-
thermal precipitator can be u;:«:d .in conjunction with an electron micro-
scope for sizing particles.  provided the deposit is not so dense that
overlapping occurs and attention is paid to statistical errors, the thermal
precipitator provides one of the most accurate methods for sampling of non-
volatile solid particles.  The upper limit of number concentration which
can be determined with the thermal precipitator depends upon the accuracy
of measurement of the volume sample drawn through the instrument.

          2.2.3  Small-scale electrostatic precipitators;  Small-scale
electrostatic precipitators in various configurations'have been used with
some degree of success for source sampling, and subsequent particle sizing
by optical methods.  The essential feature of many of these devices is a
collecting electrode in the form of a tube down which the particles pass
and a central ionizing electrode maintained at a high potential.  The elec-
tric field is such that the particles acquire a high charge and travel to
the outer electrode, where they are deposited.  A drawback is that the de-
posit varies in density and size distribution along a length of the electrode
so that a full assessment entails considerable counting and sizing.  Electron
microscope screens have also been used as deposit sites.£/  Figure A-3 pre-
sents a schematic of an electrostatic precipitator for sampling.57

                                  Dust Laden Air
                    Microscope
                    Cover Glass
                     Heated
                     Wire
                         Strip of
                         Deposited
                         Dust
        Figure A-2 -
         To Water Aspirator

Sampling Head of Standard Thermal Precipitator^/

               164

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                                                    -p
                                                    
                                                   O
                                                   -p
                                                   cd
                                                   -P
                                                   •H
                                                   PH
                                                   •H
                                                   O
                                                   o;
                                                   o
                                                   •H
                                                   -P
                                                   w
                                                   o
                                                   SH
                                                   -P
                                                   O
                                                   
-------
          Impactors, thermal precipitators, and electrical precipitators
are all capable of collecting particles in the submicron range.  The cas-
cade impactor is probably the most versatile of these devices  for  "in-
stack" collection of submicron particles.  Unfortunately, impactors have
been used only to a limited extent,5/  Research groups at the University of
Washington have utilized ouccude impactors to ,'jump.lo pulp mill recovery
furnaces, plywood veneur dryerc, bark boilnrs, and aluminum reduction
I'.nllr..H>12/  The thermal prccipitutor has boon iiiiod by liush and co-workers,
in conjunction with an electron microscope, to study power plant ctack dis-
charges .£l§/  In the device used by Bush, the particles were thermally pre-
cipitated onto the electron-microscope specimen grids.

          2.2.4  Other devices;  Investigations by Whitby and co-workers
at the University of Minnesota have led to development of a particle-size
distribution analyzer based on electric mobility analysis.  This instru-
ment, designed for atmospheric sampling of submicron airborne particles,
is commercially available from Thermo-Systems, Inc., in St. Paul, Minnesota

          This electric mobility device consists of an aerosol charging de-
vice and an electrical mobility analyzer.  Entering aerosol is given a uni-
polar negative charge by a special diffusion charger (sonic-jet-diffusion-
charger) .  The charge per particle is a reproducible function of the par-
ticle size and is a monotonically increasing function over the size range
of interest.  The charged aerosol passes to the mobility analyzer, where
it is introduced as a bhin annular cylinder around a core of clean air.
A metal rod, to which a variable, positive voltage can be applied, passes
axially through the center of the analyzer tube.  Particles smaller than
a certain size (with high electric mobility) are drawn to the collecting
rod while the larger particles escape collection because of their lower
mobility and are therefore collected by a current collecting filter.  The
electrical charges on these particles drain off through an electrometer,
giving a measure of current.  A step increase in rod voltage will cause
particles of a discrete larger size to be collected by the rod with a re-
sulting decrease in electrometer current.  The change in electrometer cur-
rent is related directly to the number of particles in the aerosol between
the two discrete particle sizes.

          With a constant applied voltage, the removable collector rod may
also be used to collect particles classified by size along the length of
the rod for subsequent analysis with an electron microscope.  Discussions
with Dr. Whitby and with Dr. Olin and Mr. Sem of Thermo-Systems indicate
that the electric mobility device might be adapted for use in stack sam-
pling.   This would require the use of dilution air to decrease the mass
concentration entering the instrument to < 500
                                    166

-------
           The recently developed method of laser holography offers a po-
 tential for remote particle size analysis.   Hologram systems have recently
 been designed and used for recording and reconstructing  relatively large
 volumes of particles in the size range from 3 to 1,000 ^ mean diameter.iZzl2/
 3.   Particle  Size  Measurement

          Following collection  of  a  particulate  sample, a method of par-
 ticle  size  determination must be selected.  With the standard sampling
 techniques  utilizing filters as collectors, redispersion of the collected
 particles is  a potential problem.  The methods used to prepare the samples
 for  analysis  can be the  deciding factor  in what  the selected analysis mefchou
 actually measures.   Utilization of cascade impactors, thermal precipitaturs,
 or electrical precipitators minimizes this troublesome factor as optical
 techniques  are generally used in conjunction with these devices.

          Determination  of particle  size cannot  be unique except for the
 special case  of spherical particles.  For irregular dust particles, the
 average dimension along  three mutually perpendicular axes may be used, or
 the  diameter  of a sphere having the  same volume  or the same surface area
 as the particle may be chosen.  Obviously, the more irregular the shape
 of the particles, the greater will be the variations in equivalent diameters.
 For  extremely irregular  particles  like plates, rods, or stars, some other
 measure, such as specific surface  or settling rate, will usually be more
 significant,  in many gas-cleaning processes the settling velocity has
 direct physical meaning, independent of particle structure, and is preferred
 to equivalent diameter.

          Because of the wide variations in particle shapes and sizes, no
 universal method or  apparatus for particle size determination is possible
 even in principle.   Table A-l summarizes the type and character of size-
 discriminating properties that  have served as the basis for particle size
 analysis, as well as classes of measurement techniques.157  Each size analy-
 sis method  depends on some property or combination of properties to distin-
 guish one size from another.   Table A-2 presents examples of devices common
 to each class, and the range of particle size for which each technique is
 likely to be applicable.  References 3,  4,  and 14 present extensive discus-
 sions of particle size analysis and analyzers, and the reader interested in
more details is directed to these sources.

     3.1  Current Practice in Industry

          A major portion of the data currently available on the particle
 size of particulates emitted from industrial  sources  has  been obtained by
using the Bahco Micro-Particle  Classifier.   The Coulter Counter, Whitby
Centrifuge/MSA Sedimentation, and microscopic  techniques  have also  been
                                   167

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                                 TABLE A-l

                   SHORT SUMMARY OF ANALYSIS TECHNIQUES^
           Size-Discriminating Property
        Type                    Character
Geometric
Mechanical or Dynamic
   (in fluids)
Optical
Electrical
Magnetic

Thermal

Physico-chemical
Physical barrier
Inertia
                        Terminal settling
                          velocity
Diffusion


Imaging



Transmission

Scattering


Diffraction



Resistance

Capacitance

Charge



Magnetic particles

Particle deposition

Condensation
Types of Measurement
	Technique	

Sieving
Ultrafiltration

Impaction on surface
Pressure pulse (sonic)

Elutriation
Sedimentation
Decantation
Photo-sedimentation

Particle displacement
Particle deposition

Light microscopy
Ultramicroscopy
Electron microscopy

Spectrum

Single particle count
Macroscopic

Light
X-ray
Laser

Current alteration

Potential pulse

Tribe-charging
Induction charging
Corona cnarging

Particle migration; pulse

Particle migration

Growth of nuclei
                                    168

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                TABLE A-2
SUMMARY OF TYPES OF SEE-ANALYSIS TECHNIQUES
Slie-dlicr
~ Tjfp.
Geometric
Mcrhonicol
nf Dynamic
(in flutdi)

Optical
Electrical
Magnetic
Thermal
Physico-
chemical
mlnallni Proptrty
Chancier or
Mtcrt»n.tfti
Physical barrier
Inorlio
Tcrmmol settling
vcloc ity (in
gravity or ccntri"
fugal fields)
(possibilities of
using electrical
fields exist)

Diffusion
Imaging!
Transmission
• (spectral)
Scattering
Diffraction
Resistance
Capacitance
Charge
Applicable to
magnetic
materials only
Particle deposition
Condensation
Technique and Volitions
Sieving
Uttrnlihtolion
Impar. lion on lufl
Wet
Dry
nee
Pressure pulse (some)
Elutnotion
Sedimentation
Deeanlation (in I
Single Liquid
froctionation
Gas
Sertes Liquid
Cos
Layer Liquid
methods
(differential)
Gas
Suspension Differential*
methods liquid
Integral-
liquid
Integral-gat
quid only)
[Photo-sedimentation (photography of particle streaks)
Porlicle displacement (random walk}
Particle deposition
Light microscopy
Ultromicroscopy (gives mean size only)
Electron microscopy
Extinction measured at function of wavelength
Single porttcfe
count
Right angle (90°)
Angular
Forward
Polarization
Macroscopic (gives mean size only)
Light
X-ray
Laser (hologrophy*reconstruction of diffraction
pattern)
Alteration of current flow by particles
Potentiaf pulse due to particle deposition
Tribo*chorging
Induction charging
Corona charging
Particle mi grot ton in magnetic fields; magnetic
pulses
Particle migration in thermal gradient
Growth of nuclei with controlled super saturation
Eiantple of Common
Applfltui*
Ro-Top (Tyler),' Pulver.t
Sholtor, Sonic Sifter
(All.n-Brodley); eloelro-
formed novel (Buckboe
M*o>»)
M*r*hr0netf Millipore,
Gtlmon
Greenburg-Smlth, Moy,
Andyrfton, Cotiello;
Bottelli
IITRI
Schone
Roller (G); Federal
Pneumatic (C), Bohca (C)
Andrews
Kaultain "Infrasiler";
Gonell; Aminco
Palo Travis (G), Werner
(G), MSA-Whnby (G, C);
Koy. (C)
Micrcmerigraph (Sharpies)
(G); Con i fug* (C)
Pipette (Andreasen) (G);
hydrometer (G); diver
(G), Komack (C); turbi-
diffleter (G,C), differen-
tial manometer; gamma-
ro^ absorption
Sedimtntation balance
(Oden, Cahn, Sartorius)
(G); rnanometer (Weigner)
(G); pendulum (C)
Aerosol spectrometer
(Oa'ii'l (C), ndimenlo-
lion chonnol (C)
Cummlngs
Corey & Stoirmond
Mlllihan cell
Oiffuiion battery
American Optical; Bausch
& Lamb; Leitz; Nikon
Reichert, Tivodo;
Unitron; Vickers; Wild,
Zeiss, etc. Flying-Spot
counters

Hitachi; Norelco; RCA; '
Siemens
Boiley
Royco counter (gas.
liaurd); O'Konski
Owl (monodisperse
oorosols)
Sincfair-Phoenix (aerosol
concentration)

Slat Volt Co.
Coulter counter

Guylon counter
Drozin and LaMer; Mercer

Cas.ello;
GE condensotion nucloi
counter
Rjnje of
Appliciult Pj'tlq'*
Oljmelir," !
Micron I I
!/ 1000 ;
0.01 S
0,1 K'O
10- 1000' 'I
5 100
l-IOO(G)
0.02- IOIC)
0.002- I(UC)
1 \W.)
1 lOWOi
0.01-1
0.2-100
0.005-1
0.002-15
0.1-2C)
0.2-50
(higher with
microwave)

1-100

1-30

0.1- lOf?) !
0.01-0. 1C)
* Items in parentheses hove following significance: C - in centrifugal field; G = in gravity field; UC * uitNKMtrlfug*.
1 Replicas may b« used in place of particles that might evaporate or be destroyed during measurement, e.g,, in electron microscopy to ovoid the effect of voct/*mi
or electron beam, and in magnesium oxide film method for measuring size of drops
                  lea

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used.  Cascade impactors,  such as the Andersen and those developed by
Pilat,iiii£/ are just beginning to be introduced  in  routine stack sampling.
Since in this program nearly all the data used to estimate fine particle
emdssionn were obtained  b.y one of the above; methods, the capabilities of
each method will be discu.'ined In come detail.
          3.1.1  Banco c la s s i f ie r ;  The Bahco Micro-Particle Classifier is
used extensively for routine measurements by control device manufacturing
companies .  The Bahco instrument is a  combination air eentrifuge-elutriator
consisting of a brush feed system and  a rotor assembly.  The Bahco instru-
ment separates a dry dust into nine fractions, according to terminal set-
tling velocity.  It does this by subjecting the particles to a centrifugal
force, which is opposed by a current of air.  The dust is thus divided into
an elutriated or fine fraction and a settled or coarse fraction.  By varying
the air flow through the instrument, it is possible to change the particle
size limit of division and thus the material can be divided into any number
of fractions with limited particle size ranges.  Eight throttles or air-
orifice settings are used successively to permit the collection of nine
fractions.  If the weight and some measure of particle size of each dust
fraction are known, a particle-size distribution curve can be plotted .2±i/
A simplified schematic diagram of a Bahco unit is shown in Figure A-4.15/
                 1.  Electric Motor      9.
                 2.  Threaded Spindle   10.
                 3.  Symmetrical Disc   11.
                 4.  Sifting Chm        12.
                 4.  Sifting Chamber    13.
                 5.  Container          14.
                 6.  Housing            I 5.
                 7.  Top Edge           16.
                 8.  Radial Vanes
Feed Point
Feed Hole
Rotor
Rotary Duct
Feed Slot
Fan Wheel Outlet
Grading Member
Throttle
        Figure A-4 - Simplified Schematic Diagram of a Bahco-Type Micro-
                      Particle Classifier Showing Its Major Components'^/
                                     170

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           Failure to disperse the particles adequately as discrete particles
 is a major source of error with the Bahco instrument.   Also,  friable par-
 ticulate matter may be broken by the analyzer and nonrepresentative size
 distributions will be obtained.  Another common and inherent  error in all
 elutriation techniques is that the fluid velocity is not constant  across
 the ducts, so that the assumption of particle velocity equal  to fluid
 velocity is usually invalid.  In addition, the fractions obtained  from
 elutriation do not have a sharp size distribution, so  that average, esti-
 mated sizes have to be assigned.  No quantitative measure is  made  of the
 amount of dust lost during transfer into and out of the instrument, but the
 loss can be miniwr'.cd by careful handling.  The range  of applicable partici<>
 diameter for the Bahco instrument is b to 60 jj,.

           3.1.2  Coulter Counter;  The Coulter Counter utilizes a  change
 in electrolytic resistivity to determine particle size.  The  instrument de-
 termines a number-volume particle-size distribution of particles suspended
 in an electrically conductive liquid.  The suspension  flows through a small
 aperture having an immersed electrode on either side.   The particle con-
 centration is made low enough that the particles traverse the aperture one
 at a time in most cases.i^/  A simplified layout of the Coulter. Counter is
 presented in Figure A-5.i§/

           Each particle passage displaces electrolyte  within  the aperture,
 momentarily changing the resistance between the electrodes and producing a
 voltage pulse, presumably proportional to particle volume. The resulting
 series of pulses is amplified, scaled, and counted using pulse-height
 analysis.

           In order to have the Coulter Counter response proportional to
 size, a highly conducting medium is required, about 0,1 M electrolyte.  In
 some instances this type of medium may interact with and/or solvate the
 particles and alter their size-to-voltage response ratio.   Other potential
 sources of error are poor particle dispersion and the  response of  the in-
 strument to physical-chemical properties of the particulate matter other
 than particle volume.  The size range of applicability of this instrument
 is approximately 0.3 to 100 jj,.

           3.1.3  Differential sedimentation;   The MBA-Whitby  device is based
 on the differential layer sedimentation technique.   Basic  to  the method
"are specially designed centrifuges that have  speeds constant  to  withir. l£
 and whose speed versus time curves during starting and stopping are known
 and constant enough so that corrections do not vary by more than ±0.5 sec.
 Centrifuges of 300, 600,  1,200, 1,800 and 3,600 rpm whose  starting  and
 stopping characteristics  are controlled by a  combination of an inertia disk
 and a variable resistor in series with one winding  of  the  motor  have been
 developed.  Special centrifuge tubes and a feeding  chamber are employe^.

                                     171

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172

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          At the beginning of a size analysis, the  clean tube is filled to
the line near the top of the tube with a suitable sedimentation liquid
(Figure A-6).  Next a suspension of particles is made up in a liquid that
is irascible with the sedimentation liquid but has a slightly lower density
and a slightly higher viscosity, in order to minimize density streaming.
An aliquot of this suspension is placed in  a feeding chamber and then trans-
ferred to the sedimentation tube, leaving a sharp layer of suspension on
top of the sedimentation liquid.  Then, at  the time calculated from Stokes'
equation for desired sizes, the sediment height is  read.  When the particle-
size distribution lies below 20 to 30 jj,, the sedimentation tube is trans-
ferred to the lowest speed centrifuge and run for precalculated times,
after which the sediment height is observed.  The ratio of the sediment
height at any time to the final height of sediment  is assumed to give the
fraction larger than the size calculated.
               FEEDING  CHAMBER
             40-MESH  WIRE SCREENlJX
                                          1.4 CM.
                        1.1  CM.
                 FILLING
r


i
12.5
i
C
             0.75 OR 1.0 MM.
                    CAPILLARY
             Figure A-6 - Centrifuge Tube and Feeding Chamberi§/
                            Design According to Whitby
                                   173

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          Sediment height is assumed to be proportional to sediment weight.
When complete dispersion of particulate matter is achieved, this is a good
assumption, because one-size particles are essentially settling at one time,
and the void space is independent of size for monodisperse systems.  In many
cases, however, strong aggregates of small particles exist; for example,
2-p, silica particles are aggregates of 0.01 to 0.03 ultimate particles.  In
these cases, compression of the sediment column with increasing centrifuge
speed takes place, and bulk density correction factors must be used.16/

          Another complication with this device is that no temperature con-
trol is provided, so that data obtained in non-air-conditioned laboratories
are suspect.  When a material having a narrow size distribution is studied,
many particles may enter the capillary at the same time, causing plugging.
Although a tapper is provided to minimize plugging and surface diffusion
after settling, it disturbs sedimentation.  In some cases involving trans-
parent particles, serious difficulty may arise in deciding where to read
the sediment height, because a sharp line is not apparent.  With proper
choice of sedimentation fluids, distribution of particle sizes in the range
of 0.1 to 80 p, can be measured with this device .M/

          3.1.4  Optical techniques; Optical techniques are the most direct
method for particle-size distribution measurements.  Theoretically, the
applicability range of optical methods is unlimited; but practical limita-
tions and availability of more expedient techniques make microscopy a less
desirable tool in certain size ranges.

          Microscopic examination is generally considered most reliable
for particle size analysis provided samples are properly prepared, the
particles are all or nearly all of one geometric shape, and enough of them
are measured to give statistically reliable data.  Inevitably, these methods
are difficult and time-consuming.  The particles must be magnified to such
an extent that individual particles can be examined and their dimensions
measured.  Of course, the images may be photographed and the analysis made
from the photographs.  The particle-size distribution is then determined
from the individual particle data.  Optical techniques are generally used
in conjunction with impactors, thermal precipitators, and electrostatic
precipitators.

          Table A-3 shows the particle size regions of applicability of
several microscopic techniques.  The lower limits are imposed by the at-
tainable resolving power.  A particle cannot be resolved if its size is
close to the wavelength of the light source.
                                   174

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                                 TABLE A-3

               RANGE OF APPLICABILITY  OF MICROSCOPIC TECHNIQUES

                  Method               Normal Size Range

               White light                  0.4  - 100
               Ultraviolet  light            0.1  - 100
               Ultramicroscopy              0.01 - 0.2
               Electron microscope          0.001 - 5
          The  errors  involved  in the microscope method can be broadly
grouped  in  four  categories:  technique of slide preparation including sam-
pling, dispersion  and mounting; the optical arrangements; technique of par-
ticle measurement  including questions of aggregation, shape factor and
choice of diameter; and  counting procedures.

          Significant results  from light microscopic measurements depend, first,
on  depositing  a  representative sample on a substrate by one of the sampling
methods  or  on  redispersing the sample effectively when a mass of material has
been collected,  perhaps  with a filter.  If the particle collection method,
perhaps  impingement or thermal precipitation, produces a deposit on a glass
slide, the  particles  can be measured directly, provided the deposit is not
dense (i.e., minimal  superposition).  When the collection is on a membrane
filter,  measurements  can be made directly if the filter is made transparent.

          Extreme  care must be taken to ensure that a representative portion
of any bulk sample is selected for analysis and that no classification occurs
during microscope-slide  preparation procedures.  One method commonly used to
distribute  fine  particles over a slide is to disperse the particles by means
of agitation in  a  nondissolving liquid containing, usually, a dispersion
agent.   Stirring is continued to avoid any settling of the larger particles.
A drop of this suspension is placed on the microscope slide for measurement.
Classification may occur on the slide as the liquid evaporates.  In so doing,
small particles  tend to  migrate to the liquid boundaries, while the larger
ones stay in place.  If  this is the case, individual particle measurements
may be made by passing through the center of the deposit and examining par-
ticles from one  periphery to the other.   Sometimes classification caused by
liquid evaporation can be avoided by spreading the suspension as quickly as
possible  into a  thin film.  A proper concentration of the particle sus-
pension  can be obtained only by experience or the trial-and-error approach.

          Because separating previously  collected particles  into  discrete
entities without actually producing particle  disruption  is often  difficult,
the dispersing or wetting agent must be  carefully chosen  and only sufficient

                                    175

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 agitation provided  to  achieve the required dispersion.  Lists of agents for
 use with a number of materials have been prepared. J-4,16/  jn some cases,
 when  analyzing a mass  of  collected aerosol material, complete dispersion
 may not  be desirable.  What may really be desired is the degree of agglomera-
 tion  that prevailed in the aerosol state.  Direct sampling by precipitation
 on a  slide is best  for this purpose.

           Under a microscope a particle is seen as a projected area whose
 ilimensions depend on the  orientation of the particle on the slide.  In
 order to get consistent measurements of the profiles of irregularly sized
 particles it is essential to adopt certain conventions; in practice, the
 most  suitable
          1.  Martin's diameter, which is the length of a line intercepted
by the profile boundary which approximately bisects the area of the profile.
The line may be drawn in any direction, but must be maintained constant for
all the profile measurements.

          2.  Feret's diameter — length between two tangents on opposite
sides of the particle and perpendicular to the bottom of the microscope
field.

          3.  The diameter of the circle whose area is equivalent to the
projected area of the particle.

          Most observers find it easier to use the equivalent circle method.
To facilitate use of this method, a graticule, which has a series of cir-
cles of different diameter scribed on it, is placed in the microscope eye-
piece ,14/

          A real difficulty in size estimation arises with some precipitated
materials and sintered powders in which the partieulate may be aggregates
which are unaffected by dispersing agents.  Such aggregates may have a very
open  structure and extremely variable shape, together with a rather in-
definite density depending on particle size.  The density may vary from the
true material density for the smallest particle to a quite low figure for
the largest aggregates.  In such cases an approximation must be made in
order to obtain figures for the weight distribution.  A suitable one might
be to measure the equivalent circle diameter of the aggregates, but to use
for each size group an estimated density based on the apparent closeness of
packing in the aggregates or found from settling tests on individual aggre-
gates .li/

          Many particulates emitted from industrial sources contain a high
proportion of particles smaller than 0.5 ^ in diameter, and for these very
fine particles electron microscopy provides a direct means of measuring

                                   176

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size and shape.  The electron microscope is the ultimate tool used to ref-
erence submicron particles to the size parameter.  It is the only means of
obtaining a full-size analysis of extremely small samples containing par-
ticles in the size range 0.001 to 5 jj,.  As the instrument uses electron
lens or objectives of very small numerical aperture, it has a large depth
of focus, while its resolving power is many times greater than that of the
visible light microscope.

          Electron microscopy requires specialized techniques for specimen
preparation and these require some consideration if the utility of the
method is to be fully appreciated.4>.16/  Selection of the proper technique
for preparing for electron microscope measurements depends on the kind of
information sought, the condition of the sample, and the physical proper-
ties of the particles, just as in light microscopy.  Likewise, other prob-
lems encountered are those of securing a representative sample and getting
it sufficiently dispersed for individual particles to be distinguished one
from another.

          Direct examination of the particles from an aerosol is possible
if the particles are deposited directly on prepared specimen grids by means
of thermal or electrical precipitation.  Caution should be exercised here,
for particle classification can inadvertently occur depending on the loca-
tion of the grids.  Several grids placed at various locations in these
samplers should be exposed unless the aerosol is known to contain a narrow
particle size range.

          Because of the very small field of view available and the con-
sequently large number of plate exposures which must be made in order to
count sufficient particles for an accurate analysis, electron microscopy
is not suitable for routine analysis.  However, the method is invaluable
as a reference method when the time involved in specimen preparation may be
justified.
                                   177

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                                  REFERENCES
 1.  Parkes, G. J., "Some Factorn Governing the Deaifjn of Probou for nim-
       pling in Particle- and Jjrop-Jnden ;;t;reumr.," Atmospheric Knvlro runout,
       Vol. 2, 477-490 (l'JC.0).

 2.  Strauss, W., Industrial Gas Cleaning, Pergaiaon Press, New York (1966).

 3.  Cadle, R. D., Particle Size - Theory and Industrial Applications,
       Reinhold Publishing Corporation, New York (1965).

 4.  Cadle, R. D., Particle Size Determination, Interscience Publishers,
       New York (1955).

 5.  Sales Brochure, "Andersen Air Samplers," 2000, Inc., South State Street,
       Salt Lake City, Utah.

 6.  Bush, A. F., and E. S. C. Bowler, "Electron Microscopy Studies of  a
       Coal-Fired Steam Electric Generating Stack Discharge," Report No.
       S.I. 395, Department of Engineering, University of California,
       Los Angeles, California, December 1965.

 7.  Bush, A. F., and E. S. C. Bowler, "Electron Microscope Studies of  a
       Bag Filterhouse Pilot Installation on a Coal-Fired Boiler,"  Report
       No. S.I. 405, Department of Engineering, University of California,
       Los Angeles, California, September 1966.

 8.  Bush, A. F., and E. S. C. Bowler, "Electron Microscopy Studies of  a
       Steam Electric Generating Stack Discharges," Report No. C 60-79,
       S. I. 8007, Department of Engineering, University of California,
       Los Angeles, California (1960).

 9.  Green, H. L., and W. R. Lane, Particlulate Clouds;  Dusts, Smokes, and
       Mists, 2nd Edition, D. Van Nostrand Company, Inc., Princeton,
       New Jersey (1964).

10.  Flesch, J. P., "Calibration Studies of a New Submicron Aerosol Size
       Classifier," Journal of Colloid and Interface Science, 29 (3),
       502-509 (1969).

11.  Private communication, Prof. M. J. Pilat, University of Washington,
       Seattle, Washington, November 1970.

12.  Bosch, J. C., "Size Distribution of Aerosols Emitted from a Kraft
       Mill Recovery Furnace," M. S. Thesis, University of Washington,
       Seattle, Washington (1969).
                                     178

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13.  Lapple, C. E., "Particle-Size Analysis and Analyses," Chemical
       Engineering, .149-156, May 20, 1968.

14.  Harden, G., Small Particle Statistics, 2nd Edition, Butterworth's
       Scientific Publications, London (i960).

15.  Sales Brochure, If. W. Dietert Company, Detroit, Michigan.

16.  Irani, R. R., and C. F. Callis, Particle Size;  Measurement, Inter-
       pretation y. and Application, John Wiley, New York (1963).

17.  Thomson, B. J., et al., "Application of Hologram Techniques for
       Particle Size Analysis," Applied Optics, Vol. 6, No. 3, 519-526
       (1967).

18.  "Holographic Determination of Injected Limestone Distribution in
       Unit 10 of the Shawnee Power Plant," TRW Report 14103-6001-RO-OO,
       June 1970 (Contract CPA 22-70-4).

19.  "Investigation of Scattered Light Holography of Aerosols and Data
       Reduction Techniques," TRW Report 14103-6002-RO-000, November 1970
       (Contract CPA 22-70-4).
                                   179

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                  APPENDIX B


ADVERSE EFFECTS OF PARTICULATES ON HUMAN HEALTH
                    181                    .,  -,
                            Preceding page blank

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 Summary

           The  adverse  offsets  caused by particulate  matter on hurn.Mn h
 are, for  the most  part,  related  to injury to the  surfaces  o1' the  re::pi r.-ii,ory
 system.   Particulate material  in the respiratory tract may  produce injury
 itself, or it  may  act  in conjunction with gases,  altering  their sites  or  their
 modes of  action.   A combination  of particulates and  gases  may produce  &n
 effect  that is greater than the  sum of the effects caused  by either individ-
 ually (i.e., synergistic effect).

           Laboratory studies of  man and other animals show that the depo-
 sition, clearance,  and retention of inhaled particles is a very complex
 process,  which is  only beginning to be understood.   Particles 'cleared  from
 the respiratory tract  may exert  effects elsewhere.   Available data from
 laboratory experiments do not  provide  suitable quantitative relationships
 for establishing air quality criteria for particulates.  These studies do,
 however,  provide valuable information on some of  the  bio-environmental
 relationships  that  may be involved in  the effects of  particulate  air pollution
 on human  health.

           Toxicological  studies  on animals have shown that:

           1.   Particulate matter may exert a toxic effect  via one  or more
 of three mechanisms:

                (a)  The  particle may be  intrinsically toxic  because  of its
 inherent  chemical and/or physical  characteristics.

                (b)  The  particle may interfere with one or more of the
clearance mechanisms in  the  respiratory tract.

                (c)  The  particle may act as  a carrier of an adsorbed toxic
substance.

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

          3.   The toxicological  importance  to mankind of submicron particles
cannot be overemphasized.

          4.  Particles below  1  ^ may have  a greater  irritant potency th&n
larger particles.

          5.  A small  increase in concentration could produce a greater-then-
   linear increase  in  irritant response when the particles  are < 1 .|i.

                                    182

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          6.  All particulate matter does not potentiate the response to
irritant gases.

          7.  Both solubility of sulfur dioxido in  a droplet and catalytic
oxidation to sulfuric  acid play a role in the potentiation of sulfur dioxide
by certain particulate matter.

          The analyses of numerous epidemiological  studies clearly indicate
an association between air pollution, as measured by particulate matter
accompanied by sulfur dioxide, and health effects of varying severity.  This
association is most firm for the short-term air pollution episodes.  The
studies concerned with increased mortality also show increased morbidity.

          The association between long-term residence in a polluted area
and chronic disease morbidity and mortality is somewhat more conjectural.
However, in the absence of other explanations, the  findings of increased
morbidity and of increased death rates for selected causes, independent of
economic status, must still be considered consequential.

          Information is lacking regarding the mechanisms involved in the
enhancement of viral virulence by specific air pollutants.  Specific methods
by which air pollutants can synergistically affect  viral infections are
unknown.  It is possible thot fine particulate matter may act as carriers
for certain virus agents.
                                    183

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 1.   Introduction

           The  effects  on man and his  environment  of particulate matter  are
 produced by  a  combination of particulate  and  gaseous pollutants.   The effects
 on human health  are, for the most pert, related to  injury  to  the  surfaces
 of the respiratory  system.   Such injury may be permanent or temporary.  It
 may  be confined  to  the surface,  or it may extend  beyond, sometimes producing
 functional or  other alterations.   Particulate material  in  the respiratory
 tract may produce injury itself,  or it may act in conjunction with gases,
 altering their sites or their modes of action.  A combination of  particulates
 and  gases may  produce  an effect  that  is greater than the sum  of the effects
 caused by either individually (i.e.,  synergistic  effect).

           Laboratory studies of  man and other animals show clearly that the
 deposition,  clearance,  and retention  of inhaled particles  is  a very complex
 process,  which is only beginning to be understood.   Particles cleared from
 the  respiratory  tract  may exert  effects elsewhere.   Available data from
 laboratory experiments  do not provide suitable quantitative relationships"
 for  establishing air quality criteria for particulates.  These studies do,
 however,  provide valuable information on  some of  the bio-environmental
 relationships  that  may be involved in the effects of particulate  air pollution
 on human health.

           The  following sections  present  an overview of (l) the physics  ^
 and  physiology of deposition, retention,  and  clearance in  the respiratory
 system;  (2)  toxicological studies of  atmospheric  particulate  matter; and
 (3)  epidemiological studies  of atmospheric particulate matter.
2.  Deposition, Retention, and Clearance Processes in the Respiratory ,
      System

          An understanding of the effect on human health of particulate
pollutants requires knowledge of the following processes:                ;

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

          2.  Retention mechanisms;

          3.  Clearance mechanisms; and

          4.  Secondary relocation to other sites in'the body.

Theoretical and experimental studies have been conducted to define the fac-
tors involved in deposition, retention and clearance processes.  The princi-
pal results of these studies are summarized in the following sections.
                                   184

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      2.1  Deposition

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

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

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

           3.  Diffusion (Brownian motion) -  major mechanism for the depo-
 sition of  small particles  (below 0.1 (a,) in the lower pulmonary  tract.

           Hie effectiveness with which the decomposition forces remove
 particles  from  the  air  at  various sites depends upon the obstruction en-
 countered,  changes  in direction of air flow,  and the magnitude  of particle
 displacement necessary  to  remove them  from the  air stream.   The anatomical
 arrangement and physical dimensions  of the respiratory system,  transport
 mechanisms, flow rates  and gas  mixing,  and aerosol particle  size  are important
 factors  that must be considered in any physical analysis of the deposition
 of  inhaled aerosols.

           The Task  Group on Lung Dynamics  has  recently developed  a model
 for the  deposition  of particles in the  respiratory tract.^/  Findeisen's
 anatomical model?/  was  chosen  as the basis for  the Task Group Model.   The
 Task Group used the  conventional division  of the  respiratory tract into
 three  compartments  (nasopharyngeal,  tracheo-bronchial,  and pulmonary),
 and made three  fundamental assumptions  in  the development of their model.
 These were:£/

           1.  Log-normal frequency distribution is  generally applicable  to
particle sizes  in the atmosphere.

          2.  The physical activity of  the individual  affects deposition
primarily by its  action on ventilation.

          3.  The aerodynamic properties of the particle,  the physiology
of respiration,   and the anatomy of the respiratory  tract provide  a basis  for
a meaningful and reliable  deposition model.

                                     185

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           Calculations,  basically similar to those of Findeisen,  were  used
 to  estimate  the  deposition in the three  respiratory compartments.   When
 the mass median  aerodynamic diameters of  0.01 to 100 (a, of various  distri-
 butions  were plotted against the estimated mass deposition of particles
 occurring  in each  respiratory compartment,  surprisingly little variability
 was seen.  The geometric standard deviation for these distributions varied
 from  1.2 to  4.5.   The results of these calculations are shown in  Figure
 B-1.2/  The  curves indicate a relationship  between the mass median aero-
 dynamic diameter and  the gravimetric  fraction of the inhaled particles
 which would  be deposited in each anatomical compartment.   Within  these limits
 (0.01 to 100 ji), the-mass median aerodynamic diameter served to characterize
 the deposition probabilities of the entire  particle size  distribution.  Other
 pnr rime trie functions  of  the particJo  distribution failed to produce such
 uimple cohesive relationships.!^/ Figures B-2 and B-?> present plots  of  the
 mass  median  diameter  versus mean respiratory performance.   The deposition in
 the tracheo-bronchial compartment is  considered as constant at approximately
 8%  of the respired particulate matter.

          2.1.2  Experimental studies;   Experimental studies of the deposi-
 tion  of inhaled particulate material  may be divided into  two broad cate-
 gories.  The first group deals with the  measurement of total deposition in
 the respiratory tract, and the second group is  concerned with regional
 deposition within  the  various  areas of the  respiratory tract.   Details of
 these experiments  are  given in Refs.  1 and  4.   The following points can be
 made  with respect  to  the  overall retention  characteristics  of the  respiratory
 system:!/

          1.  Percentage  deposition increases with aerodynamic particle
 size from a  minimum value  of  about 25% at approximately 0.5  y. and  approaches
 100$ for particles  > 5 \i.   Particles -of  different  densities  and shapes
 follow the same deposition curve  wh'?n size  is expressed in  terms of equivalent
 diameter of  unit-density  spheres.

          2.  Percentage  deposition also increases  as  particle  size  decreases
below 0.5 M,  owing  to the  increasing magnitude of the  force  of deposition
by  diffusion.  For  particles < 0.1 p,, the percentage  deposited out of  the
 total respired air  approaches,  in value,  the  fraction of tidal volume  which
reaches the  pulmonary  air  spaces.  This  fact  suggests  that  the  absolute
efficiency of alveolar deposition of  these  submicron  particles  approaches
100%.

          3.  Particles of hygroscopic materials  are  removed in higher per-
centages than are  nonhygroscopic  particles  of the  same  (dry) size  because
of the growth of such particles by water  adsorption from the moist air  in
the respiratory system.
                                    186

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                   NASOPHARYNGEAL
             MASS MEDIAN DIAMETER, MICRON
Figure B-l - Fraction of Particles Deposited in the Three
               Respiratory  Tract Compartments as a
               Function of  Particle Diameter^/
                        187

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           4.   Percentage deposition varies with br^wthing frequency, in-
 creasing,  for n heterogeneous aerosol, in both directions from a minimum
 level et frequencies of ]5 to I'O cycl''C/min.  At slower rates, the prob'ibNi'.y
 of deposition by gravity settlement and diffusion goey up in proportion to
 the increase  in transit time of the dust-laden eir into and out of the lungs.
 With more  rapid breathing, percentage deposition of the coarser particles
 increases  because of the rise in force of  inertial  deposition with increasing
 air velocity.

           5.   There  is reasonably good agreement between the directly mee-
 sured values  of overall deposition and the levels predicted from mathematical-
 physical equations,  with respect to both particle size and dynamics of air
 flow into  and out of the respiratory system.  Thus,  in its behavior as a
 dust-trapping device,  the respiratory system appears to act very much like
 any other  similar physical apparatus.

           The differing characteristics of particle  retention at various
 depths within the respiratory system may be summarized as follows:—'

           1.   Particles larger than 10 n are essentially all removed in the
 nasal chamber and therefore have little probability  of penetrating to the
 lungs.   Upper respiratory efficiency drops off as size decreases and becomes
 essentially zero at  about 1 |j,.

           2.   The efficiency of particle removal is  high in the  pulmonary
 air spaces, being essentially 100$ down to around 2  p-«  Below this size it
 falls off  to  a minimum at about 0.5 jj,.   It then increases again  as the force
 of  precipitation by  diffusion increases with further reduction in size.

           3.   The percentage  penetration of particles  into the pulmonary
 air spaces rises  from  essentially zero  at 10 jj, to a  maximum at and below
 1 n, where it equals the  fraction of tidal air which reaches the  lung.

           4.   Below  0.5 m  the  probability of deposition in the pulmonary
 air spaces rises  in proportion  to the  increase in the  force of precipitation
by  diffusion  with decreasing  size.

          5.   Relative  amount deposited and the  distribution of the  collected
particles  in  the  respiratory  system change  with  breathing frequency and
tidal volume.   Upper respiratory trapping increases  as the  rate of inspired
air flow goes  up  with  faster  breathing  frequency.  Magnitude  of deep-lung
deposition increases with slow,  deep breathing because  of the  larger frac-
tion of tidal  air which reaches  the  pulmonary spaces and the  longer transit
time of air into  and out of the  lungs.
                                     189

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      2.2   Clearance  of Particulate  Matter from the  Respiratory System

           The  overall effectiveness of clearance  mechanisms  in the  lung is
well  documented by the finding that the actual amount of mineral dust found
in  the  lungs of miners or city dwellers at autopsy  is only a minor  fraction
of  the  total dust  that must have been deposited there  during  their lives.
The clearance  of certain particles  may be very slow,  and the rate is  dependent
upon  size,  site of deposition,  and  chemical composition.

           Relative to other  factors,  the  importance of removal from the
respiratory system of trapped particulate materials depends  on the  rate at
which the  material elicits a pathological or physiological response.   The
effect  of  an irritant substance which produces a  rapid response may depend
more  on the amount of initial trapping than on the  rate of clearance.   On
the other  hand, materials such as carcinogens,  which  may produce a  harmful
effect  only after  long periods  of exposure,  may exhibit activity only if the
relative rates of  clearance  and deposition are  such that a sufficient con-
centration of  material remains  in the body long enough to cause pathological
change.  In such a case,  the  amount of initial deposition will be of  rela-
tively  minor importance,=J

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

           The  Task Group on Lung Dynamics developed a model  for  respiratory
clearance  and  also summarized experimental work on clearance.   Details  of
the model and  the  analysis of experimental data are presented in Refs.  1
and 2,  and  the  reader  interested in  a more complete discussion  of respiratory
clearance is directed  to these  sources.
                                    190

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 3.   Toxicological Studies of Atmospheric Particulate Matter

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

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

           In spite of  these limitations,  toxicological  studies  have  shown that
 atmospheric  particles  may elict a  pathological  or physiological response.
 Three types  of  responses have been determined:

           1.  The particle  may be  intrinsically toxic;

           2.  The presence  of an inert particle  in the  respiratory tract may
 interfere  with  the clearance  of other airborne  toxic materials;  and

           3.  The particle  may act as a carrier  of toxic  material.

           Few common atmospheric particulate  pollutants  appear  to be  in-
 trinsically  toxic; of  these,  the most important  toxic aerosol is  sulfur
 trioxide (SOs)  (either as  the  free  oxide,  or  hydrated as  sulfuric  acid—
 112804), which has a high  degree of toxicity,  at  least for the guinea pig.
 Although silica (from  fly ash) is  frequently  present as a pollutant,
 atmospheric concentrations  are  normally too low  to  lead to  silicosis.   In
 recent years, however, concern has  been expressed over a  number of less
 common toxic particulate pollutants,  including lead, beryllium, and asbestos.

           Toxic substances may be adsorbed on the surface of particulate
matter, which may then carry the toxic  principle into the respiratory  system.
 The presence of carbon or soot  as  a common particulate pollutant is note-
worthy, as carbon is well known as  an efficient  adsorber  of a wide range of
organic and inorganic compounds.
                                    191

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           The  role  played by the  affinity for the  adsorbate  by the particle
 is  complex.  A high affinity will mean that relatively large loads of ad-
 sorbate  may be carried by each particle.   If the  adsorbate in its  free state
 is  slowly removed from the air in the  respiratory  system,  then the deposi-
 tion of  particles carrying high concentrations may constitute a greater toxic
 hazard,  especially  at the localized deposition points.  Whether or not the
 effect is significant .depends on  whether  the efficiency of the desorption
 and elution processes is  greater  or less  than that of the  clearance process.
 The chemical nature of both adsorber and  adsorbate,  and the  size of the ad-
 sorbing  particle, all play a part in determining these various efficiencies,
 and each system will show its own individual characteristics.

      3.1  Toxicological Studies of Specific Particulate Materials

           Certain particulate materials are pulmonary irritants, and have
 been shown to  produce alterations in the  mechanical  behavior of the lungsj
 the alteration is predominantly an increase in flow  resistance.  This was
 demonstrated by Amdur for sulfuric acid,Z/ and by  Amdur and  Cornjy  for am-
 monium sulfate,  zinc sulfate,  and zinc  ammonium sulfate, using the guinea
 pig as an assay animal.   Nader and co-workers report a correlation between
 the alterations  in  pulmonary mechanics  and actual  anatomical change in cats
 exposed  to aerosols of histamine  and zinc ammonium sulfate.§/

           The  effect of various aerosols  on the response to  SOg  has also been
 also examined, using the  guinea pig bioassay system.   These  data are pre-
 sented in detail in Ref.  9.   Conditions which lead to the  solution of SOg
 in  a droplet and catalyze its  oxidation can alter  the irritant potency of
 levels of SOg  which occur in areas of high pollution.   The concentration of
 the  catalytic  aerosols  (soluble salts of  iron,  manganese,  and vanadium) was
 of  the order of  1 mg/m3 which is  higher than concentrations  reported for
 these metals in  urban air.   Particles which do not form liquid droplets, i.e.,
 non-soluble  salts such  as iron oxide fume,  carbon  fly ash, open  hearth dust,
 and manganese  dioxide,  did not show a potentiating effect.

           Dautrebande  and DuBois  have reported constriction  and  increased
 airway resistance in isolated guinea pig  lungs and in human  subjects with
 a wide variety of supposedly inert particulates ,12/   The relationship of
 their'results  to Amdur*s  work  is  not clear since Dautrebande*s particle
 concentrations  appear to  be  abnormally  high.

           When a substance is  dispersed in the air in the form of  particulate
matter,  a simple  statement of  its  concentration is insufficient  to define  in
meaningful terms  its  toxic potential.   The  size of the  particles is also a
prime factor in  the  overall  biological  impact of inhaled particulate material.
                                    192

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 This  point can be  illustrated with data obtained by Amdur and Corn for an
 aeroso^ of zinc ammonium sulfate,^J  The investigation of this compound wee
 undertaken because it had been identified as one of the substances'present
 during  the 1040 Donora i'of/.ly   FJj/ure B-4  tihows the response of //u.inea plfis
 to  zJnc nmmoniium ou'lfnlc i\\, n i"on;;Utnl concentration (fibout I  ro#/rn3), !>nt of
 different  pnrtide size;:.   W.illiin the nizc r tinge studied, the  irritant
 potency increased  with d<;<: reusing partJcle size.  Figure B-5 shows the more
 extensive  data obtained on the dose-response curves of zinc ammonium sulfato
 at  different  particle sizes.   These data show that not only is the irritant
 effect  greater for the smaller particles at a given concentration, but also
 the dose-response  curve steepens as the particle size is decreased.   Thus,
 if  an irritant aerosol is  composed of very small particles, a  relatively
 slight  increase in its concentration can produce a relatively  great increase
 in  irritant response.

           From the analytical datajy  it can be estimated that  the concentra-
 tion  of zinc  ammonium sulfate  present during the Donora fog might have been
 on the  order  of magnitude  of  0.05  to 0.25  mg/m^.  The toxicological  data
 can in  no  way be extrapolated to predict what, if any,  contribution  this
 substance  made to  the  overall irritant character of the atmosphere.   On the
 other hand, the  data  do indicate that without information on particle size,
 such predictions are  not possible.

           The  possible  influence of inert  particulate matter on the  toxicity
 of irritant gases  has  been the  subject of  considerable  speculation and a
 limited amount of  experimental  work.   Work on the  synergistic.effects of
 aerosols and  irritant  gases  is  reported in Refs.  11 to 19.  The potentiation
 of irritant gases  by particulate material  noted in these  studies was  attrib-
uted to  the adsorption of  gas on the  particles.   Adsorption of the gas on
 small particles would  tend to carry more gas  to  the  lungs  and  thus increase
 the toxicity.   Unfortunately  in many  of these  studies,  the  end point  was the
 dosage  required to produce  death.  With concentrations  of this magnitude,
 the results have little  applicability to air pollution.

           Amdur has studied the  effect of  particulate material on the
response to sulfur dioxide using the  pulmonary flow  resistance technique.
 None of the aerosols used  in the studies produced  any effect alone.£/  From
 these studies  it appears that the major mechanism  underlying the  potentia-
tion is solubility of  sulfur dioxide  in a  droplet  and subsequent catalytic
oxidation  to  sulfuric  acid.
                                    193

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   200-
   100-
   50^
   20-
   10
    5-
                                        10
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^*    1
    0.01   0.05      0/50
AEROSOL MEAN SIZE BY WEIGHT, MICRON
                                                 111 ii
                                                 5.0
   Figure  B-4  -  Effect of Particle  Size on the Response to Approximately
                   1 mg/m3 Zinc Ammonium Sulfate.  Numbers beside
                    each point indicate the number of animals.§/
                                                   3.6
                                    mg/n
Figure B-5 - Relationship of Response to Concentration for Zinc Atnmonium
               Sulfate of Different Particle Sizes.  Numbers beside
               each point indicate the number of animals.57
                                    194

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          Figure  B-6  shows the effect of aerosols  of sodium chloride,
potassium chloride,  and ammonium thiocyanate,  at concentrations  of about
10 mg/m^, on  the  response  to about 2  ppm sulfur  dioxide.   All these  sub-
stances are soluble  salts  which would absorb water to become liquid  droplets
at the humidity of the  respiratory tract.   Sulfur  dioxide  is increasingly
soluble in aqueous solutions of these salts as one goes from sodium  chloride,
to potassium  chloride,  to  ammonium thiocyanate.  The degree of potentiation
observed  can  be related in a reasonable  manner to  the degree of  solubility
of sulfur dioxide in  the salt solutions.

          Figure  B-7  shows the results of exposure to about 2 ppm of sulfur
dioxide alone and in  the presence  of  another group of aerosols.   These
aerosols  do not take  on water to become  droplets during transit  of the
respiratory tract, and  have  no detectable  effect upon the  response to sulfur
dioxide.  The combination  of data  in  Figures B-6 and B-7 suggests that
solubility in a droplet plays a role.2/

          Figure  B-8  shows  the dose-response curves  to sulfur dioxide alone
and in the presence of  aerosols of soluble  salts of manganese, iron, and
vanadium.  These  substances  were present at a  concentration of about 1 mg/m^.
They have another property in common.  When such salts become nuclei of  fog
droplets, they are capable  of catalyzing the oxidation of  sulfur dioxide to
sulfuric  acid.§2/ The  addition of these inert particles produced about  a
threefold potentiation  in  the response to  sulfur dioxide.   The similar
magnitude of  potentiation produced by the  three salts suggests a similar
mechanism for the potentiation.  The  data from Figure B-7  showing the lack
of potentiation by dry manganese dioxide or iron oxide would appear  to in-
dicate the importance of solubility.

          Experimental  data  on the  effect  of particulate matter  on the
responses to  sulfur dioxide  in human  subjects  are  very limited.£ii£5/
Furthermore,  there is no general agreement  regarding potentiation by
particulates.  To date human exposures have been disappointing in disclosing
mechanisms of interaction between various  air  pollutants.   On the  other  hand,
there is no evidence  as yet  for  a species difference between animals and
man; therefore, we may extrapolate  judiciously to  man from the animal studies.
Conclusions

          1.  Particulate matter may exert a toxic effect via one or more of
three mechanisms:

               (a)  The particle may be intrinsically toxic because of its
inherent chemical and/or physical characteristics.
                                     195

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Figure B-6 - Effect of Aerosols Capable  of Dissolving

               Differing Amounts of Sulfur Dioxide on

               the Irritant Potency of the Gas§/
Z.
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Figure B-8 -  Effect of Aerosols Which Would Form Droplets
              and Also Catalyze the Oxidation of Sulfur
              Dioxide  to  Sulfuric Acid on the Irritant
              Potency  of  the Gas.  The numbers beside
              each point  indicate the number of animals.^/
                            197

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                ('())  'llu; I'.'irUr li; limy iiitx^r/V-r'; wJth on<: or trio/1'.- of Ui';
 olunruneu mc.'chaniumt; in l,lx: i".:;;pjrulory trfju-t.

                (c)  Ihe particle may act as a carrier of an adsorbed toxic
 substance.

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

           3.   The toxicological importance to mankind of submicron particles
 cannot be overemphasized.

           4.   Particles below 1 M, may have a greater irritant potency than
 larger particles.

           5.   A small increase in concentration could produce a greater-than-
 'linear increase? in irritant response whnn the particles ar*: < ~\ M-.

           6.   All particulate matter does not potentiate the response to
 irritant gases.

           7.   Both solubility of sulfur dioxide in a droplet and catalytic
 oxidation to  sulfuric acid play a role  in the potentiation of sulfur dioxide
 by certain  particulate  matter.
4.  Epidemiological  Studies  of Atmospheric Particulate Matter

           Ihe ultimate  assessment of the  impact of air pollution on human
health can come only from epidemiology.   Because particulate matter and
sulfur oxides tend to occur  together in  a polluted atmosphere,  few epidemic-
logic studies have been able adequately  to differentiate the effects of the
two pollutants.  Because  we  do not now have a good epidemiological basis for
stating the  influence of particulates, only a brief synopsis of epidemiological
studies of atmosphere particulate matter  will be presented.  References 1
and 26 present an extensive  review of epidemiological studies,  and those
seeking more detail  are directed to these sources.

           Epidemiologic studies of the relationship between pollutant con-
centrations  and their effects  on health have  used indices varying from
disturbance  of lung  function to death. British studies of acute episodes
of increased pollution  show  excess deaths occurring at smoke levels from
750 |j,g/m3  to 2,000 ng/m3.  High SOg levels are,  of course, concurrently
present.   The excesses  of mortality are  always accompanied by a very large
                                     198

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increase  in  illness, mainly exacerbations  of chronic conditions.   Similar,
but less  spectacular,  episodes  have  been reported in Now York City.i/

          Winkelstein  found in  Buffalo that increases in the  mortality rate
were significantly linked to higher  levels of suspended particulate pollu-
tion.27/  His studies  showed that mortality from all causes,  from chrord';  .
respiratory  diseases,  and from  gastric carcinoma increased from the lowest
of his five  levels of  pollution (less  than 80 ^.g/m3) through  the  three higher
ranges, after the  effects of socioeconomic status had been considered.
Zeidberg  found  in  Nashville significant increases in all respiratory deaths
at soiling levels  over 1.1 cons annual average.28^29/  Neither of these
studies took smoking habits into account,  and the Nashville study only
partially allowed  for  socioeconomic  factors.

          Studies  of illness in relation to residence in more- and less-
polluted  areas  contribute additional information.   Fletcher e_t al.  noted
a proportional  decline in the production of morning sputum in chronic
bronchitics  in  West London from 1961 to 1966 as  smoke pollution in their
residence areas declined  from 140 (jg/m3 annual mean.30./  Douglas  and Waller
found an  increase  in frequency  and severity of lower respiratory  illness at
smoke and S02 levels over 130 ^g/m3  annual average.3i/  A study of Lunn
ot al. shows similar differences occurring with  more morbidity measured be-
twoen about  100 ^g/m3  and 200 u-g/m3  of smoke,  and for others  between 200
|j,g/m3 and 300 jig/m3 annual average .3§/

          Physiologic  studies of lung  function have  also been made  in both
adults and children.   On  the basis of  present  limited knowledge it  appears
that the  alterations found may  be both temporary and permanent.   The obser-
vations now  available  relate  to long-term  residence  in a given area.   The
study reported  in  Ref.  32 shows reduced pulmonary function in the  children
in the most polluted area,  i.e., where  smoke concentration is above  300 ^tg/m3.
Studies in Japan show  a decrease in pulmonary  function in school  children
living in areas of high dustfall as  compared with  those  living in  low dust-
fall areas.  In Osaka  the  dustfall levels  were 6.5 gm/n^-month and 13.3 gm/m^-
month.33/

          The analyses  of numerous epidemiological studies  clearly  indicate
an association between air pollution,  as measured by particulate matter
accompanied by  sulfur  dioxide,  and health  effects of varying  severity.  This
association is most firm  for the short-term air pollution episodes.   The
studies concerned with  increased mortality also  show increased morbidity.

          The association between longer term community exposures to
particulate matter  and respiratory disease  incidence  and prevalence rates
is believed  to be  intermediate in its reliability.!/
                                     199

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          The association between long-term residence in a polluted area
and chronic disease morbidity and mortality is somewhat more conjecture].
However, in the absence of other explanations, the findings of. increased
morbidity and of increased death rates for selected causes, independent
of economic status, must still be considered consequential.

          Information is also lacking regarding the mechanisms involved in
the enhancement of viral virulence by specific air pollutants.  Specific
methods by which air pollutants can synergistically affect viral infections
are unknown.  It is possible that fine particulate matter may act as carriers
for certain virus agents.  Experimental evidence bearing on this point is
lacking.  The complex interrelationship between the dynamic inflammatory
processes is difficult to define.  So are the equally important irritative
effects of air pollutants and viral infections.
                                    200

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                                   REFERENCES
 1.  Air  Qiality Criteria for Particulate Matter,  USDHEW, NAPCA Publication
       AP-49,  Washington,  D.  C.,  January 1969.

 2.  "Deposition and Retention Models for Internal Dosimetry of the Human
       Respiratory Tract," Task Group on Lung Dynamics, Health Physics,
       12,  173-207 (1966).

 3.  Findeisen,  W.,  "Uber  das Absetzen kleiner  in  der Luft suspendierten
       Teilchen  in der menschlichen Lunge bei der  Atraung," Arch.  Ges. Physiol.,
       Vol. 236,  367-379  (1935).

 4.  Hatch, T. F.,  and Paul Gross,  Pulmonary Deposition and Retention of
       Inhaled Aerosols, Academic Press,  New York  (1964).

 5.  Andur, Mary 0.;  and Morton Corn, "The Irritant Potency of Zinc Ammonium
       Sulfate of Different Particle  Sizes," Amer.  Indust.  Hyg. Assoc.  Journal,
       24_,  326-333 (1963).

 6.  Hemeon, W.  G.  L., "The Estimation of Health Hazards from Air Pollution,"
       Arch. Indust.  Health,  11,  397-402  (1955).

 7.  Amdur, M. 0.,  "The Respiratory Responses of Guinea Pigs to Sulfuric Acid
       Mist,"  Arch.  Ihd. Health,  18,  407-414 (1958).
 8.  Nader, J. A., .et al.,  "Location  and Mechanism  of  Airway Constriction
       after Inhalation of  Histamine  Aerosol  and  Inorganic  Sulfate  Aerosol,"
       Ir:  Inhaled Particles  and  Vapors,,Vol.  11,  C.  N.  Davies  (ed.),  Pergamon
       Press, London (1967).

 9.  Amdur, M. 0., and D. Underhill,  "ihe  Effect  of Various  Aerosols  on the
       Response of Guinea Pigs to  Sulfur Dioxide,"  Arch.  Environ. Health, !£,
       460-468 (1968).

10.  Dautrebande, L., Microaerosols,  Academic Press, New  York (1962).

11.  Dautrebande, L., "Bases experimentales de  la protection centre les  gas
       de combat," J. Duculot  (Belgium) (1939).

12.  Dautrebande, L., and R. Capps, "Studies  on Aerosols.  DC. Enhancement
       of Irritating Effects of Various Substances  in  the Eye, Nose,  and Throat
       by Particulate Matter and Liquid Aerosols  in Connection with Pollution
       of the Atmosphere," Arch. Intern. Pharmacodyn, 82^ 505-527 (1950).
                                     201

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 13.   Dautrebande,  L.,  J, Shaver and R. Capps, "Studies on Aerosols. XI.
        Influence of Particulate Matter on Eye Irritation Produced by
        Volatile Irritants and Importance of Particle Size in Connection
        with Atmospheric Pollution," Arch. Intern. Pharmacodyn, 85^ 17-48
        (1951).

 14.   LaBelle,  C. W.,  J. E.  Long and E. E. Christofano, "Synergistic Effects
        of Aerosols.  Particulates as Carriers of Toxic Vapors," Arch. Ind.
        Health,  11,  297-304  (1955).
 15.   Dalharan,T.,  and L.  Reid, "Ciliary Activity and Histologic Observations
        in the  Trachea after Exposure to Ammonia and Carbon Particles," In:
        Inhaled Particles and Vapours, Vol. II, C. N. Davies (ed.), Pergamon
        Press,  London (1967).

 16.   Boren,  H.  C.,  "Carbon as a Carrier Mechanism for Irritant Gases,"
        Arch. Environ.  Health, 8,  119-124 (1964).

 17.   Gross,  P., W.  E.  Rinehard and R. T. DeTreville, "The Pulmonary Reactions
        to Toxic Gases,"  Am.  Ind.  Hyg. Assoc. J., 2JT, 315-321 (1967).

 18.   Pattle, R. E.,  and  F.  Burgess,  "Toxic Effects of Mixtures of Sulphur
        Dioxide  and  Smoke with Air," J. Pathol. Bacteriol., 73, 411-419
        (1957 ).                                              "*""

 19.   Salem,  H., and H. Cullunbine,  "Kerosene Smoke and Atmospheric Pollutants,"
        Arch. Environ.  Health, 2,  641-647 (1961).

20.   Johnstone, H.  F., and D. R.  Coughanowr, "Absorption of Sulfur Dioxide in
        /_•?-,- o>:i Lition in  Dropn Containing Dis.iolvad Catalysts," Induct. Erg.
        Chc.a., _5Q, 1169-1172  (1958).

21.   Frank,  N. R.,  M.  0.  Amdur and J. L. Whittenberger, "A Comparison of the
        Acute Effects of  SO^  Administered Alone or in Combination with NaCl
        Particles on the  Respiratory Mechanics of Healthy Adults," Intern. J.
        Air & Water  Poll.,  8_, 125  (1964).

22.   Burton, G. G.,  M. Corn, J. B.  L. Gee, C. Vassallo and A.  Thomas, "Absence
        of Synergistic  Response to Inhaled Low Concentration Gas-Aerosol Mix-
        tures in Healthy  Adult Males," Presented at Ninth Annual Air Pollution
        Medical Research  Conference,  Denver,  Colorado (1968).

23.   Toyama, T., "Studies  on Aerosols. I.  Synergistic Response of the
        Pulmonary Airway  Resistance  of Inhaling Sodium Chloride Aerosols and
        S02 in Man,"  Japan J. Ind.  Health,  4, 86 (1962).
                                     202

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24.  Nakamura, K.,  "Response of  Pulmonary  Airway  Resistance  by Interaction
       of Aironola  and Gfiaea in  Different  PhyaJoal  '».nd Chemical States,
                                                                        "
25.   Toyama,  T. ,  and K.  Naknmura, "yynergistit: Response of Hydrogen K- ro /.:.'>.•
        Aerosols  and Sulfur Dioxide to Pulmonary Airway Resistance," Ind.
        Health, 2,  34 (1964).

26.   Speizer, F. E., "An Epidemiological Appraisal of the Effects of Ambient
        Air  on Health:   Particulates and Oxides of Sulfur," JAPCA,
        647-656 (1969).

27.   Winkelstein,  W.,  "The Relationship of Air Pollution to Cancer of the
        Stomach," Arch.  Environ.  Health, 18. 544-547 (1969).
28.  Zeidburg,  L.  D.,  R.  M.  Hagstrom,  H.  A.  Sprague and E. Landau, "Nashville
       Air  Pollution  Study.   VII.   Mortality from Cancer in Relation to Air
       Pollution," Arch.  Environ.  Health,  !£, 237-248 (1967).
29.  Zeidberg,  L.  D.,  R.  J.  M.  Ilorton and E.  Landau, "'Hie Nashville AJr
       Pollution Study.   V.   Mortality from Diseases of the Respiratory
       System in Relation to Air  Pollution," Arch.  Environ. Health,
       214-224  (1967).

30.  Fletcher,  C.  M.,  B.  M.  Tinker,  I.  D.  Hill and  F.  E.  Speizer,  "A Five-
       Year Prospective Field Study  of Chronic Bronchitis," Preprint.
       (Presented  at the  llth Aspen  Conference on Research in Emphysema
       June 1968. )

31.  Douglas, J. W. B., and  R.  E. Waller,  "Air Pollution  and Respiratory
       Infection in Children,"  Brit.  J.  Prevent.  Soc.  Msd., j2
-------
          APPENDIX C

MODIFICATION OF THE ATMOSPHERE
   BY PARTICULAR! POLLUTION
            205
Preceding page blank

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Summary

          Suspended fine particles may have considerable influence on the
behavior of the atmosphere and thus on human activities.  They can act as
condensation or freezing nuclei and thereby modify weather patterns.
They absorb and scatter light and decrease visibility.  Fine particlcc in
the atmosphere may nine influence xnlnr radiation and interfere with
astronomical observation.'; .

          Visibility reduction related to air pollution is caused primar-
ily  by the 0.1 to 1.0 )J, radius particles in the atmosphere.  The visi-
bility problem associated with particulate air pollution can be divided
into specific smoke plumes and well-aged aerosols.  The visual appearance
of smoke plumes and visual obscuration by smoke plumes are closely related
to the amount of light the plumes scatter in the direction of the viewer
from their surroundings and the sun.  Consequently, evaluation of plumes
by a visual effect is more difficult for nonblack plumes than for black
plumes, and depends on plume illuminating and viewing conditions.  Because
of this, nonblack plumes could be evaluated differently when viewed on
different days or viewed from different  directions, though their aerosol
content has not changed.  Furthermore, the size of particles and mass per
unit time emitted from the stack, and not the appearance or optical prop-
erties of the plume, are more important to the eventual air composition,
even though appearance may be aesthetically objectionable.
          Recent advances in our knowledge of the Hize distributions and
optical properties of well-aged atmospheric aerosols have resulted in a
clearer description of visibility reduction by such aerosols.  Theoretical
and experimental studies of well-aged aerosols have shown that:

          1.  Aerosols in the lowest region of the atmosphere (troposphere),
whether over urban areas or not, tend to have similar size distributions.

          2.  A narrow range of particle sizes, usually from 0.1 to 1.0 p,
radius, controls the extinction coefficient and thereby visibility.

          3.  The mass concentration of a well-aged aerosol -is approximately
proportional to the light scattering coefficient for atmospheric aerosols
originating naturally or as the result of man's activity.

          The increased emission of fine particles into the atmosphere may
cause changes in the delicate heat balance of the earth-atmosphere system,
thus altering worldwide climatic conditions.  Comparisons at different
sites over the world covering periods of up to 50 years suggest that a
general worldwide rise in turbidity may be taking place .   This may well  be
indicative of a gradual buildup of worldwide background levels of suspended

                                   206

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particulates.  The net influence of atmospheric turbidity on surface tem-
perature is uncertain, but *ne emission of long-lived particles may well be
leading to a decrease in world air temperature.  As more is learned nbout
the general circulation of the atmo.-iphore and the delicate bnlnncc b •tw-'-n
incoming and outgoing radiation, It r^eems increasingly probable that r;m/ij,i
changes such as those occasioned by increasing particle loads in the atmo-
sphere may produce very long-term meteorological effects.

          Suspended particulate matter may alter weather patterns.  There
is evidence that some of the particles introduced into the atmosphere by
man's activities can act as nuclei in processes which affect the formation
of clouds and precipitation.  Investigations of snow and rainstorm patterns
indicate that submicroscopic particulates from man-made pollution may be
initiating and controlling precipitation in a primary manner, rather than
being involved in the secondary process wherein precipitation elements com-
ing from natural mechanisms serve to remove the particles by diffusion,
collision, and similar scavenging processes.
                                  207

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1.  Introduction

          The suspended atmospheric particles are of four general types.
The first are the  "light ions" produced in the air by cosmic rays and
radioactivity.  They consist of small aggregates of molecules having dimen-
sions up to a few  molecular diameters.  The second important type of par-
ticle consists of  the so-called "aitken nuclei."  These particles range in
radius from 2 x 10  cm. up to 10   cm.  They are particularly prevalent
near cities and the earth's surface.  As a rule of thumb, one anticipates
finding about 100,000 of these particles per cm3 in a large city, about
10,000/cm  in the  country, and about 1,000/cm3 at sea.  The numbers decrease
with increasing altitude and only about 10$ of the surface populations are
found at an Altitude of 7 km.  Thu fine jiurticl^ polDutJori of the air is
largely composed of these nuclei.

          The third type of atmospheric particle is the cloud droplet hav-
ing a radius from  10"^ cm. to 5 x 10"^ cm. Finally, the cloud droplets
associate to form  raindrops or snowflakes  that fall at velocities depen-
dent upon their size.  Rain or snow represents the final stage for the re-
moval of atmospheric pollution by natural methods.

          Suspended fine particles may have considerable influence on the
behavior of the atmosphere and thus on human activities.  They can act as
condensation or freezing nuclei and thereby modify weather patterns.  They
absorb and scatter light and decrease visibility.  Fine particles in the
atmosphere may also influence solar radiation and interfere with astronom-
ical observations.  These facets of fine particulate pollution are reviewed
in the following sections.
2.  Visibility

          Decreased visibility obviously interferes with certain human ac-
tivities, such as safe operation of aircraft and automobiles and the enjoy-
ment of scenic vistas.  Air pollution that reduces visibility, in addition
to endangering the safety of both air and land travel, results in incon-
venience and economic loss to the public, and to transportation companies
due to disruption of traffic schedules.

          Visibility reduction related to air pollution is caused primarily
by the 0.1 to 1.0 p. radius particles in the atmosphere.  Deterioration of
visibility caused by suspended particulate matter is the result of absorp-
tion and scattering of light.  Both the brightness of the viewed object
and its visual contrast with the background are reduced by attenuation of
light due to scattering and absorption.  In addition, a further contrast
                                   208

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reduction results from scattering of sunlight into the observer's line of
sight.  Loss of brightness and contrast are responsible for the subjective
impression of impaired visibility.

          The visibility problem associated with particulate air pollution
can be divided into specific smoke plumes and well-aged aerosols.  The vi-
sual appearance of smoke plumes and visual obscuration by smoke plumes are
closely related to the amount of light the plumes scatter in the direction
of the viewer from their surroundings and the sun.  Consequently, evaluation
of plumes by a visual effect is more difficult for nonblack plumes than for
black plumes, and depends on  plume illuminating and viewing conditions.  Be-
cause of this, nonblack plumes could be evaluated differently when viewed
on different days or viewed from different directions, though their aerosol
content has not changed.

          At least two real difficulties exist in making any generalizations
about visual aspects of smoke plumes.  First, it is not possible to deter-
mine the mas? emitted per unit time from a smokestack solely on the basis
of visually perceived light scatter or absorption.  The size and mass per
unit time emitted from the stack, and not the appearance or optical proper-
ties of the plume, are pertinent to the eventual air composition, even though
appearance may be aesthetically objectionable.

          Second, although many meteorological mixing equations have been
proposed, they cannot describe individual eddies of smoke as the plume dis-
integrates.  The equations were meant for describing averages and not an
instantaneous property such as the extinction of light on some particular
eddy cf smoke as determined by eye.

          The problem of measuring the contribution of individual plumes
to overall visibility reduction in a specific locality is extremely complex
and more detailed study is necessary to develop improved techiques.  Ref-
erence 1 presents a detailed study of plume optics, and the reader is re-
ferred to it for further information.

          Recent advances in our knowledge of the size distributions and
optical properties of well-aged atmospheric aerosols have resulted in a
clearer description of visibility reduction by such aerosols.  Theoretical
and experimental studies of well-aged aerosols have shown that:

          1.  Aerosols in the lowest region of the atmosphere (troposphere),
whether over urban areas or not,  tend to have similar size distributions.2"5/

          2.  A narrow range of particle sizes,  usually from 0.1 to 1.0 p.
radius, controls the extinction coefficient and thereby visibility.6"8/
                                   209

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           3.  The mass concentration of well-aged aerosols is approximately
 proportional to the light scattering coefficient for atmospheric aerosols
 originating naturally or as the result of man's activity.—/

           Studies by Charlson, et al. ,—'  and Noll, _et al_.,—-'  suggest that
 a useful relationship between visual range and mass concentration of atmo-
 spheric part iculate matter can be obtained from the observation that mass
 concentration is approximately proportional to the scattering coefficient.
 The visual range is defined as the distance, under daylight conditions, at
 which the apparent contrast between object and background is just equal to
 the threshold contract of 1,b
-------
from sources  to allow aerosol aging)  suggests  that these results will be
useful  in the estimation of the  effects  of control of emissions  of partic-
ulatc matter  on visibility, provided  the control techniques  applied do not
ultfjr 1,ho  tii'/.i: di:ilribut.i
-------
termed freezing nuclei.  Without these, the water droplets would not freeze
except at temperatures below -40°C.  There is evidence that some of the
particles introduced into the atmosphere by man's activities can act as
nuclei in processes which affect the formation of clouds and precipitation.

          The potential influence of fine particles on solar radiation and
weather patterns is discussed separately in the next two sections.

     3.2  Solar Radiation

          The int"unity -md cpnobral distribution of direct sunlight and
scattered daylight, and the variation of intensity with time of day, season,
latitude, altitude, and atmospheric conditions are important because they
affect photosynthesis in plants and the distribution of plants and animals
on earth, the weathering of natural and man-made materials, climate, and
illumination for human activity.—/

          The attenuation of solar radiation through the atmosphere is
caused by a number of physical factors ;-""-*-°/

          1.  Rayleigh scattering by air molecules such as ^ and Og, and
particles in size ranges less than the wavelength of solar radiation;

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

          3.  Scattering and absorption by atmospheric dusts and particulate
matter of a size greater than the wave Length of solfir radiation.

          The scattering of light by aerosol particles in ambient air is a
complicated process.  Part of the light is transmitted, part is reflected
in all directions either at the front surface of the particle or at an in-
ternal discontinuity and part is absorbed.  The transmission factor for
scattering is a function of the wavelength of the incident light and the
physical qualities of the scattering medium.  In simple cases where the
form, size, and composition of scattering particles are known, the factor
can-be derived on a theoretical basis and is known as "Mie" scattering.

          Except in cases of heavy particulate pollution of the atmosphere,
such as may occur in large urban centers or heavy industrial areas, it ap-
pears that the effect of turbidity is to scatter radiation out of the direct
solar beam and add an almost equal amount to the diffuse beam arriving from
the rest of the sky by forward-scattering.  In cases of heavy particle con-
centrations, however, the loss from the direct solar beam greatly exceeds
the gain in the downward scattered beam, the difference being lost to
                                   212

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backscattering off the  top of the pollution  layer,  and to absorption within
the polluted  layer or column.

          Landsberg . /  and SteinhauserM/ report that cities  in general re-
ceive  less solar  radiation than  do  their rural environments.  Seasonal,
weekly, and dnily variations  in  total  solar  radintjon in urban comunities
have also been noted. ..°/  Those  variations appear to be related, in part,
to cycles of  industrial and commercial activity.

          Comparisons at different  sites over the world covering periods
of up  to 50 years suggest  that a general worldwide  rise in turbidity may
be taking place.   This  may well  be  indicative of a  gradual buildup of world-
wide background levels  of  suspended particulates.SZ/  The net influence of
atmospheric turbidity on surface temperature is uncertain, but the emission
of long-lived particles  may well be leading  to a decrease in world air tem-
perature .^=/  As  more is learned about the general  circulation of the atmo-
sphere and the delicate balance between incoming and outgoing radiation, it
seems  increasingly probable that small changes such as those occasioned by
increasing particle loads  in  the atmosphere may produce very long-term
meteorological effects.

     3.3  Weather Modification

          As  noted previously, there is evidence that some of the particles
introduced into the atmosphere by man's activity can act as nuclei in pro-
cesses which  affect the  formation of clouds and precipitations.  An example
of increased  precipitation from  air pollution appears to exist at La Porte,
Indiana, some 30  miles downwind  from the heavy industrial complex in Chicago.
Precipitation and thunderstorm activity have increased significantly since
1925, and precipitation  peaks  have  coincided with peaks in steel production
in the Chicago area.£=/  Hobbs,  et al.=£/ have reported measurements of the
concentrations of cloud  condensation nuclei in Washington State resulting
from pulp and paper mills  and other industrial sources.   Their study of the
precipitation and stream flow  records  in Washington State for the past 40
years revealed that in recent years there have been significant increases
in precipitation  in several areas in the vicinity of large industrial sources
of cloud-condensation nuclei.

          Excessive dustiness  in the atmosphere can also reduce rainfall
under certain conditions when overseeding occurs.   This  happens when many
small droplets, formed by  condensation, do not fall to earth if there is
insufficient moisture available  to continue the droplet  growth by condensa-
tion.   Consequently, what would have fallen as rainfall  stays in the form
of clouds.   A case  in point of this reduction in rainfall has occurred in
the sugar producing area in Queensland, Australia.   During the cane  harvest-
ing season,  the common practice  is to burn off the  cane  leaf before  cutting

                                   213           ~

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and harvesting.  This results in fires over extensive areas and large palls
of smoke.  The fine smoke particles have modified the cloud formation and
hindered the rainfall process.  A reduction of up to 25$ in the rainfall
has occurred downwind of these areas, but there is no such effect in neigh-
boring areas unaffected by the smoke plume.^i/  Similar effects have been
reported in Puerto Rico, Africa, and yfowaii.25,26/  Schaefer has also re-
ported on observations of changes in micro-physics of clouds in the vicin-
ity of large cities during airplane flights through convective clouds.—/
His observations suggest that such clouds contain an increasing number of
cloud droplets.  Schaefer's investigations of snow and rainstorm patterns
in New York State indicate that submicroscopic particulates from man-made
pollution may be initiating and controlling precipitation in a primary man-
ner, rather than bcJng involved in tho nr.-condnry proccsr, whoroln precipib.'i-
bion elements coming from natural mechanism:; uorvo to remov: thr; particloc
by diffusion, collision, and similar scavenging processes.
                                  214

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                                 REFERENCES
 1.  Connor, W. D., and J. R. Hodkinson, Optical Properties and Visual
       Effects of Smoke-Stack Plumes, PHS Publ. No. 999-AP-30,  Cincinnati,
       Ohio (1967).

 2.  Junge, C. E., Air Chemistry and Radioactivity, Academic Press,  New  York
       (1963).

 3.  Friedlander, S. K., and C. S. Wang, "The Self-Preserving Particle Size
       Distribution for Coagulation by Brownian Motion,"  J. Colloid  Inter-
       face Sci., 2£, 126-132 (1966).

 4.  Whitby, K. T., and W. E. Clark, "Electric Aerosol Particle Counting and
       Size Distribution Measuring System for the 0.15 p,  to 1 p, Size Range,"
       Tellus, IB, 573-586 (1966).

 5.  Peterson, C. M., and H. J. Paulus, "Micrometeorological Variables Ap-
       plied to the Analysis of Variation in Aerosol Concentration and
       Size," Preprint.  (Presented at the 60th Annual Meeting, Air  Pollu-
       tion Control Association, Cleveland, Ohio, June 11-16, 1967).

 6.  Mie, G., "Beitrage zur Optik truber Medien, Speziell Kblloidaler Metallo-
       sungen," Ann. Physik, 2£, 377-455 (1968).

 7.  Pueschel, R. F., and K. E. Noll, "Visibility and Aerosol Size Frequency
       Distribution," J.  Appl. Meteorol., (5, 1045-1052 (1967).

 8.  Air Quality Criteria for Parbiculate Matter, NAPCA Publ. AP-49,
       Washington, D. C.  (1969).

 9.  Charlson, R. J., H.  Horvath, and R. F. Pueschel, "The Direct  Measure-
       ment of Atmospheric Light Scattering Coefficient for Studies of
       Visibility and Air Pollution," Atmos. Environ., !L, 469-478  (1967).

10.  Noll, K. E., P. K. Mueller, and M. Unada, Atmos. Environ., 1, 501 (1967).

11.  Charlson, R. J., N.  Ahlquist, and H. Horvath, Atmos. Environ., 2, 300
       (1968).                                                     ~

12.  Charlson, R. J., N.  Ahlquist, and H. Selvidge, "The  Use of the Inte-
       grating Nephelometer for Monitoring Parbiculate Pollution," Pre-
       sented at 10th Conference on Methods, San Francisco  (1969).

13.  Fett, W., Beitr.  Phys. Atmos., 40, 262 (1967).

                                   215

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14.  McCormick, R. A., and D. M. Baulch, "The Variation with Height of tho
       Dust Loading Over a City as Determined from the Atmospheric Tur-
       bidity," JAPCA, 12, 492-496 (1962).

15.  Gates, D. M., "Spectral Distribution of Solar Radiation at  the Earth'3
       Surface," Science, 151, 523-529 (1966).

16.  Robinson, N.,  Solar Radiation,  Elsevier, Amsterdam,  London, ani
       New York (1966).

17.  Landsberg, H.,  Physical Climatology,  2nd Edition, Gray, Dubois,
       Pennsylvania, 317-326 (1958).

IB.  Steinhauser, F., 0. Eckel, and F. Sauberer, "Klima und Bioklima von Wien,"
       Wetter und Leben, 7 (1955).

19.  Meetham, A. R.,  Atmospheric Pollution;  Its Origins and Prevention,
       Pergamon Press, New York (1961).

20.  Mateer, C. L., "Note on the Effect of the Weekly Cycle of Air Pollution
       on Solar Radiation at Toronto," Intern. J. Air Water Pollution, _4,
       52-54 (1961).

21.  "Restoring the Quality of Our Environment," Report of  the Environrner.tal
       Pollution Panel, President's Science Advisory Committee.  The White
       House, Washington, D. C., 111-151, November 1965.

22.  Changnon, S. A., "The LaPorte Weather Anomaly—Fact or Fiction,"
       Bulletin of American Meteorological Society, 49 (l), 4-11 (1968).

23.  Hobbs, P. V., et al., "Cloud Condensation Nuclei from  Industrial Sources
       and Their Apparent Influence on Precipitation in Washington State,"
       Journal of Atmospheric Sciences, 27, 81-89 (1970).

24.  Aynsley, E., "How Air Pollution Alters Weather," New Scientist, 66-67,
       October 9, 1969.

25.  Schaefer, V. J., "The Inadvertent Modification of the  Atmosphere by
       Air Pollution," Bulletin of American Meteorological  Society, 50 (4),
       199-206 (1969).

26.  Warner, J., "A Reduction in Rainfall Associated with Smoke  from Sugar
       Cane Fires - An Inadvertent Weather Modification," J.  Applied
       Meteorology, 7, 247-251 (1968).

27.  Gunn, R., "The Secular Increase of the World-Wide Fine Particle Pollu-
       tion," J. Atmos. Sci., 21, 168-181 (1964).

                                   216

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 APPENDIX D





DATA SOURCES
   217

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I.  Companies that provided data
          Organization
              Courcoc
 1.  TVA
 2.  Coulter Electronics
 3.  Koppers Company
 4.  H. W. Dieteret Company
     (Banco sales representative)

 5.  PEDCo - Environment.-i,l
 6.  Resources Research
10 distributions - power plants
(before and after control devices)

4 distributions - power plants and
cement plants (before control)

6 distributions - power plants
(before control)

6 miscellaneous distributions by
Banco methods

P dlr:tributionr; - power plant"
(bc:f.'ore control)

Compilation of 25-30 particle size
distributions for several sources—
power plants, kilns, dryers, electric
furnaces
 7.  Roy F. Weston Company
 8.  Abe Matthews Engineering
     Company
 9.  George Clayton Associates
10.  Universal Oil Products
     (Air Correction Division)

11.  Western Precipitator
12.  National Dust Collector
6 distributions - power plants
(before control)

15 distributions - cupolas, power
plant, lime kiln, cement kiln, mineral
processing (before control)

10 distributions - power plant, cupolas,
lime kiln, cement kiln, electric
furnace (before control)

25 distributions - power plant (before
and after control)

Compilation of 250-300 particle size
distributions—12-15 different sources
(before control)

9 distributions - cupola, coal cleaning,
asphalt dryers, and mineral processing
(electron microscope data, before and
after control)
                                    218

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           Organization

 13.   Environmental Research
      Corporation

 14.   Meteorology Research, Inc.
              Sources

 1  distribution  -  secondary aluminum


 Power plant plume data
 II.  Other companies contacted that have data which were not acquired

  1.  Cottrell Environmental          Data available, cost prohibitive

  2.  American Air Kilter
  3.   American Standard

  4.   Wheelabrator

  5.   Pulverizing Machinery

  6.   Buffalo Forge
Data available, will work only through
IGCI

Data not available for public disclosure

Data not available for public disclosure

Data not available for public disclosure

Data not available for public disclosure
III.  Research groups

  1.  Dr.  M. Pilat
      University of Washington
  £.   Prof. A. F.  ituch
      UCLA

  3.   Dr.  S. K. Fried-lander
      Cal  Tech

  4.   Dr.  P. K. Mueller
      California Department of
        Public Health

  5.   Dr.  A. Cohen
      Ecological Research Branch
      APCO, Durham
Power plant, recovery furnace (pulp
mill), plywood veneer dryer (cascade
impactor)

Power plant (thermal precipitator,
electron microscope data)

No source data
No source data
No source data
                                    213

-------
 6.  Dr. Jack Wagman                 No source data
     Division of Chemical and
       Physical Research and
       Development
     APCO, Durham

 7.  Dr. Myron Robinson              No source data
     Atomic Energy Commission

 8.  Prof. M. Kerker                 No source data
     Clarkson College

 9.  Dr. Mary Amdur                  No source data
     Harvard School 'of Public
       Health
IV.  Companies contacted that did not have data

 1.  Mr. J. Katz                     10.   Mr.  J.  Pizzo
     Jacob Katz Associates                U.  S. Testing Company,  Inc.

 2.  Mr. Jorgen Hedenhag             11.   Mr.  R.  E.  Sommerclad
     Polycom Corporation                  Foster  Wheeler Corporation

 3.  Mr. Charles Billings            12.   Mr.  A.  Licberman
     GCA                                  Royco Instruments

 4.  Mr. Ray Droger                  13.   Dr.  William A. Perkins
     Seversky Electronatom                Metronics  Associates

 5.  Mr. Sid Orem                    14.   Mr.  H.  D.  Wheeler
     Flyash Arrester                      Kaiser  Engineers

 6.  Mr. I. Shah                     15.   Dr.  M.  Feldstein
     Chemico                              Bay Area Air  Pollution  Control
                                            District
 7.  Mr. Ballard
     Menardi and Company             16.   Mr.  Walter Hamming
                                          Los Angeles APCD
 8.  Mr. Charles Cook
     Mine Safety Appliances Company  17.   Dr.  E.  R.  Hendrickson
                                          Environmental Engineering, Inc.
 9.  Mr. Dick Glover
     Monsanto Environmental Control
       System

                                   220

-------
              APPENDIX E
CALCULATIONS OF FINE-PARTICLE EMISSIONS

-------
                                  APPENDIX E

                              TABLE OF CONTENTS

                                List of Tables

  Table                             Title

1.  Asphalt, Hot Mix Batch Plant

   E-l      Summary of Fino-Par tide Emission::; From Asphalt Dryers  .  .  230

   E-2      Distribution of Process Emissions From Asphalt Dryers   .  .  231

   E-3      Fine-Particle Emissions From Uncontrolled Asphalt Dryers  .  252

   E-4      Fine-Particle Emissions From Asphalt Dryers Controlled
              by Cyclones	233

   E-5      Fine-Particle Emissions From Asphalt Dryers Controlled
              by Cyclones Plus Scrubber  .	234

   E-6      Summary of Fine-Particle Emissions From Vent Lines ....  235

   E-7      Distribution of Process Emissions From Vent Lines  ....  236

   E-8      Fine-Particle Emissions From Uncontrolled Vent Lines .   .  .  237

   E-9      Fine-Particle Emissions From Vent Lines Controlled by
              Cyclones	238

   E-10     Fine-Particle Emissions From Vent Lines Controlled by
              Cyclones Plus Scrubber	239

2.  Cement Plants, Kilns
            *
   E-ll     Summary of Fine-Particle Emissions From Cement Kilns .  .  .  240

   E-12     Distribution of Process Emissions From Cement Kilns   .  . .  241

   E-13     Fine-Particle Emissions From Uncontrolled Cement Kilns  . .  242

   E-14     Fine-Particle Emissions From Cement Kilns Controlled by
              Electrostatic Precipitators   	  ...  243
                   *v
   E-15     Fine-Particle Emissions From Cement Kilns Controlled
              by Cyclones	244
                                     221

-------
                         List  of Tables  (Continued)

  Table                             Title                              Page

   E-16     Fine-Particle Emissions From Cement Kilns Controlled
              "by Cyclones Plus Electrostatic Precipitators  	  245

   E-17     Fine-Particle Emissions From Cement Kilns Controlled by
              Fabric Filters	246

3.  Ferroalloy Plants, Electric Furnaces                                          .'
                                                                                   (
   E-18     Summary of Fine-Particle Emissions for Ferroalloy
              Electric Furnaces	,	'247         •

   E-19     Distribution of Process Emissions From Ferroalloy
              Electric Furnaces  	  248

   E-20     Fine-Particle Emissions From Uncontrolled Ferroalloy                     ;'
              Electric Furnaces  	  249

   E-21     Fine-Particle Emissions From Ferroalloy Electric Furnaces
              Controlled by Fabric Filters and Disintegrators  ....  250

4.  Fertilizer Plants, Granulators and Dryers

   E-22     Summary of Fine-Particle Emissions From Fertilizer
              Granulators and  Dryers 	  251

   E-23     Distribution of Process Emissions From Granulators and
              Dryers	252

   E-24     Fine-Particle Emissions From Uncontrolled Granulators
              and Dryers	253

   E-25     Fine-Particle Emissions From Granulators and Dryers
              Controlled by Wet Scrubbers  	  254

5.  Iron and Steel Plants  •

    a.  Basic Oxygen Furnace

   E-26     Summary of Fine-Particle Emissions From Basic Oxygen
              Furnaces^ Iron and Steel	255

   E-27     Distribution of Process Emissions From Basic Oxygen
              Furnaces	256
                                     222

-------
                        List of Tables (Continued)

Table                             Title                              Page
 E-28     Fine-Particle Emissions From Basic Oxygen Furnaces
            Controlled by Electrostatic Precipitator 	  257

 E-29     Fine-Particle Emissions From Basic Oxygen Furnaces
            Controlled by Venturi Scrubber 	  258

  b.  Electric Arc Furnace

 E-30     Summary of Fine-Particle Emissions From Electric Arc
            Furnaces, Iron and Steel	  259

 E-31     Distribution of Process Emissions From Electric Arc
            Furnaces	  260

 E-32     Fine-Particle Emissions From Uncontrolled Electric Arc
            Furnaces	  261

 E-33     Fine-Particle Emissions From Electric Arc Furnaces
            Controlled by Wet Scrubber 	  262

 £-34     Fine-Particle Emissions From Electric Arc Furnaces
            Controlled by Electrostatic Precipitator 	  263

 E-35     Fine-Particle Emissions From Electric Arc Furnaces
            Controlled by Fabric Filter  	  264

  c.  Open Hearth Furnace

 E-36     Summary of Fine-Particle Emissions  From Open Hearth
            Furnaces	265

 E-37     Distribution  of Process Emissions From Open Hearth
            Furnaces	266

 E-38     Fine-Particle Emissions From Uncontrolled Open Hearth
            Furnaces	   267

 E-39     Fine-Particle Emissions  From Open Hearth Furnaces
            Controlled  by Electrostatic Precipitator 	   268
                                  223

-------
                          List  of Tables  (Continued.)
    d.  Sinter  M;J
   E-40     Summary of Fine-Particle Emissions From Sinter Machines,
              Iron and Steel Plants
   E-41     Distribution of Process Emissions From Sinter Machine   .  .   270

   E-42     Fine-Particle Emissions From Sinter Machines Controlled
              by Cyclones   ......................   271

   E-43     Fine-Particle Emissions From Sinter Machines Controlled
              by Cyclone Plus Electrostatic Precipitator .......   272

6.  Iron. Foundries, Cupola

   E-44     Summary of F:ino-Partic:lo Kmi;;.';ion;; Kroiri J ron Foundry
              Cupolas  ........................   275

   E-45     Distribution of Process Emissions From Iron Foundry
              Cupolas  ........................   274

   E-46     Fine-Particle Emissions From Uncontrolled Iron Foundry
              Cupolas  ........................   275

   E-47     Fine-Particle Emissions From Iron Foundry Cupolas
              Controlled by Cyclones .................   276

   E-48     Fine-Particle Emissions From Iron Foundry Cupolas
              Controlled by Wet Scrubbers and Wet Caps ........   277

   E-49     Fine-Particle Emissions From Iron Foundry Cupolas
              Controlled "by Fabric Filters . . . . ..........   278

7.  Kraft Pulp Mills

    a.  Bark Boilers

   E-50     Summary of Fine-Particle Emissions From Bark Boilers .  .  .   279

   E-51     Distribution of Process Emissions From Bark Boiler ....   280

   E-52     Fine-Particle Emissions From Uncontrolled Bark Boilers  .  .   281

                                     224

-------
                          List  of Tables  (Continued)

  Table                              Title                              Page
   E-53     Fine-Particle Emissions From Bark  Boilers  Controlled
              by Cyclones	282

    d.  Re c overy Furnac e

   E-54     Summary of Fine-Particle Emissions From Recovery
              Furnaces	283

   E-55     Distribution of Process Emissions  From  Recovery Furnace   .   284

   b'-fjG     Fine-Particle Krni.'jcjons I'Yorn Uncontrolled  Rf:r:
-------
                           List of Tables (Continued)

   Table                             TJtle                              T'n ge

    E-66     F.ine -Particle- Emissions From Hol.Mry  Liin<:  Kilns Controller!
               by Wet Scrubbers ....................   291;

    E-67     Fine-Particle Emissions From Rotary  Lime  Kilns Controlled
               by Fabric Filter ....................   296

 9.  Municipal Incinerators

    E-68     Summary of Fine -Particle Emissions From Municipal
               Incinerators ......................   297

    E-69     Distribution of Process Emissions From Municipal
               Incinerator  .................. .  .  .  . .   298

    E-70     Fine-Particle Emissions From Uncontrolled Municipal
               Incinerators ......................   P99
    E-71     Fine -Particle ISmisaiony From Municipal Incinerators
               Contolled by Low Efficiency Scrubber ..........  300

    E-72     Fine-Particle Emissions From Municipal Incinerator
               Controlled by Medium Efficiency Scrubber  ........  301

    E-73     Fine-Particle Emissions From Municipal Incinerators
               Controlled by Cyclones . . ...............  302

10.  Stationary Combustion

     a.  Electric Utility 3 Pulverized Coal-Fired Boiler

    E-74     Summary of Fine-Particle Emissions From Electric Utility
               Pulverized Coal-Fired Boilers  .............  303

    E-75     Distribution of Process Emissions From Electric Utility
               Pulverized Ccal-Fired Boiler ..............  304

    E-76     Fine-Particle Emissions From Uncontrolled Electric Utility
               Pulverized Coal-Fired Boilers  .............  305

    E-77     Fine-Particle Emissions From Electric Utility Pulverized
               Coal-Fired Boilers Controlled by Electrostatic
               Precipitator ......................  306

                                      226

-------
                        List of Tables (Continued)

                                  TJflQ                              	

 E-78     Fine-Particle Emiufiionr; From Electric Utility Pulverized
            Coal-Fired Boilers Controlled by Cyclones	SO/

 E-79     Fine-Particle Emissions From Electric Utility Pulverized
            Coal-Fired Boilers Controlled by Cyclone Plus
            Electrostatic Precipitator 	   308

  b.   Electric Utility, Stoker Coal-Fired Boiler

 E-80     Summary of Fine-Particle Emissions From Electric  Utility
            Stoker Coal-Fired Boilers  	   309

 E-81     Distribution of Process Emissions From Electric Utility
            Stoker Coal-Fired Boiler 	   310

 E-82     Fine-Particle Emi:;nions From Uncontrolled EJeotric  Utility
            Stoker Coal-Fired Boilers  .  .  .	3j 1

 E-83     Fine-Particle Emissions From Electric Utility Stoker
            Coal-Fired Boilers Controlled by Electrostatic
            Precipitator 	   312

 E-84     Fine-Particle Emissions From Electric Utility Stoker
            Coal-Fired Boilers Controlled by Cyclones  	   313

  c.   Electric Utility, Cyclone Coal-Fired Boiler

 E-85     Summary of Fine-Particle Emissions From Electric  Utility
            Cyclone  Coal-Fired Boilers  	   314

 E-86     Distribution of Process Emissions From Electric Utility
            Cyclone  Coal-Fired Boiler  	   315

 E-87     Fine-Particle Emissions  From  Uncontrolled Electric
            Utility  Cyclone Coal-Fired  Boilers  	   316

E-88     Fine-Particle Emissions  From  Electric Utility Cyclone
            Coal-Fired Boilers  Controlled by Electrostatic
            Precipitator	'"	3j_y

E-89     Fine-Particle  Emissions From  Electric Utility Cyclone
            Coal-Fired Boilers Controlled by Cyclone  	   318

                                   227

-------
                        List of Tables (Continued)

Table                             Title

   d.  Industrial Boilers, Pulverized Coal-fired

 E-90     Summary of Fine-Particle Emissions From Industrial
            Pulverized Coal-Fired Boilers  .............  319

 E-91     Distribution of Process Emissions From Industrial
            Pulverized Coal-Fired Boiler ..............  320

 E-92     Fine -Particle Emissions From Uncontrolled Industrial
            Pulverized Coal-Fired Boilers  .............  321

 E-93     Fine-Particle Emissions From Industrial Pulverized Coal-
            Fired Boilers Controlled by Electrostatic  Precipitator  .  322

 E-94     Fine-Particle Emissions From Industrial Pulverized Coal-
            Fired Boilers Controlled by Cyclones ..........  323

  e.   Industrial Boilers, Stoker Coal -Fired

 E-95     Summary of Fine -Particle Emissions From Industrial Stoker
            Coal-Fired Boilers ...................  324

 E-96     Distribution of Process Emissions From Industrial Stoker
            Coal-Fired Boilers ...................  32C
 E-97     Fine-Particle Emissions From Uncontrolled Industrial
            Stoker Coal-Fired Boilers  ...............  326

 E-98     Fine -Particle Emissions From Industrial Stoker  Coal-Fired
            Boilers Controlled by Electrostatic  Precipitator  ....  327

 E-99     Fine-Particle Emissions From Industrial Stoker  Coal-Fired
            Boilers Controlled by Cyclones  .............  328

  f .   Industrial Boilers,  Cyclone Coal-Fired

 E-100    Summary of Fine-Particle Emissions From Industrial
            Cyclone Coal-Fired Boilers ...............  329

 E-101    Distribution of  Process Emissions  From Industrial Cyclone
            Coal-Fired Boiler  ...................  330
                                   228

-------
                        List of Tables (Concluded)

Table                             Title                              Page

 E-102    Fine-Particle Emissions Fron Uncontrolled Industrial
            Cyclone Coal-Fired Boilers	331
 E-103    FJne-Partide Emissions Prom industrial Cyclone Coal-
            Fired Boilers Controlled by Electrostatic Precipitator .   332

 E-104    Fine-Particle Emissions From Industrial Cyclone Coal-
            Fired Boilers Controlled by Cyclones 	   333

  g.  Electric Utility and Industrial Boiler, Qil-Fired

 E-105    Summary of Fine-Particle Emissions From Electric Utility
            and Industrial Oil-Fired Boilers 	   334

  h.  Electric Utility and Industrial Boiler, Gas-Fired

 E-106    Summary of Fine-Particle Emissions From Electric Utility
            and Industrial Gas-Fired Boilers	 .   335
                                   229

-------
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-------
                              TABLE E-2
        DISTRIBUTION OF PROCESS EMISSIONS FROM ASPHALT DRYERS
Source -   Asphalt
Process -   Dryers
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 251 x 1Q6   )      (  52 )
Application of Control =   99   ^

Process Emissions into Uncontrolled Plants =
                                                    .    -v
                                                   f  j\ = 4
                                                40,200
Process Emissions into Controlled Plants   =  3,975,800
                                                           = 4,016,000 tons/year
                                                             tons/year

                                                             tons/year
    Type of
Control Device

 Cyclone
                          % Application on
                          Controlled Plants
                                                       Process  Emissions  into
                                                       Control  Device  (tons/year)

                                                            198,600
 Cyclone + Scrubber
 FF
                                   95
                                                         3,777,000
                                  231

-------
                               TABLE ]-;-3


       FINE-PARTICLE EMEIioIONo FROM IJNCONTHOLLM) ASPHALT




Process -   Asphalt Dryers	


Control Device -   Uncontrolled
Process Bnissions into Control Device	40,200	tons/year
                         Control Device      Control Device
                         [Uncontrolled |      |              |
Process Snissions        Penetration (%)     Penetration (%)    fiaissions
Size (n)	Percent    (l - efficiency)    (l - efficiency)   (tons/year)

1-3            12.6           100                                 5,100


0.5-1.0	2.18	100	300


0.1-0.5	0.71	100	300


0.05-0.1	


0.01-0.05
                                                                  6,300
                                 232

-------
                                TABLE E-4
   FINE-PARTICLE EMISSIONS FROM ASPHALT DRYERS CONTROLLED BY CYCLONEC
 Process -  AsPhalt
 Control Device -  Cyclones
 Process Emissions into Control Device   198,800
                                                tons/year
 Process Emissions
 Size (jj.)	Percent
 1-3
 0.5-1.0
12.6
 2.18
                          Control Device
                              Control Device
                            Cyclones
 Penetration  (#)     Penetration (#) .   Emissions
 (l  -  efficiency)^/  (l - efficiency)   (tons/year)

	73	;	16.300
       89
5.900
 0.1-0.5
 0.71
      100
1.400
 0.05-0.1
 0.01-0.05
                                                                 23,600
a/ Efficiency values were taken from medium fractional efficiency curve,
     Figure 17.
                                  233

-------
                               TABLE E-5

         FINE-PARTICLE EMISSIONS FROM ASPHALT DRYERS CONTROLLED
                      BY CYCLONES PLUS SCRUBBER


 Process  -   Asphalt Dryers
 Control Device -  Cyclones plus Scrubber

 Process Bnissions  into Control Device   3,777,000	tons/year
                          Control Device     Control Device
                          I  Cyclone    I     [ Scrubber    ]
 Process  Bnissions         Penetration  ($)     Penetration  ($)    Emissions
 Size  (u)     Percent    (l  -  efficiency)^/   (l - efficiency)^/  (tons/year)

 1-3	12.6	73	21	75,000

 0,5-1.0	2.18	89	45	51,500

 Q.l-0.5  	0.71	100	•	74	    19,800

 0.05-0.1	95	

 0.01-0.05	100	

                                                                 124,300
a/ Efficiency values were taken from medium fractional efficiency curve,
     Figure 17.
                                 234

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-------
                               TABLE E-7
            DISTRIBUTION OF PROCESS EMISSIONS FROM VENT IJNE.r;
Source -  Asphalt
Process - Vent Line
                    Production       Emission Factor
                    (tons/year)         (ib/ton)    /
Process Emissions = ( 251 x 10°   )      (  8  )
Application of Control =    99   

Process Emissions into Uncontrolled Plants
10,000
Process Emissions into Controlled Plants   =    994,000
                                                           = 1,004,000 tons/year
                                                             tons/yeai
                                                             tons/y
                  •ear
    Type of
Control Device

 Cyclone	
                          $ Application on
                          Controlled Plants
      Process Emissions into
      Control Device (tons/year)

      	49.700	
 Cyclone plus Scrubber
                                  95
             944.300
                                 236

-------
                               TABLE E-8

          FINE-PARTICLE EMISSIONS FROM UNCONTROLLED VENT LINES




Process -   Asphalt - Vent Lines	

Control Device -   Uncontrolled
Process Bnissions into Control Device	10,000	tons/year
                         Control Device      Control Device
                         [Uncontrolled |
Process Bnissions        Penetration (%)     Penetration (%)    Emissions
Size (p.)	Percent    (l - efficiency)    (l - efficiency)   (tons/year)

1_3	7.55	100	800


0.5-1.0	0.41          100	

0.1-0.5	0.05	100	

0.05-0.1	

0.01-0.05	

                                                                   800
                                 237

-------
                                TABLE E-9
     FINK-PARTICLE EMIJJUIOIW FKOM VKNT LBJKii CON'i'hOLLI'IL)  Iff  CYCLONIC
Process  -  Asphalt - Vont Lino3
Control Device -    Cyclone
Process Emissions  into Control Device   49,700
                                                  tons/year
                          Control Device
                                Control Device
Process
Size (n)
1-3

Emissions
Percent
7.55
1
Cyclone
1
Penetration ($)
(l - efficiency)^/

73

1 _.

1
Penetration ($)
(l - efficiency)



Emissions
(tons /year)
2,700
0.5-1.0
0.41
 •89
200
0.1-0.5
0.03
100
0.05-0.1
0.01-0.05
                                                                   2,900
a/ Efficiency values were  taken from inedium fractional efficiency curve,
     Figure 17.                                                  '.
                                  238

-------
                               TABLE E-10

          FINE-PARTICLE EMISSIONS FROM VENT LIMES CONTROLLED
                       BY CYCLONES PLUS SCRUBBER
Process -  AsPhal"t - Vent Lines
Control Device -  Cyclone plus Scrubber
Process Emissions into Control Device       944,500 _ tons/year
                         Control Device      Control Device
                         I  Cyclone     |      ( Scrubber     ]
Process Emissions        Penetration {%)     Penetration ($)    Emissions
Size (tx)     Percent    (l - efficiency )£/  (l - efficiency)^/ (tons /year)
1_3 _ 7.55 _ 73 _ 21 _ 10,900

0.5-l.Q _ 0.41 _ 89    _ 43 _      1,500

Q.l-0.5 _ 0.05 _ 100 _ 74 _ 200

0.05-0.1 _ _ 95

0.01-0.05 _ 100

                                                                 12,600
a/ Efficiency values were taken from medium fractional efficiency curve,
     Figure 17.
                                 239

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-------
Source -
                               TABLE E-12
          DISTRIBUTION OF PROCESS EMISSIONS FROM CEMENT KILNS
           Cement Pl£mts
Process -  Kilns
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = (74.6 x 106   )      ( 167 )
                                                              6.299
                                                           =  x 106   tons/year
Application of Control =    94  ^

Process Emissions into Uncontrolled Plants =  0.574 x 10°    tons /year

Process Emissions into Controlled Plants   =  5.855 x 106    tons /year
    Type of
Control Device

   ESP

   Cyclones

   Cy  + ESP

   FF
                          % Application on
                          Controlled Plants

                                  47

                                  16

                                  18

                                  17
                                                       Process Emissions into
                                                       Control Device ( tons/year)

                                                         2.752 x 106     _

                                                         1.054 x 106 _

                                                         1.0J54 x 106 _ :

                                                         0.995 x 106
                                 241

-------
                               TABLE E-13
         FINE-PARTICLE EMISSIONS FROM UNCONTROLLED CEMENT KILNS
Process -   Cement Kilns
Control Device -   Uncontrolled
Process Emissions into Control Device  0.374 x
                                                tons/year
                         Control Device
                              Control Device
Process Emissions
Size (u)	Percent
1-3
9.7
   Uncontrolled!
 Penetration ($)
(l - efficiency)

       100
 Penetration  (^b)    Emissions
{l  -  efficiency)    (tons/year)

	36,500
0.5-1.0
1.75
       100
                      6,500
0.1-0.5
0.54
      100
                      2.000
0.05-0.1
0.01-0.05
                                                                 44,800
                                  242

-------
                                TABLE E-14
           FINE-PARTICLE EMISSIONS FROM CEMENT KILNS CONTROLLED
                      BY ELECTROSTATIC PRECIPITATORS
Process  -   Cement  Kiljis
Control Device  -  Electrostatic  Precipitators
 Process  Emissions into Control Device    2.752 x 10
                                                 tons/year
                         Control Device
                               Control Device
Process
Size (n)
1-3

Emissions
Percent
9.
7
1
ESP 1
Penetration (%
(l - efficiency

11
}*/


X 1
Penetration ($)
£L - efficiency)


Emissions
(tons/year)

29,
400
0.5-1.0
0.1-0.5
 0.05-0.1
0.01-0.05
•1.75
 0.54
17
29
8,200

4,300
                                                                 41,900
a/ Efficiency values used were  uaken from average fractional efficiency curve,
     Figure 17.

Note:  Outlet particle size distribution for cement kiln controlled by ESP
         showed 43$ <  3 p,.   (Figure 34).

       If the overall efficiency of ESP's is assumed to average about 95%,
         then the quantity emitted by ESP controlled plants is as follows:

       (2.752 x 106 tons/year)(1-0.95)(43$) = 59,200 tons/year <  3 p,.

       The 59,200 tons/year gives a cross-comparison with 41,900 tons/year.
                                  243

-------
                                TA.BLE E-15
     FINE-PARTICLE EMISSIONS FROM CEMENT KILNS CONTROLLED BY CYCLONES
 Process  -    Cement Kilns
 Control Device -   Cyclones
 Process  Emissions into  Control Device  1.054 x 106
                                                tons/year
                          Control Device
                              Control Device
Process Emissions
Size (n) Percent
1-3 9-7
1 Cyclones 1
Penetration ($)
(l - efficiency)^/
57
1
X 1
Penetration ($)
(l - efficiency)


Emissions
(tons /year)
58,300
 0.5-1.0
1.75
82
15.100
 0.1-0.5
0.54
94
 5.400
 0.05-0.1
 0.01-0.05
                                                                  78,800
a/ Efficiency values used were taken from fractional efficiency curve for
     high efficiency cyclones, Figure 17, because some plants use multi-
     clones and since the dust is reusable to a certain extent, it is assumed
     that higher efficiency devices would be used.
                                  244

-------
                               TABLE E-16

    FINE-PARTICLE EMISSIONS FROM CEMENT KILNS CONTROLLED BY CYCLONES
                    PLUS ELECTROSTATIC PRECIPITATOR
Process -   Cement Kilns
Control Device -  Cyclone + ESP
Process Emissions into Control Device  1.054 x 106
                                                               tons/year
                         Control Device
                         I  CycloneI
                                             Control Device
                                                 ESP
Process Emissions
Size (p.)	Percent
1-3
                9.7
 Penetration
(l - efficiency)

       57
 Penetration
(l - efficiency)

       11
                                                                Emissions
                                                               (tons/year)

                                                                  6.400
0.5-1.0
                1.75
                               82
                           17
                      2.600
0.1-0.5
                0.54
                               94
                           29
                      1.600
0.05-0.1
0.01-0.05
                                                                 10,600
                                 245

-------
                               TABLE E-17
          FINE-PARTICLE EMISSIONS FROM. CEMENT KILNS CONTROLLED
                           BY FABRIC FILTERS
Process -   Cement Kilns
Control Device -   Fabric Filters
Process Emissions into Control Device  0.995 x 10
                                                tons/yi
                                       •ear
Process Emissions
Size (n)	Percent
1-3
               9.7
          Control Device
          i'    F£   —i
          Penetration (%)
         (l - efficiency)
               0.5
                                             Control Device
               Penetration
              (l - efficiency!)
 Emisoionc
(tons/year)

   400
0.5-1.0
1.75
1.8
   300
0.1-0.5
               0.54
               3.3
                                    200
0.05-0.1
0.01-0.05
                                                                  900
                                  246

-------
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-------
                                TA.BLE E-19

   DISTRIBUTION OF PROCESS EMISSIONS FROM FERROALLOY ELECTRIC FURM.CES
                               (Tons/Year)
 Source -
            Ferroalloys
 Process -   Electric  Furnaces
                    Production       Emission Factor
                     (tons/year)          (ib/ton)
 Process Emissions = ( 2.119  x  10s  )       (  240  )

 Application of Control =    ^°  jo ^
Process Emissions into Uncontrolled Plants =   152,600

Process Emissions into Controlled Plants   =   101,700
                                                           =  254,300 tons/year
                                                             _tons/year

                                                              tons/year
          of
 Control Device
                          % Application on
                          Controlled Plants
Process Emissions into
Control Device (tons/year)

     lbl.700	
a/  Page 233,  Reference 1, showed 50$ application of control.  However,
      the 80$ efficiency was mainly a result of capture efficiency.  Control
      devices are high efficiency type, such as baghouses, Venturi scrubbers
      or disintegrators.  Most are disintegrators and baghouses.
b/  Assume disintegrators are equivalent to fabric filters.
                                  248

-------
                               TABLE E-20
 FINE-PARTICLE EMISSIONS FROM UNCONTROLLED FERROALLOY ELECTRIC FURNACES
Process -  Ferroalloys - Electric Furnace

Control Device -   Uncontrolled	

Process Emissions into Control Device     152,600
                                                               tons /year
Process Emissions
Size (M-)	Percent
1-3
               12
 Control Device
 I Uncontrolled I
 Penetration ($)
(l - efficiency)

     100
                                             Control Device
                                             Penetration (%)    Emissions
                                            (l - efficiency)   (tons/year)

                                           	18,300
0.5-1.0
               18
                             100
                                         27,500
0.1-0.5
               52
                             100
                                         79,400
0.05-0.1
               11
                             100
                                         16,800
0.01-0.05
                4.9
                             100
                                          7,500
                                                                149,500
                                 249

-------
                               TABLE E-21

   FINE-PARTICLE EMISSIONS FROM FERROALLOY ELECTRIC FURNACES CONTROLLED
                  BY FABRIC FILTERS AND DISINTEGRATORS
Process -  Ferroalloys - Electric Furnace

Control Device - Fabric Filters and Disintegrators^8/

Process Emissions into Control Device	101,700	tons/year


                         Control Device      Control Device
                         |FF + Disinteof      |              |
Process Emissions        Penetration (%)  ,   Penetration (%)    Emissions
Size (n)	Percent    (l - efficiency)—'  (l - efficiency)   (tons/year)

1-5	12	0.5	100

0.5-1.0	18	1.8	500

0.1-0.5	52	5.5	1,700

0.05-0.1	11	4.2	..	500

0.01-0.05	4.9	•-  4.5	200

                                                                2,800
a/  Assume disintegrators are equivalent to fabric filters.
                                250

-------
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-------
                               TABLE E-23
     DISTRIBUTION OF PROCESS EMISSIONS FROM (XANUIATOR AND DRYER
Source -
            Fertilizer
Process -   Granulation and Drying
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 18.1 x 106  )      ( 195 )
Application of Control =    _95  $

Process Emissions into Uncontrolled Plants =
                          2,OUU) ~ •
                          ^   /
    =1,764,800 tonc/yoar-
                       88,200
Process Emissions into Controlled Plants   =  1,676,600
     _tons/year

      tons/year
    Type of
Control Device

 Wet Scrubbers
% Application on
Controlled Plants

       100
Process Emissions into
Control Device (tons/year)

     1,676,600
                                252

-------
                                TABLE E-24

   FES-PARTICLE SMISSI017S FROM UKCOMRQT.T.TTn GRAirUIATORS AMD DRYERS



Process -  Fertilizer,  Granulation  and Drying,  etc.

Control Device -  Uncontrolled	;

Process Bnissions into  Control Device    88,200	tons/year


                         Control Device      Control Device
                         I Uncontrolled)
Process Bnissions        Penetration ($)     Penetration  (%)    Snissicr.s
Size (M,)     Percent    (l - efficiency)    (l - efficiency)    (tons/year)

1-3	1.62	100	1,400

0.5-1.0	0.45	100	400

C.l-0.5	0.25	100	|	200

0.05-0.1	

C.01-0.05	

                                                                   2,000
                               255

-------
                               TABLE E-25
          FIME-PARTICLE EMISSIONS FROM (SANUIATORS AND DRYERS
                      CONTROLLED BY WET SCRUBBERS
Process -  Fertilizer> Granulation and Drying, etc.

Control Device -   Wet Scrubbers	

Process Emissions into Control Device    1,676,600
                                tons/year
                         Control Device
              Control Device
Process Emissions
Size (y.) Percent
1-3 1-62
Scrubber |
Penetration ($)
(l - efficiency)^/
21
1
Penetration ($)
(l - efficiency)

Emissions
(tons/year)
5,700
0.5-1.0
               0.43
                                   3,100
0.1-0.5
               0.23
74
2,900
0.05-0.1
                               95
0.01-0.05
                              100
                                                                 11,700
a/  Efficiency values were taken from medium fractional efficiency curve,
      Figure 17.
                                 254

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-------
                               TABLE E-27
      DISTRIBUTION OF PROCESS EMISSIONS FROM BASIC OXYGEN FURNACE
Source -   Iron ajlci Steel
Process -  BOF
                    Production       Emicsion Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 45 x 106    )      (  40 )

Application of Control =   100  %

Process Emissions into Uncontrolled Plants =
                                                   (y,oou)
                                 =  960,000 tons/yeai
                                                             tons/year
Process Emissions into Controlled Plants   =     960,000     tons/year
         of
Control Device

  ESP
% Application on
Controlled Plants

       42
                                                       Process Emissions into
                                                       Control Device :(tons/year)

                                                            403,200	-
  Venturi
       58
                                                            556.600
                                  256

-------
                               TABLE E-28
     FINE-PAETICLE EMISSIONS FROM BASIC OXYGEN FURNACES CONTROLLED
                     '- BY ELECTROSTATIC PRECI1TCATOK
Process -  Basic Oxygen Furnace
Control Device -  Electrostatic Precipitator
Process Emissions into Control Device   405,200
                                                tons/year
                         Control Device
                              Control Device
Process
Size (n/
1-3
Emissions
) Percent
6
. I ESP |
Penetration (#)
(l - efficiency)-^
1.6
L
1
Penetration ($)
(1 - efficiency)

••
Emissions
(tons /year)
400
0.5-1.0
36
2/6
3,300
0.1-0.5
57.8
3.8
8.900
0.05-0.1
 0.2
5.5
0.01-0.05
             8.2
                                                                 12,600
a/  Efficiency values were taken from high fractional efficiency curve,
      Figure 17.
                                257

-------
                                TABLE E-29
           FINE-PARTICLE EMISSIONS FROM BASIC  OXYGEN FURNACES
                     CONTROLLED  BY VENTURI SCRUBBER
Process -  Ba.sic Oxygen Furnace
Control Device -  Venturi Scrubber
Process Emissions Into Control Device   556,800
                                                tons/year
Process Emissions
Size (iQ	Percent

1-3             6
                         Control Device
                         I  Venturi     I
                              Control Device
 Penetration
(l - efficiency)

      1.4
                              Penetration
                             (l - efficiency)
                                   Emissions
                                  (tons/year)

                                       500
0.5-1.0
36
 7.8
                                         15,600
0.1-0.5
57.8
45
                                        144,800
0.05-0.1
 0.2
86
                                          1,000
0.01-0.05
                                                                161,900
                                 258

-------
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-------
                               TABLE E-31
      DISTRIBUTION OF PROCESS EMISSIONS FROM ELECTRIC ARC FURNACE
Source -  Iron and Steel
Process -  Electric Arc Furnace
                    Production       Emission Factor
                    (tons/year)         (Ib/ton)
Process Emissions = ( 16.8 x 1Q6  )      (  10 )
Application of Control
                            79
Process Emissions into Uncontrolled Plants =

Process Emissions into Controlled Plants   =
                         (27000")
                       18,000
                       66,000
     =  84'000   tons/year
      _tons/year

       tons/year
    Type of
Control Device

Wet Scrubber

ESP	

FF
% Application on
Controlled Plants

      11
     82
 Process Emissions  into
 Control Device (tons/year)

	7,300	

.	4.600	

	54.100	
                                 260

-------
                               TABLE E-32
    FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC AIR FURNACES
Process -   Electric Arc Furnace
Control Device -   Uncontrolled
Process Emissions into Control Device  	16,000
                                       tons/year
Process Emissions
Size (n)	Percent
1-3
               20
 Control Device
 [Uncontrolled |
 Penetration (#)
(l - efficiency)

      100
                                             Control Device
                                             I              I
 Penetration
(1 - efficiency)
 Emissions
{•tons/year)

   3,600
0.5-1.0
               12
      100
                      2,200
0.1-0.5
               21
      100
                      3,800
0.05-0.1
                              100
                                           900
0.01-0.05
                5.6
      100
                      1,000

                     11,500
                               261

-------
                                TABLE E-33

           FINE-PARTICLE EMISSIONS FROM ELECmiC ARC FURNACES
                        CONTROLLED BY WET SCRUBBER


Process -  Electric Arc Furnace

Control Device -  Wet Scrubber	

Process Emissions into Control Device     7,300	
                                tons/year
                         Control Device
              Control Device
Process
Size (|i)
1-3
Emissions
Percent
20
| Wet Scrubber |
Penetration (#) ,
(l - efficiency)^
9
1

1
Penetration (#)
(l - efficiency)



Bid ss ions
^tons/year)
100
0.5-1.0
               12
26
  200
0.1-0.5
               21
62
1,000
0.05-0.1
                               92
                                   300
0.01-0.05
                5.6
98
  400
                                                                2,000
a/  Efficiency values were taken from high fractional efficiency curve,
      Figure 17.
                                262

-------
                               TABLE E-34

           FINE-PARTICLE EMISSIONS FROM ELECTRIC ARC FURNACES
                CONTROLLED Hf ELECTROSTATIC PRECIPITATOR
Process  -  Electric Arc Furnace
 Control  Device  -  Electrostatic Precipitator
Process Bnissions into Control Device _ 4? 600
                                                               tons/y
                                                                     ear
                         Control Device
                                             Control Device
Process Emissions
Size (p.) Percent
1-3 20
1
ESP I
Penetration ($)
(1 - efficiency)2^

1.6
L
1
f Penetration (#)
(1 - efficiency)


Emissions
(tons /year)

0.5-1.0
                12
 0.1-0.5
 0.05-0.1
 0.01-0.05
                5-6
                              8-2
                                                                    100
a/  Efficiency values were taken from high fractional efficiency curve,
      Figure 17.
                                263

-------
                               TABLE E-35
           FINE-PARTICLE EMISSIONS FROM ELECTRIC ARC FURNACES
                      CONTROLLED BY FABRIC FILTER
Process -  Electric Arc Furnace
Control Device -  Fabric Filter
Process Emissions into Control Device
                   54,100
                   tons/year
Process Emissions
Size (p.)	Percent
1-3
                20
                         Control Device
 Penetration
(l - efficiency)

      0.5
 Control Device
 I              I
 Penetration (%)
(l - efficiency)
 Emissions
(tons/year)

    100
0.5-1.0
                12
      1.8
                       100
0.1-0.5
                21
      3.3
                       400
0.05-0.1
                              4.2
                                           100
0.01-0.05
                 5.6
      4.5
                       100
                                                                   800
                               264

-------



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                               TABLE E-37
      DISTRIBUTION OF PROCESS EMISSIONS FROM OPEN HEARTH FURNACES
Source .   Iron and Steel

Process -  °Pen Heaxth
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 65.8 x 106  )      (  17 )

Application of Control =    41  
-------
                          TABLE E-38
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED OPEN HEARTH FURNACES
Process - Open Hearth


Control Device - Uncontrolled
Process Hnissions into Control Device
1. Based on Particle
Process Emissions
Size (n) Percent
1-3 17
0.5-1.0 15
0.1-0.5 59
0.05-0.1 5-2
0.01-0.05 °-8
Size Distribution
Control Device
I Uncontrolled 1
Penetration (#)
(1 - efficiency)
100
100
100
100
100
2. Based on "Composite" Particle Size
Control Device
[Uncontrolled 1
Process Hnissions Penetration (#)
Size (M-) Percent (l - efficiency)
1-3 22.5
0.5-1.0 5.3
0.1-0.5 2.16
0.05-0.1 0.04
100
100
100
100
330,400 tons/year
in Lower Right of Figure 26.
Control Device
1 I
Penetration (#) Emissions
(l - efficiency) (tons/year)
56,200
49,600
194,900
17,200
2,600
320,500
Distribution in Figure 26.
Control Device
1 1
Penetration (%) Emissions
(l - efficiency) (tons /year)
74,300
17,500
7,100
100
0.01-0.05
                                                            99,000
                            267

-------
                                TABLE E-39
            FINE-PARTICLE EMISSIONS FROM OPEN HEARTH FURNACES
                 CONTROLLED BY ELECTROSTATIC FRECIPITATOR
 Process -  Open Hearth
 Control Device -  Electrostatic Precipitator

 Process Emissions into Control Device    229,600
                                                 tons/year
   1.  Based on Particle Size Distribution in Lower Right of Figure 26.
                          Control Device      Control Device
                               ESP
 Process Emissions        Penetration (#)     Penetration (#)    Emissions
 Size (n)	Percent    (l - efficiency)**/  (1 - efficiency)   (tons/year)
 1-3
17
 11
 4,300
 0.5-1.0
15
 17
 5,900
 0.1-0.5
59
 29
39,500
 0.05-0.1
 5.2
 41
 4.900
 0.01-0.05
 0.8
 55
 1,000
                                                                  55,400

   2.  Based on "Composite" Particle Size Distribution in Figure 26.
                          Control Device
                               Control Device
                               ESP
                        J
 Process Emissions         Penetration (%)  .    Penetration (#)     Emissions
 Size (ii)     Percent    (l -  efficiency^   (l  -  efficiency)    (tons/year)
 1-3
              22.5
                 11
                                   5,700
 0.5-1.0
               5.3
                 17
                                   2,100
 0.1-0.5
               2.16
                 29
                                   1,400
 0.05-0.1
0.04
41
 0.01-0.05
                55
                                                                  9,200
a/  Efficiency values were taken from medium efficiency curve, Figure 17.
                                    268

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-------
                               TABLE E-41
         DISTRIBUTION OF PROCESS EMISSIONS FROM SINTER MACHINE
Source -   Iron
                    Steel
Process -  Sinter Machine—Windbox
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 51.0 x 106  )      (  20 )
Application of Control =   100  

Process Emissions into Uncontrolled Plants

Process Emissions into Controlled Plants
                                                   (2,000)
     = 510,000   tons/year
                                                             tons/year
                                               510,000
       tons/y i
ear
    Type of
Control Device

 Cyclone
                          % Application on
                          Controlled Plants

                                 45
 Process Emissions into
 Control Device (tons/year)

	229,500        	
 Cyclone + ESP
 FF
                                  36
                                  19
     185,600

      96,900
                                270

-------
                                TABLE E-42

             FINE-PARTICLE EMISSIONS  FROM SINTER MACHINES
                          CONTROLLED BY CYCLONES
Process  -  Sinter Machines—Windbox
Control Device -  Cyclones
Process Emissions into Control Device    229,500
                                tons/year
                         Control Device
              Control Device
Process Emissions
Size (n) Percent
1-3 2.7
[ Cyclones
Penetration (#)
(l - efficiency)^/
57
I
Penetration (#)
(1 - efficiency)

Emissions
(tons/year)
3,500
 0.5-1.0
               0.56
82
1,100
0.1-0.5
               0.23
94
  500
0.05-0.1
0.01-0.05
                                                                  5,100
lyEfficiency values were taken from high fractional efficiency curve,
      Figure 17.
Note:  Outlet particle size distribution for sinter machines controlled by
         cyclones showed 20 wt. #< 3 (j,.  If overall efficiency of cyclones
         is assumed to be 80$, then quantity emitted by sinter machines
         controlled by cyclones is

            (229,500 tons/year) (1-0.80)(0.20) = 9,200 tons/year .
                                271

-------
                                TABLE E-43

   FINE-PARTICLE EMISSIONS FROM SINTER t&CHINES CONTROLLED BY CYCLONE
                     PLUS ELECTROSTATIC PRECIPITATOR

 Process  -  Sinter Plant—Windbox
  Control Device  -  Cyclone + Electrostatic Precipitator

  Process Emissions into Control Device	163,600	tons/year
                          Control Device      Control Device
                          I Cyclones    I      I     ESP      I
  Process Emissions        Penetration  ($)     Penetration (#)    Emissions
  Size  (iQ     Percent     (l - efficiency )£/  (l - efficiency)**/ (tons/year)
  1-3 _ 2/7 _ 57 _ 11 _ 300

  0.5-1.0 _ 0.56 _ 82 _ 17 _ 100

  0.1-Q.5 _ 0.25 _ 94 _ 29 _ 100

  0.05-0.1

  0.01-0.05

                                                                    500


a/  Efficiency values were taken from high fractional efficiency curve,
      Figure 17.
b/  Efficiency values were taken from medium fractional efficiency curve
      Figure 17.
                                   272

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-------
                               TABLE E-45
      DISTRIBUTION OF PROCESS EMISSIONS FROM IRON FOUNDRY CUPOLAS
Source -  Iron Foundries
Process -  Cupolas
                    Production       Emission Factor
                    (tons/year)         (Ib/ton)
Process Emissions = ( 18.0 x 106  )      ( 16  )
Application of Control
                           53
Process Emissions into Uncontrolled Plants =

Process Emissions into Controlled Plants   =
                                                   (2,oCo)
      144,000  tons/year
                                                 96,000
      tons/;
                                                                  year
                                                 46,000	tons/year
         of
Control Device

 ESP
                          % Application on
                          Controlled Plants

                             Neglect < l
Process Bnissions into
Control Device (tons/year)
 Cyclone
                                 16
       7,700
Wet Scrubber
 FF
                                 74
                                 10
      35.500
       4.800
                                 274

-------
                               TABLE E-46
     FINE-PARTICLE EMISSIONS FROM UNCONTROLLED IRON FOUNDRY CUPOIAS
Process -   Cupolas
Control Device -   Uncontrolled
Process Emissions into Control Device
                                           96,000
                                                               tons/year
Process Emissions
Size (n>)	Percent

1-3            6
                         Control Device
                         IUncontrolled1
                         Penetration (#)
                        (l - efficiency)

                              100
                                             Control Device
                                             Penetration
                                            (l - efficiency)
                                                                Emissions
                                                               (tons/year)

                                                                  5,800
0.5-1.0
                              100
                                                                  1,900
0.1-0.5
               2.3
                              100
                                                                  2,200
0.05-0.1
               0.34
                              100
                                                                    300
0.01-0.05
               0.31
                              100
                                                                    300
                                                                 10,500
                                  275

-------
                                TABLE E-47

            FINE-PARTICLE EMISSIONS  FROM IRON FOUNDRY CUPOIAS
                          CONTROLLED BY CYCLONES
Process  -  Cupolas
Control Device  -  Cyclones
Process Emissions into Control Device      7,700
                                 tons/year
                         Control Device
               Control Device
Cyclones | | j
Process
Size (u)
1-3

Emissions
Percent
6
Penetration (#)
(l - efficiency)^/

73

Penetration (#)
(l - efficiency)



Emissions
(tons /year)
300
0.5-1.0
                               89
                                     100
0.1-0.5
                2.3
100
200
 0.05-0.1
                0.34
100
0.01-0.05
                0.31
100
                                                                   '600
a/  Efficiency values were taken from medium fractional efficiency curve,
      Figure 17.
                                  276

-------
                                TA.BLE E-48


      FINE-PARTICLE EMISSIONS  FROM IRON FOUNDRY CUPOLAS CONTROLLED
                      BY WET SCRUBBERS AND WET GAPS


Process -  Cupolas	

Control Device -  Wet Scrubbers and Wet Caps


Process Bnissions into Control Device	35,500	tons/year



                         Control Device     Control Device
                         I Wet  Scrubber!      I              I
Process Bnissions        Penetration ($)  ,   Penetration ($)    Bnissions
Size (M.)     Percent    (l - efficiency)-^  (l - efficiency)   (tons/year)

1-5            6             31                                    700


0.5-1.0        2	fi	40°


0.1-0.5        2'3           86                                    70°
0.05-0.1
               0.34          99                                    100
0.01-0.05
               0.31         100                                    100
                                                                 2,000
a/ Efficiency values were taken from low fractional efficiency curve,
     Figure 17.
                                277

-------
                               TABLE E-49

           FINE-PARTICLE EMISSIONS FROM IRON FOUNDRY CUPOLAS
                      CONTROLLED BY FABRIC FILTERS
Process -  Cupolas
Control Device -  Fabric Filter
Process Emissions into Control Device    4,800
                                       tons/year
                         Control Device
                         I      FF      I
                     Control Device
Process Emissions
Size (iQ	Percent
1-3
                6
 Penetration
(l - efficiency)

       0.5
 Penetration (%)    Emissions
(l - efficiency)   (tons/year)
0.5-1.0
                               1.8
0.1-0.5
                2.3
       3.3
0.05-0.1
                0.34
       4.2
0.01-0.05
                0.31
       4.5
                                                                 « 100
                                  278

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-------
                               TABLE E-51
           DISTRIBUTION OF PROCESS EMISSIONS FROM BARK BOILER
Source -
                Mills
Process -  Bark Boilers
                    Production
                    (tons/year)
Process Bnissions = (	
Application of Control
                           72
           Emission Factor
              (ib/ton)
                         (SjOUu)
     = 7 54,400£/tons/yoar
Process Emissions into Uncontrolled Plants =    205,600
                                  _tons/year
Process Bnissions into Controlled Plants   =    528,800
                                   tons/year
    type of
Control Device

  Cyclones
% Application on
Controlled Plants

      100
 Process Emissions  into
 Control Device (tons/year)

	528,800	
 a/  See Reference 1  for method of process emissions calculations.
                                   280

-------
                                TABLE E-52
          PINE-PARTICLE EMISSIONS FROM UNCONTROLLED BARK BOILERS
Process -   Bark Boilers
Control Device -   Uncontrolled	

Process Emissions into Control Device   205,600
                                                tons/year
                         Control Device
                              Control Device
Process Emissions
Size (ti)	Percent
1-3
8.3
  Uncontrolled(
 Penetration (#)
(l - efficiency)

     100
 Penetration ()     Emissions
 (l  -  efficiency)    (tons/year)

	17,100
0.5-1.0
1.77
     100
                      3,600
0.1-0.5
0.89
     100
                      1,800
0.05-0.1
0.03
     100
                        100
0.01-0.05
                                                                22,600
                                   281

-------
                                TABLE  E-53
    FINE-PARTICLE EMISSIONS FROM  BARK  BOILERS CONTROLLED BY CYCLONES
Process -
                 Boilers
Control Device -  Cyclones
Process Emissions into Control Device    528,800
                                                               tons/year
                         Control Device
                                             Control Device
1 Cyclones
Process
Size (n)
1-3

Emissions
Percent
8.3
1
Penetration (<$>)
(l - efficiency)^/

73

1

1
Penetration ($)
(l - efficiency)



Emissions
(tons /year)
32,000
0.5-1.0
              1.77
 89
8,300
0.1-0.5
              0.89
100
4,700
0.05-0.1
              0.03
100
  200
0.01-0.05
                                                                 45,200
a/  Efficiency values were taken medium fractional efficiency curve,
      Figure 17.
                                   282

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-------
                               TABLE E-55
        DISTRIBUTION OF PROCESS EMISSIONS FROM RECOVERY FURNACE
Source -  Pulp Mill
Process -  Recovery Furnaces
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 24.5 x 106  )      (150 )
Application of Control =
                            99
Process Emissions into Uncontrolled Plants =
                                                 18.200
                                                           = 1,822.500 tons/year
      tons/year
Process Emissions into Controlled Plants   =   1.804.300	tons/year
    Type of
Control Device
                          % Application on
                          Controlled Plants
Process Emissions into
Control Device (tons/year)
ESP
ESP + Wet
Venturi Evaporator
Venturi + Wet
82
4
11
3
1,804,300
(See Notej



Note:  Fractional efficiency characteristics of these specialized Venturi
         evaporator systems are not known. Since electrostatic precipitator
         represents most applications, we will assume all are equivalent to
         "medium" efficiency electrostatic precipitators.
                                   284

-------
                               TABLE E-56
     FINE-PARTICLE EMISSIONS FROM UNCONTROLLED RECOVERY FURNACES
Process -  Recovery Furnace
Control Device -  Uncontrolled
Process Emissions into Control Device    18.200
                                       tons/year
Process Emissions
Size (n)	Percent
1-3
              44
 Control Device
 [Uncontrolled|
 Penetration ()
(l - efficiency)

      100
                                             Control Device
                                             I              I
Penetration
l - efficiency)
 Emissions
(tons/year)

   8,000
0.5-1.0
              24
      100
                     4,400
0.1-0.5
              13.8
      100
                     2,500
0.05-0.1
              0.19
      100
0.01-0.05
                                                                 14,900
                                  285

-------
                                TABLE E-57

        FINE-PARTICLE EMISSIONS FROM RECOVERY FURNACES CONTROLLED
                     BY ELECTROSTATIC PRECIPITATOR

 Process - Recovery Furnace	

 Control Device - Electrostatic Precipitators^
Process Emissions into Control Device
Control Devic<
ESP
Process Emissions Penetration ('
Size (p,) Percent (l - efficiency
1-3 44 11
0.5-1.0 24 17
0.1-0.5 13«8 29
0.05-0.1 0-19 41
0.01-0.05 55
Control Device
1
Process Emissions Penetration ($
Size (u) Percent (l - efficiency
1-3 44 1.6
0.5-1.0 24 2.3
0.1-0.5 13.8 3.8
0.05-0.1 0.19 5.5
0.01-0.05

1,804,300 tons/year
2 Control Device
1 1
») Penetration ($) Emissions
f^ (l - efficiency) (tons/year)
87,300
73,600
72,200
1,400

234,500
Control Device
1
) Penetration (#) Emissions
)£/ (l - efficiency) (tons /year)
12,700
10 ,000
9,500
200

32,400
a/  Efficiency values used were taken from medium fractional efficiency  curve,
      Figure 17.
b/  Efficiency values used were taken from high efficiency curve, Figure 17.
                                  286

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-------
                               TABLE E-59
      DISTRIBUTION OF PROCESS EMISSIONS FROM PULP-MILL LIME KILNS
Source -
               Mills
Process -   Lime Kilns
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 24.5 x 106  )      ( 45  )
Application of Control =
                            99
                                                   (2,600)
        546,800  tons/year
Process Emissions into Uncontrolled Plants = _ 5,500 _ tons/year

Process Emissions into Controlled Plants   =     541,500 _ tons/year
         of
Control Device

 Wet Scrubljers
                          % Application on
                          Controlled Plants

                                 100
 Process EMssions  into
 Control Device (tons/year)

	541»300	
                                  288

-------
                               TABLE E-60

     FINE-PARTICLE EMISSIONS FROM UNCONTROLLED PULP-MILL LIME KILNS

Process -  Lime Kiln — Pulp Mill _

Control Device -   Uncontrolled
Process Emissions into Control Device
                  5,500
                                                               tons/year
 Control Device
 I Uncontrolled I
Process Emissions
Size (iQ _ Percent

1-3            1
 Penetration
(l - efficiency)

      100
                                             Control Device
                                             Penetration ($)    Emissions
                                            (l - efficiency)   (tons /year)

                                                                  100
0.5-1.0
               0-09
0.1-0.5
0.05-0.1
0.01-0.05
                                                                  100
                                  289

-------
                                TA.BLK  E-C1
           FINE-PARTI OLE  EMISSIONS FHOM  PULP-MtJ.L  JJMK  KILNS
                      CONTROLLED  BY WET  SCRUBBERS
Process -   Lime Kiln—Pulp Mill
Control Device -  Wet Scrubbers	

Process Emissions into Control Device    541,300
                                                tons/year
                         Control Device
                              Control Device
Process Emissions
Size (M.) Percent
1-3 1.3
| Scrubbers j
Penetration ($)
(l - efficiency);*/
21
I
1
Penetration (#)
{l - efficiency)


Emissions
(tons /year)
1,500
0.5-1.0
0.09
43
200
0.1-0.5
               74
0.05-0.1
               95
0.01-0.05
              100
                                                                 1,700
a/ Efficiency values were taken from medium efficiency curve, Figure 17.
                                    290

-------





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-------
                               TABLE E-63
        DISTRIBUTION OF PROCESS EMISSIONS FROM ROTARY LIME KILN
Source -   Lime
Process -  Rotary Kilns	
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
                    fie r\ ,, irt6
)
                                         ( 160 )
                                 =1,458,000 tons/year
Process Emissions = (16.2 x •

Application of Control =   87   %

Process Emissions into Uncontrolled Plants =    190,000	tons/year

Process Emissions into Controlled Plants   =  1,268,000	tons/year
    Type of
Control Device

 Cyclones	
% Application on
Controlled Plants

     20.6
                     Process  Emissions  into
                     Control  Device  (tons/year)

                    	261,000	
 Wet
     35.4
                           449,000
 FF
     44.0
                           558.000
                                  292

-------
                               TABLE E-64

      FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ROTARY  LIME KILNS

Process -  Lime Kilns—Rotary
Control Device -  Uncontrolled Plants
Process Bnissions into Control Device    190,000	tons/year
                         Control Device      Control Device
                         I Uncontrolled I      I              I
Process Bnissions        Penetration ($)     Penetration ($)    Bnissions
Size (M-)	Percent    (l - efficiency)    (l - efficiency)   (tons/year)

1-3	8.5	100	16.200

0.5-1.0	3_.0	100	5.700

0.1-0.5	2.95	100	5,600

0.05-0.1	0.55	100	600

0.01-0.05	0.20	100	400

                                                                 28,500
                                  293

-------
                                TABLE E-65

 FINE-PARTICLE EMISSIONS FROM ROTARY LIME KILNS CONTROLLED BY CYCLONES
Process -
                   Lime  Kilns
Control Device -   Cyclone
Process Emissions into Control Device
                                           261.000
                                       tons/year
                                             Control Device
Process Emissions
Size (|i)	Percent

1-3            8-5
 Control Device
 I  Cyclone    1
 Penetration ($)     Penetration (%)
(l - efficiency)^/  (l - efficiency)
                               73
 Emissions
(tons/year)

  16,200
0.5-1.0
               3.0
       89
   7,000
0.1-0.5
               2.95
      100
   7,700
0.05-0.1
               0.33
      100
     900
0.01-0.05
               0.20
      100
     500
                                                                 32,300
a/  Efficiency values used were taken from medium fractional efficiency curve,
      Figure 17.
Note:  Particle size distribution for kilns controlled by cyclones shows
         58$ < 3 (j,.  Therefore, assuming overall cyclone efficiency  of
         70$, emissions are calculated to be

            (261,000 tons/year)(1-0.70)(58$) = 45,400 tons/ year < 3 u.
                                   294

-------
                                TABLE E-66

FIDE-PARTICLE EMISSIONS FROM ROTARY LIME KILNS CONTROLLED BY WET SCRUBBERS
 Process -  Rotary Lime Kilns
 Control Device -  Wet Scrubbers
 Process Emissions into Control Device   449,000
                                                 tons/jn
                                        •ear
                          Control Device
                               Control Device
Process Emissions
Size (n) Percent
1-3 8.5
Wet Scrubber
Penetration (#)
(l - efficiency)^/
21
1
Penetration ($)
(l - efficiency)

Emissions
(tons /year)
8,000
 0.5-1.0
3.0
 43
5,800
 0.1-0.5
2.95
 74
9,800
 0.05-0.1
0.33
                               95
                                     1,400
 0.01-0.05
0.20
100
  900
                                                                  25,900
 a/  Efficiency values used were taken from medium efficiency curve, Figure 17,
 Note:   Particle size distribution for kilns controlled by wet scrubber in-
          dicates 67% < 3 p,. Assuming overall scrubber efficiency of
          emissions are calculated to be

            (449,000 tons/year)(1-0.90)(0.67)  = 30,100 tons  year < 3 p,.
                                   295

-------
                                TABLE  E-67

       FINE-PARTICLE EMISSIONS  FROM ROTARY LIME KILNS CONTROLLED
                           BY FABRIC  FILTER
Process - Rotary Lime Kilns

Control Device -  Fabric Filter
Process Emissions into Control Device	558,000
                                                tons/year
                         Control Device
                         L
                       J
Process Emissions
Size (n)	Percent
1-3
8.5
 Penetration
(l - efficiency)

      0.5
                              Control Device
 Penetration (%)    Emissions
(l - efficiency)   (tons/year)

                      200
0.5-1.0
3.0
      1.8
                      300
0.1-0.5
2.95
      3.3
                      500
0.05-0.1
0.33
      4.2
                      100
0.01-0.05
0.20
      4.4
                                                                1,100
                                   296

-------
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-------
                               TABLE E-69
      DISTRIBUTION OF PROCESS EMISSIONS FROM MUNICIPAL INCINERATOR
Source - Municipal Incineration
Process -  Incinerators
                    Production       Emission Factor
                    (tons/year)         (ib/ton)
Process Emissions = ( 20 x 1Q6    )      ( 24  )
Application of Control =   60   %

Process Emissions into Uncontrolled Plants =

Process Emissions into Controlled Plants   =
                         (2,ouo)
     =  240,000 tons/year
                        96,000     tons/year

                       144,000     tons/year
    Type of
Control Device

 Low efficiency scrubber
$ Application on
Controlled Plants

        77
 Process Emissions into
 Control Device (tons/year)

	1U .000	
 Medium efficiency scrubber	8_

 Cyclones                         15
                                    11,500

                                    21,500
                                  298

-------
                                TABLE E-70
    FINE-PARTICLE EMISSIONS  FROM UNCONTROLLED MUNICIPAL INCINERATORS
Process -  Municipal Incinerator	

Control Device -   Uncontrolled	

Process Bnissions into Control Device
                            96,000
                                 tons/year
                         Control Device
Process Emissions
Size (M.)	Percent
1-3
7.0
  Uncontrolled]
 Penetration (#)
(l - efficiency)

      100
                               Control Device
                               Penetration
                              (1 - efficiency)
                                  Emissions
                                 (tons/year)

                                    6,700
0.5-1.0
3.5
100
                                          5,400
0.1-0.5
5.2
100
                                          5,000
0.05-0.1
1.5
100
                                          1,400
0.01-0.05
1.8
100
                                          1,700

                                         18,200
                                  299

-------
                                TABLE E-71

     FINE-PARTICLE EMISSIONS  FROM MUNICIPAL  INCINERATORS CONTROLLED
                       By LOW EFFICIENCY  SCRUBBER

Process -  Municipal Incinerator	

Control Device -  Low Efficiency  Scrubber
Process Emissions into Control Device  111,000
                                   tons/year
                         Control Device
                 Control Device
Process
Size (u)
1-3
Emissions
Percent
7.0

Scrubber |
Penetration ($)
(l - efficiency)^/
31
1
1
Penetration (%)
(l - efficiency)


Emissions
(tons /year)
2,400
0.5-1.0
              3.5
 61
2,400
0.1-0.5
              5.2
 86
5,000
0.05-0.1
              1.5
 99
1,600
0.01-0.05
              1.8
100
2,000
                                                               13,400
a/  Efficiency values were taken from low efficiency curve, Figure 17.
                                  300

-------
                                TABLE E-72

       FIHE-PARTICLE EMISSIONS FROM MUNICIPAL INCINERATOR CONTROLLED
                      BY MEDIUM EFFICIENCY SCRUBBER

Process -   Municipal Incinerator	

Control Device -   Medium Efficiency Scrubber

Process Emissions  into Control Device	11,500	tons/year


                         Control Device      Control Device
                          I  ScrubberI      II
Process Bnissions        Penetration (#)     Penetration (%)    Emissions
Size (p.)	Percent    (l - efficiency)^/  (l - efficiency)   (tons/year)
1-3
              7.0              21                                    200
0.5-1.0       5-5	«	200

0.1-0.5       5-2	74	400

0.05-0.1      1-5	95	200

0,01-0.05     3-6	1£0	200

                                                                 1,200
a/ Efficiency values were taken from medium efficiency curve, Figure 17.
                                   301

-------
                                TABLE E-73

          FINE-PARTICLE EMISSIONS FROM MUNICIPAL  INCINERATORS
                          CONTROLLED BY CYCLONES
Process -  Municipal Incinerator
Control Device -  Cyclones
Process Emissions into Control Device
                             21,500
                                                               tons/year
           Control Device
           |  Cyclone     |
                                             Control Device
Process Emissions
Size (u)	Percent
1-3
0.5-1.0
7.0
3.5
                         Penetration ($)     Penetration ($)    Emissions
                        (l - efficiency)^/  (l - efficiency)   (tons/year)

                               73                                 1,100
                               89
  700
0.1-0.5
5.2
                              100
1,100
0.05-0.1
1.5
                              100
  300
0.01-0.05     1.8
                              100
                                                      400
                                                                  3,600
a/  Efficiency values were taken from medium efficiency curve, Figure 17.
                                  302

-------
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                               TAULE K-'/b

   DISTRIBUTION OF PROCESS EMISSIONS FROM ELECTRIC  UTILITY PULVERIZED
                           COAL-FIRED BOILER

Source -  Stationary Combustion
Process -  Electric Utility Pulverized Coal-Fired Boiler
                    Production       Emission Factor
                    (tons/year)         (ib/ton)    .   -^
Process Emissions = ( 258.4 x 106 )      ( 190 )   L j^] = 24.6 x 106 tons/year

Application of Control =   96.9 %

Process Emissions into Uncontrolled Plants =   0.6 x 10	tons/year

Process Emissions into Controlled Plants   =   25.8 x 1Q6    tons/year
         of
Control Device

 Cyclones	

 Cy + ESP

 ESP
% Application on
Controlled Plants

     24.3	

     15.1	

     60.6
        Fiimiorjlorin Into
Control Device (torm/y^ar)

    5.8 x 106	

    5.6 x 106	

   14.4 x 106
                                  304

-------
                               TABLE E-Y(J
      FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC UTILITY
                     PULVERIZED COAL-FIRED BOILERS

Process - Electric Utility Pulverized Coal-Fired Boiler
Control Device -   Uncontrolled
Process Bnissions into Control Device    °»8 x 10
                                                 tons/year
Process Bnissions
Size (p.)     Percent
1-3
10
 Control Device
 I  Uncontrolled!
 Penetration (#)
(l - efficiency)

      100
                                             Control Device
  Penetration (%)     Enissions
 (l  -  efficiency)    (tons/year)

	60,000
0.5-1.0
 2.1
      100
                      16,600
0.1-0.5
 0.87
      100
                       7,000
0.05-0.1
 0.02
      100
                         200
0.01-0.05
                                                                104,000
                                  305

-------
                                TABLE E-77

FINE-PARTICLE EMISSIONS FROM ELECTRIC UTILITY PULVERIZED COAL-FIRED BOILERS
                 CONTROLLED BY ELECTROSTATIC PRECIPIIATOR
 Process - Electric Utility Pulverized Coal-Fired Boiler

 Control Device - Electrostatic Precipitator

 Process Emissions into Control Device  14.4 x 106	
                                               _tons/year
                          Control Device
                              Control Device
1 ESP 1 1
Process
Size (n)
1-3

Emissions
Percent
10
Penetration (%)
(1 - efficiency)^/

11

Penetration ($)
(l - efficiency)



Emissions
{tons /year)
158,400
 0.5-1.0
2.1
17
51,400
 0.1-0.5
0.87
29
36,300
 0.05-0.1
0.02
41
 1.200
 0.01-0.05
                                                                 247,300
 a/  Efficiency values used were taken from average fractional efficiency
       curve, Figure 17.
                                   306

-------
                                 TAHI.I'! K-'/H

FINE-PARTICLE EMISSIONS M
-------
                                TABLE E-79

FINE-PAHTICLE EMISSIONS FROM ELECTRIC UTILITY PULVERIZED COAL-FIRED BOILERS
          CONTROLLED BY CYCLONE PLUS ELECTROSTATIC PRECIPITA.TOR

 Process -  Electric Utility Pulverized Coal-Fired Boiler
 Control Device -  Cyclone + Electrostatic Precipitator
                                                 c
 Process Emissions into Control Device   3.6 x 10°
                                                tons/year
                          Control Device
                          |   Cyclone    [
                              Control Device
                                   ESP
 Process Emissions
 Size (M.)	Percent
 1-3
10
 Penetration
(l - efficiency)

       57
              Penetration
             (1 - efficiency)

                    11
             Emissions
            (tons/year)

              22.600
 0.5-1.0
 2.1
82
17
                                         10.500
 0.1-0.5
                 0.87
                94
                    29
               6,500
 0.05-0.1
                 0.02
               100
                    41
                 300
 0.01-0.05
                                                                  41,900
                                   308

-------


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-------
                               TABLE E-81

     DISTRIBUTION OF MtOCI'gjn BMliJmoN.'I 1'KQM ELk'CTKlC  UTILITY  ."'J'OKEK
                           COAL-FIRED BOiLEK


Source -  Stationary Combustion
Process -  Electric Utility Stoker Coal-Fired Boiler
                    Production       Emission Factor
                    (tons/year)          (ib/ton)    *    >.
Process Emissions = ( 9.9 x 106    )       ( 146  )    L^  *^\  = 0.72xl06  tons/year

Application of Control =    87  %

Process Emissions into Uncontrolled Plants =  0.095 x  106    tons/year

Process Bnissions into Controlled  Plants  =  0.627 x  106    tons/year
         of
Control Device

 ESP	

 Cyclones
$ Application on
Controlled Plants

      5.2	

     94.8
Prcxjess
Control Device (tons/your)

    0.035 x 1Q6	

    0.594 x 106
                                   310

-------
                               TABLE E-82

    FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC UTILITY STOKER
                           COAL-FIRED BOILERS

Process -  Electric Utility Stoker Coal-Fired Boiler
Control Device -  Uncontrolled	
                                                  ft
Process Emissions into Control Device   0.093 x 10	tons/year


                         Control Device      Control Device
                           Uncontrolled
Process Emissions        Penetration (%)     Penetration (%)    Emissions
Size (ti)     Percent    (l - efficiency)    (l - efficiency)   (tons/year)
1-5	4.8	100	4.500

0.5-1.0	0_.9	100	800

0.1-0.5	0.29	100	300

0.05-0.1	

0.01-0.05	i

                                                                  5,600
                                   311

-------
                                TA.BLE E-83

FINE-PARTICLE EMISSIONS FROM ELECTRIC UTILITY STOKER COAL-FIRED BOILERS
                  CONTROLLED BY ELECIROSIA.TIC PRECIPITATOR

Process -   Electric  Utility Stoker Coal-Fired Boiler_
Control Device  -  Electrostatic  Precipitator

Process Emissions into Control Device   0.053 x 106
                                                tons/year
                         Control Device
                              Control Device
Process
Size (n)
1-3
Emissions
Percent
4.8
1
ESP 1
Penetration (#)
(1 - efficiency)^/
11


1
Penetration (#)
(l - efficiency)



Emissions
(tons /year)
900
0.5-1.0
0.9
17
500
0.1-0.5
0.29
29
300
 0.05-0.1
0.01-0.05
                                                                 1,700
a/  Efficiency values used were taken from average fractional efficiency
      curve, Figure 17.
                                   312

-------
                               TABLE E-84

 FIME-PARTICLE EMISSIONS FROM ELECTRIC UTILITY STOKER COAL-FIRED BOILERS
                         CONTROLLED BY CYCLONES

Process -  Electric Utility Stoker Coal-Fired Boiler

Control Device -   Cyclones
Process Bnissions into Control Device  0.594 x 10
                                                 ,6
                                                 tons/year
                         Control Device
                              Control Device
Process Bnissions
Size (n) Percent
1-3 4.8
1 Cyclone
Penetration (#)
(l - efficiency)^
57
1
Penetration (#)
(l - efficiency)

Emissions
(tons /year)
16,300
0.5-1.0
0.9
82
4,400
0.1-0.5
0.29
94
1,600
0.05-0.1
0.01-0.05
                                                                  22,300
a/  Efficiency values used were taken from high efficiency cyclone curve,
      Figure 17, because power plants use higher efficiency units.
                                  313

-------

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-------
                               TABLE E-86

    DISTRIBUTION OF PROCESS EMISSIONS FROM ELECTRIC UTILITY CYCLONE
                            COAL-FIRED BOILER

Source -  Stationary Combustion

Process -  Electric Utility Cyclone Coal-Fired Boiler
                    Production       Emission Factor
                    (tons/year)         (It/ton)    .   
-------
                                TABLE E-87

       FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC UTILITY
                        CYCLOME COAL-FIRED BOILERS

Process -  Electric  Utility Cyclone Coal-Fired Boiler

Control Device - Uncontrolled
                                                   C
Process Emissions into Control Device    0.148  x 10°
                                                 tons/year
                         Control Device
Process Emissions
Size (M.)	Percent
1-3
22
 Uncontrolled  I
 Penetration (%)
(l - efficiency)

      100
                               Control Device
                               I             I
                               Penetration
                              (l  -  efficiency)
                                  Emissions
                                 (tons/year)

                                   52.600
0.5-1.0
               5.5
                100
                                    8,100
0.1-0.5
 2.44
100
                                          3,600
0.05-0.1
               0.05
                100
                                      100
0.01-0.05
                                                                 44,400
                                   316

-------
                                TABLE  E-88

FINE-PARTICLE EMISSIONS  FROM ELECTRIC UTILITY  CYCLONE COAL-FIRED  BOILERS
                CONTROLLED  BY ELECTROSTATIC PRECIPITA.TOR
Process -  Electric Utility Cyclone Coal-Fired Boiler

Control Device -  Electrostatic Precipitator

Process Emissions into Control Device   0.294 x 106
                                               tons/year
                         Control Device
                             Control Device
Process Emissions
Size (n) Percent
1-3 22
1 ESP 1
Penetration ($)
(l - efficiency)^/
11
L
1
Penetration ($)
(1 - efficiency)


Emissions
(tons/year)
7,100
0.5-1.0
5.5
17
2,700
0.1-0.5
2.44
29
2,100
0.05-0.1
                0.05
               41
                                     100
0.01-0.05
                                                                 12,000
a/  Efficiency values used were taken from average fractional efficiency curve,
      Figure 17.
                                   317

-------
                              TABLE E-89

        FINE-PARTICLE EMISSIONS FROM ELECTRIC UTILITY CYCLONE
               CCAL-FIRED  BOILERS CONTROLLED BY CYCLONE

Process -  Electric Utility Cyclone Coal-Fired Boiler

Control Device -  Cyclone	

Process Emissions into Control Device  0.068 x 10	tons/year


                         Control Device      Control Device
                         I   Cyclone    I      I              I
Process Emissions        Penetration ($)     Penetration (%)    Emissions
Size (ii)	Percent    (l - efficiency)^/  (l - efficiency)   (tons/year)

1-3	22	57	8,500

0.5-1.0	5.5     	82	5,100

0.1-0.5	2.44	94	-	1,600

0.05-0.1	0.05	100	

0.01-0.05	

                                                                  13,200
a/  Efficiency values used were taken from high efficiency cyclone curve,
      Figure 17, because power plants use higher efficiency units.
                                  318

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                               TABLE E-91

           DISTRIBUTION OF PROCESS EMISSIONS FROM INDUSTRIAL
                      PULVERIZED COAL-FIRED BOILER

Source -  Stationary Combustion

Process -  Industrial Pulverized Coal-Fired Boiler
                    Production       Emission Factor
                    (tons/year)         (ib/ton)    -   >.
Process Emissions = ( 20 x 106    )      ( 170 )   f  j^A = 1.7xl06  tons/year
                                                   V   /
Application of Control =  95.5  %

Process Emissions into Uncontrolled Plants =   0.076  x  106   tons/year

Process Emissions into Controlled Plants   =   1.624  x  106   tons/year
    Type of
Control Device

   ESP	

   Cyclones
 % Application on
 Controlled Plants

	31	

        69
Process Emissions into
Control Device (tons/year)

  0.505 x 106	

  1.12 x 106
                                  320

-------
                                TABLE E-92

          FINE-PARTICLE EMISSIONS FROM UNCONTROLLED  INDUSTRIAL
                     PULVERIZED COAL-FIRED  BOILERS

Process -  Industrial  Pulverized Coal-Fired Boiler

Control Device -   Uncontrolled _

Process Emissions into Control Device    0.076 x 10 _ tons/year


                         Control Device      Control Device
                         lUncontr oiled |      I              |
Process Emissions        Penetration (#)     Penetration (#)    Emissions
Size (tO _ Percent    (l - efficiency)    (l - efficiency)   ( tons /year >
1-5 _ 1.95 _ 100 _ 1.500

0.5-1.0 _ 0.05 _ 100

0.1-0.5 _

0.05-0.1

0.01-0.05 __ .

                                                                 1,500
                                  321

-------
                                TABLE E-93

 FINE-PARTICLE EMISSIONS FROM INDUSTRIAL PULVERIZED  COAL-FIRED BOILERS
                 CONTROLLED  BY ELECTROSTATIC PRECIPIIATOR

Process -  Industrial Pulverized Coal-Fired Boiler
Control Device -  Electrostatic Precipitator

                                                 r*
Process Emissions into Control Device  0.505 x 10P
                                                tons/year
                                             Control Device
Process Emissions
gize (iQ	Percent
1-3
          Control Device
          I      ESP  "~1      I
          Penetration ($)     Penetration
         (l - efficiency)^/  (l - efficiency)
1.95
11
 Emissions
(tons/year)

   1.100
0.5-1.0
0.05
17
0.1-0.5
0.05-0.1
0.01-0.05
                                                                  1,100
a/  Efficiency values used were taken from average fractional efficiency
      curve, Figure 17.
                                    322

-------
                               TABLE E-94

 FINE-PARTICLE EMISSIONS FROM INDUSTRIAL PULVERIZED COAL-FIRED BOILERS
                         CONTROLLED BY CYCLONES


Process -  Industrial Pulverized Coal-Fired Boiler

Control Device -  Cyclones
Process Emissions into Control Device
                                            x 10
                                                tons/year
                         Control Device
                              Control Device
Process
Size (n)
1-3

Emissions
Percent
1.95
1
Cyclone
1
Penetration ($)
(l - efficiency^/

57




Penetration ($)
(1 - efficiency)



Emissions
(tons /year)
12,500
0.5-1.0
0.05
82
500
0.1-0.5
0.05-0.1
0.01-0.05
                                                                 13,000
a/  Efficiency values used were taken from high efficiency cyclone curve,
      Figure 17.
                                  323

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-------
                               TABLE E-96
            DISTRIBUTION OF PROCESS EMISSIONS FROM INDUSTRIAL
                       STOKER COAL-FIRED BOILERS
Source -  Stationary Combustion
Process -  Industrial Stoker Coal-Fired Boilers
                                     Emission Factor
                                        (ib/ton)
                                         ( 155 )
                    Production
                    (tons/year)
Process Emissions = (  70 x 106   )
Application of Control =   62
fy,ouu)
   4.655 x
=  lp6	tons/year
Process Emissions into Uncontrolled Plants =   1.77 x 10°    tons /year

Process Emissions into Controlled Plants   =   2.886 x 106   tons/year '
    Type of
Control Device

  ESP	

  Cyclones	
                          $ Application on
                          Controlled Plants

                                14.8	

                                85.2
    Process Emissions into
    Control Device (tons/year)

       0.427 x 106	

       2.46 x 106
                                  325

-------
                               TABLE E-97
          FIUE-PARTICLE EMISSIONS FROM UNCONTROLLED INDUSTRIAL
                       STOKER COAL-FIRED BOILERS
Process -  Industrial Stoker Coal-Fired Boiler

Control Device -  Uncontrolled
Process Emissions into Control Device  1.77 x 10
                                                tons/year
                         Control Device
                              Control Device
                          Uncontrolled]
Process Emissions
Size (|i)	Percent
1-3
1.76
 Penetration
(l - efficiency)

     100
                              Penetration
                             (l - efficiency)
 Emissions
(tons/year)

  31,100
0.5-1.0
0.19
                             100
                                          3,400
0.1-0.5
0.05
                             100
                                            900
0.05-0.1
0.01-0.05
                                                                 35,400
                                   326

-------
                               TABLE E-98
   FINE-PARTICLE EMISSIONS FROM INDUSTRIAL STOKER COAL-FIRED BOILERS
                CONTROLLED BY ELECTROSTATIC PRECIPITATOR
Process -  Industrial Stoker Coal-Fired Boiler
Control Device - Electrostatic Precipitator
Process Emissions into Control Device   0.427 x
                                                 tons/year
                         Control Device
                               Control Device
Process
Size (n)
1-3

Emissions
Percent
1.76
1
ESP 1
Penetration ($
(l - efficiency

11
)»/

1

1
Penetration (%)
(l - efficiency)



Emissions
( tons/year')
800 .
0.5-1.0
0.19
17
100
0.1-0.5
0.05
29
0.05-0.1
0.01-0.05
                                                                  900
 a/  Efficiency values used were taken from average fractional efficiency
       curve,  Figure 17.
                                  327

-------
                                TABLE l-J-99

   FINE-PARTICLE EMISSIONS FROM INDUSTRIAL STOKER  COAL-FIRED  BOILERS
                         CONTROLLED  BY  CYCLONES

Process  -  Industrial  Stoker Coal-Fired Boiler

Control  Device -   Cyclone	

Process  Emissions into Control  Device   2.459 x 106	tons/year


                         Control Device     Control Device
                            Cyclone
Process Emissions        Penetration  ($)     Penetration ($)    Emissions
Size (it)     Percent     (l - efficiency)^/  (l - efficiency)   (tons/year)

1_3	1.76	57	24,700

0". 5-1.0	0.19	82	5,800

0.1-0.5	0.05	94	1,200

0.05-0.1	

0.01-0.05	

                                                                 29,700
a/  Efficiency values were taken from high efficiency cyclone curve,
      Figure 17.
                                  328

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                              TABLE E-101
       DISTRIBUTION OF PROCESS EMISSIONS FROM INDUSTRIAL CYCLONE
                           COAL-FIRED BOILER
Source -  Stationary Combustion
Process -  Industrial  Cyclone  Coal-Fired Boiler
                                     Emission Factor
                                        (Ib/ton)    ,
                                         ( 31 )
                    Production
                    (tons/year)
Process Emissions = (  10 x 106    )
        0.155
    =   x Ip6  tons/year
Application of Control =    91  #

Process Emissions into Uncontrolled Plants =  0.014 x  10°    tons/year

Process Emissions into Controlled Plants   =  0.141 x  106    tons/year
         of
Control Device

  ESP
                          % Application on
                          Controlled Plants

                                55
Process Emissions into
Control Device (tons/year)

   0.078 x 106
  Cyclones
                                45
   0.063 x 106
                                  330

-------
                              TABLE E-102
     FINE-PARTICLE EMISSIONS FROM UNCONTROLLED INDUSTRIAL CYCLONE
                           COAL-FIRED BOILERS
Process -  Industrial Cyclone Coal-Fired Boiler
Control Device -  Uncontrolled
Process Emissions into Control Device	0.014 x
                                                tons/year
Process Emissions
Size (n)     Percent
1-3
              23
          Control Device
          |Uncontrolled!
          Penetration ($)
         (l - efficiency)

               100
                                             Control Device
               Penetration
              (l - efficiency)
 Emissions
(tons/year)

  3,200  _
0.5-1.0
8.5
100
  1,200
0.1-0.5
4.3
100
    600
0.05-0.1
0.16
100
0.01-0.05
0.04
100
                                                                 5,000
                                  331

-------
                               TABLE  E-103
  FINE-PARTICLE EMISSIONS  FROM  INDUSTRIAL CYCLONE  COAL-FIRED BOILERS
                CONTROLLED BY ELECTROSTATIC PRECIPITATOR
Process  -  Industrial Cyclone Coal-Fired Boiler
Control Device -  Electrostatic Precipitators
Process Emissions into Control Device   0.078 x 10
                                                tons'/year
                         Control Device
                              Control Device
Process Emissions
Size (jj,) Percent
1-3 23
1
ESP 1
Penetration ($)
(l - efficiency)^/
11
L_
1
Penetration ($)
(l - efficiency)


Emissions
(tons /year)
2,000
0.5-1.0
8.5
17
1,100
0.1-0.5
4.3
29
1,000
0.05-0.1
0.16
41
0.01-0.05
0.04
55
                                                                  4,100
a/  Efficiency values used were taken from average fractional efficiency
      curve, Figure 17.
                                   332

-------
                              TABLE E-104
   FINE-PARTICLE EMISSIONS FROM INDUSTRIAL CYCLONE COAL-FIRED BOILERS
                         CONTROLLED BY CYCLONES
Process -  Industrial Cyclone Coal-Fired Boiler
Control Device -   Cyclones
                                                 C
Process Bnissions into Control Device  0.065 x 10
                                                tons/year
                         Control Device
                              Control Device
Process Snissions
Size (p.) Percent
1-3 23
1
Cyclone 1
Penetration (#)
(l - efficiency)*/

57
1
1
Penetration ($)
(l - efficiency)


Bnissions
(tons /year)
8,300
0.5-1.0
8.5
 82
4,400
0.1-0.5
4.3
 94
g,500
0.05-0.1
0.16
100
  100
0.01-0.05
0.04
100
                                                                 15,300
a/  Efficiency values were taken from high efficiency cyclone curve,
      Figure 17.
                                   333

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