EPA-450/3-76-003
January 1976
                   DEVELOPMENT
            OF A METHODOLOGY
      AND EMISSION INVENTORY
             FOR FUGITIVE DUST
              FOR THE REGIONAL
          AIR POLLUTION STUDY
       U.S. ENVIRONMENTAL PROTECTION AGENCY
           Office of Air and Waste Management
         Office of Air Quality Planning and Standards
        Research Triangle Park, North Carolina 27711

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                           EPA-450/3-76-003
        DEVELOPMENT
    OF A METHODOLOGY
AND EMISSION INVENTORY
    FOR FUGITIVE DUST
    FOR THE REGIONAL
  AIR POLLUTION STUDY
      Dr. Chaltcu Cowherd ami Ms. Christine (Jiienlher

           Midwest Research Iii.stitiiti*
             125 Volker Boulc\ard
           Kansas Cilj. Missouri1 61110

            Contract .No. 68-02-20-1 0
        EPA Project Officer: Charles C. .Masser
               Prepared for

       ENVIROMEiNTAL PROTECTION AGENCY
         Office of Air and Waste Management
       Office of Air Quality Planning and Standards
      Research Triangle Park, North Carolina 277 1 1

               Januarv 1976

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This report is issued by the Environmental Protection Agency to report
technical data of interest to a limited number of readers.  Copies are
available free of charge to Federal employees,  current contractors and
grantees, and nonprofit organizations - as supplies permit - from the
Air Pollution  Technical Information Center, Environmental Protection
Agency,  Research Triangle Park, North Carolina 27711; or, for a fee,
from the  National Technical Information Service, 5285 Port Rdyal Road,
Springfield, Virginia 22161.
This report was furnished to the Environmental Protection Agency by
Midwest Research Institute,  Kansas City, Missouri 64110,  in fulfillment
of Contract No, 68-02-2040.  The contents of this report are reproduced
herein as received from Midwest Research Institute.  The opinions,
findings, and conclusions expressed are those of the author and not
necessarily those of the Environmental Protection Agency. Mention of
company or product names is not to be considered as an endorsement
by the Environmental Protection Agency.
                Publication No.  EPA-450/3-76-003
                                   11

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                           ACKNOWLEDGEMENTS
     This report was prepared  for  the  Environmental  Protection Agency's
Office of Air Quality  Planning and Standards  under EPA Contract No.  68-
02-2040. Mr. Charles Masser  served as  EPA Project  Officer.

     The program was conducted in  MRI1s  Physical  Sciences Division under
the supervision of Dr. Larry J.  Shannon,  Assistant Director.  Dr.  Chatten
Cowherd, Jr., Project  Leader for MRI,  was assisted by Ms.  Christine
Guenther, Mr. Daniel Nelson, and Mr. Kenneth  Walker.
Approved for:

MIDWEST RESEARCH INSTITUTE

      I
L. J.lJShannon, Assistant Director
Physical Sciences Division
March 22, 1976
                                 iii

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                                  CONTENTS

                                                                     Page

List of Figures	•	   vii

List of Tables	   ix

Summary	   1

Introduction ... 	  ...................   3

Technical Approach	   5

Unpaved Roads	   9

  Grid Source Extent 	   9
  Emission Factor	12
  Temporal Apportioning Factors	12

Agricultural Tilling	15

  Grid Source Extent	15
  Emission Factor	18
  Temporal Apportioning Factors	19

Wind Erosion From Tilled Land	23

  Grid Source Extent	23
  Emission Factor	23
  Temporal Apportioning Factors	.26

Construction ..... 	  29

  Grid Source Extent	29
  Emission Factor	32
  Temporal Apportioning Factors. .......  	  ....32

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                            CONTENTS  (concluded)

                                                                    Page

Aggregate Storage	35

  Grid Source Extent	35
  Emission Factor	37
  Temporal Apportioning Factors	37

Unpaved Airstrips	41

  Grid Source Extent	41
  Emission Factor	  44
  Temporal Apportioning Factors.  	  ......  44

Data Tabulations and Calculated Results	47

Analysis of Results and Estimated Accuracies  	  ....  53

References .......... 	  .........  57

Appendix A - Example Calculations (RAPS Grid  No.  1)	  61

Appendix B - Factors Affecting Atmospheric Transport of Fugitive
               Dust	65
                                    vi

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                                 FIGURES

 [2s.                               Title                              Page

 1    Project Data Flow Diagram	     6

 2    Example of RAPS Grid System Overlay	     7

 3    Procedure for Determination of Annual Vehicle-Miles  on Un-
        paved roads.	    10

 4    Percentage of Total Daily, Weekly, and Annual Vehicle-Miles
        on Unpaved Roads	    13

 5    Procedure for Determination of Annual Acres  of  Land  Tilled  .    16

 6    Soil Silt Content (7o) for RAPS Grid  System	    20

 7    Percentage of Total Daily, Weekly, and Annual Agricultural
        Tilling	    21

 8    Procedure for Determination of Acreage of Exposed  Agri-
        cultural Land	    24

 9    Percentage of Total Daily, Weekly, and Annual Wind Erosion
        from Agricultural Tilled Land	    27

10    Procedure for Determination of Annual Acres  of  Construc-
        tion 	    30

11    Percentage of Total Daily, Weekly, and Annual Construction
        Activity	    33

12    Procedure for Determination of Annual Tons of Aggregate
        Storage	    36
                                 vii

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                           FIGURES  (concluded)

                                   Title                              Page

13    Percentage of Total  Daily, Weekly,  and Annual  Aggregate
        Storage Operations	39

14    Procedure for Determination  of  Annual LTO Cycles on Un-
        paved Airstrips	   42

15    Percentage of Total  Daily, Weekly,  and Annual  LTO Cycles.  .  .   45

16    Simplified Flow  Diagram of Calculation  Procedure for Annual
        Emissions by Grid  .......  	   50

17.   Simplified Flow  Diagram of Calculation  Procedure for Hourly
        Emissions by Grid  	  .........   51

18    Example Computer Output of Annual  Emissions  by Grid	52

B-l   Roughness Heights  for  Various  Surfaces	68

B-2   Relationship Between Particle  Size and  Drift Distance ....   72
                                    vizi

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                                   TABLES

No.                                Title                              Page

 1    County Statistics for Unpaved  Roads	    11

 2    County Breakdown of  Harvested  Acres  by  Crop and Equivalent
        Tillings	    17

 3    Agricultural Operations by  Crop	    18

 4    Seasonal Exposed Acreage by County  	    25

 5    Construction Acreage by County	    31

 6    Annual Acres of Aggregate Stored by  County .  .  .	    38

 7    Data on Unpaved (Turf) Airstrips by  County 	    43

 8    Example Coded  Source Extent and Correction Factor Data ...    48

 9    Hourly Adjustment Example Coded Factors	    49

10    Summary of Annual Emissions by County	    54

11    Estimated Errors for Tabulated Data	    55

B-l   Particle Drift Distances Calculated  from Eq.  (9b)	    71

B-2   Distances to Point of Maximum  Settling, xmax ,  Calculated
        from Eq. (12)	    74
                                    ix

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                                  SUMMARY

     This report outlines the methodology that was used in developing
an hourly fugitive dust emissions inventory for the Metropolitan
St. Louis Air Quality Control Region as part of the Regional Air Pol-
lution Study (RAPS). The inventory encompassed the following source
categories:  (a) unpaved roads, (b) agricultural land tilling, (c) wind
erosion of agricultural land, (d) construction sites, (e) aggregate
storage piles, and (f) unpaved airstrips.

     For each of approximately 2,000 RAPS grid areas, data were compiled
on annual emissions of fugitive dust. This required, in addition to basic
emission factors adjusted for local climatic and surface conditions, an-
nual measures of source extent (vehicle-miles traveled on unpaved roads,
acres of land tilled, etc.) for each grid area. Finally, hourly apportioning
factors were derived to account for emissions variations by hour of the
day, day of the week, and season of the year.

     Results presented in this report include temporal apportioning fac-
tors, county totals of annual source extent and annual emissions for
each source category. Fine particle emissions from fugitive dust sources
in the St. Louis area are found to comprise 39% of the total emissions
of suspended particulates.

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                             INTRODUCTION

     Analysis of the physical relationships between air pollutant source
emissions and ambient air quality is essential to the rational develop-
ment and implementation of pollution abatement and control strategies.
These relationships are predictable through the use of mathematical mod-
els which simulate the processes of atmospheric transport, dispersion,
transformation, and removal of pollutant emissions.

     The Environmental Protection Agency (EPA) is currently sponsoring
a comprehensive regional air pollution study (RAPS) in the St. Louis
Air Quality Control Region (AQCR 70). The primary purpose of the RAPS
program is the development and validation of improved air quality mod-
els. To accomplish this purpose, a major portion of the program effort
is being directed to the preparation of a comprehensive regional data
base.

     Inputs required for model verification include an emissions in-
ventory, meteorological data (wind velocity and temperature) and air
quality data. The spatial and temporal resolution of the RAPS data base
will be far more precise than any previously compiled in an undertaking
of this type. This will permit verification of sophisticated models
which predict air quality distributions on a short term (hourly) basis.

     Recently it has become evident that fugitive dust sources contri-
bute substantially to atmospheric concentrations of total suspended
particulates (TSP) in both urban and rural areas. Failure to incorporate
fugitive source emissions into model-based control strategies has re-
sulted in widespread overestimation of TSP reductions resulting from
the control of conventional point and area sources. Therefore, the need
to include fugitive dust sources in the RAPS emissions inventory is
evident.

     This report presents the results of an investigative program di-
rected to (a) development of a methodology for reporting fugitive dust

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emissions in the RAPS region and (b) compilation of an hourly emissions
inventory of fugitive dust sources for the nearly 2,000 RAPS grid areas.

     The following six categories of fugitive dust sources were addressed
in this study:

     1.-  Unpaved roads;

     2.  Agricultural land tilling;

     3.  Wind erosion of agricultural land;

     4.  Construction sites;

     5.  Aggregate storage piles; and

     6.  Unpaved airstrips.

     Appendix B presents an assessment of factors affecting atmospheric

transport of fugitive dust.

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                          TECHNICAL APPROACH

     Figure 1 traces the methodology that was developed to compile hourly
emissions of fugitive dust by grid. The key data elements in this scheme
are:

     1.  Appropriate annual measures of the extent of each source_type
           within each grid area.

     2.  Emission factors adjusted to climatic conditions and surface
           properties characteristic of the St. Louis area.

     3.  Temporal apportioning factors to account for emissions varia-
           tions by hour of the day, day of the week, and season of the
           year.

The basic emission factors and associated correction terms used in this
study, as shown in Figure 1, were developed by Midwest Research Institute
(MRI) under EPA Contract No. 68-02-0619.!/ These factors refer to dust
particles  smaller than 30 \im in diameter, the approximate effective cut-
off diameter of a standard high-volume particulate sampler (based on a
particle density of 2 to 2.5 g/cnP).

     The initial work objective was to prepare a base map of the RAPS
grid system which incorporated county outlines and river outlines.
United States Geological Survey (USGS) maps with a scale of 1:250,000
were used to locate the RAPS grid system based on Universal Transverse
Mercator (UTM) coordinates designated for Zone 15.

     A reduction of the resulting overlay map is shown in Figure 2. The
overlay was photographically scaled to fit appropriate land use and
street maps of the St. Louis area. A computer-generated plot of the grid
system, supplied by the EPA project officer, was also reduced to the size
of the MRI overlay for comparative purposes.

     The following sections of this report document, for each source
category, the methodology used to obtain annual grid source extent, cor-
rected emission factors, and temporal apportioning factors. Also pre-
sented are key computational results summarized by county, including
extent of fugitive dust sources, temporal apportioning factors, and
annual totals of fugitive dust emissions.
                                   5

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For Each County
Annual for Each County
 DATA

   Miles of Unpaved Roads
   Acres of Harvested Cropland
   Construction Projects
   NEDS Aggregate Listing
   Number of Based Aircraft
 COUNTY SOURCE EXTENT

   Unpaved Roads (vehicle miles)-
   Land Tilling (acres)
   Wind Erosion (acres)
   Construction (acres)
   Aggregate Storage  (tons)
   Unpaved Airstrips (LTO cycles)
For Each Grid
                            Annual for Each Grid i
  SPATIAL  APPORTIONING
  FACTORS
    Land Use
    Grid Area
 GRID  SOURCE EXTENT

   Unpaved Roads (vehicle miles)
   Land Tilling (acres)
   Wind Erosion (acres)
   Consfrucfion (acres)
   Aggregate Storage (tons)
   Unpaved Airstrips (LTO c/cles)
                            Annual for Each Grid
            CORRECTION FACTORS
            • Number of Dry Days per Year (d)
            • Precipitation-Evaporation Index (PE)
            • Duration of Construction Activity (D^
            • Silt Content - Roads, Gravel (sg)
                         - Roads, Dirt (sd)
                         - Tilling (sr)
                         - Airstrips (sa)
            • Vehicle Speed - Roads (Sr)
                           - Airstrips (SQ)
                                 Calculate : EMISSIONS
                                            (tons/yr, Mtons/yr)
                                 • Unpaved Roads
                                 • Land Tilling
                                 • Wind Erosion
                                 • Construction
                                 • Aggregate Storage
                                 • Unpaved Airstrips
                             Hourly for Each Grid '
 TEMPORAL APPORTIONING
 FACTORS

 • Critical Wind Speed
 • Activity
     -Work Cycle
     -Traffic Cycle
    Compute :  EMISSIONS
              (Ib/hr, kg/M
    • Unpaved Roads
    • Land Tilling
    • Wind Erosion
    • Construction
    • Aggregate Storage
    • Unpaved Airstrips
                                       Compute:  EMISSION FACTORS


                                                              *•"•'"•
• Unpaved Roads
    - Grovel
                    d
                   365
    - Dirt


• Land Tilling


• Wind Erosion

• Construction

• Aggregate Storage

• Unpaved Airstrips
                                                              EFd=0.49sdK
                                                                          (30

                                                              EFt=   l.Ut
                                                                   (PE/50)2
EFW = 0.9
EFC=D
EF$ = 0.33

EFa = 0.49sa/Sa.
            \30
                                                                                                                  d
                                                                                                                 365
                                Ib
vehicle mile

     Ib
vehicle mile

Ib/acre


tons/acre

tons/acre

Ib/tons stored
         S
    Ib
LTO cycle
                                       Figure  1.    Project  data  flow diagram

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Figure 2.   Example of RAPS grid system overlay

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                             UNPAVED ROADS

GRID SOURCE EXTENT

     The measure of source extent for fugitive dust emissions from un-
paved roads is vehicle miles traveled (VMT). The basic equation for cal-
culation of annual VMT on unpaved roads in a specified grid area is given
by:

                                  4
                        VMT = 365 £     (ADT.)m.
                                  i = l

where  ADT^  is average daily traffic on unpaved roads with surface type
i , and  m.  is the mileage of unpaved roads with surface type  i  within
the grid area. Road surface types considered in this study were:  (a)
gravel/stone surfaced, (b) soil surfaced, (c) graded and drained, and
(d) unimproved. The procedure used to determine  ADT.  and  m.j.  for each
grid is depicted in Figure 3.

     Traffic volume on unpaved roads within each grid was derived from
appropriate county maps. Traffic flow and road surface-type maps were
obtained from the Illinois Department of Transportation^-' for each of
the seven Illinois counties in the St. Louis AQCR. Highway maps, desig-
nating road surface type, were obtained from the Missouri State Highway
Commission?-' for the counties of Franklin, Jefferson, St. Charles, and
St. Louis in Missouri. Communications with officials of St. Louis City
and County-^' indicated that there are no unpaved roads in the city and
only a few municipal or private unpaved roads in the St. Louis County.

     The RAPS grid system was scaled to each county map, and mileage
and average ADT for each of the four road surface types were manually
obtained for each grid. Table 1 presents a county summary of the mile-
age and ADT for each road type. As indicated, values for ADT on unpaved
roads in the Missouri counties were estimated based on reported ADT val-
ues for Illinois roads differentiated by road surface type.

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    For Illinois Counties:
    By County
     Map of Roads
     by Surface Type
     By County
      Map of ADT
      on Each Road
                        By Grid
 Miles of Road
 • Gravel or Stone
 • Soi I Surfaced
 • Graded & Drained
 • Unimproved
By Grid
  Daily Vehicle
  Miles on Unpaved
  Roads
By Grid
Annual Vehicle
Miles on
Unpaved Roads
     For Missouri Counties:
     By County
     Map of Roads
     by Surface Type
     By Road Type
      Average ADT
      (Based on
      7-County
      Illinois Data)
                         By Grid
 Miles of Road
 • Gravel or Stone
 • Soil Surfaced
 • Graded & Drained
 • Unimproved
                                         By Grid
                                          Annual Vehicle
                                          Miles on
                                          Unpaved Roads
Figure 3.   Procedure for determination  of annual vehicle-miles  on unpaved roads

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                                                      Table  1.   COUNTY  STATISTICS FOR UNPAVED ROADS


State
Illinois






Missouri





Spunci
Bond
Clinton
Madison
Monroe
Randolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
Mao
Road
surface
1972
1972
1973
1973
1973
1973
1971
1973
1975
1971
1969
date

Traffic
1969
1968
1971
1973
1973
1972
1973

__
..
--
St. Louis City --

Gravel/
stone
351.1
504.7
20.0
234.2
284.5
209.0
339.5
606.1
260.7
282.7
0.0
0.0

Soil
surfaced
39.5
11. 0
285.0
0.0
13.7
42.2
24.0
0.0
0.0
0.0
0.0
0.0
Mlleaae
Graded and
drained
41.7
36.0
11.0
32.5
42.2
15.0
107.5
1.2
0.0
0.0
0.0
0.0


l/n.inproved
1.5
1.5
0.2
1.7
9.0
0.2
3.5
3.0
0.0
0.0
0.0
0.0


Total
433.8
553.2
316.2
268.4
449.5
266.5
474.5
610.3
260.7
282.7
0.0
0.0

Gravel/
stone
81
83
92
64
65
— •
73
71^
71-
71-a'
--


Soil
surfaced
57
58
63
—
280
— •
85
73*;
7ja
73*'
—

ADT
Graded and
drained
51
72
50
64
50
— •
51
53*'
53*'
53*'
—

Annual VMT
(th.9U.sand.s)
Unimoroved
25
25
25
25
25
25
25
25
25
25
—

Qrave,!
10,321
15,226
675
5,548
9,429
13,500
9,079
16,563
6,882
6,967
0
0
Dirt
1,607
1,361
6,736
591
2,304
2,284
2,821
33
0
190
0
0
Average value based on Illinois counties in the  St.  Louis AQCR  weighted  by miles of each road surface type.

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EMISSION FACTOR

     The emission factor for dust emissions from unpaved roads (pounds
per VMT) is given by:
where  sr  = silt content of road surface material, gravel (sg) and dirt
(sj) (percent), i.e., particles smaller than 75 p-m in diameter, Sr  =
average vehicle speed (miles per hour), and  d  = number of dry days per
year, i.e., days with less than 0.01 in. of precipitation. Based on driver
interviews, the average vehicle speed on unpaved roads in the St. Louis
area was taken to be 30 mph. On the average, there are 250 dry days per
year in the RAPS study region.^.'
                                                              6/
     The silt content of gravel roads was estimated to be 16%,""  and the
silt content of dirt roads (i.e., soil-surfaced, graded and drained, and
unimproved) was assumed to be the same as the soil silt content deter-
mined for agricultural sources (see Section Agricultural Tilling, Emis-
sion Factors). Composite road silt content by grid was found to vary from
10 to 70% with corresponding emission factors ranging from 3.36 to 23.5
Ib/vehicle mile.

TEMPORAL APPORTIONING FACTORS

     Little data are available describing temporal variations in traffic
on unpaved roads. Figure 4 illustrates hourly, daily, and seasonal varia-
tions of VMT on unpaved roads for a farming area in California.-'-' These
data were assumed to approximate temporal variations in the St. Louis
area.
                                   12

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                TEMPORAL APPORTIONING FACTORS

Source Type: Unpaved Roads
                      A
                       s
                                                  s
                                                       X
      01  2345678 91011121314151617181920212223
                             Hour of Day
    20
    15
    10
    5
        Mon     Tue    Wed     Thu     Fri
                            Day of Week
                       Sat
   Sun
   30
   25
   20
   15
   10
    5
         Winter
Spring        Summer
   Season of Year
Fall
  Figure  4.   Percentage of total daily, weekly,  and  annual
                 vehicle-miles on unpaved roads
                              13

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                         AGRICULTURAL TILLING

GRID SOURCE EXTENT

     Dust emissions from agricultural tilling can be quantified in terms
of annual acres of cropland tilled. Data used for this determination (see
Figure 5) were:

     1.  Acreage of harvested cropland by grid, for five major crops (corn,
           soybeans, wheat, milo and hay).

     2.  Number of yearly agricultural operations by crop, including til-
           ling, planting, and harvesting.

     The acres of harvested cropland for all farms on a county basis,
as presented in Table 2, were obtained from the 1969 Census of Agricul-
ture.—  The number of yearly agricultural operations for the five major
crops (see Table 3) were estimated by knowledgeable MRI personnel. This
information was used to determine the equivalent acres of land tilled
per year by county, based on the following equation:
Equivalent acres
of land tilled
annually by       .—..
county
                        'Number of equiv-        Acres of har-"
                        alent tilling           vested crop-
                        operations by           land, by crop
                        crop, i                 i,
                                                              by county
Planting and harvesting operations were estimated to have half of the fugi-
tive dust potential of tilling, based on visual observations made by MRI
personnel.

     Annual acreage of land tilled by grid was determined by spatial ap-
portioning of county totals on the basis of grid area and land use, ac-
cording to the following equation:
Annual acres of    Annual acres of     Agricultural acreage     Fraction of
land tilled by  =  land tilled by   X  within grid           X  grid in county
grid               county                Agricultural acreage within county

                                   15

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                   By County

                    Area of Each
                    Grid (Acres)
                     % of Grid
                     in County
By County
                                           Acres in
                                           Each Grid
                                        By Grid
                      1970 Land
                      Use Maps
 % Agricultural
 Land in Grid
cr>
                                         By Crop
Number of
Agricultural
Operations
• Tilling

planting
• Harvesting
By County

1969 Acres
of Each Crop
Harvested










By County
Number of
Equivalent
Til lings
per Year












By County

Annual
Acres of
Agricultural
Land
Tilled






i






By Grid
Annual
Land Tilled



                           Figure 5.   Procedure for  determination  of  annual acres of land  tilled

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                          Table 2.  COUNTY BREAKDOWN OF HARVESTED ACRES  BY  CROP AND EQUIVALENT TILLINGS


St.ate
Illinois






Missouri




County-
Bond
Clinton
Madison
Monroe
Randolph
St. Glair
Washington
Franklin
Jefferson
St. Charles
St. Louis
Harvested
cropland
(acres)
122,755
170,718
224,634
114,343
148,136
214,750
204,371
74,974
27,506
108,909
35,460
b/
Percentage of acres by crot)
Corn (5)
32.9
39.7
32.0
36.9
32.9
31.5
28.3
32.7
18.0
37.9
29.1
Wheat (41
16.3
16.7
18.1
25.3
19.4
20.9
20.5
17.4
13.8
22.8
29.1
Soybean,? (4.)
39.6
29.1
38.7
27.1
29.6
38.6
38.1
3.9
7.0
25.5
22.2
Milo (5)
0.4
0.4
0.9
0.1
0.1
0.2
0.5
0.9
1.8
0.2
0.5
H.aY (2.5)
8.6
12.0
8.0
6.9
13.4
5.0
9.4
39.8
52.6
10.7
10.5
Other (0)
2.2
2.1
2.3
3.7
4.6
3.8
3.2
5.3
6.8
2.9
8.6
Equivalent
tillings
oer year
4.1
4.1
4.1
4.1
4.0
4.1
4.0
3.5
3.1
4.1
3.8
aj  St. Louis  City  not  included;  harvested  cropland  (acres) = 0.
_b/  Numbers  in parentheses  are  equivalent tillings per  year for each crop.

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                 Table 3.   AGRICULTURAL OPERATIONS BY CROP

Number of equivalent tillings per year—'
Crop
Corn
Wheat
Soybeans
Milo
Hay
Primary
tilling
1
1
1
1
1/2
(F)
(Su)
(W, Sp)
(F, W,
Sp)
(Su)
Secondary
tilling
3 (Sp)
2 (Su, F)
2 (Sp)
3 (Sp)
1 (Su, F)
Planting
1/2 (Sp)
1/2
1/2
1/2
1/2
(F)
(Sp)
(Sp)
(F)
Harvesting Total
1/2 (F) 5
1/2
1/2
1/2
1/2
(Su) 4
(F) 4
(F) 5
(Su) 2.5
aj  Season of operation is abbreviated by W = winter, Sp = spring,
      Su = summer, and F = fall.
     Agricultural acreage within each grid and within each county was
determined by analysis of land use maps supplied by the East-West Gateway
Coordinating Council.9»lw xhe area of a grid lying within a particular
county was determined from the base map of the RAPS grid system (Figure
2). Results for grids which cross county lines were summed.

EMISSION FACTOR

     The emission factor for dust emissions from agricultural tilling
operations (pounds per acre tilled) is given by:
                             EFt =1.1
                                       (PE/50)'
where  st  = silt content of soil (percent), i.e., particles between 2
and 50 pm in diameter, and  PE  = Thornthwaite* s Precipitation- Evaporation
     Soil silt content for each grid was determined from an analysis of
soils maps, obtained from Soil Conservation Service offices for the coun-
ties of Bond, Clinton, Madison, St. Clair, and Washington in Illinoisi?/
                                      18

-------
and St. Charles County in Missouri.—' A map of the soils of the North
Central United Statesi^t'  was used for the remaining counties and to pro-
vide data comparisons.

     The soil classification system for each map was converted to soil
families (the second most specific classification of soils, indicating
the soil texture), and a soil texture trianglei^/ was used to estimate
silt content for each family designation. Areas of uniform soil family
were superimposed on a grid map (see Figure 6) and appropriate silt con-
tent values were assigned to each grid.

     A map of the PE-index by state climatic division, generated in an
earlier MRI study^i' indicates a PE-index of 93 for both state climatic
divisions which comprise the Metropolitan St. Louis AQCR.

TEMPORAL APPORTIONING FACTORS

     Agricultural land tilling, planting, and harvesting follow a regu-
lar yearly cycle dependent on the type of crop. Within these yearly cy-
cles, agricultural operations are performed mainly during the hours from
dawn to dusk and uniformly through the week, with only a slight reduction
on Sundays. The temporal apportioning factors derived for agricultural
operations are shown in Figure 7.

     Based on seasonal performance of primary and secondary tilling, plant-
ing, cultivation, and harvesting for the main crops in the St. Louis AQCR,
as determined by MRI personnel (see Table 3), seasonal apportioning factors
were determined for each county, taking into account the respective crop
mixes. Separate average seasonal factors were calculated for Missouri and
Illinois to reflect wide differences in types of crops in the two states.
                                   19

-------
FRANKLIN  '  j

    40     :-: •'
i WASHINGTON '
       70
                     Figure 6.  Soil silt  content  (7.) for RAPS Grid system

-------
                 TEMPORAL APPORTIONING  FACTORS

Source Type: Agricultural Tilling

       01  2345678 91011121314151617181920212223
                              Hour of Day
    20
    15
    10
    5
Mon     Tue     Wed     Thu      Fri

                    Day of Week
                                               Sat      Sun





/
f
//
//
//
r
/\
/ . V
/ '^ \
/ / ^'A
/ / N
/









\
V- ^
\N^- — "
\ ^









-^-'




— — Illinois
	 Missouri
   50	
   45	
   40
   35
   30
   25
   20
   15
   10
         Winter
                Spring        Summer
                   Season of Year
Fall
   Figure  7.   Percentage of  total daily, weekly, and  annual
                           agricultural tilling
                                   21

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                     WIND EROSION FROM TILLED LAND

GRID SOURCE EXTENT

     The measure of source extent for wind erosion from tilled agricul-
tural land is average exposed (unvegetated) acreage. Agricultural land
is assumed to remain vulnerable to wind erosion from the time of primary
tilling to about 1 month after planting. The procedure used to determine
average area of erodible agricultural land within each grid is depicted
in Figure 8.

     Annual average exposed acreage for each county was determined from
seasonal values (see Table 4) which were calculated from the acreage
planted in each crop and the corresponding months of exposure. Erodible
acreage for each grid was determined by apportioning county totals on
the basis of the proportion of county agricultural acreage which lies
within the grid.

EMISSION FACTOR

     An emission factor for wind erosion from agriculturally tilled land
was derived from data on atmospheric loadings of suspended dust measured
by Gillette^/ during dust storms in West Texas. The threshold rate of
wind erosion was adjusted to apply to values of soil silt content and
climatic factor which are representative of the St. Louis area.

     The threshold value for the St. Louis area was calculated to be:
3.5 tons/acre/year. Based on meteorological data for 3-hr time incre-
ments, winds in the St. Louis region exceed 12 mph approximately 26% of
the time.-=-£' Thus, the annual average emission factor for wind erosion
becomes:

                    3.5 tons/acre x 0.26 = 0.9 tons/acre
                                   23

-------
By County
Area of Each
Grid (Acres)


% of Grid
In County

1970 Land
Use Maps








—







By County
Acres in
"" Each Grid


By Grid
% Agricultural
"" Land in Grid








                                              By County

                                               Acres of
                                               Agricultural
                                               Land in
                                               Each Grid
           By Crop
             Time Period
             of Crop
             Til lings
           By County
             1969 Acres
             of Each  Crop
             Harvested
By County
 Annual
 Exposed Acres
 of Agricultural
 Tilled  Land
By Grid
 Annual
 Exposed Acres
 of Agricultural
 Tilled  Land
              Figure 8.   Procedure for determination of acreage of
                                  exposed agricultural  land
                                         24

-------
                          Table 4.   SEASONAL EXPOSED ACREAGE BY COUNTY


State
Illinois






Missouri



_ /
a/
Countv~
Bond
Clinton
Madison
Monroe
Randolph
St. Glair
Washington
Franklin
Jefferson
St. Charles
St. Louis
Average acres exposed
Winter
58,292
86,609
104,702
53,762
65,426
97,786
86,719
26,462
6,166
51,505
13,384
Spring
77,427
97,376
138,675
60,500
78,736
131,115
119,832
19,943
5,626
56,288
15,168
Summer
18,474
27,109
37,021
25,744
27,379
39,798
38,340
15,061
5,154
22,584
9,269
Fall
42,190
67,420
79,008
49,070
54,667
77,749
69,983
27,822
7,216
45,657
14,402
Average
49,096
69,628
89,851
47,269
56,552
86,612
78,718
22,322
6,040
44,008
13,055
a)  St. Louis City not included; harvested cropland  (acres) = 0.

-------
TEMPORAL APPORTIONING FACTORS

     Temporal apportioning factors for wind erosion are shown in Figure
9. Seasonal apportioning factors were scaled to the product of (a) sea-
sonal values of exposed acreage by state and (b) the seasonal climatic
factorM'  for the St. Louis AQCR. Hourly factors were proportioned to
the probabilities that the wind speed will exceed 12 mph, the threshold
value for the onset of wind erosion.
                                   26

-------
                      TEMPORAL APPORTIONING FACTORS
      Source Type: Wind Erosion from Tilled Land
            01  2345678 91011121314151617181920212223
                                   Hour of Day
         20
         15
         10
          5
             Mon     Tue     Wed     Thu      Frl
                                 Day of Week
                       Sat
    Sun
               Winter
Spring        Summer
   Season of Year
Fall
Figure 9.  Percentage of total daily, weekly, and  annual wind erosion
                      from agricultural tilled land
                                    27

-------
                             CONSTRUCTION

GRID SOURCE EXTENT

     Fugitive dust emissions from construction activities are directly
related to the land area being worked, over a specific time period. Fig-
ure 10 presents the methodology used to determine annual acres of con-
struction within each grid area. Construction activity considered in this
study was confined to the Source Industrial Classification (SIC) Major
Group 15 (Building Construction—General Contractors and Operative
Builders) and Group 16 (Construction Other than Building Construction-
General Contractors).

     Detailed 1974 data for major building construction sites in the
Missouri counties except Franklin were obtained from the East-West
Gateway Coordinating Council.«=•?-' These data included:  county, location,
census tract, description of activity, project name, size in acres  (or
square feet), and stage of development. All sites were located by grid
and construction acreage was totaled by county. It was evident that the
building construction centered around St. Louis County.

     A detailed listing of road construction projects in the St. Louis
area was also obtained from the East-West Gateway Coordinating Council.—
For the Missouri counties except Franklin, road construction projects
differentiated by type and mileage were assigned to the proper grid areas.
Estimates of contruction acreage per mile of road construction, for each
type of project, were used to convert mileage to acreage within each grid.
Road construction acreage totals for St. Charles and St. Louis Counties,
which amounted to less than 10% of building construction acreage, were
disregarded.

     Table 5 gives construction acreage by county. Construction acreage
totals for Jefferson, St. Charles and St. Louis counties are slightly
larger than the estimates reported earlier by MRI,—  which were based
on state construction receipts,^-**' and county construction employment;•=•=•'
this is apparently due to increased area development. However, the
St. Louis City construction acreage was smaller than the previously reported
                                   29

-------
                             CONSTRUCTION

GRID SOURCE EXTENT

     Fugitive dust emissions from construction activities are directly
related to the land area being worked, over a specific time period. Fig-
ure 10 presents the methodology used to determine annual acres of con-
struction within each grid area. Construction activity considered in this
study was confined to the Source Industrial Classification (SIC) Major
Group 15 (Building Construction—General Contractors and Operative
Builders) and Group 16 (Construction Other than Building Construction—
General Contractors).

     Detailed 1974 data for major building construction sites in the
Missouri counties except Franklin were obtained from the East-West
Gateway Coordinating Council.•=•£' These data included:  county, location,
census tract, description of activity, project name, size in acres (or
square feet), and stage of development. All sites were located by grid
and construction acreage was totaled by county. It was evident that the
building construction centered around St. Louis County.

     A detailed listing of road construction projects in the St. Louis    .
area was also obtained from the East-West Gateway Coordinating Council.—
For the Missouri counties except Franklin, road construction projects
differentiated by type and mileage were assigned to the proper grid areas.
Estimates of contruction acreage per mile of road construction, for each
type of project, were used to convert mileage to acreage within each grid.
Road construction acreage totals for St. Charles and St. Louis Counties,
which amounted to less than 10% of building construction acreage, were
disregarded.

     Table 5 gives construction acreage by county. Construction acreage
totals for Jefferson, St. Charles and St. Louis counties are slightly
larger than the estimates reported earlier by MRI,—  which were based
on state construction receiptsy2i'  and county construction employment»•=•=•'
this is apparently due to increased area development. However, the
St. Louis City construction acreage was smaller than the previously reported
                                   29

-------
    For Missouri CounHes (except Franklin)
      1974 Construction
      Projects
      • Residential
      • Commercial
      • Highways
                                By Project
    Acres of
    Construction
                                By Project
                                 Grid Location
                                 of Construction
                                 Projects
                          By Grid
                          Annual Acres
                          of Construction
     For Illinois Counties and Franklin County, Missouri

     By County
      1972 Acres
      of Construction
     By County
        Land Area
     By Grid
        Land Area
                             By Grid
Annual Acres
of Construction
Figure 10.   Procedure for determination  of  annual acres of construction
                                     30

-------
               Table 5.  CONSTRUCTION ACREAGE BY COUNTY
                                    	Construction acreage	
  State            County           Building       Road       Total

Illinois       Bond                                             143
               Clinton                                          254
               Madison                                        1,640
               Monroe                                           151
               Randolph                                         333
               St. Glair                                      1,760
               Washington                                        87

Missouri       Franklin                                         435
               Jefferson                989         204       1,193
               St. Charles            1,088          al       1,088
               St. Louis City           234          62         296
               St. Louis              4,999          a/       4,999
a/  Road construction acres less than 107. of total.
                                     31

-------
value, which was based on the assumption that construction employees
residing in the city worked only within the city.

     For the remaining counties, i.e., Franklin County in Missouri and
all of the Illinois counties, MRI estimates of total construction acre-
age^' (buildings plus roads) were apportioned to grids within a county
on the basis of grid area.

EMISSION FACTOR

     County-wide emission factors for dust emissions from construction
activities were determined by multiplying a previously determined emis-
sion rate factor (1 ton/acre/month)i' by an average duration of construc-
tion within the county, weighted by the relative proportion of acreage
differentiated by project type and the average duration for each project
type. MRI estimates of the average duration of construction^/ are:

      6 months for residential buildings,

     11 months for nonresidential buildings, and

     18 months for nonbuilding construction.

     The emission factor for construction can thus be written as follows:
                           EFc = D tons/acre

where     D = weighted average duration of construction within a given
              county.

     The value of  D  for St. Louis City and the Missouri counties of
Jefferson, St. Charles, and St. Louis was determined to be 9.1 months,
and the value for the remaining counties was estimated to be equal to
12 months .£/

TEMPORAL APPORTIONING FACTORS

     Temporal apportioning factors for determining construction emissions
by hour of the day, day of the week, and season of the year were derived
from analysis of the work cycle of construction activity (see Figure 11).
Construction activity reaches its peak level during June and July and
is lowest during December through February. Weekday activity is relatively
uniform with some reduction on weekends. The hourly factor distribution
has mid-morning and mid-afternoon peaks.
                                   32

-------
                TEMPORAL APPORTIONING FACTORS

Source Type: Construction
                                 2
                 i
      01  2345678 91011121314151617181920212223
                             Hour of Day
   20
   15
   10
    5
        Man     Tue     Wed     Thu      Fri

                           Day of Week
Sat
Sun
35
30
25
20
15
10
5
I







^***^~








^^^-"•^
^-^-








^-^^^-^^^











"*- 	 _





Winter Spring Summer Fall
Season of Year
'igure 11. Percentage of total daily, weekly, and
annual construction activity
                              33

-------
                           AGGREGATE  STORAGE

GRID  SOURCE  EXTENT

      The amount of fugitive dust emissions from aggregate  storage piles
is proportional to the  quantity of aggregate  storedyi' i.e., the tonnage
put through  the storage cycle. Figure  12 illustrates  the methodology for
determining  the quantity of aggregate  stored  annually within each grid.

      The following Source  Classification Codes of the National Emissions
Data  System  (NEDS) were identified as  industrial producers and users of
mineral aggregate:

                         	SCC  ID
                          I    II    III     IV

                          3    05    All    All
                                             23/
A NEDS point source listing (August 25, 1975)—  for the above codes was
obtained for the St. Louis AQCR.

     Aggregate storage data from the NEDS listing were analyzed and the
grid numbers for aggregate user and producer industries were determined
from the respective UTM coordinates. Only industries with open aggregate
storage were considered in this study.  Producers are stone quarries and
sand/gravel processors, and users  are cement manufacturing (wet and dry),
and concrete batching. Asphalt batching plants in the St. Louis area nor-
mally  store aggregate in  enclosed  areas.

     The methodology employed to determine the amount of aggregate mate-
rial stored on-site by a  producer  or user industry and the average period
of storage is presented below.

     Stone quarries - The amount of aggregate material stored annually
is specified in the NEDS  output. An estimated 3-month storage period is
assumed from previous experience with the stone quarry industry.
                                   35

-------
CO
1975 NEDS
Listing of SCC
Codes 03-05-
(Industrial
Process -
Mineral Products)

Contacts with
Industries



By County
Aggregate Storage
• Users
• Producers

Methodology
for Determining
Annual Tons of
Material Stored


By Grid
Aggregate Storage
• Producers


E

>y Grid

Annual Tons
of Aggregate
Storage
                    Figure 12.   Procedure for determination of annual  tons  of  aggregate storage

-------
     Sand and gravel - The amount of aggregate material stored in an an-
nual period is taken to be 50% of the tonnage processed. An estimated
3-month inventory period is assumed from previous experience with the
sand and gravel industry.

     Cement manufacturing - The following equation for calculating the
amount of aggregate stored by this user industry was determined from tele-
phone contacts with area plants and a literature survey:

        A              j — r,    4.    j   j   i i tons aggregate
        Aggregate stored — Cement produced x 1.2
         65  5                    *               tons cement
          (tons)                  (tons)

The NEDS output designates tons of cement produced from wet and dry pro-
cess facilities. On the average, aggregate material used in cement manu-
facturing is stored for 1 week.

     Concrete batching - Cubic yards of concrete produced by each batch-
ing plant is specified in the NEDS listing. Based on contacts with this
user industry, the following conversion factors were obtained:  (a) 1
cu yd of concrete is equivalent to 2 tons, and (b) approximately 75% of
each ton of concrete produced is comprised of aggregate material taken
from open storage. The average aggregate storage period for this user
industry is 1 week.

     Table 6 summarizes by county the quantity of aggregate stored an-
nually for each of the above user and producer industries.

EMISSION FACTOR

     The emission factor for dust emissions from aggregate placed in open
storage for a period of 3 months is:

                 EFg = 0.33 Ib/ton placed in storage

which includes emission contributions from wind erosion (33%), movement
of traffic among the storage piles (40%), and loading and unloading op-
erations (27%).—'  The corresponding emission factor for a 1-week storage
cycle is 0.22 Ib/ton placed in storage.

TEMPORAL APPORTIONING FACTORS

     Temporal apportioning factors (see Figure 13) were determined sep-
arately for the emission contributions from storage pile activity and
from wind erosion. The factors for storage pile activity were derived
on the basis of the information from industrial personnel and NEDS data.
                                    37

-------
                              Table 6.  ANNUAL ACRES OF AGGREGATE STORED BY COUNTY
U)
00

Aggregate storage (tons/year)

State
Illinois






Missouri





County
Bond
Clinton
Madison
Monroe
Randolph
St. Glair
Washington
Franklin
Jefferson .
St. Charles
St. Louis City
St. Louis
Sand/
gravel
0
0
0
0
0
0
0
0
12,950
0
•
0
189,500
Stone
quarry
0
20,000
74,000
46,800
275,000
1,900,000
100,000
0
8,000
220,000
0
64,000
Cement
manufacturing
0
0
0
0
0
0
0
0
1,232,700
0
0
1,709,600
Concrete
batching
0
11,300
0
0
0
0
0
37,950
54,000
125,550
0
0

Total
0
31,300
74,000
46,800
275,000
1,900,000
100,000
37,950
1,307,650
345,550
0
1,163,100

-------
                 TEMPORAL APPORTIONING FACTORS

Source Type:  Aggregate Storage





6














































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i






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it
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*^~









^*










^~










—










[-•










•~*










•••'
































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^^




       01  2345678  91011121314151617181920212223
                               Hour of Day
                                                                 	Wind
                                                                     Erosion

                                                                 —~- Activity

                                                                 	 Weighted
                                                                     Average
    20
    15
    10
     5
                                       	Wind
                                             Erosion

                                       ——— Activity

                                       	 Weighted
                                             Average
        Mon     Tue    Wed     Thu      Fri
                             Day of Week
                        Sat
   Sun
    35
    30
    25
    20
    15
    10
     5

          Winter
Spring        Summer
   Season of Year
Fall
   Figure 13.   Percentage of  total daily, weekly, and annual
                     aggregate storage operations
                                             Climatic
                                             Factor

                                             Activity

                                             Weighted
                                             Average
                                     39

-------
     For aggregate producers (stone quarries and sand/gravel processors),
approximately 75% of the industry operates year-round and the remaining
25% operate 9 months during the year. Production rates are at peak level
during June and July, and are lowest during December through February.
For most of the year, the operating schedule is 6 days/week and 15 hr/day.

     For aggregate users (cement manufacturing and concrete batching),
approximately 60% of the industry in the St. Louis AQGR operate year-
round, and the remaining 40% operate 9 to 10 months during the year.
Production rates change seasonally with demand for concrete for local
construction projects. The operating schedule is normally 6 days/week
and 16 hr/day. Spring and summer are peak seasons, and activities de-
cline during the winter months (December through February).

     Seasonal and hourly apportioning factors for wind erosion from stock-
piles were based on observed variations in governing climatic conditions.
Seasonal factors were scaled to values of the climatic factor for wind
erosion,.L§/ and hourly factors were proportioned to the probability that
the wind speed will exceed 12 mph, the threshold value for the onset of
wind erosion.
                                    40

-------
                           UNPAVED AIRSTRIPS

GRID SOURCE EXTENT

     The landing/takeoff (LTD) cycle is the designated measure of source
extent for fugitive emissions from unpaved airstrips. Figure 14 illus-
trates the procedure used to determine LTO cycles on unpaved airstrips
by grid.
                                                           9/ /
     Airport data were extracted from an "Airport Services'1—  computer
tape obtained by MR! from the Federal Aviation Administration (FAA) under
EPA Contract No. 68-02-1437. Data on this tape include the following in-
formation for each airport:  site number, city, state, airport name,
county code, latitude, longitude, airport type, number of total based
aircraft, number of multi-engine based aircraft, runway pavement type,
runway length, population served, ownership type, and usage type. A com-
puter program was written to list all Missouri and Illinois airports and
to output required data onto standard computer cards.

     Nine airports within the St. Louis AQCR were designated as Pavement
Type 5 (dirt or gravel runways). However, seven of these airports did
not have any based aircraft and the remaining two were helicopter bases.

     Airstrips with Pavement Type 4 (turf runways) numbered 43, of which,
25 turf airstrips (excluding heliports) listed based aircraft. Grid num-
bers for each of these 25 airstrips (see Table 7) were determined from
latitude and longitude indicated on the FAA tape.

     Regional FAA officials estimated the number of operations per based
aircraft at small airport facilities to be in the range of 400 to 800
operations per year with a typical value being 500, i.e., 250 LTO cycles
per yea.r.2.'  The total number of LTO cycles on unpaved airstrips in each
grid was calculated by multiplying 250 LTO cycles per year times the total
number of aircraft based at unpaved airstrips within each grid.
                                    41

-------
By Airport
     1974 Based
     Aircraft
By Airport
   1974 Pavement
   Type
  Annual LTO
  Cycles per
  Based  Aircraft
  (Estimated =250)
By County
By Grid
 Number of
 Based Aircraft
 on Unpaved
 Airstrips
 Number of
 Based Aircraft
 on Unpaved
 Airstrips
                                                                    By Grid
                                          Annual  LTO
                                          Cycles on
                                          Unpaved
                                          Airstrips
   Figure  14.   Procedure for determination of annual LTO cycles on
                           unpaved  airstrips
                                    42

-------
Table 7.   DATA ON UNPAVED (TURF) AIRSTRIPS BY COUNTY



State
Illinois








Missouri






County
Bond
Clinton
Madison
Monroe
Randolph
St. Clair


Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
No. of turf
airstrips with
based aircraft
2
3
3
4
3
7


1
0
1
1
0
0


Grid location
1,764
1,739, 1,761, 1,784
1,595, 1,641, 1,710
951, 990, 1,057, 2,273
1,579, 1,582, 1,633
1,456, 1,484, 1,586,
1,617 (2), 1,639,
2,341
1,842
_
185
166
-
-

LTO cycles/
Year
500
2,500
5,250
12,000
750
8,750


250
0
3,000
1,250
0
0

-------
EMISSION FACTOR

     The emission factor for unpaved airstrips, in units of pounds of
dust per landing/takeoff cycle, was derived by analogy to the equation
for unpaved roads,.2/ doubled to include propeller-generated wind ero-
sion. The expression for dirt airstrips is given by:

                      EFa = 2[0.49 sa

where  s   is the silt content (percent) of dirt airstrips (equivalent
to the agricultural soil silt content),  Sa  is the average aircraft
ground speed (mph),  d  is the number of dry days per year, and  (1)
mile is the approximate length of runway used for an LTO cycled.' in-
cluding taxiing. Regional FAA officials*-' estimated  Sa  to be 40 mphj
and, on the average, there are 250 dry days per year in the St. Louis
area.J/

     During the months of July through October, turf airstrips will ap-
proximate dirt airstrips due to dry weather conditions and higher volume
of traffic. It was estimated that the emission factor for turf airstrips
should be one-half the factor for dirt airstrips to account for the ef-
fect of grass cover in reducing wind erosion. The emission factor for
turf airstrips ranged from 4.5 to 31 Ib/LTO cycle for agricultural silt
contents ranging from 10 to 70%.

TEMPORAL APPORTIONING FACTORS

     Temporal apportioning factors were derived from the following infor-
mation (see Figure 15):

     1.  Air traffic, i.e., landings and takeoffs, occurs primarily be-
           tween the hours of dawn to dusk.

     2.  Approximately 50% of the air traffic occurs on weekends and holi-
           days.

     3.  Approximately 70% of the air traffic occurs between the months
           of April through October.
                                    44

-------
                  TEMPORAL APPORTIONING FACTORS

 Source Type:  Unpaved Airstrips
                                                                   __ Saturday,
                                                                     Sunday
                                                                     Monday
                                                                     through
                                                                     Friday
        01 2345678  91011121314151617181920212223
                               Hour of Day
     30
     25
     20
     15
     10
      5
     35
     30
     25
     20
     15
     10
      5
           Winter
Spring        Summer
   Season of Year
         Mon     Tue     Wed     Thu     Fri      Sat      Sun

                              Day of Week
Fall
Figure 15.   Percentage of total  daily, weekly, and  annual LTO cycles
                                   45

-------
                DATA TABULATIONS AND CALCULATED RESULTS

     Tables 8 and 9 illustrate example data tabulations prepared for this
project. Table 8 gives data on (a) annual extent of fugitive dust sources
and (b) agricultural soil silt content, for the first 35 grids in the
RAPS study region. Table 9 presents the hourly adjustment factors for
a Sunday in the winter season. A complete set of example calculations is
detailed in Appendix A.

     The preceding data were used as input for two computer programs:

     1.  Program 1, which calculates the annual emissions of fugitive
           dust for each source category, by grid, and

     2.  Program 2, which calculates hourly emissions of fugitive dust
           within a specified grid, for any hour of the year, through
           multiplication of the annual emissions total by the particu-
           lar hourly adjustment factor.

Simplified logic diagrams of these programs are presented in Figures 16
and 17.  Both programs were written in Fortran IV to provide compatibility
with most computer systems. Example output for the annual emissions com-
puter program is illustrated in Figure 18.
                                    47

-------
Table 8.   EXAMPLE CODED SOURCE EXTENT AND CORRECTION FACTOR DATA
Source extent
Coordinates
Grid
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
19
20
21
22
25
26
27
28
29
32
33
34
35
37
38
39
40
43
44
(UTM
E
640
640
640
640
645
645
645
645
645
650
650
650
650
650
650
655
660
660
660
660
665
670
670
670
670
670
670
670
670
671
671
672
672
673
673
Zone 15)
-JL
4,235
4,245
4,265
4,280
4,230
4,255
4,260
4,275
4,280
4,230
4,235
4,245
4,255
4,265
4,275
4,230
4,235
4,245
4,255
4,265
4,230
4,230
4,235
4,245
4,250
4,260
4,265
4,268
4,269
4,268
4,269
4,268
4,269
4,265
4,266
Size
(tan)
10
10
10
5
5
5
5
5
5
5
10
10
10
10
5
5
10
10
10
10
5
5
10
5
5
5
3
1
1
1
1
1
1
1
1
Unpaved
(102 veh.
Gravel
8,827
10,690
8,260
1,296
907
1,490
2,203
1,101
2,389
583
10,496
7,710
8,876
6,673
405
713
7,580
5,377
7,256
5,759
1,684
1,500
6,738
1,555
1,745
130
0
0
0
0
0
0
0
0
0
roads
mi.)
Dirt
0
0
0
0
242
0
0
0
0
0
0
0
0
0
0
0
0
0
0
101
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

Land tilling
(acres)
11,103
11,102
11,102
2,774
2,776
2,776
2,776
2,776
2,774
2,776
11,105
11,105
11,105
11,448
2,774
2,776
11,105
11,105
11,105
11,102
2,776
2,776
11,105
2,776
2,776
2,776
999
110
110
110
110
110
110
110
110
Wind
erosion
(acres)
944
945
945
236
236
236
236
236
236
236
944
944
944
944
236
236
944
944
944
945
236
236
944
236
236
236
85
9
9
9
9
9
9
9
9

Construction
(10"1 acres)
147
153
156
23
46
46
46
46
34
46
184
184
184
178
32
46
184
184
184
156
46
46
184
46
46
46
17
2
2
2
2
2
2
2
2

Aggregate storage
(tons)
0
0
0
0
0
0
0
0
43,050
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

Dirt airstrips
(LTO cvcles)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Correction
factor
Silt
content (7.)
40
40
59
59
40
40
40
59
59
40
40
40
40
59
59
40
40
40
40
59
30
40
40
40
40
67
67
50
50
50
50
50
50
67
67

-------
                                       Table 9.   HOURLY  ADJUSTMENT EXAMPLE CODED FACTORS
vD

Hourly acHustment factors (10 )

Number
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Time of
day
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Unpaved
roads
283
252
189
63
63
377
1,227'
2,139
1,667
1,919
1,919
1,887
1,699
1,887
2,328
2,265
2,517
2,863
1,919
1,510
1,070
692
440
283
Land tilling
Illinois
3
3
3
3
3
78
130
156
182
182
208
208
182
182
208
182
182
156
130
104
78
26
10
3
Missouri
1
1
1
1
1
39
65
78
91
91
104
104
91
91
104
91
91
78
65
52
39
13
5
1
Wind erosion
Illinois
1,667
1,667
1,667
1,620
1,667
1,667
1,667
1,805
1,944
2,083
2,129
2,222
2,268
2,268
2,315
2,315
2,222
2,083
1,991
1,944
1,805
1,805
1,759
1,713
Missouri
1,713
1,713
1,713
1,665
1,713
1,713
1,713
1,855
1,998
2,141
2,188
2,283
2,331
2,331
2,378
2,378
2,283
2,141
2,046
1,998
1,855
1,855
1,808
1,760
Construction
8
8
8
8
38
188
375
525
600
675
675
525
525
675
675
600
525
375
225
150
75
30
8
8
Aggregate
storage
311
311
311
311
311
851
851
867
884
900
900
916
916
916
933
933
916
900
884
884
425
311
311
311
Unpaved
airstrips
36
36
36
36
72
360
720
1,440
2,160
3,240
2,880
2,880
2,880
2,880
5,400
4,320
2,880
1,440
1,080
720
360
72
36
36

-------
                         For Each Grid:
INPUT: GRID  DATA
• Number
• Coordinates
• Width (km)
• County
• Agricultural  Silt
    Content, % (st,
                                                ,  so)
                           INPUT: SOURCE  EXTENT  DATA
                            • Unpaved Roads (vehicle miles)
                               - Gravel & Dirt
                            • Land Tilling  (acres)
                            • Wind Erosion (acres)
                            • Construction  (acres)
                            • Aggregate  Storage (tons)
                            • Unpaved Airstrips (LTO cycles)
                       INPUT: CORRECTION FACTOR CONSTANTS
                       • Number of Dry Days Per Year (d)
                       • Precipitation-Evaporation Index (PE)
                       • Duration of Construction Activity (D)
                           Missouri, Illinois
                       •Silt Content -  Roads, Gravel (sg)
                                   -  Roads, Dirt (sj)
                                   -  Tilling (it)
                       •Vehicle Speed  - Roads (Sr)
                                      - Airstrips (Sa)
       For  Each  Grid:
         COMPUTE: EMISSION  FACTORS
         • Unpaved Roads - Gravel  EFg  = 0.49 sg (Sr/30) (d/365) Ib/vehicle mile
                         - Dirt   EFd = 0.49 sd (Sr/30) (d/365) Ib/vehicle mile
         •Land Tilling  EFt = 1.1 st/(PE/50)2 Ib/ocre
         •Wind Erosion EFw =0.9 tons/acre
         • Construction  EFC = D tons/acre
         •Aggregate Storage   EFS = 0.33 Ib/ton stored
         • Unpaved Airstrips  EFa = 0.49sa (Sg/30) (d/365) Ib/LTO cycle
      For Each Grid:
       COMPUTE AND OUTPUT: ANNUAL EMISSION  RATE (tons/year, M tons/year)
        •Unpaved Roads
        • Land Tilling
        •Wind Erosion from Agricultural Tilled Land
        •Construction
        •Aggregate  Storage
        • Unpaved Airstrips
       *Total
Figure 16.   Simplified flow diagram  of  calculation procedure
                           for  annual  emissions by grid
                                         50

-------
         For Each Season,  Day,  and  Hour:
           INPUT: TEMPORAL APPORTIONING FACTORS
           • Unpaved  Roads
           • Land Tilling
           •Wind Erosion
           • Construction
           • Aggregate Storage
           •Unpaved  Airstrips
                               I
           COMPUTE: HOURLY ADJUSTMENT  FACTORS
           Season Factor x Day Factor x Hour Factor
            • Unpaved Roads
            • Land Tilling
            •Wind Erosion
            • Construction
            • Aggregate  Storage
            • Unpaved Airstrips
        For Each Grid:
          INPUT: ANNUAL EMISSION RATE (tons/year)
          • Unpaved  Roads
          • Land Tilling
          • Wind Erosion
          • Construction
          • Aggregate Storage
          • Unpaved  Roads
For  Specified Grids:
   COMPUTE & OUTPUT:
   • Unpaved Roads
   • Land Tilling
   • Wind Erosion
   • Construction
   • Aggregate  Storage
   • Unpaved Airstrips
HOURLY  EMISSION RATE  (Ib/hr,  kg/hr)
 Figure  17.   Simplified flow diagram of calculation procedure
                   for hourly emissions by grid
                               51

-------
                                      CALCULATED ANNUAL EMISSION HATES BY &f>W
NJ
.RIO
1
2
3
4
5
6
7
a
9
10
ll
12
13
14
15
16
19
20
21
22
25
26
27
28
29
32
33
34
35
37
38
39
40
43
44
45
46
47
48
49
i, nun
E
640
640
640
640
645
645
645
645
645
650
650
650
650
650
650
655
660
660
660
660
665
670
670
67 i 1>
670
670
670
670
670
671
671
672
672
673
673
673
673
673
674
674
U i«« 1C
N
4235
4245
4265
4280
4230
4255
42bO
4275
42BO
4230
4235
4245
4255
4265
4275
4230
4235
4245
4255
4265
4230
4230
4235
4245
4250
4260
4265
4268
4269
4268
4269
4268
4269
4265
4266
4267
4268
4269
4265
4266
- u« ;
Si/
10
10
10
5
5
5
5
5
5
5
10
10
10
10
5
5
10
10
10
10
5
5
10
5
5
5
3
1
1
1










u
C
M
a
a
a
8
8
8
8
a
u
a
8
a
8
8
8
8
8
a
a
3
8
6
8
8
B
8
a
8
8
8
B
B
B
8
8
a
8
8
8
-''uNPV. ROADS
2369.99
2870.19
2217.75
347.97
405.96
400.05
591.49
295.61
641.43
156.53
2818.10
2070.08
2383.15
1791.65
108.74
191.44
2035.18
1443.69
1948.19
1646.25
452.14
402.74
1809.11
417.51
468.52
34.90
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
                                                         EMISSION RATE (TONS/YPl
                                             AQ. TILLING  WIND EROSION  CONSTRUCTION
                                     AG. STORAGE  UNP.AIRSTRIP
 70.61
 70.61
10*.15
 36.04
 17.65
 17.65
 17.65
 26.04
 26.04
 17.65
 70.62
 70.62
 70.62
104.15
 26.04
 17.65
 70.62
 70.62
 70.62
10-.15
 13.24
 17.65
 70.62
 17.65
 17.65
 29.57
 10.64
   .87
   .87
   .87
   .87
   .87
   .87
  1.17
  1.17
  1.17
   .87
   .87
  1.17
  1.17
                                                                 849.6
                                                                 850.5
                                                                 850.5
                                                                 212.4
                                                                 212.4
                                                                 212.4
                                                                 212.4
                                                                 212.4
                                                                 212.4
                                                                 212.4
                                                                 849.6
                                                                 849.6
                                                                 849.6
212.4
212.4
849.6
849.6
849.6
850.5
212.4
212.4
849.6
212.4
212.4
212.4
 76.5
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
  8.1
176.4
1*1.6
187.2
 27.6
 55.2
 55.2
 55.2
 55.2
 40.8
 55.2
220.8
220.8
220.8
213.6
 38.4
 55.2
220.8
220.8
220.8
187.2
 55.2
 55.2
220.8
 55.2
 55.2
 55.2
 ?0.4
  2.4
  2.4
  2.4
  2.4
  2.4
  2.4
  2.4
  2.4
  2.o
  2.4
  2.4
  2.4
  2.4
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
'.103
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
o.oeo
0.000
o.eoo
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
                                                                                                                      ••TOTAL**
3467
3975
3360
 614
 691
 685
 877
 589
 928
 442
3959
3211
3524
2959
 386
 477
3176
2585
3089
2788
 733
 688
2950
 703
 754
 332
 108
  11
  11
  11
  11
  11
  11
  12
  12
  12
  11
  11
  12
  12
           a/  Grid size (width) in kilometers.
           b/  County which represents major portion of grid.
                                 Figure 18.   Example computer output of annual emissions by grid

-------
              ANALYSIS OF RESULTS AND ESTIMATED ACCURACIES

     Table 10 presents a county breakdown of annual fugitive dust emis-
sions in the Metropolitan St. Louis AQCR. This  data represents all grids
which lie entirely or partially within a specific county. As indicated,
unpaved roads and wind erosion from agricultural tilled land account for
more than 80% of the total fugitive dust emissions for the St. Louis area.

     The total quantity of particulate emissions smaller than 30 um in
diameter emitted by fugitive dust sources considered in this project is
1,145,000 tons/year. Assuming that 20% of the emissions (i.e., the por-
tion smaller than 5 um in size) will be transported to ambient air qual-
ity monitoring stations (see Appendix B), then 229,000 tons/year of fugi-
tive dust will have an impact on regional air quality and must be taken
into account in modeling the St. Louis AQCR. In comparison, total nonfugitive
emissions for the St. Louis AQCR are 355,000 tons/year;2^J thus, fugitive
emissions may be said to represent 39% of the total particulate pollutant
problem.

     Table 11 presents estimates for possible error in the calculated
values corresponding to a 90% confidence level and were determined by a
progressive analysis of errors associated with each calculation step.
Composite ranges of error are presented for calculated source extent, cor-
rected emission factors, and hourly adjustment factors.
                                     53

-------
                                            Table 10.   SUMMARY OF ANNUAL EMISSIONS BY COUNTY
Oi

Emission rate (tons/vear)

State County
Illinois Bond
Clinton
Madison
Monroe
Randolph
St. Glair
Washington
Subtotal
Missouri Franklin
Jefferson
St. Charles
St. Louis City
St. Louis
Subtotal
Total
Unpaved
roads
46,594
56,874
69,509
21,338
50,431
62,286
57,524
364,556
44,721
18,478
19,818
0
0
83,017
447,573
Agricultural
tilling
5,612
7,804
8,796
4,852
6,132
9,509
9,115
51,820
3,750
678
2,478
0
1,395
8,303
60,123
Wind
erosion
44,186
62,665
80,865
42,542
50,896
77,950
70,846
429,950
20,089
5,436
39,607
0
11,749
76,881
506,831

Construction
1,716
3,048
19,680
1,812
3,996
21,120
1,044
52,416
5,220
12,765
9,901
3,256
45,491
76,633
129,049
Aggregate
storaee
0
5.2
12.2
7.7
45.4
313.5
16.5
400.5
6.3
215.8
57.0
0
323.9
603.0
1,003.5
Unpaved
airstrips
7.8
39.1
70.4
174.6
10.9
133.0
3.9
439.7
0
33.6
9.8
0
0
43.4
483.1

Total
98,115
130,435
178,932
70,726
111,511
171,311
138,549
899,582
73,788
37,606
71,870
3,256
58,958
245,478
1,145,058

-------
            Table 11.  ESTIMATED ERRORS FOR TABULATED DATA
                                    Estimated relative error
       Source            Source        Corrected        Hourly adjust-
      category           extent     emission factor      ment factor

Unpaved roads            + 5%            + 20%              + 15%
Agricultural tilling     + 15%           + 30%              + 20%
Wind erosion             + 30%           + 20%              + 15%
Construction             + 35%           + 30%              + 20%
Aggregate storage        + 25%           + 30%              + 20%
Unpaved airstrips        + 15%           + 25%              + 20%
                                     55

-------
                               REFERENCES

1.  Cowherd, C., Jr., K. Axetell, Jr., C.  M.  Guenther,  and  G. A.  Jutze,
      Development of Emission Factors for Fugitive Dust Sources,  prepared
      for the U.S. Environmental Protection Agency, Office  of Air and
      Waste Management, Office of Air Quality Planning  and  Standards,
      Contract No. 68-02-0619, Publication No. EPA-450/3-74-037,  June
      1974.

2.  Personal communication from Mr. John Godar, Head, Planning  Depart-
      ment, Illinois Department of Transportation, District 8,  East
      St. Louis, Illinois, September 1975.

3.  Personal communication from Mr. Robert Barren, Mapping  Department,
      Missouri State Highway Commission, Jefferson City,  Missouri,
      November 4, 1975.

4.  Personal communication from Mr. George Daykin, County Engineer,
      St. Louis County, Clayton, Missouri, November 3,  1975.

5.  Climatic Atlas of the United States, U.S. Department  of Commerce,
      Environmental Science Services Administration, Environmental Data
      Service, U.S. Government Printing Office, Washington, D.C., June
      1968.

6.  Cowherd, C., Jr., C. Guenther, and D.  Wallace, Emissions Inventory
      of Agricultural Tilling, Unpaved Roads  and Airstrips, and Construc-
      tion Sites, EPA Publication No. EPA-450/3-74-085, November  1974.

7.  Kennedy, N., J. H. Kell, and W. S. Homburgcr, Fundamentals  of Traffic
      Engineering, 8th edition, Institute of  Transportation and Traffic
      Engineering, University of California,  Berkeley,  California,  1973.

8.  1969 Census of Agriculture, County Summary, Table 2,  U.S. Department
      of Commerce, U.S. Government Printing Office, Washington, D.C.
                                  57

-------
 9.   1971-72 Existing Land Use Update  and Analysis, Land Use Component
       Technical Report,  East-West Gateway  Coordinating Council, June 1973.

10.   "Generalized Existing Land Use  1970—-St. Louis Metropolitan Area,"
       East-West Gateway  Coordinating  Council,  1973.

11.   Thornthwaite, C. W.,  "Climates  of North America According to a New
       Classification," Geograph. Rev.,  2^:633-655 (1931).

12.   Personal communication from J.  Wiley Scott, Assistant State Soil
       Scientist, Soil Conservation  Service, Champaign, Illinois, July
       28, 1975.

13.   Personal communication from J.  Vernon  Martin, State Conservationist,
       Soil Conservation  Service, Columbia, Missouri, July 22, 1975.

14.   "Major Soils of the  North  Central Region,  U.S.A.," a map from Soils
       of the North Central Region of  the United States, North Central
       Regional Publication No. 76,  Bulletin 544, published by the Agri-
       cultural Experimental Station,  University of Wisconsin, in coop-
       eration with the U.S. Department of  Agriculture, June 1960.

15.   "Guide for Textural  Classification in  Soil Families," supplement
       to Soil Classification;  A Comprehensive System, Seventh Approxi-
       mation, Soil Survey Staff, Soil Conservation Service, U.S. Depart-
       ment of Agriculture, p.  40, March 1967.

16.   Gillette, D. A., "Production of Fine Dust  by Wind Erosion of Soil:
       Effect of Wind and Soil  Texture," paper  presented at the Atmos-
       phere-Surface Exchange of Particulate and Gaseous Pollutants, 1974
       Symposium, September 1974.

17.   STAR program, six stability classes (day/night), seasonal and annual
       listing, National  Climatic Center, Asheville, North Carolina,
       January 1970 - December  1974.

18.   Personal communication from Neil  Woodruff, U.S. Department of Agri-
       culture, Agricultural Research  Service,  Kansas State University,
       Manhattan, Kansas, January 10,  1974.

19.   Personal communication from John  Kinsey, East-West Gateway Coordi-
       nating Council, September-November  1975.

20.   1974 Short-Range Improvement Program,  East-West Gateway Coordinating
       Council, St. Louis, Missouri, June  1974.
                                58

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21.  1972 Census of Construction Industries,  Preliminary Report, U.S.
       Department of Commerce,  Bureau of  the  Census.

22.  County and City Data Book  1972,  a Statistical Abstract Supplement,
       U.S. Department of Commerce,  Bureau of the Census, U.S. Govern-
       ment Printing Office,  Washington,  D.C. (1973).

23.  Personal communication from Mr.  Charles  C. Masser, Project Officer,
       U.So Environmental Protection Agency,  Office of Air Quality Plan-
       ning and Standards, September 15,  1975.

24.  "Airport Services Tape," Federal Aviation Administration, Public
       Information Center, AIS  230,  Washington, D.C. 20591.

25.  1972 National Emissions  Report,  National Emissions Data System (NEDS)
       of the Aerometric and  Emissions Reporting System (AEROS), U.S.
       Environmental Protection Agency, Publication No. EPA-450/2-74-012,
       June 1974.
                                   59

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     APPENDIX A
EXAMPLE CALCULATIONS
  (RAPS GRID NO.  1)
         61

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 GRID DATA
           Number:   1
           UTM Coordinates:   E 640,  N 4235
           Size (length):   10 km
           County:   Franklin
           State:   Missouri
 ANNUAL SOURCE EXTENT
           Unpaved Roads:  gravel = 8,827 x 10^ vehicle miles
                           soil = 0 vehicle miles

           Agricultural Tilling:  11,104 acres
           Wind Erosion:  944 acres
           Construction:  147 x 10   acres
           Aggregate Storage:  0 tons
           Unpaved Airstrips:  0 LTD cycles
CORRECTION FACTORS
           Number of Dry Days Per Year (d):  250 days
           Precipitation-Evaporation Index (PE):  93
           Duration of Construction Activity (D):  12 months
           Silt Content:  Unpaved roads, gravel (sr):  16%
                          Dirt (sr):  40%
                          Agricultural tilling  (st):  40%
                          Unpaved airstrips (sa):  40%
           Vehicle Speed:  Unpaved roads (Sr):  30 mph
                           Unpaved airstrips (S&):  40 mph
ANNUAL EMISSION FACTORS
          Unpaved Roads:  EFr = 0.49 sr { —)(—'     lb
            r               J-           I or> I \ n C. c
            Gravel:  EFr = 0.49 (lb)
            Dirt:  EFV =  (0.49) (40)1=  13>4
          Land Tilling:  EFt = }'l .      ~
                            L   (PE/50)^  acre
                                         30/1365/ vehicle mile
                                         7  \
= 5.37
                                                         lb
                                                     vehicle mile

                                                         lb
                     r              30   365          vehicle mile
                         EF               .  12.72 -.
                           t    (93/50) 2          acre
           Wind Erosion:  EFW =0.9 tons /acre
                                    62

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          Construction:   EFC  - D
                                  acre

                          EF  = 12 months x 1 ton/acre = 12 ton/acre
                            c                   month
           Aggregate  Storage:   EFS =0.33
                                          ton stored
                                               t  \ /
           Unpaved Airstrips:   EFa = 0.49 (sa) (^Jj--!-.'    lb
                                                30/\365/ LTD cycle

                               „  . 0.49 (40)         \ - 17.9
                                                                 LTO cycle
                                               \ /\   /
ANNUAL EMISSIONS

           Annual  Emissions  (tons) = Annual Source Extent x Annual Emission Factor

           Unpaved Roads:  gravel = (8,827 x 1Q2 veh.  mile)(5.37 Ib/veh. mile)
                                                   2,000 Ib/ton
                                  = 2,370 tons

                          dirt = 0 tons

           Land Tilling:   (11,10* acres)(12.72 Ib/acre)  = 70-6 tons
                                  2,000 Ib/ton

           Wind Erosion:  (944 acres)(0.9 tons/acre) =  850 tons

           Construction:  (147 x  10   acres)(12 tons/acre) = 176.4  tons

           Aggregate Storage:  (0 tons)(0.33 lb/ton)(l  ton/2,000  lb) = 0 tons

           Unpaved Airstrips:  (0 LTO cycles)(l7.9  Ib/LTO cycles)(l  ton/2,000  lb) = 0 tons

TEMPORAL APPORTIONING FACTORS

           Temporal Apportioning  Factor =  (Seasonal Factor)(Day  of  the Week
                                          Factor)(Hour  of the  Day Factor)

           Example:  (Winter Factor)(Sunday Factor)(Hour 0 Factor)

           Unpaved Roads:  (0.214)(0.147)(0.009) = 283  x 10"6

           Agricultural Tilling:   1 x 10"6

           Wind Erosion:  1,713 x 10"6

           Construction:  8 x 10""
                                          63

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          Aggregate  Storage:   311 x 10"°

          Unpaved  Airstrips:   36 x 10"^

HOURLY  EMISSIONS

          Hourly Emissions  (tons) = Annual Emissions (tons) x Temporal
                                     Apportioning Factor

          Example:   Winter,  Sunday, Hour 0, Grid 1

          Unpaved  Roads:   (2,370 tons)(283 x 10"6) - 0.671 tons

          Agricultural  Tilling:   (70.6 tons)(l x 10~6) =70.6 x 10"6 tons

          Wind Erosion:  (850  tons)(l,7l3  x 10"6) =  1.46 tons

          Construction:  (176.4  tons)(8 x  10~6)  =  1.41 x 10~3 tons

          Aggregate  Storage:   (0 tons)(311 x 10"^) = 0 tons

          Unpaved  Airstrips:   (0 tons)(36  x 10~6) =  0 tons

METRIC UNITS CONVERSION

           Annual Emissions  (Mtons)  =  Annual Emissions  (tons) x 0.907185
                                                                (Mtons/ton)

           Hourly Emissions  (Mtons)  =  Hourly Emissions  (tons) x 0.907185
                                                                (Mtons/ton)
                                     64

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                         APPENDIX B
FACTORS AFFECTING ATMOSPHERIC TRANSPORT OF FUGITIVE DUST
                            65

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     This appendix presents an assessment of factors which determine
the drift distances of fugitive dust particles in the atmosphere.  Drift
distance is defined as the horizontal displacement from the point of
particulate injection to the point of particulate removal by ground-
level deposition.

     Factors to be considered in this assessment may be grouped into
two categories:

     1.  Meteorological factors - properties of the atmosphere which
affect contaminant advection and turbulent diffusion over surfaces of
varying roughness scales.

     2.  Source factors - height of injection and particulate properties
which affect gravitational settling and vertical mixing.

This assessment does not treat atmospheric washout of particulate matter.

METEOROLOGICAL FACTORS

     Fugitive dust particles are typically injected into the lower por-
tion of the "surface layer" region of the atmosphere which extends from
ground level to a height of about 100 m.  In this region the profile of
the wind and its turbulence characteristics are strongly dependent on
surface roughness properties.

     For neutral atmospheric stability, the vertical profile of mean
wind speed,  u(z) , in the surface layer is described by a logarithmic
relationship:

                                U.jt.
                                k

where     u* = friction velocity

           k = von Karman's constant (0.4 for clear fluids)

          ZQ = surface roughness height

Neutral stability occurs with wind speed exceeding 12 mph or with over-
cast conditions regardless of wind speed.

     The friction velocity, u*  , is related to the rate of momentum ex-
change at the  surface:
                                 66

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                                       1/2
                              =  
-------
        High Rise Buildings-
        (30+Floors )jy
          Suburban
          Medium Buildings-
          (Institutional)-!/
 E
 u
 o
N
X
O
LLJ
X
1/1
00
UJ
z
X
O
o
Suburban
Residential  Owe 11 i ngs_L/_
        Wheat Field JA
            Plowed FieldJ/-
                                Zo (cm)
                                  1000
           Natural SnowJy-
                            —800	
                            —600—

                             -400—
                                  -200—
                                   100
                             -80.0-
                             -60.0-
                            h-40.0_
                             -20.0-

                              10.0
  -8.0-
  -6.0-
—4.0—


  -2.0-

   1.0
                                 -0.8-
                                 -0.6-
                                	0.4—
                              -0.2-

                               0.1
                                          • Urban Area _i/
                                           Woodland Forest-?/
                                       Grassland -=-/
          Figure B-l.   Roughness heights for various  surfaces
                                   68

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 where     V,. = terminal settling velocity (cm/sec)
            s
                                         o
           p  = density of particle (g/cnr3)

            D = particle diameter (um)

 Fugitive dust particles typically have a mineral composition with a
 density of about 2.5 g/cm .

 CALCULATION OF DRIFT DISTANCE

      In the past,  most analyses of the atmospheric  disperison of par-
 ticles with appreciable settling tendencies have focused on the dis-
 tribution of settling rate,  S(x) , expressed as:
                            S(x)  - Vg C0(x)                           (6)


 where     C0 = the ground-level  concentration of particulate with
                  settling velocity  Vs

            x = downwind distance from the source

 Accordingly, an Eulerian approach to the problem has been taken.

      However,  analysis of particle drift with no net effect of atmospheric
 turbulence,  is most conveniently treated by a Lagrangian approach.   This
 is illustrated in the following  section.

     Case 1:  Monodisperse particles, single injection height, negligible
turbulence effect.

     Consider the case of a steady stream of monodisperse particles re-
leased from a continuous crosswind line source at height  h .  It is
assumed that each particle during its lifetime in the atmosphere is sub-
jected to a balanced set of vertical turbulent velocity fluctuations with
the result that the particle does not deviate appreciably from the tra-
jectory it would have in the absence of turbulence.

     The vertical position, z  ,  of the particle as a function of time is
given by
                              zp(t) = h-Vgt                          (7)
                                 69

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Substitution of Eq.  (7) into Eq. (1) gives the following expression for
the horizontal speed of the particle:
                                                                    (8)
     The particle drift distance, x  , is given by:
                                                                    (9a)
where the upper limit of integration is the lifetime of the particle
in the atmosphere.  Integration of Eq. (9a) yields
                                                                    (9b)
     To determine the effect of injection height and roughness height
on the drift distance of particles of given aerodynamic sizes, the wind
speed at z = 100 m was fixed at 6.9 m/s (15.4 mph) and friction velocities
were determined from Eq. (1).  The results are shown in Table B-l for
injection heights of 1, 3 and 10 m and for roughness heights spanning
the range given in Table B-l.  Figure B-2 shows the variations of  xp
for h = 3 m, measured above  ZQ .

     As expected, for particles of a given size, drift distance increases
with injection height and decreases with roughness height.  The latter
effect is a direct result of the decrease in wind velocity near the sur-
face caused by obstacles to the flow.

     Case 2:  Monodisperse particles, single injection height, turbulent
atmosphere.
     The analysis presented under Case 1 assumed that all particles gen-
erated from a particular fugitive dust source were deposited at the same
point downwind (xp).  Clearly, however, particles subjected to a pre-
ponderance of downward turbulent velocity fluctuations will settle from
the atmosphere at distances less than  xp  and particles propelled above
the trajectory defined above may drift far beyond  Xp .  In other words,
because of the random nature of turbulent velocities, Xp  approximates
the distance at which half of the particles have deposited on the surface.
                                  70

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                  Table B-l.   PARTICLE DRIFT DISTANCES CALCULATED FROM EQ.  (9b)
Injection Roughness
height,-/ height,
h zo
(m) (m)
I 0.01
0.05
0.10
0.50
3 0.01
0.05
0.10
0.50
1.00
10 0.01
0.05
0.10
0.50
1.00
Friction
velocity,
u*
(cm/sec)^
30.0
36.4
40.0
52.2
30.0
36.4
40.0
52.2
60.0
30.0
36.4
40.0
52.2
60.0
Drift distance, xp , by particle size
30 um
40.6 m
29.5
24.2
12.5
157.1 m
128.2
112.9
73.5
56.4
655 m
582
541
423
363
20 urn
91.2 m
66.4
54.4
28.1
353 m
288
254
165
127
1,474 m
1,309
1,216
952
816
10 um
366 m
266
218
113
1,418 m
1,157
1,019
663
509
5.92 km
5.25
4.88
3.82
3.28
5 um
1,460 m
1,060
871
450
5.66 km
4.62
4.07
2.65
2.03
23.6 km
21.0
19.5
15.3
13.1
1 um
36.6 km
26.7
21.8
11.3
141.8 km
115.7
101.9
66.3
50.9
592 km
525
488
382
328
a/  Injection height measured above roughness height.

-------
to
                                                                                       Injection Height (h) = 3m  above z<
                                                                                      	Natural Snow (zo= 0.1 cm)
                                                                                      	Plowed Field (z0= 1 .0 cm)
                                                                                      	—  Grassland (zo = 3.0 cm)
                                                                                      	  Suburban Residential
                                                                                              Dwelling (zo = 5.0 cm)
                                                                                      	Suburban Medium
                                                                                              Building (zo= 70.0 cm)
                                                  103                                    104

                                                            DRIFT DISTANCE (meters)
105
                            Figure B-2.  Relationship between particle size  and drift distance

-------
     The  specific  question addressed  here  has  to  do with  the  form of
 the  settling  rate  distribution.  Recalling Eq.  (6), this  problem re-
 duces  to  finding the distribution  of  ground-level concentration by
 solving the appropriate  transport  equations  and accompanying  boundary
 conditions.

     The  phenomena of quasi-steady advection and  turbulent  diffusion
 from a continuous  line source  under the  condition of  uniform  wind speed
 is described  by the  following  equation:
                                                                     (10)
where     C = particulate  concentration

          U = uniform speed of crosswind

          p = turbulence parameter.

The uniform wind speed, U  ,  is  assumed to have the value given by the
Case 1 velocity profile at z =  h.  The quantity pUz becomes the coef-
ficient of eddy diffusivity.
case in point, it has been shown=i/ that the distribution of ground-level
     Although Eq. (10) is not amenable to analytical solution for the
     in point, it has been shown=i/ th.
concentration has the following form:

                                     -h/px
                          Co(x) = A
where     A = constant
The function given in Eq. (11), and hence the settling rate, reaches a
maximum at:
and then decays to zero as  x—>« .  Values for  xL.ax  are given in
Table B-2 based on values of  p  determined by comparing the two forms
of the eddy diffusivity, yielding

                               p = ku*/U      .                      (13)

                                 73

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Table B-2.  DISTANCES TO POINT OF MAXIMUM SETTLING,
CALCULATED FROM EQ. (12)
Injection Roughness
height, height,
h
	 (m) 	
1



3




10




zo
(m)
0.01
0.05
0.10
0.50
0.01
0.05
0.10
0.50
1.00
0.01
0.05
0.10
0.50
1.00
Turbulence
parameter,
P
0.0347
0.0534
0.0695
0.2308
0.0281
0.0391
0.0470
0.0893
0.1456
0.0232
0.0302
0.0347
0.0534
0.0695
Friction
u*
(cm/ sec)
30.0
36.4
40.0
52.2
30.0
36.4
40.0
52.2
60.0
30.0
36.4
40.0
52.2
60.0
Values of a and xmax (m) by particle size
30
a
0.564
0.465
0.423
0.324
0.564
0.465
0.423
0.324
0.282
0.564
0.465
0.423
0.324
0.282
urn
^a^
18.4
12.8
10.1
3.27
68.3
52.4
44.9
25.4
16.1
276
226
203
141
112
20 um
« "max
0.251 23.0
0.207 15.5
0.188 12.1
0.144 3.79
0.251 85.3
0.207 63.6
0.188 53.7
0.144 29.4
0.125 18.3
0.251 345
0.207 274
0.188 243
0.144 164
0.125 128
10
a
0.0625
0.0515
0.0469
0.0359
0.0625
0.0515
0.0469
0.0359
0.0312
0.0625
0.0515
0.0469
0.0359
0.0312
pm
Xmax
27.1
17.8
13.7
4.18
100.5
73.0
61.0
32.4
20.0
406
315
275
181
140
5 um
« xmax
0.0157 28.4
0.0129 18.5
0.0118 14.2
0.0090 4.29
0.0157 105.1
0.0129 75.7
0.0118 63.1
0.0090 33.3
0.0078 20.4
0.0157 424
0.0129 327
0.0118 285
0.0090 186
0.0078 143
1
or
0.00062
0.00052
0.00047
0.00036
0.00062
0.00052
0.00047
0.00036
0.00031
0.00062
0.00052
0.00047
0.00036
0.00031
um
Xmax
28.8
18.7
14.4
4.33
106.7
76.7
63.8
33.6
20.6
431
331
288
187
144

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     The constant  A   in Eq.  (11) may be evaluated by equating the emis-
sion rate  E  to the  integrated settling rate.
                                       ff<
                        CoVs dx = AVS  /

                                     -
                         o
E = /   CoVQ dx - AVS /   ei+g   dx                 (14)
With the transformation  y = b/x  where  b = h/p  , the above equation
becomes
    AV   /"°
  '£/
    b  y
                                        dy
where   T(.oi)  is the gamma function.

     Similarly it can be shown that the mass fraction  K  of particles
remaining suspended beyond some distance  x  is given by:
where the incomplete gamma function  F(a,b/x)  is defined as


                             -b/x
                                           dy                       (17)
     The above analysis assumes that particles of all sizes are uniformly
responsive to turbulent diffusion.  More realistically, the time constant
of particle response to vertical velocity fluctions increases with in-
creasing aerodynamic particle size.

     In studies of the vertical flux of particulates over an agricultural
field undergoing wind erosion, Gillette et al.—'  have characterized this
phenomena in terms of the ratio  Va/u* .  If settling velocity is small
compared to the root mean square velocity fluctuation, i.e., Vg/u* <0.1 ,
the particulate is dispersed as a gas.  On the other hand for  Vs/u* ~ 1 ,
settling effects begin to predominate.  Clearly,  in the latter case, the
settling distribution is more strongly focused around the distance  xp .
                                   75

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     Case 3;  Polydisperse particles, distributed injection height, tur-
bulent atmosphere.

     This case is treated by separately analyzing the dispersion of
particles within narrow size ranges and injection height ranges and by
superimposing the results.  The analytical techniques to be used are
those described above.
                                 76

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                            REFERENCES TO
                             APPENDIX B
1.  Lettau, H. H., "Physical and Meteorological Basis for Mathematical
      Models of Urban Diffusion Processes," Chapter 2, Proceedings of
      Symposium on Multiple-Source Urban Diffusion Models, U.S. Environ-
      mental Protection Agency, Publication No. AP-86 (1970).

2.  Davenport, A. G., "The Relationships of Wind Structure to Wind Load-
      ing, in Wind Effects on Buildings and Structures," National Physi-
      cal Laboratory, Symposium 16, Her Majesty's Stationery Office,
      London (1965).

3.  Deacon, E. L., "Vertical Diffusion in the Lowest Layers of the
      Atmosphere," Quarterly J. Royal Meteorological Society, 75:89
      (1949).

4.  Gillette, D. A., and P. A. Goodwin, "Microscale Transport of Sand-
      Sized Soil Aggregates Eroded by Wind," J. of Geophysical Research.
      79(27):4080-4084, September 20, 1974.

5.  Bosanquet, C. H., and J. L. Pearson, "The Spread of Smoke and Gases
      from Chimneys," Trans. Faraday Soc.. 32:1249-1264 (1936).

6.  Gillette, D. A., and I. H. Blifford, Jr., "The Influence of Wind
      Velocity on Size Distribution of Aerosols Generated by the Wind
      Erosion of Soils," J. Geophysical Research. 79(27):4068-4075,
      September 20, 1974.
                                77

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                                   TECHNICAL REPORT DATA
                            (Please read Instructions on the reverse before completing)
 1. REPORT NO.
   EPA-450/3-76-003
                                                            3. RECIPIENT'S ACCESSIOWNO.
4. TITLE AND SUBTITLE
   Development of  a  Methodology and Emission Inventory
   for Fugitive  Dust for the Regional Air  Pollution
   Study
              5. REPORT DATE
               January.  1976
             6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)

   Dr.  Chatten Cowherd and Ms. Christine  Guenther
                                                           8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
   Midwest Research  Institute
   425 Volker Boulevard
   Kansas City, Missouri  64110
                                                            10. PROGRAM ELEMENT NO.
              11. CONTRACT/GRANT NO.
                                                            68-02-2040
 12. SPONSORING AGENCY NAME AND ADDRESS
   U.S.  Environmental  Protection Agency
   Office of Air and Waste Management
   Office of Air Quality  Planning and Standards
   Research Triangle Park, North Carolina   27711
              13. TYPE OF REPORT AND PERIOD COVERED

              	Final  Report	
              14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
        This report outlines  the methodology  that was used in developing an hourly
   fugitive dust emissions  inventory for the  Metropolitan St. Louis Air Quality
   Control Region as  part of  the Regional Air Pollution Study (RAPS).   The inventory
   encompassed the following  source categories:   (a)  unpaved roads,  (b) agricultural
   land tilling, (c)  wind erosion of agricultural  land, (d) construction sites,
   (e)  aggregate storage piles, and (f) unpaved  airstrips.

        Results presented in  this report include temporal apportioning  factors, county
   totals of annual source  extent and annual  emissions for each source  category.
 7.
                                KEY WORDS AND DOCUMENT ANALYSIS
                  DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS  C. COSATI Field/Group
  Regional  Air Pollution Study
  Fugitive  Dust Emissions
  Emission  Models
 3. DISTRIBUTION STATEMENT
  Release Unlimited
19. SECURITY CLASS (ThisReport)
   Unclassified
21. NO. OF PAGES

  84
                                              20. SECURITY CLASS (This page)
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                           22. PRICE
EPA Form 2220-1 (9-73)

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