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                       903R78001
                                                     EPA Report Number
                                                     November  1978
TD
883.5
.M32
B255
1978
                   A PARTICULATE MATTER STUDY FOR THE
                    METROPOLITAN BALTIMORE INTRASTATE
                       AIR QUALITY CONTROL REGION
                                   by    -

                            John Schakenbach
                             Robert C. Koch
                          GEOMET, Incorporated
                            15 Firstfield Road
                      Gaithersburg, Maryland  20760

                          Including Appendix E by
                            Katherine Severin
                             Ronald G. Draftz
                          IIT Research Institute
                          Chicago, Illinois  60616
                                  under

                      EPA Contract Number 68-02-2850

                    Project Officer, William Belanger

               Environmental Protection Agency, Region III
                             Curtis Building
                         6th and Walnut Streets
                    Philadelphia, Pannsylvania  19106

                                   and

                    Project Officer, Alvin L. Bowles

                   Environmental Health Administration
                 Department of Health and Mental Hygiene
                        201  West Preston Street
                       Baltimore, Maryland  21203

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                                                              November 1978
A   "                                                         EPA Report Number



I

I                            A PARTICULATE MATTER STUDY FOR THE
                             METROPOLITAN BALTIMORE INTRASTATE
                                AIR QUALITY CONTROL REGION


I


I                                          by

I                                     John Schakenbach
                                      Robert C. Koch
                                   GEOMET, Incorporated
                                    15 Firstfield Road
A                             Gaithersburg, Maryland  20760

                                  Including Appendix E by
                                     IKatherine Severin
                                      Ronald G. Draftz
                                   IIT Research Institute
•                                Chicago, Illinois  60616
                                           under

                               EPA Contract Number 68-02-2850
I
                             Project Officer, William Bel anger

I                      Environmental Protection Agency, Region III
                                      Curtis Building
                                  6th  and Walnut Streets                          .  ,efiCu
                             Philadelphia, Pannsylvania  19106                   *
                                                                 u
                                            and

•                           Project  Officer,  Alvin L.  Bowles

f                            Environmental  Health  Administration
                          Department  of Health and Mental  Hygiene
                                 201   West Preston Street
                                Baltimore, Maryland  21203

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                              DISCLAIMER
       This report has been reviewed by Region III, U.S. Environmental
Protection Agency, and approved for publication.  Approval does not
signify that the contents necessarily reflect the views and policies
of the U.S. Environmental Protection Agency, nor does mention of trade
names or commercial products constitute endorsement or recommendation
for use.

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FOREWORD
                    Where violations of the national primary 24-hour standard for total
M       suspended particulate (TSP) matter occur, it is necessary to identify the
          sources which contribute to these violations and to adopt appropriate source
 p       control strategies which will lead to the elimination of violations.  Region  III
 •       of the U.S. Environmental Protection Agency is actively engaged in helping
          states to identify the causes of TSP air quality violations by examination of
•       material  collected by high-volume filter samplers and by extending their emis-
          sion inventories to include fugitive emissions.  In this study GEOMET, Incorpo-
P       rated has compiled a fugitive emission inventory for the Metropolitan Baltimore
•       Intrastate Air Quality Control Region (MBIAQCR) and has characterized the par-
          ticulate matter captured by high-volume samplers at three sites in the MBIAQCR
•       which had registered violations of Federal standards during 1976.

W                                                      William E. Bel anger
                                                         Project Officer
                                                         fU.S. Environmental Protection
                                                           Agency, Retion III
  -in-

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                                 ABSTRACT





          Portions of the MBIAQCR exceeded the national primary 24-hour



standard for TSP in 1975 and 1976 and are expected to  continue to exceed



this standard through 1985 unless mitigative action  is taken.  In response



to this, hi-vol sampling was done at three representative  locations within



the nonattainment area.



          According to results from microscopical analysis of the hi-vol



filters, about 50 percent of the filter particulate was mineral.  This



result agreed with empirical emission equation calculations which indicated



that the largest particulate emission rates were from  active dirt and gravel



roads, unpaved parking lots and active construction  sites.  By applying



appropriate control strategies, the TSP emissions can  be reduced by about



35 percent and thus result in attainment of both the 24-hour and annual TSP



standards for most areas within the MBIAQCR.

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                                 CONTENTS
Foreword	     iii
Abstract	      iv
Figures	      vi
Tables   	     vii

     1.  Introduction  	       1
     2.  Conclusions 	       8
     3.  Recommendations for Control Strategies   	       9
     4.  Fugitive Emission Estimates 	  	      10
     5.  Analysis of Hi-Vol Samples  	      39
     6.  Fugitive Emission Control Strategies   	      49
     7.  References  	      54

Appendices

     A.  Hi-Vol Sampling	      58
     B.  Fugitive Emission Survey Form  	      61
     C.  Fugitive Source Characteristics  	      63
     D.  Fugitive Emission Programs  	      78
     E.  IIT Research Institute's Report  on Analysis
              of Hi-Vol Filters	     95
     F.  Orientation of Point Sources to  Hi-Vol Samplers   	    139
     G.  Wind Directions on Hi-Vol Sampling Days	    146
                                 -v-

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                                FIGURES
Number                                                              Page

  1       Location of TSP monitoring stations exceeding
            primary NAAQS in 1976	    5

  2       Metropolitan Baltimore nonattainment area for TSP,
            including the three hi-vol  stations used in the
            project 	    6

  3       Baltimore City surface soil silt and credibility
            quadrants	17

  4       Observed Mineral Concentration as a function of TSP
            concentration at Fire Department #10 Hi-Vol
            Sampling Station  	   53
                                  -vi-

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Number
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2

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10


11

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15

16
17







TABLES

Page
Stations Exceeding Annual TSP Standard in the
Metropolitan Baltimore AQCR in 1975 and 1976 	 2
Stations Exceeding 24-Hour TSP Standards in the
Metropolitan Baltimore AQCR in 1975 and 1976 	 3
Soil Erodibility for Various Soil Textural Classes ... 15
Baltimore Erodibility and Silt Content 	 16
Summary of Fugitive Emission Factors and Regional
Source Data 	 19
Mass Median Diameter (MMD) and Percentage of Emission
Less 5 and 30 Microns for Fugitive Sources 	 . 21
Stockpile Fugitive Parti cul ate Emissions 	 22

Baltimore City Fugitive Dust Emission by Source Type . . 24
Baltimore and Anne Arundel Counties Fugitive Dust
Emissions by Source Type 	 28

Fugitive Particulate Emissions tor 1977 Maryland
Inventory Baltimore County and Baltimore City
Major Point Sources 	 36
High-Volume Sampler Data 	 40

Predominant Materials Found on Hi-Vol Filters 	 41

Microscopical Properties of Particles 	 42

Summary of Particles Classified by Source Type
by Microscopy 	 43
Results of Duplicate Microscopy Analysis 	 45

Baltimore Harbor Material Throughput for 1976 and 1977 . 47
Resultant 24-Hour Wind Direction and the Range of
Hourly Variations from the Resultant Wind 	 48


-vii-

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                                SECTION  1

                               INTRODUCTION
BACKGROUND

     In the Metropolitan Baltimore  Intrastate Air Quality  Control  Region
(MBIAQCR) violations of both the annual and  24-hour  standards  for  total
suspended particulate matter have occurred and will  continue  to  occur  through
1985 at a number of locations  in the region.  The objective of this  report  is
to identify those air pollution emission sources or  classes of sources
which are contributing to the  exceedance of  the National Ambient Air Quality
Standards (NAAQS) for total suspended particulates  (TSP) and  the extent  to
which each source is a contributor.  Of particular  concern is  the  extent  to
which fugitive dust emissions  contribute to  this problem.

     At the time that State Implementation Plans were first developed, no
quantifiable estimates of the  impact of fugitive emission  sources  were
available.  Therefore, most states  did not adopt regulations  to minimize
emissions from such sources.   However, it  is now believed  that fugitive
emission sources may be major  contributors to the particulate  problem  in
Baltimore and in other cities.  Fugitive emissions  are  of  two  types:
(1) those that result from industrial operations and  (2) those dusts that
became airborne due to forces  of wind, man's activity or both.   In some
industrial operations those particulates that escape  through windows,  doors
or vents, but not through control devices, stacks or  flues, are  categorized
as fugitive.  Specific sources can  be metallurgical  furnace operations,
materials handling, transfer and storage operations  and crushing and grind-
ing operations.  Wind blown dust can result  from paved  and unpaved roads,
wind erosion of exposed surfaces, construction sites, and  uncovered  aggre-
gate storage piles.

     Fugitive emissions can have a  greater effect on  ground-level  air
quality in the vicinity of a source than stack emissions.  Stack emissions
are released above ground level usually with upward  velocity  and buoyancy.
Fugitive emissions occur near  the ground and generally  remain  near ground
level downwind.

     Monitoring data for TSP have been archived by  the  Maryland Bureau of Air
Quality and Noise Control (BAQNC) and show violations of both  primary  and
secondary NAAQS occurring in the region.  Table 1 lists the monitoring sta-
tions in the MBIAQCR at which  the annual standards  for  TSP were exceeded  in
1975 and 1976.  Table 2 shows  those stations at which the  24-hour  standards
were exceeded.
                                   -1-

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 TABLE 1.  STATIONS EXCEEDING ANNUAL TSP STANDARD*
IN THE METROPOLITAN BALTIMORE AQCR IN 1975 AND 1976


Station
Fire Dept. HQ
FireDept. #10
Ft. McHenry
Fire Dept. #22
Patapsco STP
S. E. Police Station

Station
FireDept. #10
Fire Dept. #22
Ft. McHenry
Patapsco STP
S. E. Police Station
AAI
1975 Annual Geometric
Mean (yg/m3)
86
128
86
86
150
78
1976 Annual Geometric
Mean (yg/m3)
164
82
105
144
77
90

* Annual Standard = 75 yg/m^ geometric mean
                        -2-

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       TABLE 2. STATIONS EXCEEDING 24-HOUR TSP STANDARDS

      IN THE METROPOLITAN BALTIMORE AQCR IN 1975 AND 1976
      Stations Exceeding             2nd Highest 24-Hour

   Federal Primary Standard*      TSP Concentration (yg/m3)      Year
Riviera Beach
Fire Dept. #10
Patapsco STP
Fire Dept. # 10
Patapsco STP
Lansdowne High School
357
358
398
559
509
271
1975
1975
1975
1976
1976
1976
      Stations Exceeding

  Federal Secondary Standard**
St. John's College
Fire Dept. HO
N. E. Police Station
S. E. Police Station
S. W. Police Station
Ft. McHenry
Fire Dept. #22
Cockeysville
Riviera Beach
Fire Dept. HQ
Fire Dept. #22
Ft. McHenry Nat1 1 Park
S. E. Police Station
S. W. Police Station
Spring Gardens
AAI
Edgemore Fire Station
Essex
Campbell Scale House (Texas)
Sellers Point Vocational
178
184
203
204
161
182
208
167
174
188
198
255
214
157
164
230
235
151
155
185
1975
1975
1975
1975
1975
1975
1975
1975
1976
1976
1976
1976
1976
1976
1976
1976
1976
1976
1976
1976

 * Primary Standard = 260 yg/m3.

** Secondary Standard = 150 yg/m3.
                                  -3-

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     The highest annual TSP concentrations for 1975 and 1976 were found at
the Fire Department #10 and the Patapsco Sewage Treatment Plant  (STP)  located
in the Fairfield and East Brooklyn areas of South Baltimore.  The locations
of the stations violating the 1975 and 1976 primary standards are shown on
the map in Figure 1.  The metropolitan Baltimore nonattainment area where
violations for suspended particulates occurred is indicated in Figure  2.  The
high readings at the Patapsco STP are biased due to temporary heavy construc-
tion in the immediate vicinity of the monitor, according to the Maryland
BAQNC.   Therefore samples from the site are not suitable for developing con-
trol strategies.

     The BAQNC operated, maintained and calibrated the three hi-vol stations
used in this project,  these hi-vol samplers are located at Fire Department
#10, Fire Department #22 and Fort McHenry.  These three stations are repre-
sentative of the nonattainment area (Figure 2).  The hi-vol filter sampling
procedure followed is described in Appendix A.  In addition, BAQNC has pro-
vided GEOMET with 18 hi-vol filters, 3 blank filters - 1 from Fort McHenry
and 2 from Fire Department #22.  Also, BAQNC personnel furnished reports
detailing weather conditions and activities, such as construction, demolition
or dumping operations during sampling periods occurring in the vicinity of
each station.

     The Environmental Protection Agency, Region III, has provided support
and advice on hi-vol site selection, filter selection and criteria, and
updated fugitive emission equations.

     The scope of the work performed in each of five task areas  is described
below:

Filter Analysis

     The filters were analyzed by I IT Research Institute.  Physical and chemi-
cal analyses were performed on the hi-vol filters.  The microscopical  analysis
identified types of particles by shape, mass, color, transparency, size, resil-
iency,  and refractivity.  In some cases particle concentration was determined
by microscopy (stratified visual counting).  Particle combustibility is
determined by low temperature ashing.  Plasma emission spectroscopy was
used in determining the metal particulates.  Sulfates were determined  turbidi-
metrically.  For details on sulfate, metals and particle mass determination,
see Appendix F.

Identification of Fugitive Emission Sources

In  1977, BAQNC performed a ground area "windshield" survey  (see Appendix E for
survey form) of Baltimore City and surrounding areas of Baltimore and  Anne
Arundel Counties.  The purpose of this survey was to identify potential fugi-
tive emission sources.  Types of surface material, such as percent grass
cover, asphalt, and dirt and gravel, were  identified along with  amount of
vehicle activity and type of industrial activity.
                                   -4-

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Lansdowne.

   H.S.
             fire D«pt,

             *10
                       Figure 1.  Location of TSP monitoring stations

                        exceeding primary NAAQS in 1975 and 1976.
                                            -5-

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Nonattairunent area boundary
       Figure 2.  Metropolitan Baltimore nonattainment area for TSP,
           including the three hi-vol stations used in the project.
                                  -6-

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     Types of particulates were identified by microscopy and chemical
analyses of the hi-vol filters.  Sources were then  identified that emit-
ted these kinds of materials.

Fugitive Emission Factors

     Empirical equations have been developed in recent years to determine
the particulate emission rates from various nontraditional fugitive  sources.
Some such sources are unpaved roads, active construction sites and wind
erosion.  The empirical equations are referenced in this report as fugitive
particulate emission equations.  More information on these equations  is pre-
sented in Section 4.

     Using the BAQNC survey results as input to a computer program which
contains six fugitive particulate emission equations, source emission rates
were calculated for paved roads, unpaved roads, construction sites,  storage
piles, wind erosion and railroads within Baltimore City and surrounding parts
of Baltimore and Anne Arundel Counties.

Revision of State Emission Inventory

     A fugitive particulate emission inventory has been prepared to  supple-
ment the existing Maryland emission inventory.  This supplementary inventory
consists of fugitive particulate emission factors, location of each  source
in UTM and Maryland coordinates, major point source fugitive emission rate
tables, typical flue gas characteristics for industrial sources, size distri-
bution graphs, and microscopy results which indicate types and concentrations
of airborne-sampled materials.

Recommendation of Control Strategies

     Appropriate control  strategies have been selected for each of six types
of fugitive particulate emission sources.  The feasibility of implementation
and the effectiveness of these control  strategies have been included when
possible.
                                    -7-

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                                SECTION 2

                               CONCLUSIONS
      Microscopy and supporting chemical analyses of hi-vol filters from
Fire Department #10, Fire Department #22, and Fort McHenry show that about
50 percent of the sampled TSP is mineral, and thus probably comes from
nontraditional fugitive emission sources.  According to our emission
estimate, the most likely sources are wind- and vehicle-generated fugitive
particulate emissions from dirt and gravel road surfaces.  The remaining
50 percent of the material found on the filters is probably due to emis-
sions from traditional sources including cornstarch from harbor grain
transfer operations in the Fort McHenry area, slag particulate probably
from operations within and around Bethlehem Steel plant on Sparrow Point,
and sulfate generated by a combination of nearby industrial operations
and distant combustion of sulfur-bearing fuels.

     In 1975 and 1976 all of the MBIAQCR's 24-hour and annual TSP vio-
lations exceeded the appropriate standards by about a factor of two or
less.  About 50 percent of the sampled TSP is estimated to be from fugi-
tive emission sources.  Since available fugitive particulate control
strategies are generally at least 60 to 80 percent efficient, proper
application of the fugitive particulate control strategies can reduce
TSP emissions by about 35 percent and will result in attainment of the
24-hour and annual TSP standards for most areas within the MBIAQCR.

     The high concentrations of TSP in the vicinity of Fire Station #10
require a larger reduction.  However, since fugitive sources account for
more than 70 percent of the high-concentration material observed at this
site, it appears that effective fugitive emission controls can achieve
compliance at this site also.
                                     -8-

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                                SECTION 3

                  RECOMMENDATIONS FOR CONTROL STRATEGIES


     The fugitive particulate emission estimates of  this  study  indicate
the magnitude of the various types of sources relative  to  one another  and
thus establish priorities for fugitive particulate emission  source  control
strategies.

     The seven fugitive particulate emission source  categories  within  Balti-
more City, ranked with largest emission rate first and  decreasing to  smallest
emission rate last, are:  dirt roads, gravel roads,  active construction  sites,
storage piles, wind erosion, railroads and paved roads.


     Because the largest emission rates are from dirt roads, gravel  roads,
and active construction sites, priority should be given  to the  control stra-
tegies for these TSP sources.  Dirt road and gravel  road  emissions  include
active dirt and gravel parking lots.  Active construction  sites include  waste
disposal sites.  Recommended control strategies for  the  three sources  will  be
most effective in reducing TSP levels.  Dirt roads should  be either paved or
oiled.  This will reduce emissions by at least 85 percent.   The paving of
gravel roads will also reduce emissions by 85 percent.   Construction  site
emissions should be controlled by using water, perhaps  from  sprinklers or
tank trucks, to regularly wet exposed surface dust sources.  Active waste
disposal emissions should be controlled by covering  the wastes  with soil,
planting vegetation and using water spray bars at dumping  areas.  These
techniques will reduce emissions by 25 to 100 percent.

     Control strategies for the other sources are also  recommended.   Storage
pile emissions should be controlled by enclosing the piles with solid  fencing
or by covering with a tarpaulin.  This should reduce emissions  by 70  to  99
percent.  Wind erosion emissions should be controlled by  paving the surface,
covering with soil  and planting vegetation or by covering  with  granulated
smelter slag, depending on the nature of the particular  source.  These tech-
niques range in efficiency from 65 to 99 percent.  Railroad  emissions  should
be controlled by oiling track shoulders and covering open  top railroad cars
containing potentially wind-blown material.  Paved road  emissions should
be reduced by adding curbs to streets.  This will reduce  dust by about a
factor of four.  Keeping roads in good repair will cut emissions by about
50 percent.
                                    -9-

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                              Section 4

                     FUGITIVE EMISSION ESTIMATES
     The Maryland Bureau of Air Quality and Noise Control has recognized
a need to update its emission inventory to include fugitive emissions.  As
a first step in this effort, the State, County, and Baltimore City control
agencies joined in conducting a survey of nonconventional sources of fugi-
tive emissions in the heart of the Metropolitan Baltimore Intrastate Air
Quality Control Region (MBIAQCR).  The survey covered the nonattainment area
for total suspended particulates including 61 square miles over the city of
Baltimore and 284 squares measuring 1000 feet on a side  in parts of the
surrounding Baltimore and Anne Arundel Counties which lie near the City of
Baltimore.  The total area covered by the survey is shown in Figure 2.  The
inspectors who performed the survey filled out the form  shown in Appendix B
for each source which he/she considered significant.  The information from
this survey formed an important and valuable  input to the fugitive emission
estimates derived in this study for the MBIAQCR.

     In this study the survey data were used  to calculate fugitive emission
estimates which supplement particulate emissions from conventional sources.
The new emission inventory includes both amount and size of fugitive particle
emissions so that revised inventory can be used in modeling studies of the
transport and dispersion of suspended particulate matter.  Fugitive emission
estimates were developed for both area sources (identified in the survey) and
point sources which are already in the Maryland emission inventory.   In the
first step, a survey of emission factors for  quality and particle size was
made from the literature and from followup contacts with investigators
currently measuring fugitive emissions.  A discussion of the best esti-
mates of both amount and particle size of all the types  of fugitive emis-
sions found in the Baltimore area is presented in this discussion.  The last
two parts of this section describe the fugitive emission estimates derived
from area and point sources respectively, in  the MBIAQCR.

Fugitive Particulate Emission Equations

     Because fugitive particulate emissions were suspected as being sig-
nificant contributors to the Federal TSP violations  in Baltimore and sur-
rounding areas, a literature search on fugitive particulate emissions
equations was performed.  Our literature search uncovered five suitable
fugitive particulate emission factor equations.  The equations are for
paved roads, unpaved roads, construction sites, storage 'piles and wind
erosion.  A sixth equation for railroad fugitive emissions was developed
from the unpaved road equation.  The emission factors are for particles
with an aerodynamic diameter of less than 30  urn.
                                    -10-

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Paved Roads —
     An equation for emission factors for paved roads was formulated after
reviewing results from a monitoring program conducted by Midwest Research
Institute (Bonn et al .  1978) and after extensive consultation with Chatten
Cowherd, Jr. of Midwest Research (MRI).  When assuming light duty vehicles,
the equations used by us and MRI are almost identical.  The following fugi-
tive particulate emission equation was used:
                    EF ' °-45
     where EF = emission factor Ob/vehicle mile travelled)

            s = silt content of road surface material (%)

            W = average vehicle weight (tons)

            L = surface dust loading on traveled portion of road (Ib/mile).


     In general there was not sufficient information available to assign
values to the above parameters.  The following values were selected as repre-
sentative values for the Baltimore area:


            s = 12%

            W = 1.5 tons

            L = 17.7 Ib/mile.

     These values result in an emission factor for Baltimore paved roads of
0.43g(9.6 x 10   Ib) per vehicle mile travelled.

     A single representative surface soil silt content for general applica-
tion to the Baltimore area was determined for paved and gravel roads and
for railroad beds.   Based on contaminants measured in street runoff (Sartor
and Boyd 1972), the silt content of mineral -like matter was found to be 5 to
15 percent.  A value of 12 percent was selected as representative of this
range because it is compatible with the EPA recommendations for gravel
material.
                                     -11-

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     On paved roads, the traffic is estimated to be primarily  light-duty
vehicles.  The average weight is assumed to be  1 to 5 tons for these  vehicles.
The accuracy of this estimate cannot be quantitatively assessed.  The equa-
tion was derived from a limited number of accurate field tests and  includes
extrapolation of parameter values from measurements not made  in  the Balti-
more area.

Unpaved Roads (Gravel and Dirt)--
     The emission factors selected for gravel and dirt roads  is  given by  the
following relationship* (EPA 1977):


           EF = 0.60 (0.81 )s(|j) „_<&),  (453.6)



     where EF = emission factor, g per vehicle  mile travelled

            s = silt content (%)

            S = average vehicle speed, mph

            P = days per year with 0.01 inch or more of precipitation or
                reported snow cover.

     The following parameter values were selected as being representative for
the Baltimore area:

            s = 12 % for gravel roads.  (See Table 4 and Figure  3 for dirt
                roads.)

            S = 10 mph for parking lots, and 25 mph for roads, unless other-
                wise stated.  (See Appendix C.)

            P = 112 days/year.

     Active dirt and gravel parking lots are analyzed as dirt  and gravel
roads, respectively.  The length of these "roads" is calculated  by  dividing
the parking lot square footage  by 2 to get the  active area of  the  lot,
then dividing the result by 20  feet (width of road) to get the length of
road. Paved parking lots are neglected because  of their minor  particulate
emissions.
*  The equation contains  a factor  of 0.6  to  produce  an  emission  estimate
representing particles  in sizes  generally measured by hi-vol  samplers,  i.e.,
less than 30 ym in diameter.   Experimental tests  show:   (1)  that the collec-
tion efficiency of hi-vols for particles  greater  than  lOydepends on the
orientation of the wind to the samples  and (2)  that, for  some orientations,
collection efficiencies as large as 34  percent  are observed  for  50 um
diameter particles (Wedding et al.  1977).
                                    -12-

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     The estimate of 12 percent  silt content  for  gravel  roads  is  from the
standard EPA emission factors  (EPA  1977).  The  vehicle  speeds  are selected
estimates for use when other data are  not  available.  The  number  of  precipi-
tations and/or snow cover days  is an average  observed at Baltimore-Washington
International Airport for the years 1972 through  1976.

     The emission factor for gravel and dirt  roads  and  parking  lots  includes
particles with aerodynamic diameters less  than  30 wm.   To  get  total  emissions
of all particulates, including particles larger than 30 ym,  the  above emis-
sion factor should be multiplied by 1.67.  The  relationship  is  estimated  to
be accurate to within _+ 20% (EPA 1977).

Construction Sites--
     The selected emission factors for construction sites  is  1.2  ton/acre/
month (269 g/m /month) (Cowherd et al . 1974).   Activity levels, which are
difficult to estimate without precise  information on the construction activ-
ity, can change this emission estimate by  a factor  of 2 or more.

     Active solid waste disposal sites with no  burning  are treated as con-
struction sites because of the similarity  of  the  activity  to  construction
operations.  No other basis for emission estimates  was  determined.

     The emission factor applies only  to the  number of  active  acres  of  con-
struction activity. The emission factor is for  medium-type construction
(townhouses, shopping centers). The emission  factor represents  the high
end of the emission range because it was developed  in the  desert  Southwest
United States.  A 30 percent silt and Thornthwaite's Precipitation-Evaporation
Index (PE) of 50 is assumed.  The emission factor is for particles with an  .,
aerodynamic diameter less than 30 um and a particle density  of  2  to  2.5 g/cm .

Aggregate Storage Piles —
     For storage piles of aggregates, the  following emission  factor  was
selected (Cowherd et al.  1974).
              EF =              (0.5)
        where EF =   emission factor, g per kg of material placed
                     in storage

              PE =   Thornthwaite's precipitation-evaporation  index.


     For Baltimore, the value of Thornthwaite's  index  is  108 (see  EPA  1977)
                                    -13-

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     Only large storage piles are treated in this study.   If  information  is
not available on the throughput of material, a rate of  100,000 tons per
year is assumed.

     In addition to the standard inventory of  industrial  aggregate storage
piles, railroad satellite yard loading and unloading operations  have  been
included as sources to which the aggregate storage pile emission factor  is
applicable. The emission factor relationship is supported  by  limited  test
data and engineering judgment.

Wind Erosion--
     An equation to estimate fugitive emissions due to wind erosion of
exposed areas was selected from a recent analysis (Bonn et al. 1978):


             EF = 3400 (ftf)(^)(^)(-S£)~2(0.

                                      2
      where EF =  emission factor, g/m /yr

             e = surface erodibility  (tons/acre/year)

             s = silt content of surface material (%)

             f = frequency that wind  speed exceeds 12 mph  (%)

            PE = Thornthwaite's precipitation-evaporation  index.


     The soil erodiblity and silt content were estimated  for  each of  four
quadrants using data available from U.S. Soil Conservation Service surveys
for Baltimore County (1970) and Anne  Arundel County (1968) and from esti-
mates of erodibility determined experimentally  (Cowherd et al. 1974)  for
each soil type  (see Table 3).  The estimates were derived  by  extrapo-
lating the data available for outlying county  land into the city limits.
The values determined by quadrant and corresponding grid  square  are  listed
in Table 4.  The area included in each quadrant  is shown  in Figure 3.

     The percent of time the wind exceeds 12 mph was estimated from the  cli-
matological data used by Maryland BAQNC to model air quality  and is based
on observations at Baltimore-Washington International Airport  (Maryland  BAQNC
1976).  A value of 21.4 percent was determined to be appropriate.  As pre-
viously discussed, the Thornthwaite index is 108 for Baltimore.

     The wind erosion emission factor is applied to the entire surface  area
of the active and unused dirt parking lots,  inactive gravel  lots and  active
and unused dirt roads within Baltimore City  and Baltimore and Anne Arundel
Counties.  The wind erosion emission  factor  is  also applied to the exposed
surface of aggregate material contained in uncovered railroad cars  (parked
and moving); however, railroad beds are not  included.
                                    -14-

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TABLE 3. SOIL ERODIBILITY FOR VARIOUS
(Cowherd 1974)

Predominant soil
textural class
Sand*
Loamy sand*
Sandy loam*
Clay
Silty clay
Loam
Sandy clay loam*
Sandy clay*
Silt loam
Clay loam
Silty clay loam
Silt


* Very fine, fine, or medium sand





-15-



SOIL TEXTURAL CLASSES


Erodibility, I,
tons/acre/year
220
134
86
86
86
56
56
56
47
47
38
38

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                TABLE 4. BALTIMORE ERODIBILITY AND SILT CONTENT
                                              Average Erodibility       Surface Soil
Quad No.                 Grid No.                (tons/acre/year)    Average Percent Silt
   1                      None                      49                  75

   2              38,  39, 40                          53                  72
   3              41-45, 51-55, 61-65, 72-75,         52                  62
                    84,  85, 95

   4              46-50, 56-60, 66-70, 76-80,         55                  65
                    86-90, 96-98, 106-109,
                    117-120
                                        -16-

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Figure 3.  Baltimore City surface soil silt  and credibility quadrants.
                             -17-

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     The emission factor is based on a limited number of measurements
of undetermined accuracy.  It is considered the best available estimate  but
its accuracy is unknown because the relationship  is based on an  insufficient
broad data base.  It is considered primarily applicable.,to particles  less
than 30 ym in diameter and with a density 2 to 2.5 g/cm  .

Railroads —
     Fugitive emissions from railroads are estimated on  the assumption that
they are related to the same factors which are applicable to unpaved  roads.
Since railroad cars do not contact the underlying ground surface, the assump
tion was made that the emissions are only 10 percent of  the emissions associ
ated with highway vehicles.  The following relationship  is used:


            EF = 0.1 (0.60)(0.81)s( ^ )[1 - (1^)](453.6)
      where EF = emission factor, g per vehicle mile travelled

             s = silt content (%)

             S = Average vehicle speed (mph)

             P = days per year with 0.01  inch or more of  precipitation
                 or reported snow cover.

     The following parameter values are selected as being representative
for the Baltimore area:

             s = 12%

             S = 15 mph and 40 mph for railroads within Baltimore City,
                 and outside of the City, respectively, unless  otherwise
                 stated  (See Appendix C.)

             P = 112 days/year for Baltimore.

     The equation is based on conversations with railroad personnel  and edu-
cated judgment because no fugitive emission equations for railroads  could
be found.  No particle size information for railroad emissions  is available.
However, it is judged that the emissions  are similar to those from unpaved
roads and that particle sizes and densities would  be similar to emissions
from that type of source.

Summary —
     Table 5 contains a summary of the fugitive emission  factors compiled
for the Baltimore area for each of the seven types  of nontraditional  fugitive
emission sources.  The table also identifies the type of  information  about
the sources which is required to apply the factor.
                                    -18-

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TABLE 5.  SUMMARY OF FUGITIVE EMISSION FACTORS
           AND REQUIRED SOURCE DATA

Type of Source
Paved road
Gravel road
Dirt road
Construction sites
Wind erosion

Railroads
Storage piles
Emission Factor
0.43 (g/VMI)
0.96 x 10"J (Ib/VMT)
61 S (g/VMT)
0.13 S (Ib/VMT)
5.1 sS (g/VMT)
O.OllZsS (Ib/VMT)
9.0 (g/m2/day)
79 (Ib/acre/day)
2.6 x 10"4 e s
(g/mVday)
2.3 x 10"3 e s
(Ib/acre/day)
6.1 S (g/VMT)
0.013 S (Ib/VMT)
0.14 (g/kg)
0.28 (Ib/ton)
Required Source
Characteristics
VMT (vehicle miles
travelled)
VMT
S (vehicle speed, mph)
VMT
S
s (silt content of road
material, %)
Site area
Area
s
e (surface erodibility,
ton/acre/year
VMT
S
Quantity placed in
storage

                    -19-

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Fugitive Particulate Size Distribution

     Airborne fugitive particulate size distribution data have been developed
for various road surfaces, for many industrial operations, and for crushed
stone and other stockpile aggregate loading operations.   Particle size dis-
tribution information has been obtained in terms of the mass median diameter,
the particle density, the percentage of particles less than 30 ym, and the
principal chemical compound present.

     The particle size distribution estimates are based on measurements with
various types of collection devices for distinguishing sizes, but primarily
with multistage cascade impactors.  Much of the reported data was obtained
by Midwest Research, Incorporated using a Sierra Instruments hi-vol parallel-
slot cascade impactor with a cyclone preseparator to remove coarse particles.
The MRI intake was isokinetic for a 4.5 m/sec (10 mph) wind speed.  Generally,
source samples were taken within 10 meters of the source.

     The particle size and density have important bearings on the particle
suspension process in which the forces of turbulence and gravity interact to
keep particles airborne or to impact them on the ground and other surfaces.
A set of data has been compiled which represents the nature of the particle
size distribution which is required to represent aerosol dynamics and which
is compatible with the available measurements.  Table 6 is a compilation of
16 types of particulate emissions which have been measured.  A list of much
less complete particle size information which describes emissions from a
aggregate stockpile loading operations is given in Table 7.

     Although no particle size measurements were found for construction
sites, wind erosion, or railroad yards, the particle size distribution for
those types of sources can be estimated from other sources which are esti-
mated to have similar particles.  It is recommended that results for agri-
cultural tilling seems reasonably applicable to construction operations
since both involve heavy equipment in earthmoving operations.  The same
data is recommended for wind erosion only because a more applicable
set of data was not found.  The data for gravel roads is recommended for
railroad operations for the same reason.

     The particle size data aviTable for roadway emissions was repeated in
two of these tests, each of which produced similar results.  These results
are very limited and the general applicability of these results, which were
measured in Kansas City, to Baltimore is reasonable but a matter of conjec-
ture until data is made in Baltimore or at least in additional locations.
The remaining nonroadway sources can be grouped into one of three classes:
(1) Insufficient information, designated NA in Table 6, (2) Highly varia-
ble particle sizes, designated variable in Table 6, and (3) Reasonably con-
sistent which applies to the remaining three categories of fugitive sources
(i.e., pulverized coal combustion, cement kilns, and municipal incinerators).
                                    -20-

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TABLE 6.












MASS MEDIAN DIAMETER (MMD) AND PERCENTAGE
OF EMISSION LESS THAN


Source
Concrete roads*

Asphalt roads*
Gravel roads*
Dirt Roads*
Agricultural tilling***
Pulverized coal
combustion**
Stoker Coal
combustion**
Basix 00 furnace**
c.
Open hearth furnace**
Electric arc furnace**
(variable)
Coke ovens**
Cement kiln**
Municipal incinerator**
Iron Foundry**

Kraft pulp recovery
furnace**

Asphalt rotary dryer
(variable)**
Crushed stone
stockpiling***

* Reference: Galkiewicz
** Reference: Vandergrift
*** Reference: Cowherd et
NA - Not available.


Particle
Density
g/cm
2.8

1.3
2.5
2.5

2.3

NA

3.4

5.0
3.8

NA
2.9
2.8
2.8

NA


2.6

2.5


and Lynn
1971.
al. 1974


5 AND 30


MMD
(urn
3.9

5.9
19.
81.

13.

58.

0.1

5.
2.5

NA
12.
21.
NA

NA


9.

1.4


1976.

.

-21-
MICRONS FOR


<5 ym
) (X)
61

42
23
9
35
25

4

NA

50
60

NA
23
6
10

NA


40

90







FUGITIVE SOURCES


<30 ym
(X)
94

90
62
32
80
75

27

NA

NA
98

90
77
69
29

NA


70

NA









Notes
Mean of 3

Mean of 2
Mean of 3
Mean of 3

43% Si00
2


85-95% <1
90% Fe203
85-90% Fe
30% Fe90.,
L. O

45% CaO
35%Si02
30% SiO?

50-85% <2
80% Na0SO
2



tests

tests
tests
tests





ym

2°3







ym


Highly variable

-------
   TABLE 7.  STOCKPILE FUGITIVE PARTICULATE EMISSIONS - SIZE AND DENSITY INFORMATION
Stockpile Material
Diameter of Emitted
 Participates  (ym)l
Density (gm/cm ) or
  Specific Gravity
Gravel or Crushed
  Stone
Sand
Coal
Oyster Dust
Manganese Ore
Iron Ore
Concrete
Stone
Road Salt
Chrome Ore
Ferrochrome Ore
Ferromanganese Ore
Batterymanganese Ore
Sand Blasting Grit
Cinder Blocks
90% <5
50% are 2-15
1-10 mean diameter
Not available
Not available
Not available
10-20% by weight < 5
50-70% < 4
Not available
Not available
Not available
Not available
Not available
Not available
Not available
    2.5 density
      2 density
    1.4 density
    2.8 spec. grav.
      3 spec. grav.
      4 spec. grav.
    2.8 density
    Not available
    2.2 density
      3 spec. grav.
      3 spec. grav.
      3 spec. grav.
      3 spec. grav.
      2 density
      2 density
 Technical Guidance for Control of Industrial Process Fugitive Particulate
 Emissions. PEDCo, March 1977.pp. 2-57, 2-221, 2-316, 2-327.
 CRC Handbook of Chemistry and Physics, 53rd Edition, 1972-73.  Section B,
 "Physical Constants of Inorganic Compounds."
                                    -22-

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Fugitive Particulate Area Source  Emissions

     Seven types of sources of fugitive  emissions  were  identified  from an
examination of the results of the survey of  fugitive  dust  sources  conducted
by the Maryland BAQNC.  Emission  factors for  estimating  emissions  for  these
sources are listed in Table 5, along with the source  parameters  required to
derive emission estimates.

     Within the City of Baltimore the  location  of  sources  in  the survey was
identified by grid squares, each  of which consisted of  about  a square  mile
area.  The survey covered the designated nonattainment  area for  suspended
particulate matter.  Fugitive emissions  have  been  estimated for  all  seven
types of sources in 61 grid squares covered  by the survey.

     Within the parts of the nonattainment area lying in Anne Arundel  and
Baltimore Counties, sources were  identified  by square areas 1000 feet  on a
side.  Emission estimates were determined for each of the  seven  types  of
fugitive sources for 284 such square areas.

     Table 8 lists the emission estimates determined  for 61 1-mile square
areas within the City of Baltimore.  The total  of  fugitive emissions within
the surveyed area of the city is  80 metric tons (88 English tons)  per  day.
Most of these emissions are from  gravel  roads (29%) and  dirt  roads (51%).
The emissions from paved roads and railroads  are negligible in comparison.
Construction sites, storage piles and wind erosion make  up the remaining
emissions by providing 11 percent, 5 percent  and 2 percent, respectively.

     In the nonattainment area within the adjacent counties the  surveyed,
fugitive emissions are estimated  to be 30 metric tons (33  English  tons) per
day (see Table 9).  Gravel roads  contribute  38  percent  to  this estimate,
dirt roads 17 percent, and construction  sites 26 perent.   Storage  piles and
wind erosion contribute the remaining 6  and  13  percent,  respectively.

     A listing of the source characteristics  by grid  square which  were used
to compute the fugitive emission  estimates is presented  in Appendix  C.  A
sample survey form which was used to record  information  by survey  personnel
is shown in Appendix B.  Information from the survey  forms was coded on
cards and entered into a program  to compute  emissions.   A  listing  of the
programs used to compute emissions is presented in Appendix D.

Fugitive Emissions Information for Point Sources

     Table 10 contains fugitive emission information  for point sources
in the Maryland emission inventory which lie  in the MBIAQCR,  which emit
100 tons per year or more, and which correspond to processes  for which
fugitive emission data is available.  Other fugitive  emissions are
                                   -23-

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expected to be smaller in comparison to these sources and the emissions coded
for area sources.  Sources with fugitive emissions were identified by listing
the Standard Industrial Classification (SIC) and equipment type used to char-
acterize the 140 largest sources in the state inventory for the MBIAQCR.
From this information, those sources which correspond to types of operations
for which fugitive emissions have been defined were selected.  The type of
material emitted, the density and size of emitted particles and appropriate
emission factors are listed in Table 10.  The available Maryland emission
inventory does not include process rates, so actual emission estimates are
not included.  The emission data are taken from a report by PEDCo Environ-
mental, Incorporated (1977); references to specific pages in this volume are
included for convenience.
                                     -38-
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                                SECTION 5

                         ANALYSIS OF HI -VOL SAMPLES
     Hi-vol filters collected at three sites in the TSP non-attainment area
over a period of 7 months were reviewed to select 18 filters for microscopy
and chemical analyses.  The selection of sampling sites and specific  filters
was made by personnel at the Maryland BAQNC.  The selected filters  represent
days with different prevalent wind directions and speeds and different
participate loadings.  On three days filters from all three sites were
selected for analysis.  Table 11 identifies the dates and day of the  week
on which hi-vol filters were exposed at the three selected sites during
the period from June to December 1977 and shows the TSP concentrations
measured by each filter.  The procedure for collecting data and determining
the measured concentration is described in Appendix A.

     For the selected filters, the weights of the filter before and after
exposure, the amount of rain which occurred on the day the sample was col-
lected and the preceding day, and the 24-hour mean wind speed on the
sampling day are shown in Table 11.  Of the nine days on which the  18
selected filters were collected, one day had more than 0.01 inches  of rain
and three other days had more than 0.01 inches of rain the day before.  The
mean wind speed varied from 0.9 to 2.9 m/sec (2.0 to 6.5 mph) among the
9 days, compared to the climatological mean wind speed for Baltimore  of
4.6 m/sec (10.4 mph).  Therefore, the samples represent lighter than
normal wind speed situations.

     The selected filters were analyzed by IITRI using microscopy,  chemical
analysis and supporting chemical and physical analyses selected by  the
microscopist.   The findings regarding the principal types of particles on
each analyzed filter are summarized in Table 12.  It was found that the
following six types of particulate materials made up from 65 to 93  percent
of the TSP matter analyzed on each filter:

     Silicates
     Sulfates
     Rubber
     Calcite
     Cornstarch
     Slag.

The results presented in Table 12 do not include estimates of less  than
10 percent.   The above categorization is based on a combination of chemical
tests of filter materials and microscopy analysis of removed particles.
                                             -39-
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                                                                                                                                                        I
              Table  11.   HIGH-VOLUME SAMPLER  DATA

-3XK
c.vt rr KSEK
5/9/77 Th
4/15/77 •:
4/21/77 r
«/27/77 M
7/J/77 Su
7/9/77 Si
7/15/77 F
7/21/77 Th
7/77/77 »
5/2/77 T
1/V77 M
«/t»/n so
tram s%
5/74/77 F
9/1/77 Th
9/7/77 »
9/13/77 T
9/19/77 M
9/25/77 Su"
tO/t/77 Sa
10/7/77 ?
IOA3/77 Th
10/19/77 U
10/23/77 Tu
10/31/77 M
11/8/77 So
11/12/77 Sa
ll/M/77 F
11/21/77 Th
ll/a)/77 7
12/S/77 Tu
1J/12/77 B
12/H/77 S
CUM.
Ft. :feH
0*0
12?
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so

55
114
141
103
65^*
103
92
75
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25
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4.6
	 1
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 * Circled values are filter* used in analysis.

** A !wir-!< filter for 9/25/77 »-as obtained from the tort!iv«t Police Stafcn.
     Coreentratiom  34 ug/aJ; Initial «t.:  3.J«e» jm»:  tlnal •*.:  4.0171  ^
X Indicates filters selected for duplicate analysis.
«*"T!iree blank fitters were sant to CEO MET, one from Ft. McHeniy and two from FD »22.
Rainfall is from Baltimore-Washinzton
International A irport.


Wind speeds are from State-operated
tower at Sun and Chesapeake Streets
in Baltimore except 11/24/77,  which
is from Baltimore-Washington Inter.
national Airport.
                                                                     -40-
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     The microscopist categorizes individual particles into component types
by optically viewing particles while testing various optical and physical
properties such as listed in Table 13.  In this study 18 different com-
ponent types were identified.  The weight percentage (of the total weight
of particles analyzed) of each component type on each filter as  identified
by the microscopist is listed in Appendix E.  These component types are
further distinguished as six particle types which have source oriented
characteristics.  The following six source type particles were  identified:

     Minerals
     Mobile source emissions
     Large combustion source emissions
     Nonspecific combustion source emissions
     Industrial emissions
     Biologicals.

The microscopist's notes on how the particle classifications were  determined
are given  in Appendix E.  The percentage of the mass on each analyzed filter
attributed to each of the above six source  types by the microscopist  is
listed  in Table  14.  Also shown  in Table 14 is the percentage of  the  filter
sample which is removed by  low temperature  plasma ashing.   This information
is a further guide to the microscopist  as to how to interpret his  particle
classifications  in terms of  sources.
                  TABLE 13.  MICROSCOPICAL PROPERTIES OF PARTICLES
             Optical                               Physical

             Transparency                          Size
             Color                                 Shape
             Refractive index                      Solubility
             Pleochroism                           Density
             Birefringence                         Surface texture
             Reflectance                           Magnetism
             Fluorescence                          Melting point
                                    -42-
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-43-
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     Duplicate microscopical analysis was performed on 3 of the 18
analyzed filter halves.  One-half inch was trimmed off the straight edge
of each of the three filter halves to prevent identification of the dupli-
cate filters by matching the cut edges.  This did not prevent filter
identification, however, as the filter color and particle characteristics
were sufficient to enable the microscopist to identify the particular
filters.  The normalized results of the duplicate analyses closely agreed
with the corresponding original normalized results as indicated in
Table 15.  The ratio of the mean difference between pairs of filters to
the average weight percentage is shown for each component particulate type.
The ratios vary from zero to 0.85.  The mean ratio is 0.25.  Because the
particulate matter collected on a filter have color and texture characteris-
tics which vary from day to day, it is not difficult for a microscopist to
match an unidentified filter to one of 18.  A much larger number of filters
is required where individual filters are not so easily distinguishable to
get a better test of the repeatability of the microscopy analysis.  It may   ;.
be noted that there are very small differences between paired filter halves
for particles which compose more than 20 percent of the total mass.  The
larger percentage of particles of a given type on a filter, the higher
the probability that the sample of particles selected for microscopy will
produce the same mass percentage estimate.  When the percentage is small,
the samples selected from the sample filter are more likely to produce
different mass estimates because a difference of one or two particles in
the selected sample will greatly change the mass estimate which is derived.
The results in Table 15 show that very consistent estimates occur for
particles which made up high mass percentages of the collected material.
On this basis, it is concluded that the types of particles which have high
contributions are accurately assessed.

     In reviewing the results of the chemical and microscopy analysis, it
is evident that soil is a probable source of the high silicate concentrations.
Vehicular traffic and wind-generated dust from surrounding bare soil-
covered areas are likely airborne silicate contributors.

     The recrystallized sulfates probably represent the background sulfate
level because as the total sampled mass concentration increases, the percent
by weight of sulfates decreases, and as the total mass concentration
decreases, the percent by weight of sulfate increases; in other words, the
sulfate concentration tends to be less variable than the TSP.

     The high concentrations of rubber tire fragments are probably generated
by vehicular travel, and carried by the wind.

     Possible sources of the high calcite concentrations are gravel and
concrete road surfaces.  Vehicular travel and wind erosion would generate
the airborne calcite particulate.
                                   -44-
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                         TABLE 15. RESULTS OF DUPLICATE MICROSCOPY ANALYSIS

% by Weight
Component
Silicates
Calcite
Mica
Clays, humus
Hemolite
Carbonaceous tailpipe
exhaust
Rubber tire fragments
Glassy fly ash
Coal fragments
Oil soot
Fine carbonaceous
particles
Recrystallized sulfates
Cornstarch
Pollens, spores, conidia
Plant parts
Insect parts
Magnetic fragments
Total
Set 1
1st
23
5
<0.5
2
2

0.5
5
1
0.5
1

1
15
41
<0.5
<0.5
1
<0.5
98.0+
Set 2
2nd
23
13
<0.5
1
1

0.5
2
0.5
0.5
1

1
9
46
1
<0.5
-------
     The high cornstarch concentrations are found only at the Fort McHenry
station on the days June 9, 1977, August 2, 1977, and October 25, 1977.  The
source of the airborne cornstarch is probably nearby loading and unloading
harbor operations.  Table 16 indicates that in the first half of 1977, 2,025
thousand tons of corn were exported through the Baltimore Harbor area.  In
1976 a total of 3,992 thousand tons were exported.  This is one of the
largest materials handled by the harbor.

     October 25, 1977, at Fire Department #10 Station, high concentrations
of slag were found.  The likely source of this .material is the Bethlehem
Steel plant.

     The results in Table 14 show that mineral plus mobile emissions consti-
tute from 35 to 79 percent of the samples analyzed.  On the average we
estimate that fugitive emissions from the seven sources identified in our
fugitive emission inventory constitute about 50 percent of the TSP concen-
trations measured by the hi-vols.  This estimate provides a basis for
determining the importance of fugitive emission control strategies.   A
further analysis of the importance of various point sources in contributing
to the concentrations measured by each filter can be deduced by modeling the
impact of point sources.  Appendix F illustrates which of the 132 major
point sources in the Maryland BAQNC inventory are upwind of each of the
three monitoring sites for each 22.5° upwind sector.  Also shown in Appendix
F is the percentage of time and the average speed that the wind blew from
each sector on each sampling day for which a filter was analyzed in this
study.  An analysis of the possible impact of point sources on the analyzed
samples has not been considered in this study.  Nor has an attempt been made
to determine the extent to which the supplemented emission inventory which
was derived will account for actual  measured TSP concentrations.  A detailed
modeling study to develop such comparisons is a reasonable extension of the
present study.

     A preliminary analysis was  to try to  identify whether a few key  point
sources would account for major  contributions to the measured TSP concentra-
tions.  However, the wind direction was generally quite variable.  The mean
wind speed  and the range of variations in  hourly wind  speeds from this mean
are  listed  in Table  17  for the nine sampling  days.  The variations in wind
direction are large  and the job  of analyzing  the contribution of individual
sources was judged to be beyond  the scope  and resources of this study.
A more detailed listing of hourly wind direction variations is  given  in
Appendix G.
                                   -46-
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               TABLE 16.   BALTIMORE HARBOR MATERIAL THROUGHPUT
                     FOR 1976 and 1977 (1Q3 SHORT TONS)*
                                  1976
Material
Import
Export
1977 (Jan to Jun)
Import	Export
Coal
Corn
Wheat
Barley
Soybeans
Soybean Meal
Fertilizers
Coke, Pitch & Asphalt
Iron Ore
Manganese Ore
Miscellaneous Ores
Petroleum and
Petroleum Products
Sugar
Molasses
Salt
Gypsum
Bauxite






45

10,308
371
183

4,297
544
161
240
685
174
6,536
3,992
905
30
857
207
37
10
















101

2,736
131
135

2,757
239
74
256
254
60
3,185
2,025
50
5
421
60
3
6










* Source:  Mr.  William Walsek,  Department of Marketing  Statistics,  Maryland
           Port Administration, World Trade  Center,  Baltimore,  Maryland.
                                   -47-
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        TABLE 17.   RESULTANT 24-HOUR WIND DIRECTION  AND THE
         RANGE OF HOURLY VARIATIONS FROM THE RESULTANT WIND
                     24-Hour             Range of Hourly  Variations
Date (1977)   Resultant Wind Direction       from Resultant Wind
  Jun 9                224                      -91  to 156
  Jun 21               270                      -45  to 22
  Jul 15               144                     -104  to 144
  Aug 2                247                      -68  to 134
  Sep 19               229                      -86  to 116
  Sep 25                57                      -33  to 34
  Oct 25               119                     -151  to 119
  Nov 24               291                      -69  to 88
  Dec 12               199                     -161  to 42
                                -48-
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                                  SECTION 6

                     FUGITIVE EMISSION CONTROL  STRATEGIES
     Our literature search has  indicated suitable  control  strategies  and,
when possible, their effectiveness for all the fugitive  particulate  source
categories.  The following control strategies listed  by  source  type  are
ranked with greatest reduction first, and  least  reduction,  last.

GRAVEL AND DIRT ROADS

     1.   Paving the unpaved roads will reduce dust emissions by
          85 percent (PEDCo 1977).

     2.   Regularly applying water to the  surface  of  unpaved roads
          or applying a chemical stabilizer will reduce  emissions
          by 50 percent.  Oiling and double chip surface will
          reduce emissions by 85 percent (PEDCo  1977).

     3.   Low vehicle speeds will minimize dust  emissions.  The
          total dust emissions from unpaved roads  increases  in
          proportion to the average vehicle speed.

     4.   Stabilizing road shoulders will  reduce shoulder  emis-
          sions by 80 percent (PEDCo 1977).

     5.   Vehicles traveling on unpaved roads generate dust  in
          proportion to their number of wheels.  Decrease  multi-
          wheeled truck activity on unpaved roads  (Cowherd et al.
          1974).

CONSTRUCTION SITES AND WASTE DISPOSAL SITES

Construction

     1.   Regularly applying water to exposed soil is an effective
          means of dust control (Cowherd et al.  1974).

     2.   Construction activity levels influence emission  rates
          from the sites significantly.  However,  this emission
          rate variation has not been quantified (Cowherd  et al.
          1974).
          Waste
               1.    Emissions  due to handing can be reduced by over 99 per-
                    cent  by keeping the handled materials wet.  Covered or
                    enclosed hauling and minimizing the free fall of material
                    can also reduce emissions (PEDCo 1977).
                                           -49-
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     2.   Revegetation of waste disposal sites can  reduce  emis-
          sions by 25 to 100 percent  (Jutze  and Axetell  1974).

     3.   Dumping emissions can be reduced by 50 percent by  using
          spray bars at dump areas.   Minimizing the free fall  of
          material and using semi-enclosed bins can also reduce
          emissions (PEDCo 1977).

     4.   Emissions due to grading operations can be  reduced
          50 percent by watering (PEDCo  1977).
STORAGE PILES
     1.   Emissions from the movement of  storage piles  can  be
          reduced by 95 to 99 percent by  enclosing the  pile
          (PEDCo 1977).

     2.   Emissions from loading onto piles can be reduced  70  to
          99 percent by enclosing piles (Cross  and Forehand 1975).

     3.   Adjustable chutes can reduce emissions by  75  percent
          (PEDCo 1977).

     4.   Chemical wetting agents or foam can reduce emissions by
          50 to 90 percent (Jutze and Axetell 1974,  Evans  1975).

     5.   Wind erosion emissions from storage piles  can be  reduced
          by 95 to 99 percent by enclosing the  piles.   Wind screens
          are inefficient at reducing emissions.  Chemical  wetting
          agents or foam can reduce emissions by 90  percent (PEDCo
          1977).

     6.   Emissions due to loadout operations can be reduced by
          50 percent by water spraying.   Gravity feed onto  conveyor
          can reduce emissions by 80 percent.   Use of a stacker/
          reclaimer can reduce loadout emissions by  25  to  50 per-
          cent (Cowherd et al. 1977).
WIND EROSION
          Reduction of surface wind speed  across  a  source  is  a
          logical means of reducing emissions.  This  takes  such
          forms as windbreaks, enclosures  or  coverings  for  the
          sources, and planting of tall  grasses or  grains  on  or
          adjacent to exposed surfaces  (PEDCo 1977).
                                     -50-
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     2.   Frequently used materials for physical  stabilization
          of fine tailings are rock and soil  obtained  from areas
          adjacent to the surface to  be covered.   Soil  provides
          an effective cover and a medium for  vegetation  growth.
          However, the soil must support vegetation  growth and
          therefore must contain nutrients, moisture,  proper
          texture and no phytotoxicants.  Vegetation cover can
          reduce emissions by 65 percent (PEDCo  1977).

     3.   Crushed or granulated smelter slag,  a waste  product,
          has been used to stabilize  tailings, and can  reduce
          emissions by 90 to 99 percent (U.S.  EPA 1976).

     4.   Another method is to cover  tailings  or  exposed  surfaces
          with bark or harrowing straw into the top  few inches of
          material (PEDCo 1977).

     5.   Watering exposed surfaces by using  sprinklers or trucks
          can reduce emissions by 50  percent  (U.S. EPA  1976).

     6.   Chemical stabilization of exposed surfaces can  reduce
          emissions by 80 percent (Engr. Mining J. 1971).

     7.   A combination of chemical and vegetative stabiliza-
          tion can result in 90 percent reduction of emissions
          (U.S. EPA 1976).
RAILROADS
     1.   Cover the open-top railroad cars so that  contained
          aggregates will not be picked up by the wind.

     2.   Oiling the shoulders of the tracks will reduce  emis-
          sions generated by turbulence created by  train
          passage.
PAVED ROADS
     1.   Keep roads in good repair.  Streets  in  bad repair  have
          dust loadings about twice as high  as  streets  in  good
          repair (Cowherd et al. 1977).

     2.   Use concrete surfaces rather than  asphalt.  Reentrained
          dust from asphalt streets is about 80 percent higher
          than concrete streets (Cowherd et  al. 1977).
                                 -51-
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     3.   Regular street cleaning may reduce reentrained  dust
          (Cowherd et al. 1977).  However, Robert M. Bradway,
          Frank A. Record, and William E. Belanger,  ("Monitoring
          and Modeling of Resuspended Roadway Dust near Urban
          Arterials," undated, GCA and U.S. EPA) found that
          vigorous, forced flushing, plus splashing  by motor
          vehicles, redistributed particulates  that  had
          previously become concentrated adjacent to the  curbs,
          and that many of these redistributed  particulates
          became airborne as soon as the street  became dry.

     4.   Adding curbs to paved streets reduces  dust by about
          a factor of four (Cowherd et al. 1977).

SUMMARY

     The above control strategies vary in effectiveness.   It  is estimated
that it is not difficult to develop a strategy  for the Baltimore  area  which
will reduce fugitive emissions by 70 percent.   Where fugitive  emissions
cause 50 percent of the TSP concentrations, this will result  in a 35 per-
cent reduction in TSP levels.  At the three sites  included  in  the micro-
scopy analysis of this study, the fugitive emission  component  increased
when the concentration increased.  This phenomenon is best  illustrated by
the seven TSP measurements at the Fire Department #10 sampling station.
Figure 4 shows how the mineral content of particulate samples  increases
as the TSP concentration increases.  It  is reasonable to  expect that fugi-
tive emission controls of the above sources will reduce as  much as
70 percent of the highest concentrations.  On this basis,  it  seems reason-
able to expect that fugitive emission controls  can be used  to  reduce TSP
levels in the Baltimore by 50 percent and bring air  quality in the area
in compliance with Federal standards.  This  is  a very preliminary and
undetailed analysis of the problem.  The nature of the results obtained
suggests that an effective control strategy can be adopted.   Suitable
alternatives could be tested using the emission  data obtained  in  this
report and available air quality dispersion models.
                                      -52-
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                                 SECTION 7

                                 REFERENCES
Anderson, D.  1973.  "Emission Factors for Trace Substances."  U.S. EPA,
  December 1973.

Armburust, D.V. and J.D. Dickerson.  1971.  "Temporary Wind Erosion
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  Water Conserv. 26 (4): 154-157.

Baum, E.J. and R.L. Fitter.  1976.  "The Impact of Emissions from Trans-
  portation Sources on Air quality:  Atmospheric Aerosol."  Oregon Graduate
  Center, March 1976.

Bonn, R.C.T., Jr. and C. Cowhred, Jr.  1978.  "Fugitive Emissions from
  Integrated Iron and Steel Plants."

Bradway, R.M., F.A. Record, and W.E. Belanger.  Undated.  "Monitoring and
  Modeling of Resuspended Roadway Dust Near Urban Arterials."

Clark, W.E. and K.T. Whitby,  1967.  "Concentration and Size Distribution
  Measurements of Atmospheric Aerosols and a Test of the Theory of Self-
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Cowherd, C., Jr., K. Axetell, Jr., C.M. Guenther, and G.A. Jutze.  1974.
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  Kansas City, Mo.

Cowherd, C., Jr., C.M. Maxwell, and D.H. Nelson,  1977.  "Quantification of
  Dust Entrainment from Paved Roadways," MRI, July 1977.

Cowherd, C., Jr.  1977.  "Fugitive Emissions from Integrated Iron and Steel
  Plants — Open Dust Sources," MRI, June 1977.

Cross, F.L., Jr. wnd G.D. Forehand.  1975.  "Air Pollution Emissions from
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  Technomic Publishing Co., Inc., Westport, Connecticut,  pp. 3-4.

Davidson, B. and L. Herbach.  1964.  "Two Dimensional Diffusion of a Poly-
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Dean, K.C. and R. Havens.  1972.   "Reclamation of Mineral Milling Wastes."
  Presented at the Annual AIME Meeting, San Francisco,  Calif., February 1972.

Dean, K.C., R. Havens,  and M.W. Glantz.   1974.  "Methods and Costs for
  Stabilizing  Fine-Sized Mineral Wastes."  Salt Lake City Metallurgy
  Research Center, Salt Lake City, Utah.
                                   -54-
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Dean, K.C. and M.B. Shirts.  1975.  "Vegetation Techniques for Acidic and
  Alkaline Tailings."  January 6-10, 1975.

de Nevers, N., K.W. Lee, and N.H. Frank.  1977.  "Extreme Values in TSP
  Distribution Functions," Journal of the Air Pollution Control Association,
  Vol. 27, October 1977.

Engineering Mining Journal.  1971.  "Chemical Treatment of Waste Tailings
  Puts an End to Dust Storms."  pp. 104-105, April 1971.

Evans, R. J.  1975.  "Methods and Costs of Dust Control in Stone Crushing
  Operations."  U.S. Bureau of Mines, Pittsburgh, Pa.  Information
  Circular 8669.

Fennelly, P.F.  1976.  "The Origin and Influence of Airborne Particulates,"
  American Scientist, Volume 64, January-February 1976.

Galkiewicz, R.C. and D.A. Lynn.  1976.  "National Assessment of the Urban
  Particulate Problem - Volume V - Baltimore."  GCA/Technology Division,
  June 1976.
ft        GCA Corp.  1976.  "National Assessment of the Urban Particulate Problem.
™          Volume I."  Summary of National Assessment.  July 1976.
Medley, W.H., et al.  1974.  "Sources and Characterization of Fine Particulate
  Test Data."  Monsanto Research Corporation, November 1974.

Islitzer, N.F. and R.K. Dumbauld.  1963.  "Atmospheric Diffusion - Deposition
  Studies Over Flat Terrain," Int. J. Air Wat. Poll.. Vol. 7.

Jutze, G. and K. Axetell.   1974.  "Investigation of Fugitive Dust, Volume I -
  Sources, Emissions, and Control."  PEDCo-Environmental Specialists, Inc.,
  Cincinnati, Ohio.  Prepared for U.S. Environmental Protection Agency.
  Contract No. 68-02-0044, Task Order No. 9, June 1974.

Kelkar, D.N. and P.V. Joshi.   1977.  "A Note on the Size Distribution of
  Aerosols in Urban Atmospheres," Atmospheric Environment. Vol. 11.

Lee, R.E., Jr. and S. Goranson.   1976.  "National Air Surveillance Cascade
  Impactor Network.  Ill Variations in Size of Airborne Particulate Matter
  Over Three-year Period."  EPA, October 1976.

Maryland Bureau of Air Quality and Noise Control.  1976.  "Air Quality
  Maintenance Analysis for the Baltimore, Maryland Intrastate Air Quality
  Control Region for Total Suspended Particulate Matter and Sulfur Dioxide,"
  Technical  Memorandum, March 1976.  Baltimore, Maryland.

Maryland Department of Health and Mental Hygiene.  "1975 Emissions Inventory
  Report."  Division of Program Planning and Evaluation, Baltimore, Maryland.
                                    -55-
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Midwest Research Institute.   1977.   "Fugitive Emissions Control  Technology for
  Integrated Iron and Steel  Plants."  Draft.   Prepared for the U.S. Environ-
  mental Protection Agency,  Industrial Environmental Research Laboratory
  under Contract No. 68-02-2120.   Research Triangle Park, North  Carolina.
  January 17, 1977.

Midwest Research Institute.   1977.   "Quanitification of Dust Entrapment
  from Paved Roadways."  pp. 3, 5.   July 1977.

National Environmental Research Center.   1974.  "Environmental Protection
  in Surface Mining of Coal."  October 1974.

NTIS.  "Air Pollution Emission Factors - A Bibliography with Abstracts,
  Search Period covered 1964 - May 1977."

PEDCo.  1973.  "Investigation of Fugitive Dust - Sources Emissions and
  Control."  May 1973.

PEDCo.  1977.  "Technical Guidance for Control of Industrial Process
  Fugitive Particulate Emissions."   March 1977.

Pooler, F., Jr.  1971.  "Atmospheric Transport and Dispersion of Pesticides,"
  Division of Meteorology, EPA, September 12-17, 1971.

Research Corporation of New England.  1976.  "Technical Manual for Measure-
  ment of Fugitive Emissions Upwind/Downwind Sampling Method for Industrial
  Emissions."  April 1976.

Research Corporation of New England.  1976.  "Symposium on Fugitive Emissions
  Measurement and Control Held in Hartford, Connecticut on May 17-19, 1976."

Sartor, J.D., and 6.B. Boyd.  1972.  "Water Pollution Aspects of Street
  Surface Contaminants."  Publication No. EPA-R2-72-081.  U.S. Environmental
  Protection Agency.

Sehmel, G.A.  1973.  "Particle Resuspension from an Asphalt Road Caused by
  Car and Truck Traffic."  Atmospheric Environment, 7, March 1973.

Shirts, M.B. and J.H. Bilbrey, Jr.   1976.  "Stabilization Methods for the
  Reclamation of Tailings Ponds."  March 29 - April 4, 1976.

Stern, A.C.  (Editor).  1968.  "Air Pollution - Volume II - Analysis,
  Monitoring, and Surveying."  p. 270.

TRW,  Inc.  1977.  "Guideline for Development of Control Strategies in Areas
  with  Fugitive Dust Problems."  Guideline Series, OAQPS No 1.2-071.
  October 1977.
                                     -56-
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U.S. Department of Agriculture.  1973.  "Soil Survey of Anne Arundel County,
  Maryland."  Soil Conservation Service.  Issued Feruary 1973, pp. 71-75.

U.S. Department of Agriculture.  1976.  "Soil Survey of Baltimore County,
  Maryland."  Soil Conservation Service.  Issued March 1976.  pp. 95-101.

U.S. Environmental Protection Agency.  1975.  "Fugitive Emissions and
  Fugitive Dust Emissions."  July 1975.

U.S. Environmental Protection Agency.  1976.  "Evaluation of Fugutive Dust
  from Mining, Task 1 Report.  PEDCo Environmental Specialists, Inc.,
  Cincinnati, Ohio.  Prepared for Industrial Environmental Research
  Laboratory/REDHD, EPA, Cincinnati, Ohio.  Contract No.  68-02-1321.
  Task No. 36, June 1976.

U.S. Environmental Protection Agency.  1973.  "Guide for Compiling a
  Comprehensive Emission Inventory."  Monitoring and Data Analysis Division.
  March 1973.

U.S. Environmental Protection Agency.  1977.  "Compilation of Air Pollutant
  Emission Factors"  (Including Supplements 1 through 7).  Third Edition.
  Research Triangle Park, North Carolina.

U.S. - U.S.S.R. Working Group on Stationary Source Air Pollution Control
  Technology.  1974.  "Proceedings of a Symposium on Control of Fine-
  Particulate Emissions from Industrial Sources, held January 15-18, 1974,
  San Francisco, California."

Vandergrift, A.E., et al.  1971.  "Participate Pollutant System Study,"
  Vol. Ill:  Handbook of Emission Properties, Midwest Research Institute,
  May 1, 1971, PB 203 522.

Wedding, J.B., A.R. McFarland and J.E. Cermak.  1977.  "Large Particle Col-
  lection Characteristics of Ambient Aerosol Samples,"  Environmental Science
  and Technology,  11, 387-90.
                                   -57-
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                                APPENDIX A

                              HI-VOL SAMPLING
HI-VOL FILTER HANDLING PROCEDURES

     Changing of the hi-vol filter at the Fort McHenry site was observed.
The procedure is as follows.  Before traveling to the hi-vol site, the new
glass fiber filters are removed from the mailing package and placed in a
plastic box.  Before the old filter is removed, the sampler is turned on
for 2 to 3 minutes to let the flow stabilize; then, a flow meter reading
is taken.  The old filter is removed, carefully lifting the edges of the
filter and placing it in a manila folder.  The folder is clipped into a
waxed envelope which is put in the plastic box.  A new filter is removed
from the plastic box and placed on the sampler.  A final flow reading is
taken after about 2 minutes of stabilization, and the timer is reset.  The
hi-vols are calibrated about every 6 months in the laboratory.  The cali-
bration procedure is included in this appendix.  Hi-vol samples were normally
taken every 6 days.

     In the BAQNC laboratory, the filters are conditioned to a standard
humidity level for at least 24 hours before being weighed.  The filters
are weighed before installation and after removal.  Each filter received
from the state in this study, except the blanks, was cut in two, and half
of the filter was submitted to IITRI's laboratory for analysis of the par-
ticulate content.  The other half of each filter was kept by GEOMET.

BAQNC PROCEDURE FOR CALIBRATING THE HI-VOL AIR SAMPLER

     1.  In order to obtain meaningful results from the hi-vol air sampler
it is necessary to accurately determine the volume of air sampled as well
as the weight of particulates.  Since the rotameter is used only as an
indicator of air flow and since only a small portion of the total air
sampled passes through the rotameter during measurement, it must be cali-
brated against actual air flows.

     2.  Assemble the hi-vol sampler with a clean filter in place and run
for at least 5 minutes.  If new brushes are being used allow the sampler
to run for one-half hour to insure proper seating.  Attach the rotameter.
Adjust the orifice at the top of the rotameter with the top brass screw
so that the top of the ball reads 60.  Lock the setting by tightening the
brass lock nut at the top of the rotameter.  Put sealing wax over the
adjusting screw and lock nut to protect this setting.  Check rotameter
again for a flow of 60.  Turn off the sampler and remove the filter paper.

     3.  Place the number 24 resistance plate into the mouth of the
limiting orifice and then connect the orifice to the hi-vol air sampler.
Rubber gaskets should be used before and after the resistance plate to
                                    -58-
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insure a leak proof seal.  Connect the static pressure tap on the orifice
to the manometer with flexible tubing, leaving one side of the manometer
open to the atmosphere.  Attach the sealed rotameter to the pressure tap
at the base of the sampler by means of flexible tubing and quick-disconnects.

     4.  Turn the sampler on and run for at least five minutes.  Observe
and make note of the manometer readings.  Repeat step 3 for plates #20,
18, 16, 14, 12 and 10.  Tabulate the manometer and rotameter readings for
each particular plate on the Hi-Vol Air Sampler Record Sheet.

     5.  Convert the manometer readings (A P) to actual air flow in cubic
feet per minute (Q, cfm) by reference to the orifice calibration curve
supplied with the calibration kit and tabulate these values.

     6.  The tabulated data (Q, cfm versus rotameter readings) are treated
by the method of least squares to obtain the equation of the line that best
fits the data when plotted.  The State of Maryland presently accomplishes
this by use of a computer program specifically written so that upon
incorporation of the raw calibration data (Q, cfm versus rotameter readings)
the equation of the line of best fit is obtained.  This program is now
available to all local air pollution agencies who desire to use it.  If
access to a computer is unavailable the data can be treated as in sections
8 and 9 of the aforementioned Federal Register or manually by the least
squares method as follows:

     6.1  Sum (IX) the column of flow meter readings including only those
values for which manometer readings were on the orifice calibration curve
(A P >_ 2.8 inches).

     6.2  Convert each air flow rate value (Q) in cubic feet per minute to
cubic meters per minute (Y) by multiplying by 0.0283 M3/ft.3.  Sum (zY) the
column of air flow rate (Y) in cubic meters per minute.
                 i)
     6.3  Sum (rX ) the squares of each of the air flow meter readings (X)
for which the corresponding A P >_ 2.8 inches.

     6.4  Sum (sXY) the products of the corresponding flow meter readings (X)
and the air flow rate (Y).

     6.5  Perform the following calculations:

                              EY = Na + bzX                             (1)

                          S(XY) = aiX + b£(X2)                          (2)

where N is the total  number of readings (X) which are being used in the
calculations.
                                   -59-
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     6.6  Substitute in equations (1) and (2) the values for zY, N, IX,
E(XY) and x(X2).  Multiply equation (1) by the factor zX/N to give the
following equation:
                                             2
                               = a£X + b l2--                           (3)
     6.7  After substituting in the known numerical values, subtract
equation (1) from equation (2).  This eliminates unknown coefficient a.
Coefficient b is then substituted into equation (1) and coefficient a is
determined.  The equation for the calibration line then turns out to be
the following:

                                Y = bX + a                              (4)

where Y represents air flow rate in cubic meters per minute and X repre-
sents flow meter reading.

     6.8  From equation  (4) and the initial and final flow meter readings
for a 24-hour sample, the total air volume sampled is calculated.  The
initial and final flow meter readings are averaged and the value (X) is
incorporated in the calibration equation.  The air flow Y multiplied by the
total sampling time in minutes gives the total air volume sampled in cubic
meters.
                                    -60-
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 Source  No.
            Appendix B

   FUGITIVE EMISSION SURVEY FORM

FUGITIVE DUST SOURCE - REGISTRATION



                 Map No. _____	
 Description  of Area;


 Paved Lot


   Asphalt


   Concrete


   Stone & Tar


   Trash 4 Debris


   Unpaved Shoulders


   Loose Gravel Surface


   Stockpiles with Fine Material


   Stockpiles with Course Material


   Other
Unpaved Lot


Q Dirt


Q Grass


(__] Weeds


    Crushed Stone


    Gravel


|~"] Broken Pavement


Q Cinder


[J Trash & Debris


    Stockpiles with Fine Material


    Stockpiles with Course Material


    Other
Map Coord.
                 Grid Coordinates


                 Terrain;


                 QFlat


                 £] Rolling


                 JTJ Steep Slopes


                    Open


                    Enclosed


                    Semi-enclosed


                 Approximate Size



                 Type of Activity;


                    Residential


                    Commercial


                    Industrial


                    Parking


                    Construction


                    Storage


                    Recreation


                    Unused


                    Railroad
                    Cinder,  Gravel Crushed Stone, Oiled
                     Not Oiled
                                      -61-
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         Comm.

      Qlnd.
Description of Emissions

Q Cars

Q Trucks

Q Stockpiles

£3 Storage

Q Natural Occurrence

Q Material Handlers

      Mobile

      Stationary

Q Other 	
Inspectors Comments:
Date Registered:

By: 	
                                       -.2  -

                                        Res.

                                    [I Comm.
                                                                   | I Cotnm.

                                                                   P Ind.
                                        Comm.
                                        Mobile Activities Frequency

                                        Q Commuter

                                        Q Continuous

                                            Occasional  (Low Activity)

                                            Occasional  (High  Activity  -  Bulk)

                                        No. of Vehicles  per  Unit  Time 	

                                        Avg.  Speed of  Vehicle 	
         $
         1
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                                         Stockpiles moved 2U Hr. j_J Wkly.
                                         Owner Information:
Mthly. 1~P


        1
Name:
Tel. No. V
•
Address:
Leased:
1
                                         Estimated Emissions:

                                         	 Ibs/day
                                     -62-
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«                                             Appendix  C
                                   FUGITIVE  SOURCE  CHARACTERISTICS
 1                      This  appendix  contains  the following  data:
 W                      •    Baltimore City fugitive  source characteristics
 *                           by grid square (1  square mile  each)
                         «•    UTM and Maryland  state coordinates for  each
                              Baltimore City grid square
                         §•    Baltimore and  Anne Arundel  fugitive source
                              characteristics by grid  square (1000  ft on a  side)
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                              Appendix D

                      FUGITIVE EMISSION PROGRAMS


          The appendix contains listings of FORTRAN computer programs

to compute emissions of fugitive sources and to compute coordinate

conversions.  The following are included:
          t    Program to compute fugitive emissions for Baltimore
               City

          t    Program to compute fugitive emissions for Anne
               Arundel and Baltimore Counties

          •    Program to compute UTM coordinates from Maryland
               state coordinates.
                                   -78-
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 I
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 I                                         APPENDIX E
 I                              IIT RESEARCH INSTITUTE'S REPORT
 ™                               ON ANALYSIS OF HI-VOL FILTERS
 I
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                                               by
 8                                      Katherine Severin
                                               and
 •                                      Ronald G. Draftz
                                          approved by
 •                                       John Stockham
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                TABLE OF CONTENTS
1.    INTRODUCTION

2.    PURPOSE AND OVERVIEW OF THE STUDY
     Summary of Analytical Methods

3.    SAMPLE ANALYSIS AND RESULTS
     Sample Preparation
     Low Temperature Ashing Procedure
     Results of Low Temperature Ashing
     Sulfate Analysis
     Elemental Analysis
     Discussion of the Elemental Analysis

4.    MICROSCOPICAL ANALYSIS
     Particle Identification
     Sample Preparation
     Microscopy Results
     Description of Quantitative Microscopy Procedure
     Calculating Component Concentrations
     Inorganic Components
     Organic Components
     Data Sheets
                       -96-
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 I
 I
             1 .   INTRODUCTION
                      This  is a final report  presenting  the results of  high volume
 ™           filter analysis to  identify the types and  sources of aerosols contributing
 •           to  non-attainment of  the  Federal  Total Suspended Particulates Standard
             at  three  sites  in Baltimore, Maryland.   IITRI's study was conducted under
 I           two subcontracts to GEOMET, Inc., who served as contractor  to the  Federal
             Environmental Protection  Agency,  Region  III, and the State  of Maryland
 B           for this  study.
 •                    The results of  both  subcontracts have been merged and incor-
             porated in  this single  report  to  provide continuity in assessing the data.

 *           2.   PURPOSE AND OVERVIEW  OF THE STUDY
 I                    Several total suspended particulate  (TSP) monitoring sites in
             Baltimore,  Maryland currently  exceed the primary Federal 24-hour particu-
 |           late standard and are projected to continue  causing violations of  this
 M           standard  through 1985.  As part of a continuing effort to eliminate
             these violations the  State of  Maryland and the U.S. Environmental  Protection
 •           Agency, Region  III, enlisted the  help of GEOMET, Inc. to perform a study
             of  the sources contributing to TSP violations.  GEOMET, Inc. subcontracted
 I           a part of their study to  I IT Research Institute to perform  microscopical
 •           and chemical analyses of  selected high volume  (hi-vol) filters.
                      The three sites selected for study are at or near Baltimore
 •           Harbor and  are  identified as:
                      Fire Department #22
•                    Fort McHenry
•                    Fire Department #10
                                              -97-
1
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These sites are thought to be representative of Baltimore's TSP non-
attainment problem and also produced some of the highest TSP concentrations
in the Baltimore area in 1976.  A total  of twenty one hi-vol filters were
sent to IITRI, including three unidentified duplicate samples.
          Polarized light microscopy was used as the primary analytical
method to identify particile types and concentrations.  Ancillary analytical
techniques were used to corroborate the microscopical identifications
on concentration measurements, as needed.  These ancillary techniques
included:
          t    chemical analysis for water soluble sulfates
          •    plasma emission spectroscopy for elemental analysis
               of lead and vanadium as tracers for vehicle exhausts
               and oil soot, respectively
          t    low temperature (plasma) ashing to determine the total
               organic content
          •    scanning electron, x-ray microanalysis to corroborate
               the identity of selected particles.
Plasma emission spectroscopy was also used for a quantitative broad
survey of acid soluble elements in nine samples.
          The results of these analyses were used by IITRI to independently
identify generic sources and their contributions to TSP concentrations.
The generic source assignment was conducted by IITRI without knowledge
of the specific sources proximate to the sampling sites.  These data
can be coupled with meteorological and emissions inventory data to
pinpoint specific stationary and fugitive dust sources.
                                 -98-
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I
I
            Summary of Analytical Methods
                      The analytical methods used to Identify the aerosols collected
1          on high volume filters include polarized light microscopy, low temperature
            plasma ashing, plasma emission spectroscopy, scanning electron microscopy,
•          and sulfate analysis.  Details of the methods are given in subsequent
•          sections.
                      Polarized light microscopy was used as the principal means of
•          identifying aerosols.  The concentration of each identified aerosol  type
            (or group, such as minerals) was determined by performing particle size
•          distributions and particle counts by aerosol type to compute the mass con-
•          centration per unit filter area.  The mass concentration of each individual
            component was then summed with all other components and normalized to
I          provide a weight percentage by component for each sample.
                      Low temperature plasma ashing was used to determine the total
•          combustible components concentration of aerosols such as starch, pollens
•          and carbonaceous vehicle exhausts.  The residue after low temperature ashing
            then corresponded to the inorganic component concentrations such as  pavement
M          and soil minerals, fly ash, and slag.  Thus, low temperature ashing  served
            as a simple, independent method for measuring the concentrations of
H          organic and inorganic aerosols, which generally originate from different
•          sources.
                      Ammonium sulfate which originates from the reaction of atmospheric
•          ammonia with sulfur oxides from fuel  combustion, was determined by a
            separate analytical procedure.  This separate analytical procedure was
•          necessary because ammonium sulfate is often found buried in the filter

i

i
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matrix or at the filter bottom.  Therefore, for heavily loaded filters,
i.e., those with high TSP concentrations, the sulfate crystals are
partially obscurred by other particles nesting on the filter surface.
(In spite of this obscuration, polarized light microscopy can still
reveal whether the sulfate concentrations are major, minor or trace
by simply mounting a sample upside down.)
          Lead and vanadium concentrations were analyzed by plasma emission
spectroscopy (PES) to determine the contributions from auto exhuast
and oil soot, respectively, from source coefficient factors.  In addition,
PES was used to determine boron, calcium, magnesium, zinc, silicon, copper,
nickel, manganese, molybdenum, cobalt, aluminum, titanium, barium,
chromium and iron concentrations in nine samples selected by the State of
Maryland.  These analyses were used to corroborate the microscopy
results.
          The same nine samples selected for PES analysis were also examined
by scanning electron microscopy (SEM) with x-ray microanalysis of individual
particles.  These analyses also served as a corroborating technique for
the particle identifications by polarized light microscopy.

3.  SAMPLE ANALYSES AND RESULTS
Sample Preparation
          Halves  (8"x5") of eighteen  standard  hi-vol filters
and three unknown filters were submitted for analysis.  The sampling
sites, dates, TSP concentrations and  average wind speeds for these samples
are shown in Table E-l.  The TSP concentrations listed  in parentheses
                                -100-
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                               Table E-l.  Hi-Vol Filter Data
Sampling
Date
6/9/77
6/21/77
7/15/77
8/2/77
9/19/77
9/25/77
10/25/77
11/24/77
12/12/77
Day of
Week
Thursday
Tuesday
Friday
Tuesday
Monday
Sunday
Tuesday
Thursday
Monday
TSP Concentration, Wg/m3
Fire Dept. #10
63
(145)
221
(142)
(165)
51
306
42
169
Fire Dept. #22
(NA)
60
149
(93)
108
38
(NA)
52
129
Fort McHenry
59
(136)
(114)
154
(69)
39
118
41
85
Average Wind
Speed, mph
9.6
10.5
5.6
6.2
5.8
11.1
3.9
4.3
(NA)
NA  - Not Available.
                                          -101-
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are for samples that were not submitted for analysis,  but they are included
for comparison.
          Each hi-vol filter was opened in a class 100  cleanbench and
visually examined for artifact contaminants such as paper fiber bundles or
sample loss due to filter tears, raindrops or fingerprints.   No contaminants
or particle losses were seen on any filter.  Each sample was also examined
by stero-microscopy for uniformity of particle deposition.   As usual,
the folded filter showed an obvious increase in the concentration of large
particles that had fallen into the crease during shipment.   Some of the
large particles had also fallen off the hi-vol filter into the envelope
used to protect the filter during shipment.  We did not determine the
extent of large particle bias in the crease, but it appeared insignificant.
          Each filter was cut with a stainless steel scalpel into a
number of sections for analysis.  The exact sizes for  each analytical  test
will be described with each test.  We presumed that areas of the various
sections had mass loadings proportional to the total filter.  This
approach was favored over weighing the cut sections because it eliminated
the need to recondition the filter for weighing and avoided the possible
problem caused by filter fiber losses.  These filter fiber losses might
make a weighed section seem smaller than its true size.

Low Temperature Ashing Procedure
          Precisely measured 6.35 cm x 3.81 cm sections were cut for low
temperature ashing.  The sections were dessicated for 24 hours, weighed,
and then ashed for two hours in an LFE Model 310 asher.  The sections
were then redessicated and weighed to determine the loss due to oxidation
of organics.
                                 -102-
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                       Each ashed  filter  strip was examined microscopically to confirm
 •          that  ashing was complete.  If  it appeared that additional ashing was needed
 ft          the sample was ashed  for two more hours.  Several filters were re-ashed but
             no additional weight  loss occurred which confirmed that ashing was complete
 v          in two  hours.
                       Low temperature plasma ashing  (LTA) is usually accomplished at
 W          temperatures below  200°C and at a pressure of approximately 1 min of mercury.
 •          At these  ashing conditions ammonium sulfate sublimes and contributes to
             the weight loss.  Therefore, the ammonium sulfate content must be subtracted
 H          from  the  LTA weight loss to  determine the organic content.
 ^                   A slight  weight increase can occur during LTA if samples contain
 •          metals  or reduced metal oxides such as FeO or Fe.^.  These compounds will
 ft          oxidize contributing  a  negligible to slight weight gain.  In practice the
             weight  gain is undetectable  because only the surface oxidizes.  The oxidized
•          surface is non-volatile and  acts as a barrier to complete oxidation.
 ^           In addition, the reduced metal oxide content of most hi-vol samples is
 P           usually below five  percent and often below one half percent.  Therefore,
 ft           the weight gain would be trivial even if the oxidation were complete.
             Since FeO, Fe3CL and  most alloys of iron are magnetic, it is fairly
W          simple  to estimate  (or  quantitate) whether a weight gain during LTA would
             be detectable.
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Results of Low Temperature Ashing
          Table E-2 shows the low temperature ash losses corrected for
sulfate loss,  for each sample.
I
                      The organic components contributing to the loss include:
                                -103-
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                           Table E-2.  Low Temperature Ash Losses
Date
6/9/77
6/9/77
6/21/77
7/15/77
7/15/77
8/2/77
9/19/77
9/25/77
9/25/77
9/25/77
10/25/77
10/25/77
11/24/77
11/24/77
11/24/77
12/12/77
12/12/77
12/12/77
Site
Fire Dept. #10
Fort McHenry
Fire Dept. #22
Fire Dept. #10
Fire Dept. #22
Fort McHenry
Fire Dept. #22
Fire Dept. #10
Fire Dept. #22
Fort McHenry
Fire Dept. #10
Fort McHenry
Fire Dept #10
Fire Dept. #22
Fort McHenry
Fire Dept. #10
Fire Dept #22
Fort McHenry
Total Organic Content
Wt. Pet.
20
21
20
16
24
50
20
3
10
1
10
30
10
15
15
28
23
26
JJg/iu
13
12
12
35
36
77
22
2
4
0.4
31
35
4
8
6
47
30
22
(1)
    Total Organic Content = (LTA Loss) - (HO soluble SO    [as (NH^SO  1).
                                            -104-
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                       •     carbonaceous  tailpipe  exhaust
 m                    •     rubber  tire fragments
 _                     t     coal  fragments
 W                    •     oil  soot
 M                    t     cornstarch
                       •     pollens  , spores,  conidia
 W                    •     plant parts
                       •     insect  parts

             Sulfate Analysis
 *                    The  two  principal  forms of  sulfates  in  the atmosphere are
 *           ammonium  sulfate and sulfuric acid.   If the sulfates are  collected as
             sulfuric  acid  they will generally react with limestone  particles  from
 m          pavement  aggregate to  form calcium sulfate, or will react with ambient
             ammonia to form ammonium sulfate.   The most abundant sulfate  form found
 p           on  hi-vol  filters  is ammonium sulfate.
 A                     Ammonium sulfate is hygroscopic and  dissolves on hi-vol filters,
 *           and the droplets penetrate to the bottom of the filter  where  they evaporate
 m           leaving crystals of ammonium sulfate.  Because these droplets containing
             sulfate may contact other particles on the filter, the  sulfates may
 9           crystallize over the surface of the water insoluble particles.  These
 A           transparent, colorless sulfate crystals coating opaque  carbonaceous  particles
             cannot  be readily  seen by optical  microscopy.  Therefore, sulfate is
 W           determined by  a separate chemical  procedure from  a water  or acid  extract of
             a filter  segment.
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-105-
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                                                                 2
          An exactly measured filter section, approximately 50 cm ,  is
placed in a 150 ml acid washed beaker.   To the beaker, 2 ml of 1:1 MN03
and 20 ml of deionized water is added.   The beaker is covered with a
watch glass and the sample heated to near dryness on a hot plate,  (approxi-
mately 6 hours).  An additional 4 ml of 1:1 MN03 and 40 ml of deionized
water are added.  The heating is repeated until a final v-lume of approxi-
mately 2 ml is achieved.
          The resulting solution is diluted with a few milliliters of
deionized water and filtered through Whatman 41 paper.  The sample filter
is agitated during the filtering and washing with a stirring rod.  The
filtered solutions are brought up to a final volume of 25 mis.
          Sulfate concentrations are determined turbidimetrically
                                              2
The detection limit is approximately 0.1 yg/cm , while the sensitivity
          2
is 2 yg/cm .
          The results of the sulfate analyses are shown in Table E-3
in weight percentage and in micrograms per cubic meter.  The weight per-
centage values show the impact of sulfates on total TSP, while the concen-
trations in yg/m   indicate whether all the sampling sites have a similar
or dissimilar exposure level due to remote or local sources, respectively.
                                 -106-
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Table E-3.  Sulfate Concentrations
Sampling Date
6/9/77
6/21/77
7/15/77
8/2/77
9/19/77
9/25/77
10/25/77
11/24/77
12/12/77
Weight Percentage
FD 10
21
-
13
-
-
36
13
35
13
FD 22
-
24
16
-
22
40
-
32
17
FT MH
30
-
-
15
-
50
18
45
25
Micrograms Per Cubic Meter
FD 10
13
-
29
-
-
18
40
15
22
FD 22
-
14
24
23
24
15
-
17
22
FT MH
18
-
-
-
-
20
21
18
21
         -107-
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ELEMENTAL ANALYSIS
          Elemental  analyses were performed for several  reasons:

          •    To corroborate the microscopical data
          •    To provide lead and vanadium concentrations so the total
               concentrations of carbonaceous auto exhaust and oil  soot
               can be calculated
          t    To provide a broad elemental scan for the presence of
               unusual components.

          Lead, vanadium, calcium, and iron were analyzed in each of the
18 known samples, as well as, the three, duplicate unknown samples.   Lead
and vanadium are somewhat unique elements that have been used as atmo-
spheric tracers for auto exhaust and oil soot, respectively.  These tracers
are used with source coefficient factors to compute the  concentration
contribution from generic sources.
          There are a few problems that affect the accuracy of the cal-
culated source contributions when using source factors.   The calculated
source impact from autos presumes a fixed ratio of lead  emissions to total
particulate exhausts.  However, the ratio of lead to carbonaceous exhaust
particles depends on vehicle speed, idling time at intersections and
leaded to unleaded fuel use ratios.  These parameters can change the source
coefficient factor by perhaps as much as 600 percent.  However, in this
study we can reasonably presume that a constant source coefficient factor
for lead is adequate.  We know from our microscopical analysis that there
were no other significant sources of lead found in the samples.
          The need for these lead and vanadium analyses  is caused by the
fact that submicrometer, opaque, particles such as those from auto and
                                   -108-
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diesel exhaust and crushed oil soot are difficult to distinguish by optical
microscopy.  (It's important to emphasize that supermicrometer particles of
oil soot are easily recognized by optical microscopy.)  Scanning electron
microscopy (SEM) could be (and has been) used to distinguish fine,
carbonaceous particles, but a quantitative SEM procedure would be extremely
time consuming.  Therefore, elemental analysis is the simplest, adequate
procedure to determine contributions from auto exhaust and oil burning.
The carbonaceous auto exhaust content is 1.5 times the lead concentration.
Oil soot is 39 times the vanadium content.
          Calcium and iron concentrations were determined to corroborate
the microscopical analysis for limestone and iron oxides.  Unfortunately,
the variation in blank values for calcium, and to a lessor extent iron,
made these analyses of doubtful benefit for corroboration.  If anything,
it appears that elemental analysis for determining major source contribu-
tions on hi-vol filters may be futile due to the variable background
values on the surface of unexposed filters, as revealed by analysis of
"blank" filters.
          Nine of the hi-vol filters were analyzed for 13 other elements
to serve as a scanning method for other components.  The same sample
dissolution procedure that was used for the sulfate analysis, described
above, was also used for elemental analyses.  The metals were analyzed
by plasma emission spectroscopy using a lithium buffer and a germanium
internal standard.
          Results for the elemental analysis are shown in Tables E-4
and E-5.
                                -109-
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                             -m-
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 DISCUSSION OF THE ELEMENTAL DATA
          Aluminum, silicon, calcium, magnesium and boron are the matrix
elements of the glass fiber hi-vol filters.   We presumed that some of these
elements would be leached from the fibers during acid dissolution of the
sample.   We also presumed that the amount of these elements leached from
the filters would be about the same so a blank could be subtracted.  How-
ever, three different blanks run for calcium gave values of 2.4, 20 and
                    2                           2
30 nvicrograms per cm .   The 30 micrograms per cm  blank value exceeded
the values for five samples.
          In comparing these results with those run by another lab we
learned that the glass fiber matrix elements can vary by a factor of 40.
This variation in blank values makes it impossible to use the sample calcium
values to verify the calcite content.  The trace elements that are not
glass matrix elements show reasonably consistent blanks that are appreci-
ably lower than sample values.  However, these are less important elements
in determining the cause of high TSP concentrations.
4.  MICROSCOPICAL ANALYSIS
    Particle Identification
          Particle properties readily observed by microscopic techniques
are listed in Table E-6.  Determination of most of these properties is
usually accomplished by simple examination with a polarized light micro-
scope.  Since particles possess unique sets of physical and optical prop-
erties, determination of these properties usually results in the identifica-
tion of the particle types.  Succinct differences in individual particle
                                   -112-
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           properties at  various  levels allows distinction  between particles of
           identical chemical  composition but of different  types of sources.   Sili-
           con dioxide  is  a  good  example of a compound  which occurs in several dis-
           tinct particle  types.   Cristobalite and quartz are forms of Si02 which
           are readily  distinguished by optical microscopy  due to their differences
           in refractive  index and birefringence.  While x-ray diffraction  (xRD)
           would distinguish these particle types, the  applicability of xRD to hi-vol
           filter analysis  is  extremely limited because a large sample size is needed.
           X-ray diffraction could not, however, distinguish between three other common
           silica forms --  beach  sand, doundry sand and soil derived quartz.  Morph-
           ological properties alone must be used to distinguish these silicas.
                             Table E-6.  Microscopical Properties of Particles
                         Optical                               Physical
                       Transparency                            Size
                       Color                                 Shape
                       Refractive Index                         Surface Texture
                       Birefringence                            Magnetism
                       Reflectance                             Solubility
                       Pleochroism                             Melting Point
                       Fluorescence                            Density
I
                      Particle types composed primarily of carbon are practically impos-
P         sible to  identify by any technique other than optical microscopy.   Oil  soot
           fand coal  fragments are primarily carbon  but do have associated  trace  elements
           which can  be  used to help distinguish  one from the other.  However, the two
•         types of  particles are readily distinguished microscopically.   Oil  soot is
                                              -113-
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hollow, opaque,  black and spherical  with a surface texture that ranges from
dull  and grainy to a lacy network of filaments.   Coal  particles,  on the
other hand, are black, angular fragments with smooth to dull,  glistening
surfaces.  Biological particles — pollens, spores, trichomes,  insect parts,
starch, etc. - are also composed primarily of carbon and would  be included
in a total organic carbon analysis of a hi-vol  filter.   Although these bio-
logical particles rarely exceed one percent of the total collected mass on
an urban filter sample, the ability to distinguish this carbon  particle type
from others is especially important in the analysis of rural  samples or
when a source influence such as a granary is expected.
           Just as the spectroscopist relies on  libraries of reference
spectra for the identification of unknown samples analyzed, the microscopist
also relies on reference collections of particle data for identification
of particle types.  These reference collections  include the microscopist's
own previous experience, handbooks of optical properties (e.g., refractive
indices, Michel-Levy birefringence charts, etc.), atlases of photomicro-
graphs, and actual (particulate) source samples.
           The specific bases for assigning particles to sources in this
study will be described in later sections.

Sample Preparation
           After surveying the hi-vol filter provided for analysis of
uniformity of particle deposition, a triangular section measuring approxi-
mately 2 cm on each side was cut from the filter and immersed in a pool
of immersion liquid on a glass slide.  After the oil had soaked through
to the front surface of the filter section, a cover slip was placed on

                                  -114-
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  I
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 H         top to complete the mount.  The immersion liquid employed had a refractive
            index of 1.515.  This liquid matched the refractive index of the glass
 ^
 •         fiber filter substrate, thereby rendering the filter transparent.
  -                    A second slide was prepared from each filter with AROCLOR 5442
 •         as the mountant.  A drop of heated AROCLOR 5442 was allowed to cool at
 A         the end of a glass rod until the drop became tacky.  The adhesive drop
            was then lightly pressed against several areas of a dry hi-volume filter
 •         section until the top surface was loaded with particles.  The AROCLOR
 ^         and particles were then transferred to a clean glass slide by heating
 *         the glass rod until the AROCLOR liquified and dropped off onto the slide.
 •         A cover glass was added to complete the mount.  AROCLOR has refractive
            index of 1.66 and thus allows viewing of particles which may be invisible
 f
 m         in the 1.515 mounting medium.  A third slide of the low temperature ash
            residue was also prepared for microscopy.  The elimination of opaque,
 *         carbonaceous particles aided in performing size distribution measurements
 4         for small mineral particles.
                       Samples of roadbed materials which were submitted for analysis
 •         along with h1-vol filters were ground'in a diamonite mortar and pestle
            before dispersing in 1.515 refractive index liquid on glass slides.  Source
 ^«          and soil samples which also supplemented the hi-vol filters were not ground
 «|         but gently disaggregated before mounting in 1.515 refractive index
            liquid on glass slides.
 •                     The mounted filter sections, AROCLOR slides, and source
 ~           samples were analyzed by polarized transmitted light and oblique
 "          reflected light microscopy.  Magnifications ranging from 62.5X through
            625X were employed to view the particle types present.
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Mineral Particles
           Quantitative analysis by polarized light microscopy is a
two step procedure.  Particles are first identified as specific com-
pounds such as quartz, calcite and hematite, or as generic types such
as coal flyash, cornstarch, and rubber tire fragments.  Then the individ-
ual particles are counted and sized to determine their areal mass con-
centration.  The areal mass concentrations of all  the components are
summed and normalized to produce a weight percentage for each component.
           Before presenting the results of the quantitative microscopical
analysis, it is necessary to describe the individual components which
comprise the samples.  The components were essentially the same at all three
sampling sites so that the particle descriptions are common for all
samples.
           The sample report format (see tables at end of Appendix E)
identifies components of particle types by generic source with the exception
of the minerals components.  Minerals  includes the components silicates,
calcite, mica, clays and humus.  The silicates include quartz (SiCL) and
feldspars (such as orthoclase,  KAlSigOg)  which are principal constitu-
ents of rocks and soils.  While the individual species in this component
group can be distinguished microscopically, their optical and morphological
characteristics are similar, especially for the feldspar minerals.  These
similarities, along with their likely common source, soil, led to the
decision to combine them under one component category.  Trace concentra-
tions of other silicates such as augite and abvine are also grouped in
the silicates component.  Calcite  (CaCCL) is another common though minor
                                 -116-
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            constituent of soils but its main occurrence is as asphalt or concrete
            pavement aggregate.  Calcite is the principal mineral of quarried limestone
            but aragonite (CaC03) and dolomite [CaMg(C03)2] may also be present in
            small concentrations.  The crushed crystals of these minerals are not
            easily distinguished by polarized light microscopy, so traces of dolomite
            and perhaps aragonite may be present in the calcite component.
H                    The three principal mica species are biotite, muscovite and
£          phlogapite which are potassium aluminosilicates.  These silicates
™          were grouped separately because the micas are so easily identified,
•          even though their primary source is also soil.
                      Clays and humus are the final soil components listed under
•          Minerals.  The submicron clay particles are generally found as agglomerates
            fand range in size from 1 ym to 10 ym.  Discrete clay particles also coat
            the larger mineral grains in soil, but these clay particles contribute
M          so little to the mass that they can be ignored.  Humus is the organic
•
            matter in soil.  Humus is predominantly decomposing plant fragments
            that appear as translucent, dark brown isotropic fragments, often
            coated with clay particles.
                      With the exception of calcite, all of the Mineral components
            are present in Baltimore's soil.  Calcite was also found in the soil
            but appears to be present as a contaminant from the roadway pavement.
            This will be discussed in the later section on TSP source assignments.

            Description of Quantitative Microscopy Procedure
                      The method for determining the weight percentages for specific
            particles in each hi-vol sample is based on a simple particle counting
                                            -117-
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and sizing procedure.  The mass of a specific particle type in a known
area of filter (the microscopical  field of view) is calculated from the
particle size distribution and number concentration.  The procedure is
repeated for each type of particle in the sample so that the mass per
unit filter area is determined for each particle.  The weight percentage
for a component is simply the mass per unit area for that component
divided by the sum of the mass per unit area of all components.
          The mass concentration for a component could be calculated
directly as micrograms per cubic meter by merely scaling individual
mass per unit area values to the total filter area and dividing by the
total air volume sampled.  This approach will work well when the particles
concentrations are uniformly deposited over the filter.  However, we know
there is some loss of large particles that fall into the crease of the
folded filter which could cause low values for certain components and
a lack of mass balance with the total filter loading.  Non-equivalent particle
shapes could also cause under or over estimates of particle size for
components becuase of their preferred orientation on the filter.  There-
fore, we elected to normalize data rather than calculate mass concentra-
tions directly.
          This approach of normalizing the sum of the component mass
ratios to unity (or one hundred percent) is valid simply becuase all of
the major and minor particles are seen microscopically.  That is, the
microscopist would deliberately have to ignore a major component to
create a serious error.  This approach offers substantial reliability
over elemental techniques which cannot survey all elements collected
                                -118-
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 I

 i
             on the  h1-vol  filter,  and  therefore must  presume  certain  combining  elements
 W          such  as oxygen to  calculate  a  mass balance.
 A                    The  microscopical  approach  also makes use of  the  low  temperature
             ashing  procedure to  fix  the  concentrations of  organic and inorganic
 •          components.   In this way,  possible cumulative  shape errors  for  particles
 ^          such  as inorganic  mica flakes  have no effect on rubber  tire fragments,
 "          which are  organic.
 m                    A  stratified sampling  procedure was  used to determine particle
             size  distributions and number  concentrations.  This statistical  method
 •          provides a means for obtaining similar precisions for the concentrations
             of the  abundant, submicrometer size particles  and the sparse, large
 w          particles  greater  than 50  ym in  diameter.  For example, a single
 4|          microscopical  field  of view  with a 10X objective  may contain only one or
             two particles  greater  than 50  ym diameter while there may be several
 •           thousand particles below 1 ym  diameter.   Since the 50 ym  particle has a
             mass  equivalent to 125,000 one-micrometer particles it  is essential
 "           to count the large particles precisely.  This  is  accomplished by using
 £           low magnifications (100X)  to count and size the large particles in
             several  fields of  view.  The small particles are  counted  and sized  at high
 •           magnifications (625) in  just a few fields of view.  By  knowing  the
             area  of the  field  of view  at each magnification,  the count  data can
 ™           be merged  to produce a complete  size  distribution.  Table E-7 shows raw
 j|           count data determined  by stratified sampling for  silicates  on a hi-vol
             filter.
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                                             -119-
I
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                    Table E-7.  Raw Count Data for a Size Distribution
                                     by Stratified Sampling
Size Range, pm
<1
1-2
2-3
3-4.5
4. 5-6. 4
6. 4-9. 6
9.6-12.8
12.8-16
16-24
24-32
32-40
>40
40 x Objective
Number of
Particles
129
95
37









Fields of
View
3
3
3









25 x Objective
Number of
Particles



71
52
41
17
15




Fields of
View



4
4
4
4
4




10 x Objective
Number of
Particles








29
14
2
0
Fields of
View








3
3
3
3
Total Particle in
Equal Field
of View Area
2122
1562
608
257
188
148
61
54
29
14
2
0
10 x Objective Field of View Area = 1. 49 x 106 Pm2

25 x Objective Field of View Area = 3. 09 x 10S Pm2

40 x Objective Field of View Area = 9. 06 x 104 pm2
                                           -120-
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1
1

I

,

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range,


To calculate the equivalent number of particles in each size
the number of particles is multiplied by the ratio of areas for
each objective magnification. For example, the 3 to 4.5 ym size range


in Table E-7 was measured with a 25X objective. The field of view area
5 2
was 3.09 x 10 ym and a total of 71 particles were counted in 4 fields
of view.
s



1



1



I
I
'?
1

I



I
I

1

counts

The calculations are continued until all of the particle
in each size range are adjusted to the same sample area. The

mass per unit area for a component can now be calculated from this size
distribution data.
Calculating Component Concentrations



The mass per unit area for a single component was calculated
from the size distribution data. The arithmetic mean diameter for each
size interval was converted to the volume of an equivalent sphere and

multipl


where n
is the
of the
in Tabl


per uni
density




ied by the number of particles in that interval:
size interval volume = n. 4 ir / d j

. is the number of particles in the size interval, i and d.
arithmetic mean diameter of the interval. The total volume
component is simply the sum of all the interval volumes as shown
e E-8.
This volume per unit filter area was then converted to mass

t filter area by multiplying the total volume by the component
as shown at the bottom of Table E-8. The densities used for

-121-

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Table E-8.  Mass Per Unit Filter Area Calculations
Size Range, ym
<1
1-2
2-3
3-4.5
4. 5-6. 4
6.4-9.6
9.6-12.8
12.8-16
16-24
24-32
32-40
>40
Mean
Diameter
ym
0.5
1.5
2.5
3.8
5.5
8.0
11.2
14.4
20.0
28.0
36.0
-
Mean
Equivalent
Spherical
Volume, ym
0.07
1.77
8.18
28.7
87.1
268
723
1563
4189
11494
24429
-
Number of
Particles Per
1.49x 106ym2
2122
1562
608
257
188
148
61
54
29
14
2
0

Number of
Particles Per
cm2
142,416
104,832
40, 805
17, 248
12,617
9,933
4,094
3,604
1,946
940
134
0
Sum
Volume, ym3
o
Per cm of
Filter
9. 97 x 103
186 x 103
334 x 103
495 x 103
1. 10 x 106
2. 66 x 106
3. 01 x 106
5. 66 x 106
8. 15 x 106
10. 8 x 106
3. 27 x 106

35. 7 x 106
(Component volume per unit area) x (Component density) = mass per unit area
35. 7 x 10« ym3 . _ _

f) A f., 1 A iU
cm''
6 3 2
v]rg/ym = 96. 4 yg/cm
               -122-
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            calculating mass concentrations for each component are shown in
 9         Table  E-9.
                       tSize distributions were used to calculate mass concentrations
            for  the  following components in each sample:
 I
I
silicates
calcite
 •                     hematite
rubber tire fragments
flyash
coal
cornstarch.
 •           The  remaining components, such as ammonium sulfate and auto exhuast,
             were determined by non-microscopical procedures or were visually
 m           estimated as trace components, such as pollens and magnetic fragments.
<•                    In some of the first samples analyzed, silicates and calcite
             were sized together.  To determine mass concentrations for silicates
•           and  calcite separately, calcite was re-sized and its mass concentration
             was  subtracted from the combined mass concentrations of silicates and
 •           calcite.
 •                    Some filter samples were so heavily loaded that it was impossi-
             ble  to perform particle size and concentration measurements.  Therefore,
 •           the  concentrations of certain components for these four samples were
             estimated (Fire Department #10:  7/15/77, 10/25/77, 12/12/77 and duplicate
w           sample C).
•>                    In some samples the opaque, carbonaceous particles obscured
             the  view of minerals.  Therefore, a number of components, silicates,
W           calcite, hematite and flyash, were sized on the low temperature ash
             residue.
™                                           -123-
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                 Table E-9.  Approximate Densities of Particle Components
MINERALS
quartz and feldspars
calcite
others
clays
humus
cement
hematite
2.7
2.7
2.7
2.7
1.9
1.4
2.0
5.2
              Components
Density, pg/cm
                                                                               -3
MOBILE SOURCES

   glassy flyash
   coal fragments
   oil soot
   partially combusted coal
   incinerator flyash
   partially combusted fragments

NON-SPECIFIC (COMBUSTION) SOURCES

   fine  carbonaceous
   ammonium sulfate

BIOLOGICALS

   pollens, spores, conidia
   plant parts
   starch
   insect parts

MISCELLANEOUS

   stack iron oxides
   magnetic  fragments
   metal fragments
   salt
   sludge
       1.1
       1.5
       1.1
       1. 1
       1.9
       1.0
       1.7
       1.8
       1.1
       1.2
       1.5
       1.5
       5.2
       7.0
       6.5
       2.2
       1.5
                                       -124-
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 I
 t
                       All  of the sized components  were measured by Feret's diameter.
 £          With this  statistical  diameter particles  can be calculated as  equivalent
f             spherical  volumes even with aspect ratios of 6:1.   The highest aspect
             ratio components were rubber tire particles (aspect ratio  4:1)  and mica
 I
flakes (aspect ratio   10:1).   Because the mica flakes were a trace
component, their high aspect ratio is insignificant.
 I
             Inorganic Components
 •                     The  total  inorganic  content was  set equal  to the low temperature
 m           ash residue.   The  ash residue  components  include:

                            *silicates
                            |*calcite
                             mica
                             clays
                            |*coal  flyash
                            *hematite
                             magnetic fragments
I                             slag
                           **ammonium sulfate

H           Components marked  with an  asterisk,  *, were generally major or minor
             components that were  counted and sized microscopically.   The other
 I           inorganic components  were  usually present  at trace levels estimated to
 _           be significantly below 0.5%.  In fact, the collective weight percentage
 ™           of all  the trace concentration,  inorganic  components were estimated to be
 •           less than 0.5%.  Therefore,  the  sum  of the major and minor inorganic
             components were set equal  to the LTA residue.   Then  the  component mass
 £           ratios  from the size  and count data  were  used to calculate percentages for
             fthe inorganic  components.  An  example calculation  is shown in Table E-10.
             Ammonium sulfate,  marked with  a  double asterisk, was determined by a
V           direct  chemical procedure  as described earlier.
                                           -125-
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Table E-10.  Calculation of Inorganic Components Concentrations
Components
Silicates
Calcite
Glassy Flyash
Hematite
Clays, Humus
Magnetic Fragments
Slag
Mica
Totals
LTA Residue = 59%
(% LTA Residue) less (%
Mass Ratios
Normalized
yg/m"2 to 100%
295 73. 2
93.5 23.2
-
14.5 3.6
-
-
-
-
403lOyg/m-2 100.0%

visually estimated components) = (c
(59%) - (3%)
Visually
Estimated
Weight Percent
-
-
-
<0.5
3
<0. 5
-
<0. 5
3%

& major and minor
(56%)
Component
Weight Percent
41
13
<0. 5
2.0
3
<0. 5
-
<0. 5
59%

inorganic components)
                           -126-
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            Organic Components
 I
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                      The calculation of organic component concentrations follows a
             similar approach to that used for the inorganic components.  The organic
^          components include:
  humus
**carbonaceous tailpipe exhaust
 *rubber tire fragments
 *coal fragments
**oil soot
  fine carbonaceous particles
 *cornstarch
  pollens, spores and conidia
  plant parts
  insect parts.
            The components marked with an asterisk were sized, counted and normalized
            to the adjusted LTA LOSS.  The LTA LOSS includes ammonium sulfate and
m          ammonium nitrate which sublime during ashing.  Therefore, the concen-
^          tration for ammonium sulfate was subtracted from the LTA LOSS to obtain
•          an adjusted LTA LOSS which is equal to the organic content.
•                    Those organic components not marked with an asterisk were trace
            components whose combined concentrations were usually less than 0.5%.
•          Components marked with a double asterisk were determined by measuring
            elemental tracers and calculating the total concentrations from source
w          coefficient factors.  Lead was used for carbonaceous auto exhaust and
•          vanadium was used for oil soot.  The reasons for this elemental approach
            for auto exhuast and oil soot were explained in the Elemental Analysis
I          section.
_                    Table E-ll shows a sample calculation for organic components.
™          This method of calculating the organic and inorganic component concentrations
•                                          -127-

I
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                       Table E-ll.  Calculations of Organic Components
                                         Concentrations
Components
Carbonaceous tailpipe exhaust
Rubber tire fragments
Coal fragments
Oil soot
Fine carbonaceous particles
Cornstaich
Pollens, spares, conidia
Plant parts
Insect parts
Totals
IJg/cm"

48.4
4.0






52.4
Mass Ratios
Normalize to 100%

92.3
7.7






100
Visually EST.
Wt. Pet.
1*


2*
2

0.5
2
0.5
47
Components
Wt. Pet.
1
12
1
2
2
0.5
0.5
2
0.5
20%
LTA Loss = 41%
(NH4)2 SO4 content = 21%
Organic content = 20%
* Determined through elemental analyses.
                                             -128-
-------
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             was  used  for all  samples  except three samples  from Fire Department #10
•           which  were  too  heavily loaded  to perform particle counting.   The results
—           for  these samples were estimated visually.
             Microscopical Data Sheets
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          The analytical results for the eighteen hi-vol samples are
reported on data forms with samples grouped by day.
                                -129-
-------
                   REPORT ON PARTICLE IDENTIFICATION
Project C6409 - Baltimore TS? Study
Date:         6/9/77
SITE:
TSP (yg/m3):
% ASKABLE:

COMPONENTS
MINERALS
silicates
calcite
mica
clays, humus
•
MOBILE SOURCES
carbonaceous tailpipe exhaust
rubber tire fragments
COMBUSTION SOURCES
glassy flyash
coal fragments
oil soot
NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallized sulfates
INDUSTRIAL EMISSIONS
cornstarch
hematite
magnetic fragments
slag
BIOLOGICALS
pollens, spores, conidia
plant parts
insect parts
FD #10
63
41%

NORMALIZED
CONCENTRATION
Weight %

,,
41
13
<0.5
3
1
12
<0.5
1
2
r\
21
<0.5
2
-------
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                   REPORT ON PARTICLE IDENTIFICATION
Project C6409 - Baltimore TSP Study

Date:         6/21/77
SITE:
TSP (Mg/m3):
% ASKABLE:

COMPONENTS
t
MINERALS
silicates
calcite
mica
clays, humus
MOBILE SOURCES
carbonaceous tailpipe exhaust
rubber tire, fragments
COMBUSTION SOURCES
glassy flyash
coal fragments
oil soot
NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallized sulfates
INDUSTRIAL EMISSION'S
cornstarch
hematite
magnetic fragments
slag
BIOLOGICALS
pollens, spores, conidia
plant parts
insect parts
FD #22
60
44%

NORMALIZED
CONCENTRATION
Weight %

52
2
<0.5
<0.5
1
14
<0.5
2
1
<0.5
24
<0.5
1
<0.5
<0.5




NORMALIZED NORMALIZED
CONCENTRATION CONLl^TRAi'IOM
Weight % Weight %




f
i


                                    -131-
-------
                   REPORT ON PARTICLE IDENTIFICATION
Project C6409 - Baltimore TSP Study
Date:         7/15/77

SITE: FD #10
TSP (yg/ra3): 221
% ASHABLE: 29%

NORMALIZED
COMPONENTS CONCENTRATION
Weight %
MINERALS
silicates 40
calcite 30
mica • 
-------
1
1
1
1
1
1
1
1
1
t
1
1
1
1
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REPORT ON PARTICLE IDENTIFICATION
Project C6409 - Baltimore TS? Study
Date: 8/2/77

SITE:
TSP (yg/m3):
% ASHABLE:
COMPONENTS
MINERALS
silicates
calcite
mica
clays, humus
MOBILE SOURCES
carbonaceous tailpipe exhaust
rubber tire fragments
COMBUSTION SOURCES
glassy flyash
coal fragments
oil soot
NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallized sulfates
INDUSTRIAL EMISSIONS
corns tarch
hematite
magnetic fragments
slag
BIOLOCICALS
pollens, spores, conidia
plant parts
insect parts
Fort McHenry
154
65%

NORMALIZED NORMALIZED NORMALIZED
CONCENTRATION CONCENTRATION CONCENTRATl ON
Weight % Weight % Weight %
t
1
23 i
5
<0.5 i
7 i
0.5
r :
1
<"•• ^ '
u . J 1
1
1
15
41
2
<0.5
<0.5
<0.5
1
'
1
-133-
-------
                     REPORT  ON  PARTICLE  IDENTIFICATION
  Project C6409 - Baltimore TSP  Study
  Date:          9/19/77
SITE:
TSP (yg/m3):

% ASKABLE:


COMPONENTS

MINERALS
silicates
calcite
mica
clays, humus
MOBILE SOURCES
carbonaceous tailpipe exhaust
rubber tire fragments
COMBUSTION SOURCES
glassy flyash
coal fragments
oil soot

NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallized sulfates
INDUSTRIAL EMISSIONS
cornstarch
FD #22
108

42%

NORMALIZED
CONCENTRATION
Weight %

45
7
<0.5
4

1
11

1
3
2


2
22

1

i


1
NORMALIZED NORMALIZED
CONCENTRATION CONCENTRATION
Weight % Weight 7,





\
\




\
\
\

\
\

  hematite
  magnetic fragments
  slag

BIOLOGICALS
  pollens, .snores,  conidia
  plant parts
  insect parts
 1
<0.5
<0.5
                                        -134-
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1
1
1
1
1
1
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1
1
1
1
1
1
1
1
1
1
REPORT ON PARTICLE IDENTIFICATION
Project C6409 - Baltimore TSP Study
Date: 9/25/77

SITE:
TSP (Ug/m3):
% ASKABLE:
COMPONENTS
MINERALS
silicates
calcite
mica
clays, humus
MOBILE SOURCES
carbonaceous tailpipe exhaust
rubber tire fragments
COMBUSTION SOURCES
glassy f]yash
coal fragments
oil soot
NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallize.d sulfates
INDUSTRIAL EMISSIONS
corns tarch
hematite
magnetic fragments
slag
BIOLOGICALS
pollens, spores, conidia
plant parts
insect parts
FD #10 FD #22 Fort McHenry
51 38 39
39% 50% 51%

:
NORMALIZED NORMALIZED NORMALIZED
CONCENTRATION CONCENTRATION j CUNCENTI'AT !0;>;
Weight % Weight % Wei.;ht «'
35 37 24
10 1 4
<0.5 <0.5 <0.5
1 1 1
1 1 1
11 12 6
<0.5 1 <0.5
2 2 1
329
<0.5 <0.5 <0.5
36 40 50
<0.5 1 <0.5
<0.5 1 2
<0.5 <0.5 <0.5
<0.5 1 1
<0.5 <0.5 <0.5
<0.5 1 <0.5
-135-
-------
                   REPORT ON PARTICLE IDENTIFICATION
Project C6A09 - Baltimore TSP Study
Date:         10/25/77
SITE:
TSP (yg/m3):
% ASKABLE:


COMPONENTS

MINERALS
silicates
calcite
mica
clays, humus

MOBlLi: SOURCES
carbonaceous tailpipe exhaust
rubber tire fragments
COMBUSTION SOURCES
glassy flyash
coal fragments
oil soot

NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallized sulfates
INDUSTRIAL EMISSIONS
cornstarch
hematite
magnetic fragments
slag

BIOLOGICALS
pollens, spores, conidia
plant parts
insect parts
FD #10
306
23%

NORMALIZED
CONCENTRATION
Weight %

17
25
<0.5
2


,
3

<0.5
3
1


3
13

<0.5
<0.5
<0.5
31


<0.5
<0.5
<0.5
Fort McHenrv
118
48%

NORMALIZED NORMALIZED
CONCENTRATION CONCENTR/ VTON
Weight % | Weight %

44
2
<0.5
*
i
1
i
7 i
i
<0.5
8
i ;
i
i
5
13 ;

8 i
1
<0.5 ' !
<0.5
! i
! !
-------
                   REPORT ON PARTICLE IDENTIFICATION
Project C6409 - Baltimore TSP Study
Date:         11/24/77
             SITE:
                                  FD  #10
FD #22
Fort McHenry
TSP (Mg/m3):
% ASKABLE:

COMPONENTS
MINERALS
silicates
calcite
mica
clays, humus
MOBILE SOURCES
carbonaceous tailpipe exhaust
rubber tire fragments
COMBUSTION SOURCES
glassy flyash
coal fragments
oil soot
NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallized sulfates
42
45%

NORMALIZED
CONCENTRATION
Weight %

32
4
<0.5
4
2
11
1
5
2
2
35
52 41
47% 60%

NORMALIZED NORMALIZED
CONCENTRATION COXCENTRA'P TON
Weight % Weight r/
t
1
35 32
4 2
<0.5 <0.5
1 ! 1
2 i 2
24 14
!
<0.5 <0.5
1 2
2 2
1 ! 2
32 ' 45
INDUSTRIAL EMISSIONS
corns tarch
hematite


0.5
i 2
magnetic fragments
slag
BIOLOGICALS
pollens, snores,
plant parts
insect parts


conidia



<0.5
<0.5
<0.5 ; <0.5


<0.5


<0.5
<0.5 <0.5
<0.5
<0.5

1
<0.5
<0.5


<0.5
<0.5
<0.5
                                    -137-
-------
                   REPORT ON PARTICLE IDENTIFICATION
Project C6409 - Baltimore TSP Study
Date:         12/12/77
SITE:
TSP (Ug/ra3):
% ASKABLE:

COMPONENTS
MINERALS
silicates
calcite
mica
clays, humus
MOBILE SOURCES
carbonaceous tailpipe exhaust
rubber tire fragments
COMBUSTION SOURCES
glassy flyash
coal fragments
oil soot
NON-SPECIFIC COMBUSTION SOURCES
fine carbonaceous particles
recrystallizcd suifates
INDUSTRIAL EMISSIONS
cornstarch
hematite
magnetic fragments
slag
BIOLOGICALS
pollens, spores, conidia
plant parts
insect parts
FD #10
169
31%

NORMALIZED
CONCENTRATION
Weight %

30
40
<0.5
<0.5
1
8
<0.5
1
1
6
13
<0.5
0.5
<0.5
<0.5
<0.5
<0.5
FD #22
129
40%

NORMALIZED
CONCENTRATION
Weight %

37
14
<0.5
5
1
10
1
1
2
5
17
1
2
<0.5
<0.5
<0.5
<0.5
Fort McHenry
85
51%

NORMALIZED
CONCENTRATION
Weight %

33
14
<0.5
1
1
12
1
2
4
3
25
5
<0.5
<0.5
<0.5
<0.5
<0.5
                                     -138-
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                                 APPENDIX F

             ORIENTATION OF POINT SOURCES TO HI-VOL SAMPLERS
     The first three tables in this appendix identify the point sources
which are upwind of each of three Baltimore hi-vol sites (namely,
Fire Dept #22, Fire Dept #10, and Fort McHenry) for each of 16 sectors.
The percentage of the time and the average wind speed with which the wind
was from each sector is also listed for each of the 9 days for which
particulate samples are analyzed in this report.   A fourth table identifies
the names of the point sources.
                                  -139-
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                                                  TABLE F-l
Site: Fire Department #22 Monitor
                                                                    Percent Occurrence WD / Average WS for WO **
                                                                                                                 i
                                         Date;    6/9/77   6/21    7/15   8/2      9/19   9/25   10/25    11/24
               2/12
               n
               Daily Average Wind Speed (mph);      g. 2
                                                         6.3
                 2.0
                                                                         _2.8
                  3.3
                6.5
               3.2
                4.3
Wind
Direction
                   Major Sources Upwind*
                       (See Table F-4)
% Calm
  0
Calm
 0
% Calm
  13
Calm
 4
Calm
 0
Calm
 0
Calm
 8
Calm
 13
        Cain
   N
            77, 101
                                                                    0.1
                                                                                                         17
                                                                                                           10.8
                                                                                                              / 5^C
                                                                                                              7
   NNE
            80, 72, 92
                                                                    1.0
                                                                                          7.0
   NE
            83, 72, 107, 94, 20, 44, 45,  39, 41,
            42, 40
                                                                                       42
                                                                                           5.7
   ENE
            86, 103, 107,  18, 31, 10, 17, 44, 41,
            43
                                                                                       50
                                                                   1.0
                                         5.5
           93, 69
                                                                    3.0
                                                                                          4.0
   ESE
            56, 30, 115,  130
                                                                17
                                                                   2.3
                                  4.5
   SE
          57, 70,  109, 74, 16, 114,  128, 118, 126
          132, 113,  119,  129, 127, 116,  112, 123,
          121, 124, 24, 111, 120, 122, 1,25, 131, 117
                                                                  17
                   3.5
                   1.0
   SSE
           78, 76, 2,  1, 9
                                                                                13
                                                                   1.5
                                  3.7
           65, 88, 58,  66, 60, 59, 98, 82, 100,
           96, 8, 68,  13, 62, 6, 3
                                                                13
                                                                    2.0
                                                                                  2.5
   ssw
          79, 63,  12, 4
                                                                    6.0
                                                                                                                 13
                                                                                                          4.0
   sw
           108, 61, 52,  99, 71, 110, 21,  12, 11,
           5, 7
                                                                                21
                                                                                   3.6
                                                          5.0
   wsw
           108, 73, 87,  84, 61, 99, 51, 21, 29,
           32, 22, 14, 46, 47
                                                                                13
                                                                                    2.
                                                                                                          3. O
   w
            106, 85, 49,  89, 54, 91, 90, 75, 105,
            102, 32, 14,  48
                                                           2.5
                                                                                 13
                                  '2.3
                                                        33
                                           i. 4
   WNW
           95, 53, 97,  67, 104, 15, 23,  33, 34
                                                                                 17
                                                                                  '6.5
                                                          3.0
   NW
            50, 53, 64,  27, 15, 26, 25, 35, 36, 37,
            38
                                                         13
                                                           8.3
                                   4.0
                                            7.0
   NNW
           101, 19, 28
                                                                                                        13
                                                                                                         '11.
 * The monitor to source distance generally increases from left to right.
** WD is direction from which the wind is blowing. WS is the wind speed in miles per hour (mph).
 Note: Sun and Chesapeake WS and WD are used with the data gaps filled in by Baltimore -Washington International Airport
       (BWI) data. Often BWI WS are higher than Sun and Chesapeake WS by about a factor of 2.  There is generally
       good agreement between BWI and Sun and Chesapeake WD. Sun and Chesapeake WS and WD are hourly
       averages. BWI WS and WD are instantaneous values.
                                                        -140-
                                                                                                                   «|
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                                                  TABLE F-2
Site: Fire Department #10 Monitor
                                                                     Percent Occurrence WD / Average WS for WD **
                                         Date:
                                                  6/9/77   6/21   7/15    8/2      9/19   9/25   10/25    11/24
                                                                                                     12/12
               Daily Average Wind Speed (mph):     6, 2
                                                      -2*0-
                                 JLi.
                                                      JL6.
Wind
Direction
        Major Sources Upwind*
             (See Table F-4)
% Calm
  0
Calm
 0
Calm
13
Calm
 4
Calm
 0
Calm
 0
* Calm
   8
a Calm
  13
Call
17
   N
            65, 78, 56, 86, 83, 77, 80, 72, 92,
            101
                                                         0.1
                                                                                              17
                                                  5.0
                                                10.8
   NNE
             76, 109, 70, 57, 93, 103, 69, 107,
             94
   NE
 74, 18, 31, 10,  20, 44, 39, 41,  45
 42, 43, 40
                                                                                         42.
                                         '5.7
   ENE
            30, 17, 41,  43, 40
                                                     1.5
                                                        1.0
                                                                                         50
                                           6.5
            16, 30, 115,  130
   ESE
 16, 24, 111,  112,  123, 113, 119, 129,
 114, 116, 117, 118,  126, 132, 120, 12;
 125, 121, 124, 127,  128, 131
                                                                  17
                 '2.3
                                                                                                 21
                                                  3.6
   SE
                                                                  17
            Zip
                                                                    3.5
  SSE
            98, 82, 62,  68, 2, 1,  9
                                       13
                                       '4.7
                   1.5
            82, 62, 68, 6, 3, 98
                                       17
                13
                                                    6.8
                                                        2.0
   SSW
            88, 58, 59,  100, 96, 8,  13, 4
                                      21
                                                     6.8
                                                        6.0
  SW
            88, 58,  60, 66, 4, 12,  11, 5, 7
  wsw
            63, 22,  5, 47
                                         6.0
  W
            79, 71,  110, 21, 29, 32,  14, 46, 48
  WNW
            79, 52,  99, 51, 84,  89,  54, 75, 102,
            105, 14, 23, 33
                                                                                                3.0
  NW
37, 38,  61, 73, 52, 84,  87, 89, 49, 91,
97, 90,  104, 67, 15, 25, 26, 35, 34,
36
                                                                                                           '7.0
  NNW
            73,  108, 106, 85, 95,  50,  53, 64, 27,
            19,  28
                                                                                              13
                                                                                                            11.
 *  The monitor to source distance generally increases from left to right.
**  WD is direction from which the wind is blowing.  WS is the wind speed in miles per hour (mph).
  Note: Sun and Chesapeake WS and WD are used with the data gaps filled in by Baltimore -Washington International Airport
       (BWI) data.  Often BWI WS are higher than Sun and Chesapeake WS by about a factor of 2.  There is generfllv
        good agreement between BWI and Sun and Chesapeake WD. Sun and Chesapeake WS and WD are hourly
        averages. BWI WS  and WD are instantaneous values.
                                                            -141-
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                                                  TABLE F-3
Site:  Fort McHenry Monitor
                                                                    Percent Occurrence WD / Average WS for WD **
                                         Date:    6/9/77   6/21    7/15   8/2      9/19   9/25   10/25    11/24  12/1
                 *
               Daily Average W4nd Speed (mph):      5. 2
                                               6.3
               2.0
        2.8
                                                                       3.5
                6.5
                3.2
                4.3
Wind
Direction
         Major Sources Upwind*
             (See Table F-4)
Calm
0
Calm
 0
Calm
13
Calm
 4
Calm
 0
Calm
 0
Calm
 8
Calm
 13
'/a Calm
   N
            108, 77, 101
                                                                                                         17
                                                                                         5.0
                                                        10.8
   NNE
           86, 83, 77, 80, 72, 92
   NE
            56, 86, 103, 93,  107, 94, 20,  44, 39,
            41, 42, 40,  45
                                                                             42
                                                                                           5.7
   ENE
           69, 18, 31, 10, 17, 44, 41, 43
                                         1.5
                                                                             50
                                                                                           6.5
           109, 57, 70,  74
                                                                                      29
                                                                                           4.0
                                                                                        2.9
   ESE
78, 76, 74, 30, 16,  115,  130, 128, 118,
126, 132,  113, 119, 129,  112,  123, 111,
114	
                                                                           5.0
                                                                                                   3.6
   SE
                                                                                             /A
   SSE
           65, 98, 82,  68, 2, 1,  9
                                       13
                                         4.7
                                                                           ...
                                                                                      13
                                               '6.0
           88, 66, 58, 60, 59,  100, 96r 8, 13,  62,
           6, 3
                                      17
                                                   '6.8
                       13
                                                                            1.4
                                                                                                      38
   ssw
79, 63, 4, 12
                                                 21
                                                   '6.8
                                                                                                                 13
   sw
           71, 12, 5,  7, 11
                                                                 5.0
                                                        5.0
   wsw
           52, 99, 110,  21, 29, 22, 47
                                                   '6.0
                                                               '3.0
                                                       5.0
   w
           61, 73, 84,  51, 89, 54, 75, 102, 32, 14,
           46, 48
                                                              17
                                                                1.1
                                              25
                                       33
                                               '5.0
                                        5.4
   WNW
           73, 87, 49,  89, 91, 90, 67, 104, 105,
           23, 33, 34
                                                                                                8.0
   NW
           106, 85, 95,  53, 97, 64, 15, 25, 26, 35
           36, 37, 38
                                        '&. 5
                                                              13
                         3.7
                                                                                                           7.0
   NNW
           108, 50, 27,  19, 28
                                                                                              13
                                                                                                [1.7
  *  The monitor to source distance generally increases from left to right.
 **  WD is direction from which the wind is blowing. WS is the wind speed in miles per hour (mph).
  Note:  Sun and Chesapeake WS and WD are used with the  data gaps filled in by Baltimore-Washington International Airport
         (BWI) data. Often BWI WS are higher than Sun and Chesapeake WS by about a factor of 2.  There is generally
         good agreement between BWI and Sun and Chesapeake WD. Sun and Chesapeake WS and WD are hourly
         averages. BWI WS and WD are instantaneous values.
                                                          -142-
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TABLE F-4
    SOURCE
    r
BG&E  (Wagner)
Kennecott
Crownsville
Exxon Chemical
Md. House of Correction
Diamond Shamrock
D. C. Children's Center
Amerada Hess
U.S.  Naval Academy
U.S.  Coast Guard
National Security Agency
Fort  Meade
U.S.  Agri-Chem
Spring Grove
Mt. Wilson St. Hospital
BG&E  (Riverside)
BG&E  (Crane)
Eastern Stainless Steel
Harry T. Campbell - Texas
Harry T. Campbell - White Marsh
Carl ing Brewing Co,
Joseph Seagram
Harry T. Campbell - Harriot
Arundel Corp. - Canal Road
Rosewood St. Hospital
Sweetheart Cup .
Federal Paperboard
Baltimore Bio Lab
Majestic Distillers
Stemmers Run JHS
Back  River STP
Concorde Yachts
Springfield St. Hospital
Lehigh Portland Cement
Congo leum Industries
Southern States - BA
Southern States - YO
Taneytown Grain
Bata Shoe Inc.
J.M. Huber
BG&E (Ferryman)
York Bldg. Products
Aberdeen Proving Ground
Edgewood Arsenal
 avis Quarry Inc.
Simkins Industries
General Electric
Glenelg Manor Association
                                 _]43_
                            SOURCE NUMBER
                                    ' ~  "
                                  1
                                  2
                                  3
                                  4
                                  5
                                  6
                                  7
                                  8
                                  9
                                 10
                                 11
                                 12
                                 13
                                 14
                                 15
                                 16
                                 17
                                 18
                                 19
                                 20
                                 21
                                 22
                                 23
                                 2'*
                                 25
                                 26
                                 27
                                 28
                                 29
                                 30
                                 31
                                 32
                                 33
                                 34
                                 35
                                 36
                                 37
                                 38
                                 39
                                40
                                41
                                42
                                43
                                44
                                45
                                46
                                47
                                48
                            (Continued)
-------
                           TABUE F-4 (Continued)
    SOURCE

BG&E (Terminal)
BG&E (Spring Garden)
BG&E (Westport)
BG&E (Gould)
Md. Penitentiary
Montgomery Ward & Co.
Exxon Company
National Brewing Co.
GAP Corporation
Chevron Asphalt Co.
FMC Corp. - Org. Chem,
Olin Matheson
Allied Chemical
Davison Chemical
General Refractories
Johns Hopkins University
Agrico Chemical Company
Continental Oil
Abex Corporation
Glidden-Durkee (Hawkins Point)
Glidden-Durkee (Eastern)
Lever Brothers
Arundel Corporation
Torake Aluminum
Proctor & Gamble
Federal Yeast Corporation
Maryland Glass Corporation
Southern Industries
Monarch Rubber Co.
National Gypsum Co.
Md. Shipbuilding & Drydock
BG&E (Philadelphia Road)
Bethle-hem Steel - Key Highway
American Oil Company
Schlude rberg-Kurdle
Carr-Lowery Glass
Lock (GE) Insulator
F&M Schaefer Brewing
American Sugar
M&T Chemical
Eastern Products
Koppers (Bush Street)
Koppers (Scott Street)
Arraco Steel
GMAD
Pulaski Highway Incinerator
City Jail
American Oil
Dept. of General Services
Shell Oil
Inter Briquetting Corp.
Hess Oil
-144-
  SOURCS NUMBER

      49
      50
      51
      52
      53
      54
      55
      56
      57
      58
      59
      60
      61
      62
      63
      64
      65
      66
      67
      68
      69
      70
      71
      72
      73
      74
      75
      76
      77
      78
      79
      80
      81
      82
      83
      84
      85
      86
      87
      83
      89
      90
      91
      92
      93
      94
      95
      96
      97
      98
      99
    100
(Continued)
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                            TABLE F-4 (Concluded)


    SOURCE                                              SOURCE NUMBER
Morgan University                                            101
MTA                                                          102
Baltimore City Hospital                                      103
Luthsm Hospital                                             104
A & P                                                        105
Philadelphia Quartz                                          106
Fort Holabird                                                107
J. S. Young Co.                                              108
American Standard                                            109
Reedbird Ave. Incinerator                                    110
Beth Steel - Penwood                                         111
Beth Steel - B Street                                        112
Beth Steet - 7th Street                                      113
Beth Steel - Tin Mill                                        im
Beth Steel - Hot Strip Mill                                  115
Beth Steel - 02 Boiler House                                 116
Beth Steel - #1 Boiler House                                 117
3eth Steel - Misc. Fuel Burning                              118
Beth Steel - BOF                                             119
Beth Steel - Coke Handling                                   120
Beth Steel - Coke Handling                                   121
Beth Steel - Ore Handling                                    122
Beth Steel - Blast Furnace                                   123
Beth Steel - Coke Battery                                    12U
Beth Steel - Sintering Plant                                 125
Beth Steel - Open Hearth                                     126
Beth Steel - Plate Mill                                      127
Beth Steel - Soaking Pits                                  V123
Beth Steel - Sheet Mill                                      129
Beth Steel - Hot Strip Mill                                  130
Beth Steel - Glaus Sulfur Recovery                           131
Beth Steel - Misc. Processes -                                132
                                -145-
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                                APPENDIX G

                  WIND DIRECTIONS ON HI-VOL SAMPLING DAYS
     The 24-hour resultant wind direction, determined as the vector mean
of 24 hourly values, and the hourly deviation ot the wind from the
resultant wind are listed for 9 days on which hi-vol filter samples
were analyzed in this report.  A wind rose showing the frequency of
occurrence of 16 wind direction sectors on each sampling day is also
presented following the  listings.
                                   -146-
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                    TABLE G-l.  HOURLY WIND DEVIATIONS
lU-. -,,;'^-7i
 oo

 o\

 02

.02

 Of

 o?



 ol

 0?

 01

 10 ..

 II  .

 12  .

 13  .
    iff

    17

    I*
    I? 	

    10




    22
                       . WP
              :£T.r
             - 23. r
                               -147-
                                              02

                                              02
                                              ol

                                              o?
                                              I/

                                              12

                                              13

                                              it
17

12



to

11

22
                                                            . WP
                                                            C

                                                            6
                                                           m
                                                              (continued)
-------
TABLE G-l. HOURLY WIND DEVIATIONS (continued)
fW
i> i r "
4va.W0: 270'
00
CM
02
03
Of
Of
Ol
0?
0?
10
11
12
IS
IV-
/£
17
1?
to
11
22
11
Dourly De/ietTto*
-£rt7« >W. WP

?2.JT
22.^
12. C
22.^
-zz.r
22. r
.-«2.r
-«.r
"32. r
-22.^
- -22. r
- 22. /
- 22. j"
** ^f C"
— (L ^"*

'-"'•*"
-/L
0
^^.£
tiS
i*.f
^
^ \
"*"" ^7,',!'-
00
01
02
oS
ot
^
07
0?
o?
10
II
12
IS
IV-
Iff
17
n
20
•w
22
11
/W! fa^'«
Jrt7w /jve. WP

-,/
-2-
-^
- '-i". r
-z^
-«?
-^
-6?
- KS
" ,^
-vsr
--zJ
- y-.-
?!,-
•7
11.
%s
S7
?7.i~
«7
<^























                                                 (continued)
                 -148-
-------
TABLE G-l. HOURLY WIND DEVIATIONS (continued)


1- 1
!.3^g: "e.-'ft rrr.
1 ' ' « ,
• 00
0\
m 02
0$
1
• of
1 "
0?
1
10
•
12 .
1 '*
If
• £
1
• J*
1
• 2
1A 3"
^—
. n..~
ri t~
- rl
^^
n ' - -' " ' ~
01
01
OS
°*s
ol
01
01
10
12
If
If
17
i?
n
22
>w; fe«u
*^7A«.w»
'/0.^
'**
12
i:
12
12
11
12
-!*.£
12.
-10, r
1 «^ . j











(continued)
1
1
• -149-
1
-------
         TABLE G-l.  HOURLY WIND DEVIATIONS (continued)

01
02
03
of
o7
o?
II
12

it
(7
I*
P
10
•Z./
22
                   . WP
             - /r/
             /r/
              6
               C
              Z7
00

02

ot
                                         0?
J/
12
13
                                         17

                                         P
                                         to
                                         tl
                                         22
C/
2/
                                                        2/
                                                        /.S"
                                                         C

                                                         C
                                                            (continued)
                            -150-
-------
• TABLE G-l. HOURLY WIND DEVIATIONS (concluded)

JJ
TI 0 M »
~ ,
|!-p"n2* P"c '-' ?"^7
<' wn -r
'"'V&.r'Ul i i '
_ 00
1
02 _
• °^
0*t
• ^r
1 "
0?
1
™ {0 ...
1
• 12
1
• It
| 16
17
I J? 	
n ...
1 20
122
^7 ^

fU^ toirfej
-irt?« ^v«rwp


-v?.-"
. 
-------
                                                     CM

                                                      
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I....,,,.......,.,,,,..,.,,... I.... I. • • .If.... I.... I......... I.... I.  .. I
                                                                                                  a
                                                                                                  Q

                                                                                                  3


                                                                                                  ||

                                                                                                  4) ^




                                                                                                  I "
                                                                                                  u oT
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                                                                                                  H
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                                       -153-
-------
                                                                      a
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                                                                     3 7
                                                                       9*
                                                                      rt
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                                                                      S


                                                                      1 1
                                                                      •—  01

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                                                                       I
                 .If,...,...,, —,....,....,...,,,
                  -154-
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rt  e
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Q
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-155-
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Figure G-9. Sun and Chesapeake, and BWI Airport Data,
           December 12, 1977 (17% calm)
                -156-
-------