EPA-450/2-77-029
October 1977
(OAQPSNo. 1.2-071)
GUIDELINE SERIES
GUIDELINE
FOR DEVELOPMENT
OF CONTROL STRATEGIES
IN AREAS WITH FUGITIVE
DUST PROBLEMS
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 2771 1
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EPA-450/2-77-029
(OAQPS No. 1.2-071)
GUIDELINE FOR DEVELOPMENT
OF CONTROL STRATEGIES
IN AREAS WITH FUGITIVE
DUST PROBLEMS
Monitoring and Data Analysis Division
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
October 1977
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OAQPS GUIDELINE SERIES
The guideline series of reports is being issued by the Office of Air Quality Planning and Standards (OAQPS)
to provide information to state and local air pollution control agencies; for example, to provide guidance
on the acquisition and processing of air quality data and on the planning and analysis requisite for the
maintenance of air quality. Reports published in this series will he available - as supplies permit from
the Library Services Office (MD-35), Research Triangle Park., North Carolina 27711; or, for a nominal fee,
from the National Technical Information Service. 5285 Port Royal Road, Springfield, Virginia 22161.
This report, based on a study by TRW, Inc., Redondo Beach. California, was furnished to the Environ-
mental Protection Agency in fulfillment of Contract No. 68-01-3152. Prior to final preparation, the report
underwent extensive review and editing by the Env ironmental Protection Agency. Subject to clarification
and procedural changes, the contents reflect current Agency thinking.
The mention of trade names or commercial products does not constitute endorsement or recommendation
for use by the Environmental Protection Agency.
Publication No. EPA-450/2-77-029
(OAQPS Guideline No. 1.2-071)
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TABLE Oh CONTENTS
Page
1.0 INTRODUCTION 1-1
T.I BASIC DEFINITIONS 1-2
1.2 SUMMARY OF PROCEDURES FOR DEVELOPMENT OF CONTROL
STRATEGIES FOR FUGITIVE DUST 1-4
2.0 ANALYSIS OF AIR MONITORING DATA 2-1
2.1 MONITOR SITE SURVEYS 2-1
2.2 NATURE AND EXTENT OF THE TSP PROBLEM 2-9
2.3 AIR QUALITY DATA ANALYSIS 2-11
3.0 EMISSION INVENTORIES AND PROJECTIONS 3-1
3.1 ESTIMATION OF BASEYEAR ANTHROPOGENIC FUGITIVE
DUST EMISSIONS 3-3
3.1.1 Motor Vehicles on Unpaved Roads 3-3
3.1.2 Entrainment of Street Dust 3-8
3.1.3 Construction Activities 3-9
3.1.4 Agricultural Tilling Operations 3-14
3.1.5 Off-Road Motor Vehicles 3-19
3.1.6 Unpaved Parking Lots and Truck Stops 3-20
3.1.7 Aggregate Storage Piles 3-21
3.2 ESTIMATION OF BASEYEAR WIND EROSION EMISSIONS 3-23
3.2.1 General Methodology 3-24
3.2.2 Soil Erosion Emissions from Specific
Source Categories 3-25
3.3 PROJECTION OF FUGITIVE DUST EMISSIONS 3-38
3.3.1 Anthropogenic Sources 3-38
3.3.2 Wind Erosion Sources 3-43
4.0 EMISSIONS/AIR QUALITY RELATIONSHIP 4-1
4.1 SOME FACTORS AFFECTING SELECTION OF THE
SOURCE-RECEPTOR RELATIONSHIP 4-1
4.1.1 Averaging Time 4-1
4.1.2 Source Configuration 4-2
4.2 DESCRIPTIONS OF SUGGESTED AIR QUALITY MODELS .... 4-3
4.2.1- AQDM and COM 4-4
4.2.2 The Atmospheric Transport and Diffusion
Model 4-4
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TABLE OF CONTENTS (cont'd.)
4.2.3 Hanna-Gifford Model 4-6
4.2.4 Modified CDM/Rollback Model ... 4-7
4.3 SUMMARY 4-9
5.0 ALTERNATIVE CONTROL MEASURES 5-1
5.1 CONTROL OF DUST FROM UNPAVED ROADS 5-1
5.2 CONTROL OF ENTRAINED STREET DUST 5-10
5.3 CONTROL OF DUST EMISSIONS FROM CONSTRUCTION AND
DEMOLITION ACTIVITIES 5-16
5.4 CONTROLS FOR AGRICULTURAL DUST EMISSIONS 5-20
5.4.1 Continuous Cropping 5-20
5.4.2 Crop Residue and Modified Tilling
Operations 5-21
5.4.3 Limited Irrigation of Fallow Melds 5-23
5.4.4 Windbreaks and Stripcropping 5-23
5.4.5 Chemical Soil Stabilizers 5-24
5.5 CONTROL OF TAILINGS PILES 5-25
5.6 CONTROL OF UNPAVED PARKING LOTS AND TRUCK STOPS. . . 5-27
5.7 CONTROL OF EMISSIONS FROM DISTURBED SOIL.
SURFACES b-27
6.0 INTEGRATION OF FUGITIVE DUST SOURCE IMPACTS INTO
THE STATE IMPLEMENTATION PLANNING PROCESS 6-1
6.1 INTRODUCTION 6-1
6.2 EVALUATION OF CONTROL STRATEGY 6-2
6.2.1 Impact of Control Strategy on Emission
Levels f>-2
6.2.2 Cost of Strategy 6-3
6.3 GUIDES FOR THE SELECTION OF REASONABLE CONTROL
MEASURES 6-4
6.4 IMPLEMENTATION ASPECTS 6-6
6.4.1 Demonstration Project 6-8
6.5 CONCLUSION ..... 6-10
APPENDIX A A-l
APPENDIX B. DETAILED DESCRIPTION OF THE HANNA-GRIFFORD
MODEL B-l
APPENDIX C. MODIFIED CDM/ROLLBACK MODEL C-l
APPENDIX D. INFORMATION REQUIRED AS INPUT TO THE
CDM/ROLLBACK MODEL D-l
APPENDIX E. SAMPLE APPLICATION OF THE CDM/ROLLBACK
MODEL E-l
REFERENCES F-l
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1.0 INTRODUCTION
The purpose of this document is to outline a methodology for development of
control strategies for areas experiencing nonattainment problems due to fugitive
dust emissions. Historically, relatively little attention has been focused on
control of fugitive dust sources. Awareness of the nature and extent of these
sources has been very limited, and potential dust control measures have not been
generally implemented. As the extent of the fugitive dust problem has become
evident, more effort is now being applied to characterize dust sources and to
develop methods for their control. This document synthesizes the results of
these recent efforts and establishes an overall procedural method for the devel-
opment of air programs to control high TSP levels caused by fugitive dust.
However, this document does not address the various policy issues associated
with fugitive dust control such as definition of those areas where control plans
should be developed or new source review as outlined in the Fugitive Dust Policy
Paper dated August 1, 1977.
Many states are now facing the problem of controlling fugitive dust.
Previously, it was routinely believed that fugitive dust emissions were unavoid-
able. However, recent studies show that while some fugitive dust emissions are
mainly a result of natural phenomena, most frequently fugitive dust sources
result directly from or during human activity. In this sense, most fugitive
dust sources are controllable although the extent of control required for attain-
ment of the National Ambient Air Quality Standards (NAAQS) may impose unreason-
able demands.
Before control strategies can be systematically formulated and evaluated,
essential and basic technical analyses must be performed. Chapters 2, 3, and
4 summarize the analytical foundation for the strategy development process.
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Subjects discussed in these chapters include: (1) representativeness of monitor-
ing sites and characterization of air quality levels; (2) compilation of parti-
culate emission inventories for the base year and projected inventories for
future years*; (3) formulation of a model to translate emission levels into sus-
pended particle concentrations. The. final chapters contain a procedure for
formulation and evaluation of an appropriate control strategy, including the
consideration of emission control effectiveness, air quality impact, costs and
implementation problems.
1.1 BASIC DEFINITIONS
Fugitive Dust - A type of particulate emission made airborne by forces of
wind, man's activity, or both, such as unpaved roads, construction sites,
tilled land or windstorms. A summary of the various significant categories
of fugitive dust sources is listed in Table 1-1. Two major categories are
identified: anthropogenic sources (those which result directly from and
during human activities) and wind erosion sources (those resulting from
erosion of soil by wind). Fugitive dust is distinguished from fugitive
(industrial process) emissions as defined belpw;
Fugitive Emissions - Particles which are generated by industrial or other
activities and which escape to the atmosphere not through primary exhaust
systems, but through openings such as windows, vents or doors, ill-fitting
oven closures, or poorly maintained equipment. Aggregate storage opera-
tions and active tailing piles are included in this category of sources.
*Refer to EPA's maintenance regulation in Subpart D, 40 CFR 51.
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TABLE 1-1. FUGITIVE DUST SOURCES CATEGORIES
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Anthropogenic Fugitive Dust Sources
V . Unpaved Roads
g . Agricultural Tilling
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. Inactive Tailing Piles
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. Construction Activities
. Street Dust
. Off-Road Motor Vehicles
9 Wind Erosion Fugitive Dust Sources
_ . Unpaved Roads
. Agricultural Fields
Disturbed Soil Surfaces
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and Baj,eJ ine - In assessing the impact of proposed emission
control strategies, it is necessary to characterize the extent and
nature of the existing and anticipated conditions related to tiie air
pollution problem. These "nominal" conditions are referred to as the
baseline. Important baseline information concerns; (1) baseline emis-
sions; (2) baseline air quality; (3) baseline control policies; and,
(4) baseline meteorology. For the purposes of this document, the base-
line consists of the baseyear, and projections for future years*. The
baseyear is selected as the current or recent year, depending on the
availability of information to characterize the air pollution problem
suitably.
In formulating control plans, it is necessary to distinguish between
control measures and control strategies. A control measure refers to a
specific emission reduction method applied to a certa-in source category.
A control strategy consists of a collection of various control measures
to be implemented jointly.
1.2 SUMMARY OF PROCEDURES FOR DEVELOPMENT OF CONTROL STRATEGIES FOR
FUGITIVE DUST
Scope and Objectives
The development of an air pollution control strategy designed to
attain and maintain the National Ambient Air Quality Standards (NAAQS)
requires an analysis of current and possible future air quality problems.
It is the objective of this Section to briefly present the quantitative
and qualitative procedures used in developing an acceptable plan for the
*Refer to EPA's maintenance regulation in Subpart D, 40 CFR 51.
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control of fugitive dust. The amount of work involved in each step will
| vary from area-to-area depending on available data, magnitude of the par-
^ ticulate problem, types of emissions sources, etc.. These steps can be
summarized as follows:
Step 1. Review air quality monitoring data to characterize nature
and extent of suspended particulate problem.
a. Assess representativeness of monitor sites. Characterize
the general area and tite site-specific area around the
| monitor. Identify local factors which exert influence on
TSP measured at each site. Establish history of these
W local influences and anticipated status in near future.
m Evaluate if TSP levels at the various sites are represen-
tative of (1) the general area surrounding the monitor, or
(2) only the specific area near the monitor. Assess the
implications of representativeness of station measurements
ฃ for the utility of the particu'iate air quality data. If
local sources contribute substantially to tne problem,
B this may indicate that local sources need to be controlled,
whereas if analyses indicate areawide sources contribute
to the monitor, then areawide controls should be considered.
b. Analyze patterns of the air quality data to characterize the
suspended particulate problem. Various analytical procedures
may be employed to develop insights into the origin and
factors affecting the particulate problem. The most signifi-
cant of these analyses concerns the apparent relationship
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between meteorology and FSP levels. Evaluate measured
data to determine seasonal patterns of TSP and associated
meteorology affecting the^e levels. Analyze daily meteor!ogy
and TSP data to determine apparent effect of meteorology on
TSP. Analyze meteoroloyiv dl circumstances associated with
particulate problem: TSP trends at various sites may be
examined, statistical correlations between TSP levels at
various sites can be developed, and the geographic distribu-
tion of TLiP levels may i^veal significant spatial patterns
in the air quality -.hu ป,- nonattainment problems. Several
ฐ>f these potent^': aialjsU methods are described in
reference 1. i'<~ v a? in, ihls. analysis may show if
local or specific scan :es contribute substantially to the
problem, thus indicating the type of sources that need to
be control!ea.
Step 2. Develop the baseline particulate emissions inventory for
sources significantly jffecting the problem area.
a. Identify particulate sources which may exert significant
effect on the area experiencing the nonattainment problem.
Such sources may be looted both within the urban areas
and in the surrounding rural areas several miles from the
urban centers. Determine the geographic area to be
included In the analysis based on the relative significance
and proximity of ^ral sources compared to other urban
sources.
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b. Select a uaseyear and estimate the emission levels for
| conventional sources including fuqitive emission and fugitive dust
sources in tiiat year. If seasonal levels vary distinctly,
estimate emission levels by season as well. Document the
flj emission inventory in terms of an emissions grid network.
c. Project the baseyear emissions inventory to future years*
by considering projected growth predictions related to the
various emission sources. Predict probable emission levels
II and spatial distribution of these levels, and express in
terms of emissions grid network.
Step 3. Formulate an emissions/air quality relationship.
m Evaluate alternative source-receptor models and select an
appropriate relationship. No single model is presently
I available for application to all areas where substantial
impact of the particulate emissions arises from larger
ฃ particles originating from the fugitive dust source types.
In lieu of a complete theoretical model which is capable of
accounting for deposition of particles, there are several
m approaches that have been utilized in previous studies
(Section 4). It is believed that these techniques do have
I application in those arid western areas with fugitive dust
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problems. Continued use of AQDM and COM appears to be most
I reasonable approach for those areas where particles less than
10 micrometers predominate.
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Step 4. Characterize alternative control measures for application
to significant fugitive dust sources. Identify control
Refer to EPA's maintenance regulations in Subpart D
40 CFR 51.
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methods available for mitigation of the area's most signifi-
cant dust sources. Determine probable effectiveness of
these methods in the subject area. Consult with local
agencies to derive estimates of cost for the candidate
control measures. Calculate expected cost effectiveness
of the various measures, and compare results.
Step 5. Select a control strategy and evaluate the impact of the
strategy on air quality.
a. Select a control measure for application to each of the
major source categories and specific geographic areas
which are the cause of high TSP levels in the nonattainment
area. The control measure selected should reflect the
technical feasibility and reasonableness of the control,
and will usually vary from region-to-region due to several
general factors. These factors should be considered before
final selection of the optimum control measures. Because
of the many candidate controls for fugitive dust sources,
selection of the overall control strategy may typically be
an iterative process accomplished by means of successive
alternative trials.
b. Evaluate the proposed strategy in terms of its impact on
emission levels and TSP levels, and adjust the strategy to
meet the primary air quality standards. Control effective-
ness data are used to estimate emission levels resulting
from the strategy, and the air quality model is employed
to estimate resulting air quality. To obtain this objective,
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degree of control, geographic area of control , type of
m control, and timetable of the control are manipulated
iteratively until trie strategy achieves the primary standard.
ff c. Estimate the cost of tiie proposed strategy, and assess
the problems associated with its implementation. Political,
legal , and socioeconomic obstacles should be assessed,
and consideration should be given to alleviating problems
- arising from strict regulatory approaches by adoption of
. an alternative approach providing for integration of the
dust control measures into ongoing governmental agency
flj programs. A demonstration strategy can be considered as
the first step in the development of the total strategy
M which can reflect phased development.
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SUMMARY
ฃ The remaining sections of the text provide detailed information
_ regarding how to consider fugitive dust in the State Implementation
Plans (SIP's).
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2.0 ANALYSIS OF AIR MONITORING DATA
In conducting preliminary analyses required for the technical base
of the control strategy formulation, existing air monitoring data must
fl| be analyzed to characterize the nature and extent of the suspended par-
ticulate problem. This characterization establishes the overall scope
of the problem and aids in identifying origins of the particulate prob-
lem. This chapter outlines the procedures which may be employed to ana-
| lyze the air monitoring data including monitoring site surveys,
statistical analysis of air quality data, identification of relationships
between TSP levels and meteorology, and relationships between TSP levels
and nearby sources.
2.1 MONITOR SITE SURVEYS
_ Many decisions concerning air program planning are dependent upon
the placement of the sensors used to measure air quality. Because ambient
pollutant levels often vary substantially throughout a planning area, it
is evident that contrasting siting procedures can result in totally
different air quality characterizations. These differences have important
implications on the nature of planning decisions for air quality standards
| and implementation programs.
Ultimately, a monitoring network cannot possibly satisfy all siting
criteria. However, the network can still be very useful. This utility
m can be assured when an understanding of the representativeness of the
monitors, and the relative levels of air quality measured there to other
V unmeasured areas in the study area, is fully developed. One means of
developing this understanding is the site survey.
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In conducting the site surveys, the geographic range of representa-
tiveness of the monitor is estimated by observation of local sources and
topography surrounding the monitor. Figures 2-1 through 2-3 illustrate
some potential source orientations with respect to monitor stations. In
Figure 2-1, the monitor is located in a rather homogeneous field of
sources, and the measurements should be representative of the general
area. In Figure 2-2, the monitor is source oriented in an uneven field
of sources, and measurements there may only be representative of a very
limited space around the sensor. In Figure 2-3, the monitor is repre-
sentative of the shaded region of area source emissions.
Figure 2-1. Monitor 1n
Homogeneous Field of
Point Sources. Repre-
sentation of General Area.
Figure 2-2. Monitor in
Inhomogeneous Field of Point
Sources. Site-Specific
Representativeness.
Figure 2-3. Monitor in Field
of Area Sources (shaded). Site-
Specific Representativeness.
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A major i^sue In the representativeness of any monitor- (such as that
flj in the example above) concerns the placement of the sensor with respect
to sources and topography immediately adjacent to the site. If the sensor
is placed directly in an emissions plume, the measurements derived from
the sensor will be dominated by this local source. If the source is well
ฃ described and can be quantitatively assessed, the domination of measure-
. ments may also be assessed and the readings recorded by the monitor may
* serve as indicators for air quality nearby. However, it is more desirable
B1
that the sensor be placed in areas where source emissions are relatively
mixed and spatial variations in concentrations are less dramatic. This is
particularly the case when the local influences next to the monitor are
not easily described, and their accountability in the measurements is inde-
ฃ terminant. A sensor located next to physical obstructions (i.e., too
^ close to ground, near a wall) can fail to sense the desired pollutant
concentrations because ambient air streamlines are directed away from
m the site.
In summary, the air quality measured at a given monitor may be repre-
sentative of either a broad or confined area. In either case, if the rela-
tionship of air quality at the sensor site to air quality at other nearby
| points can be understood, the monitor is representative in a useful way.
If it is not possible to estimate or assume this relationship with some
certainty, the measurements obtained at the monitor are of limited utility.
A However, the data could be used to estimate the degree of control needed for the
impacting sources to achieve National Ambient Air Quality Standards. Site
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surveys can provide the information necessary for these appraisals.
Si te Review Procedure
Figure 2-4 illustrates a proposed scheme for evaluating the represen-
tativeness of air quality measured by the existing monitoring network. The
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a first step in the process involves a compilation of preliminary data prepara-
* tory to the site characterizations. Frequently, significant changes in the
surrounding environment have affected air quality levels and representative-
ness of air quality at the monitor site. These changes should be documented
based on records of the local monitoring agency, and the actual site visits
later.
ฃ Each of the monitor sites should be visited, and photographs and plot
layout diagrams should be performed to characterize the site environment
and the placement and location of the monitor.
m Both the general area surrounding the site (immediate vicinity in
all directions) and the specific area at the site should be observed and
f characterized. Potential significant sources of particulate emissions should
be noted and described. These sources include soil dust surfaces subject to
m suspension influences such as vacant lots, open fields, unpaved road shoulders,
residence yards, unpaved roads and parking lots, excavated areas, and agricul-
tural lands. Observations of the general area can be greatly aided by the
m use of aerial photographs if available. Brief interviews with local residents
or employers may be conducted to establish changes which have occurred, or
I are expected to occur, in the monitor environment. The historical changes
should be documented so that it may be known what the measurements were repre-
senting at any given time of reference (i.e., the baseyear).
Based on the characterization of the general and specific areas surround-
m ing the monitor site, the representativeness of the monitor in expressing TSP
levels of the local area should be assessed. For sites whose air quality is
typical of that of the general area, the measurements there have direct
* utility in representing ambient TSP exposure levels.
For other sites where the significance of factors affecting the repre-
sentativeness is uncertain, potential bias should be identified, and awareness
of this bias should be maintained throughout the subsequent analysis of the
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source-receptor model and control strategy formulation.
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No precise formula may be outlined for conducting site reviews.
Obviously, the procedures will vary greatly depending on budget, the
monitoring network, and the requirements of the control objectives.
The basic elements comprising the review are illustrated in the case
example (Figure 2-5) provided on the following page. In this example,
the characterization of the general area and the specific environment
around the site were found to contrast. Sources were prevalent adja-
cent to the site, which were not typical in the general environment.
Accordingly, TSP levels at the site environment were judged to be
representative in a site-specific manner only.
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0_F__SITE_SP_t.CIF 1C ENVIRONMENT
The plot de.criotion of Figure 2-6 provides an orientation for structures, objects, and emission
sources in the iumpdiate vicinity of the hi-vol at the St. Johns site. The hi-Vols is located or, the
rooftop of the St. Johns Indian School administration building. The roof is approximately lb feet
above ground level, and the sampler is mounted on a conventional stand 1-1/2 feet above the flat tarpaper
rooftop The sanoler has adequate vertical clearance with all nearby objects to the east, north
and northwest, but there are potentially significant vertical barriers to wind movement from south
of the hi-Vol, and rises at its peak to an elevation of 20 feet about the hi-Vol sampler. A small
rooftop room rises 8 feet above the hi-Vol sampler only 12 feet to the southwest. Air movement from
the west is obstructed by a school building which rises 8 feet above the sampler. A thick hedqe of
trees rises 4 feet above the1 Hi-Vol to the northeast. These obstacles, in addition to the high elevation
of the sampler above ground, ire apt to prevent dust levels experienced at ground level from being
measured by the rooftop sampler.
The most significant local source of particulates consists of fugitive dust. The suspenstoi of
this dust is related to vehicle activity and other activities which disturb the ground surfa:e sifficiently
to permit suspension of soil by wind. Almost all activity in the immediate vicinity of the St. Johns School
occurs on soil surfaces. Party measurements may be considered
negligible. Then is no immec iate plan which would affect significant environmental changes to alter this
situation in the uture (1980 and 1985).
Pinure 2-5. Case Example of Monitor Site Review: St. Johns Monitor in Phoenix Area
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LEGEND:
Designates Location and Orientation for Photographs
Soil Surface
Elevation44frป ^/.-ฐ^e Ground Level)
rm fi**
IfcMWf^***
Plot Schematic of Environment in Immediate
Vicinity of H1-Vo1 Monitor Site
Figure "2-6 St. Johns Hi-Vol Monitor Site
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2.2 Nature and Extent of the TSP Problem
The air quality data should be analyzed to assess the nature of TSP
problem. In assessing the origin of TSP levels and the factors affecting
these levels, it may be useful to analyze the apparent relationship between
meteorology and TSP. The effect of meteorology on TSP levels will provide
indications of the TSP origins, that is, whether the sources are predomi-
nantly anthropogenic fugitive dust, wind-blown dust, or conventional sources.
The TSP/meteorology relationship may be demonstrated by: (1) evaluating
seasonal patterns of particulate levels and the associated meteorology
affecting the levels; (2) analyzing daily meteorology and air quality data
to isolate effects of single meteorology parameters on air quality; arid
(3) investigating the meteorological circumstances associated with particu-
late episodes and other days of interest.
Examples of procedures which may be used in demonstratina the TSP/
meteorology relationship are described in the Phoenix Study. In that
study, analysis of particulate episodes revealed clear patterns between
meteorology and high TSP levels. Table 2-1 illustrates the two distinct
patterns occurring in the Phoenix area. These patterns are typical of areas
where high levels of TSP are caused mainly by fugitive dust. In the winter-
time, when low wind speeds and low mixing heights limit dispersion of parti-
culate emissions, high ambient concentrations generate consistently at the
city monitoring sites (Categories land 2). Particulate levels also increase
at other stations throughout the entire region, but generally to a lesser
degree. For the episodes associated with strong wind gusts, particulate
concentrations are highest in the rural and suburban residential areas
(Categories 3 and 4). This behavior is consistent with known facts regard-
ing the particulate sources:
2-j
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TABLE 2-1. PARTICULATE EPISODES IN PHOENIX AREA, 1973-1975.
STATHN
CATEGI RY
1
3
2
4
1
4
2
2
1
3
4
4
4
2
1
1
3
1
2
2
1
3
2
3
3
3
3
3
3
3
4
3
4
2
NA
*
DATE & STATIONS
November 12, 1973
Downtown Phoenix
Paradise Valley
West Phoenix
Chandler
November 18. 1973
Downtown Phoenix
North Phoenix
West Phoenix
Central Phoenix
January 17. 1974
Downtown Phoenix
Paradise Valley
West Phoenix
Chandler
June 16. 1974
Chandler
Mesa
Central Phoenix
Downtown Phoenix
November 13, 1971
Downtown Phoenix
Paradise Valley
South Phoenix
Central Phoenix
December 19. 197^
Arizona State
Downtown Pheonlx
Paradise Valley
Central Phoenix
March 25. 1975
Paradise Valley
LHchfield
St Johns
N Scotts/Paradise
June 17. 1975
N Scotts/P&radlse
St Johns
LUchfield
North Phoenix
August 10. 1975
St Johns
North Phoenix
Central Phoenix
Glendale
- no' available
St. tion Category: 1
2
3
4
5
6
AVERAGE RESULTANT
FIXING NO. OF DAYS WIND WIND DIR.
CONCENTRATION HEIGHT SINCE RAIN SPEED AND MAGNI- TEMP.
U0/m3 (Meters) , MPH) TUDE.
513 253 120 6.0 'M- 5.1 70
439
364
355
ซ8 394 ,26 98 jf. 3>9 63
389
337
480 108 9 43 -J_ 4j 58
351 trl
279
261
372 J888 75 10<9 -f- 6-1 98
322
239
454 352 n 3.7 \- 1.9 64
255 '
252
234
460 261 14 5.3 ^(- z.z 54
260
234
842 NA 11 12.2 -^- 4.6 66
379
346
295
1083 NA 69 11.4 ~T~ 4.8 88
798
519
248
456 NA 25 IX. 4 f O.J %
343
287
262
' Centr. 1 City/residential commercial surrounded by fugitive sojrces.
> Centr.l City/residential, no source In immediate surroundings.
Rural, - residential , surrounded by fugitive sources.
Surbu'ban/residtntial , surrounded bv fugitive sources.
Rural, residential , no sources immed'ately nearby.
Remote
GENERAL
COMMENTS ON
WEATHER
haze most of
day. Maximum
wind speed 13
mph.
Partly cloudy
& thunderstorms
and wind gusts to
36mph beginning
at night.
Haze much of day.
Maximum wind speed
1 3 mph .
Clear, wind
gusts from SE at
43 mph.
Cloudy much of
day. Maximum
wind speed 13 mph.
Clear. Maximum
wind ipscd 12 mph.
Partly cloudy.
Wind gusts from
west at 35 mph.
Clear. Wind
gusts from West
at 35 mph.
Partly lluutly.
Wind gusts from
SE at 47 mph.
2-10
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I
. Human activity, which is most densely focused in the city
area, is responsible for sir pension of substantial fugi-
tive dust emissions. These emissions are of higher den-
ฃ sity than those released at the rural sites, and this is
reflected by the higher concentrations produced during
flj the stable atmospheric conditions of winter.
. Because vast expanses of agricultural land, unpaved
roads, and unimproved (but disturbed) soil surfaces
surround the rural sites, suspension of dust by soil
| wind erosion is very likely a dominant factor affecting
^ high particulate levels during gusty winds in the rural
m areas. Soil erosion by wind is of less consequence in
the more developed areas.
Various additional analyses of the data may be performed to char-
acterize the particulate problem. Examination of TSP trends, statisti-
cal correlations between TSP levels, interpretations of pollution
8 roses, and inspection of geographic distributions of TSP levels are a
few examples of the analyses which may be performed.
2.3 Air Quality Data Analysis
" Two methods have been suggested to determine to what extent a
given site 1s responding to areawide emission patterns or one or two
dominant nearby sources. The first of these is the pollution rose.
This is simply a graphical presentation of the average concentration
4
associated with each wind direction. Such a display requires only
g daily resultant or 3-hour average wind data along with TSP concentra-
tions. The calculation is relatively simple. It is useful to
W review the pattern for each individual site to determine if a particu-
lar or general wind direction is associated with high TSP levels.
2-H
I
-------
Particular directions with higher concentrations may indicate a
particular source or small cluster of sources; higher concentrations
in a general wind direction may indicate an industrial area or a
weather pattern where rains and cleaner air are associated with one
wind direction and stagnant conditions with another. Reviewing
several sites in the same urban area may indicate which is the case. '
A second indication of local influence may be formed by comparing
the consistency by which concentrations are similar or dissimilar at
neighboring sites on the same day. Various statistical analysis
(e.g., such as a multiple correlation analysis or use of a chi-square
test on the data among all sites for several years of data has been
used to indicate the level of correlation between neighboring sites).
Either calculation may be used to indicate which group of sites tend
to have generally similar levels. Similar levels between sites may
indicate that the sites are influenced by areawide pollutant concentra-
tions or meteorological patterns and strongly dissimilar levels may
indicate an influence by a nearby source that does not strictly adhere
to the general emission patterns of the urban area.
The multiple correlation analysis may be extended to include
meteorological variables. Data such as wind speed or rainfall may
indicate which sites are affected by wind-blown dust storms or fugitive
dust from dry conditions. A recent study used average annual values
of rainfall to indicate that changes in annual rainfall did influence
TSP concentrations
A multiple regression analysis of 5-year data sets from 10 cities
showed that a l-1nch decrease 1n precipitation is associated with an
3
increase in annual TSP levels of 4 pg/m . Such techniques must be
viewed with caution because the relationship may not be precisely
2-12
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I
linear as implied by the regression. Non-linear transformations
of the data are recommended where appropriate.
| The effect of long-range transport on TSP levels may be indi-
cated by the calculation of the path of the air parcel as it moves
across the U.S.. Such calculations have been made by computer aided
analysis using a model developed by NOAA, Air Resources Laboratory.
Such analysis may be used to indicate the general geographical sources
of exceptionally high TSP or sulfate levels.
Several other methods have been used to provide gross estimates
TSP problem assessment study. This study indicates that there is
of the sources of TSP. One such method is summarized in a National
1
I
a relatively constant average contribution from general urban activity
from city-to-city. Using this empirical value, known values of non-
urban background and secondary TSP, it is possible to determine
iteratively which sites have major influence from local sources and
the approximate level of impact of industrial particulates on TSP
levels. Another method to indicate, in a very general way, the rela-
tive contributions due to traffic and industry is to calculate changes
fj in weekend and weekday concentrations. To do this, the daily varia-
tions in both industrial emissions and average daily traffic should
be known.
Another aspect of data analysis is the examination of the hi-vol
filter to determine the components of the aerosol on the filter. The
most straight-forward approach is polarized light microscopy. This
technique can yield a semi-quantitative assessment of the generic type
H of particulate. Such an examination should be undertaken only in con-
junction with a quality control program to ensure the consistency and
^H
I
replicability of the results-
2-13
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More sophisticated techniques for the identification of individual
particles are available, but resource limitations usually preclude
their widespread application. Such techniques include scanning electron
microscopy, Ramon spectroscopy, Electron Scanning for Chemical Analysis
(ESCA) and electron microprobe.
SUMMARY
In general, the site reviews and data analysis performed in the
preceding Sections provide a useful tool for assessing whether local
or specific sources contribute substantially to the problem, thus
Indicating the type of sources that need to be controlled. Also, this
qualitative assessment can be employed to indicate areas where the
results of modeling analysis (discussed in Section 4.0) should be used
with reservations as to their representativeness.
2-14
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I
fl 3.0 EMISSION INVENTORIES AND PROJECTIONS
The development of air pollution co-.trol strategies depends on a
detailed knowledge of the quantity and character of pollutant emissions
m in the region. Appreciable concern has been devoted to the character-
ization of conventional sources, and various data sources (i.e. NEDS)
are available for the rapid assembling of regional and area-specific
emissions. With the realization that fugitive dust emissions also exert
I a substantial impact on air quality nonattainment problems, efforts
are now being increased to develop detailed characterizations of the
g various fugitive dust sources. Such efforts have recently been employed
q
to develop a fugitive dust emissions Inventory for the Phoenix area,
B The procedures employed during the Phoenix Study are generally applicable
for characterizing fugitive dust emission in other regions as well, and
are summarized herein. This chapter provides an outline of recommended
I procedures, including numerous examples of applications as applied to
the Phoenix Study. Section 3.1 concerns the estimation of emissions for anthro-
pogenic fugitive dust sources and Section 3,2 Involves estimation of fugitive
dust emissions resulting from wind erosion. Section 3.3 describes the general
m considerations associated with forecasts for emission levels in future years.
ซt The procedures for compilation of conventional sources emissions are
not repeated here. They have been in use for some time and are documented
in the literature. ' The emission factors given herein are com-
patible with AP-42, "Compilation of Air Pollutant Emission Factors" or
]| will be reflected in future updates to AP-42. As improvements in these
factors are made, they will also be reflected in AP-42; therefore, the
user should assure that the latest information is used.
I
I
-------
For potential utility in air quality impact analysis, estimates of
both fugitive and conventional emissions should be organized and spatially
disaggregated for description in a point source and grid network of the
study area. Each emissions category should be adequately described and
reflected in the grid network. Area source emissions should be tabulated
for each of the grid squares for modeling purposes. The grid boundaries
are defined by considering all sources which might significantly affect
air quality in the target control area as well as any model constraints
that exist. For areas characterized by numerous fugitive dust sources,
relatively small grid squares, but not less than a kilometer on a side,
should be considered to permit analysis of the Impact of these sources
on a local scale. When practical, emission sources should be spatially
resolved to a greater level of discrimination immediately around the
monitor sites. The gridding procedures have been in use for some tine
and are well documented in the literature.1 One of the modeling
approaches discussed in Section 4 uses particle size ranges for describe
ing the air quality/emissions level relationship. This d1saggregation
by particle size range 1s based on particle size information contained
within this section.
Emission inventory grid systems may be developed after, or before,
the emissions are calculated. For Inventories involving extensive
evaluation of small scale or localized problems where it is critical
that emissions be located fairly precisely, it 1s usually necessary to
use preliminary Inventory results and knowledge to develop the grid
system 1n advance of locating and quantifying all the sources. If the
alternate approach of developing the grid system after calculations are
complete is used, then many area source emissions will have to be re-ap-
portioned from aggregate totals to various grids by approximate
3-2
-------
I
ฃ and locally customized apportioning factors. The former procedure is
usually preferable for fugitive dust considerations.
I
3.1 ESTIMATION OF BASEVEAR ANTHROPOGENIC FUGITIVE DUST EMISSIONS
For the context of this document, anthropogenic fugitive dust
sources are considered to be those resulting directly from, and during,
human-related activities. These include motor vehicles on unpaved
and paved roads, off-road motor vehicle activity, construction activities,
etc.. Section 3.1.1 through 3.1.7 outline general procedures for estimating
ฃ emissions levels from several of these sources.
I
3.1.1 Motor Vehicles on Unpaved Roads
The basis for estimating fugitive dust emissions (j^ 20%)
I
I
I
I
arising from motor vehicles traveling on unpdved roads as derived
from AP-42 is:
\ /365-W
I
e =
where e = emission rate (Ib/vehicle-mile)
m s = silt content of road surface (percentage by weight
of particles smaller than 75 micron diameter)
1| S = average vehicle speed (mph) (valid between 30-50 mph)
W = number of days with 0.01 in. or more rainfall
It is reasonable to adjust the above by a multiplier factor of I j
* ^ i
applied to vehicles with more than four wheels where N = number of wheels
3-3
-------
on vehicle. Also, if local conditions in the area and time period
under consideration warrant, "W" -hould be modified by a multiplier
equal to the average number of days required for the road surface to
return to the dry state.
Dust emissions from unpaved roads generally exhibit the following
particle size distribution (from AP-42):
PARTICULATE DIAMETER WEIGHT PERCENT*
< 30 p 60
> 30 v 40
The data base required for estimation of dust emissions from
unpaved roads in a given study area will Include: 1} mileages and
distribution of unpaved roads, 2) vehicle speed, 3) average dally
traffic, 4) silt content of road surfaces, 5) number of days of
rainfall >0.01 inches, 6) average number of days required for road
surfaces to return to the dry state and if significant, the average
number of wheels per vehicle.
The spatial resolution of unpaved road mileages should be accom-
plished in cooperation with the local transportation department. In
one applicable approach, a grid is Imposed on a department road map
*Note: One of the modeling approaches discussed in Section 4 uses particle
size ranges for describing the air quality/emissions level relationship.
3-4
-------
showing the various road classes (dirt, gravel, paved). The mileages
of each road class are scaled and recorded for each of the grid squares
of the network. In another alternative approach, road mileages and
classifications are related to road maintenance activities in fixed
maintenance districts. Computer based summaries of the maintenance
activities in each district may be available and will facilitate the
determination of road surface type and mileage in each such district.
If a single transportation department is not responsible for all roads
within a study area, it will be necessary to consult other appropriate
local departments (e.g., county, the major cities, unincorporated cities,
private organizations).
Average vehicle speed and average daily traffic (ADT) on unpaved
roads are frequently difficult to determine since there is generally
little incentive to study traffic behavior on roads carrying limited
traffic. Speed and ADT estimates then must often be based on rough
approximations from interviews with local transportation department
personnel and/or by limited traffic studies conducted for representa-
tive road types. Expected vehicle speeds for unpaved roads in areas
i ?
studied have been between 30 to 40 mph, but local data should be
used if available. The equation above has been developed using speeds
between 30 and 50 mph. Speeds in excess of 50 mph are not likely. If
speeds below 30 mph are encountered, however, caution and engineering
judgement should be employed 1n extrapolations. ADT is typically less
than 100 vehicles per day on most unpaved roads. Table 3-1 shows some
typical values of ADT for various unpaved road types in the Phoenix
Area. Always use locally developed data if available and reliable.
3-5
-------
TABLE 3-1. AVERAGE DAILY TRAFFIC VOLUMES ON UNPAVED
ROADS IN THE PHOENIX AREA
TYPE OF ROAD AVERAGE DAILY VEHICLE COUNT
URBAN RURAL
County: dirt - county maintenance 75 40
- no county maintenance 15 10
gravel - county maintenance 100 60
City : dirt 75 40
gravel 100 60
The results of a field sampling test9 in Phoenix indicate
that the silt content of soils on unpaved road surfaces reaches an
equilibrium value substantially less than that of the native soil.
Fines are readily removed from the road surface by vehicle traffic,
and equilibrium of the particle sizes is attained with a higher percent-
age of coarse particles than are observed in the native soil. Based
on the modest tests performed by TRW, any relationships formulated
between native soil characteristics and road surface particle distri-
butions are highly questionable. Until indices of road silt levels
are available, site-specific field data is needed to insure suitable
parameterization of theAP-42 emission estimate eouation.*
The spatial variation of road surface silt levels throughout a
study region should be documented by relating general soil maps to
the field test results. Accordingly, road surface sampling sites
should be selected 1n areas that are representative of the major
unpaved road surface types, as determined by preliminary assessment
of the soils maps.
*Note: AP-42 is being revised to include this.
3-6
-------
Rainfall effectively reduces emissions of road dust to near zero
during the period the surface is wet. The drying effects of traffic,
wind, low humidity, and solar radiation will usually return the surface
to its equilibrium state in one to three days, depending upon the extent
of the rainfall. One day may be assumed as a default average, but local
experience should be utilized for the particular soil, season and other
conditions experienced during the period of interest for the area
involved. The "W" factor in the equation should be adjusted to reflect
this local experience (i.e., "2W" for two days drying time).
The emission rates may be affected by large numbers of heavy
vehicles having more than four wheels. While there is speculation
that vehicle weight is the governing factor, larger and heavier vehicles
have more wheels to carry and distribute their loads. Therefore, if
the proportion of such heavy vehicles is significant, it may be necessary
to utilize the "N" factor multiplier for the emissions equation.
Once the various influence parameters have been quantified within
the grid network, dust emissions for unpaved roads are calculated using
\
the equation. For example, a one-mile length of unpaved roadway with
surface silt content of 20%, carrying 100 light duty vehicles per day
at an average speed of 35 mph, will emit:
e *J0.81(20)(35/30)(100)(1)= 189 pounds
of suspendable dust per day (assuming no rainfall and
all four-wheeled vehicles.).
In developing the complete unpaved road emissions inventory, the cal-
culation is performed for each of the various road links within the
3-7
-------
grid network. In the limit, when the data base is complete, this process
involves a separate calculation for each identifiable link. Generally,
the available data base for unpaved roads provides less discrimination,
permitting the aggregation of road links of a given "average" description.
It may be useful and efficient to computerize the emissions modeling effort,
both for actual calculations as well as for display of results. This deci-
sion will be dependent upon local capabilities and resources.
3.1.2 Entrapment of Street Dust
Vehicles traveling on paved roads and streets are likely to be a
major source of fugitive dust emissions. Based on two separate studies of
13-14
re-entrained street dust , an average dust emission rate of .012 lb/
vehicle mile has been established [as shown in Table 3-2 soon to be pub-
lished In AP-42, Supplement 8].
Table 3-2
Measured Emission Factors for Dust Entrapment from Paved Roadways
Study
Emission Factors
(Range and Average)
Reference 13
Reference 14
Average (overall)
q/veh1cle-km
Ib/vehicle-mile
Range
Average
2.8-5.6 4.3
0.26-10.4 2.6
3.5
Range Average
0.01-0.02 0.015
0.0009-0.037 0.0009
0.012
3-8
-------
I
I
I
I
m
I
I
I
I
I
The utility of the above emission factor depends essentially on the
ability to quantify the vehicle miles traveled (VMT) on paved roads or
streets during the base year or of other years of interest. The informa-
tion necessariy for this characterization can usually be obtained from
internal documentation available within various State and local agencies.
Dust emissions from paved roads generally exhibit the following
14
particle size distribution.
Particle Size Weight Percent
Greater than 30 ym 10
Less than 30 urn 90
Less than 5 urn 50
3.1.3 Construction Activities
Construction activities inevitably result in the exposure and disturb
ance of soil. Fugitive dust is emitted both during the activities (i.e.,
excavation, vehicle traffic, human activity), and as a result of wind ero-
si on over the exposed earth surfaces. The major construction of interest is
typically occurring in "heavy" construction activities, such as roadway con-
struction and residential/commercial/industrial building which involves dis-
turbance of significant quantities of soil surface area.
3-9
-------
Based on field tests conducted at construction sites, an
average dust emission rate of 1.2 tons/acre/month for active construc-
tion has been established. The test results do not include an analysis
of the expected particle size distribution of emissions. Until further
study results are available to characterize construction emissions,
the particle size distribution may be assumed to approximate that of
the lower ranges (less than about 100 microns) of the parent soil.
Parent soil distributions may be obtained from published USDA soil surveys.
The utility of the above emission factor depends essentially on
the ability to quantify the acreage of soil which is disturbed during
the various construction projects occurring in the baseyear or of
other years of interest. The information necessary for this character-
ization must usually be obtained from.internal documentation available
within various local agencies.
Roadway Construction
Roadway construction activities and associated mileages may be
obtained and characterized by consultation with state, county, and
city transportation departments. Table 3-3 illustrates the tabulation
g
of this type of data obtained for the Phoenix area. The data
are approximate, but based on the uncertainty associated with univer-
sal application of the average emission factor, more precise survey
efforts are unwarranted. Based on average roadway clearing widths
used in construction, the average area of exposed surface may be cal-
culated. Significant borrow pits outside the roadway may be important
in areas requiring extensive cut and fill such as will exist in hilly
or mountainous terrain. The duration of active construction, during
3-10
-------
I
' which the road bed is exposed soil, is typically about 6 months for
a major road job of one mile length and 80 feet width, and about
2 months for each half a mile of local streets 33 feet wide.
Various widths of right of way disturbance may also be involved and
should be considered. Local regulations and practice are giving more
| and more attention to reducing this exposure time by temporary seeding
^ or other stabilization, and should be considered in this analysis.
Based on an average emission rate of 1.2 tons/acre/month, the dust
emissions arising from road construction are calculated by multiply-
ing the average emission rate of 1.2 tons/acre/month by two terms:
1) acres of soil exposed in road construction, and 2} the average
m
I
I
duration of the soil disturbance. Because of the variable location
and relatively minor effect of roadway construction emissions, efforts
to resolve these sources spatially on the grid network should usually
be limited. It is normally adequate, for example, to allocate con-
struction dust emissions equally to all grids on the emissions grid
network that are within the entire city boundaries, and to allocate
road construction dust for the county and State Highway Department
equally to the grids in the county portion of the study area network.
Resi denti al /Commerci al / Indus tri al Construct! on
The most significant source of construction dust typically arises
during the building of residential/commercial/industrial structures.
Residential housing usually comprises the major portion of the activity
in this construction category. Housing construction can generally be
3-11
-------
TABLE 3-3. SUMMARY OF ROAD CONSTRUCTION
ACTIVITY IN PHOENIX AREA, 1975
RES'C'iS.'dLE
AGENCY
County
Phoenix
Glendale
Paradise Valley
Peorla
Mesa
Tempe
State Highway Dept
IMPROVEMENTS SUBDIVISION
(MAJOR & LOCAL (PRIVATE CpN-
ROAOS) STRUCTION*
20.0
26.4
0
1.5
0
' 0
0
0
47. 9C
*' Of those roads financed
highways 80' wide, and
Averaca width
Average width
of these
of local
MILES OF ROADWAY
56.0
58.7
14.7
2.8
0
32.7
10.3
0
175. 2b>
by federal aid. 18.9
37.3 miles are 2 land
roads Is 33 feet.
and major roadways 1s
FEDERAL
AID
SYSTEM
15.8
3.6
0
0
0
0
0
36.8
56.2*
miles are
highways
55 feet.
CITY !
OR
COUNTY TOTALS
128.7
1.4
0
.6
i
2.1
0
0
0
1 132. 8b'
4 lane
48 ft. wide.
MoplUy
Total Houttng VMM
'CD
300-999
Dntriet
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
*Sป
\m
TซMl
1974
fl^M^M
Uwปf>
Singte
319
933
548
332
127
744
32
37
7
9
6
39
734
16
211
513
1,184
808
1,846
8,705
11,280
-22.8%
TownhouM
43
5
8
7
_
12 ..
104
v 32
22
176
409
2,354
-82.6%
AWN**
13
9
17
440 "
10
152-'
20
15
95
2
_
-_
21
14
- 3'."
30ป
2
i
t45."
, ,
6,073
-86.)%
YoMJUW*
373
,.947
5*5
.1,000.
. 134
734
.. 5(04' .
69
22
104
9
3P--
' 734
37
24)
. 631
tjJQI '
880
,/a^"*,'
* *
9,959
1ป,J07
t-
-49.5%
Sourct- M*rlcซM County Homing Study Commmw, M. R. WN) MiMttkw
ti, inc.
Ib
FIGURE 3-2. NEW HOUSING UNITS IN MARICOPA COUNTY, 1975
(Based on Building Permits issued January
through December, 1975)
3-12
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I
I
characterized from data available from local building and safety depart-
ments, but often this data is assembled it. summary form and published
by various local service organizations. Figure 3-2 illustrates a
flj typical format for presentation of building permit data to describe
new housing unit starts. Average unit land utilization for various
I housing classes may be determined from sources such as local planning
departments, building and safety departments, and local service organ-
I
I
I
I
izations. This determination may involve a synthesis of several input
Q
data items,,; such as land use ratios, average occupancy rates by
dwelling and housing unit inventories and should consider the portion
of the land area disturbed by typical construction practices utilized
locally. Average land utilization rates are then combined with new
M housing start data to calculate disturbed soil area associated with
housing construction in the various districts.
Disturbed soil acreage occurring from land use development other
than housing may be determined by employing calculation procedures
similar.to that described above for housing construction. If data
are not readily available to characterize commercial, industrial, and
public construction projects, historical land use ratios between the
various land use types may be applied to construction acreage totals
M for these land use categories. Estimates of dust emissions arising from
* all categories of construction activities are then generated by apply-
ing the general emission factor of 1.2 tons/acre/month to the number
of acres disturbed by construction in each definable district or
sector. The building construction emission levels are then assigned
3-13
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to the emission grid network by any suitable allocation procedure
(i.e., a grid network overlay may be used to accomplish the appropriate
allocations).
3.1.4 Agricultural Tilling Operations
Based on field measurements of suspended particulates arising
from tilling operations, the equation as given in AP-42 for
estimating tilling emissions 1s given as:
a - T-4s
e = *
where e = emission rate (Ib/acre),
s = silt content of soil surface (percent), and
PE = fhornthwaite's precipitatton - evaporation index
with implement speed being typical (5-7 mph).
Two general assumptions apply to the estimation equation
involves the type of implement. The field tests reflect utilization
of one-way disk and sweep-type plows. In practice, a wide variety of
implements are employed, ranging from disk plows to moldboard plows to
listers. It is assumed that emissions do not differ greatly from one
implement type to another. It is also presumed that no irrigation
is conducted before plowing. In areas where irrigation is employed,
fields may be flooded with water to leach out salts from the previous
season, but this occurs after plowing.
3-14
-------
Test results indicate that, on the average, dust emissions from
agricultural tilling have the following particle size distribution
but may vary according to the local soil characteristics.
Particle Diameter Weight Percent
< 2M 35
2-30 u 45
> 30 y 20
The data base required for estimation of dust emissions from
tilling of agricultural fields Includes: 1) silt content of the soil,
2) implement speed, 3) distribution of agricultural acreage, 4) tem-
poral distribution of tilling activities, and 5) the Thornthwaite
preci p1tati on-evaporati on i ndex.
Soi1 Si 11 Content
U.S. Department of Agriculture Soil Sample Analyses are published
and made available for use in potential farmland areas throughout the
country. These analyses typically include a detailed particle size
distribution for case samples from various representative sites in
a given area. The data may be used to estimate the silt content as
defined by the emissions equation (the percent by weight of the. top four
inches of soil having particle diameter from 2 to 50 microns). The
soil silt measurements may be related to soil types identified on
general soil maps, and agricultural regions may then be located on the
soil maps with the use of aerial photographs or some other suitable
procedure. An average silt level is estimated for cropland within
3-15
-------
each grid square (or some other suitable geographic jurisdiction such
as a township) by weighting cropland acreage with corresponding soil
silt levels.
Distribution of Croplands
The spatial distribution of croplands may be determined from aerial
photographs of the study area. Potential cropland, which was fallow at
the time the photo was taken, may also be identified, and confirmed, with
photos corresponding to another growing period. By scaling of the photos
and the suitable use of grid overlays, crop acreage in each of the grid
squares may b^ quickly estimated. Frequently, such estimates are already
available (by some alternate grid system) in documents published by state
or local agricultural agencies. A check should be made to compare the
total compiled agricultural acreage-with alternative sources of published
cropland totals. When patterns of crop types are available, acreage in
each grid square by crop type may be documented.
Implement Speed
Limited data are available to characterize typical speeds of tillage
17 9
implements Investigation during the Phoenix Study confirmed
previous findings that a speed of 5-1/2 mph is generally representative
r18
of most tillage operations' .
Since agricultural tillage occurs seasonally based on crop type,
the resulting emissions from this activity should be expressed by
season. To permit discrimination of emission by season, it is neces-
sary to characterize 1) the tillage period for each crop type, and
3-16
-------
I
2) the acreage of each crop type. Moreover, if this seasonal discrim-
ination is to be made on a grid basis, the spatial distribution of the
different crop types must be determined. The latter determination is
often non-productive in areas where use of agricultural lands is
unpredictable, or is constantly changing. In these cases, a constant
jf distribution of crop type may be assigned throughout the study area.
m However, if specific geographic patterns for cropland use can be iden-
tified, these data may be used to establish a varying spatial distri-
bution for agricultural acreage by crop type.
The tillage periods for various crop types depends on regional
Q considerations and may be identified by consulting with local agri-
cultural agencies. Figure 3-3 illustrates the planting period for
major crops in the Phoenix area, obtained from local publications
1R
of the Arizona Crop and Livestock Reporting Service. Tillage
is assumed to be distributed over the planting period.
I
I
I
Thornthwaite Precipitation-Evaporation Index
The Thornthwaite Precipitation - evaporation index is used to
reflect moisture exchange between soil and atmosphere. The use of this
B expression is an attempt to quantify the suppression or encouragement
of emissions by the presence of moisture in the soil. The use
of index for a specific area and baseyear is discussed in Section 3.2.1,
Calculation of Emissions
I
Once the various model parameters have been characterized for the
grid network, dust emissions from tillage operations are calculated
3-17
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3-18
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I
using the emission equation. For example, consider a grid square in
m which TOO acres of cotton were grown in the baseyear. If the silt
m content of the soil was 50%, the tilling implement was run at a
typical speed of 5-1/2 mph, the PE index was 50, and the tilling season
I was from March through April , the dust emissions resulting from the
tilling are:
I e = -'4 (50) = 70 Ibs/acre
-
I
or the total daily emissions from the grid square during the tilling
period is:
Emission estimates should be located and described on the emission
grid.
3.1.5 Off -Road Motor Vehicles
Recreational vehicles traveling off-road on native soil surfaces
may generate significant dust emissions in some locales, particularly
during weekend periods. While the impact of non-construction off -road
vehicle emissions is minimal in most metropolitan areas, air quality
near the areas of greatest activity may be sufficiently affected to
require consideration.
. Because documentation of off -road vehicle activities is very
" limited, only crude emission approximations are possible at this
time. Based on the emission factor for motor vehicles on unpaved
roads (Section 3.1.1), the rate of dust emissions arising from off -road
vehicle activity would be:
e=.81s()()
where N = 2 for motor bikes and 4 for 4-wheeled vehicles
3-19
-------
The size distribution of particles emitted from off-road vehicle
activity is assumed to be the same as that emitted by motor vehicle?
on unpaved roads.
The location, operational characteristics and activity levels
for off-road vehicle recreation may typically be best determined by
consultation with local motorcycle associations, city parks and recre-
ation departments, the Fortst Service, the Bureau oi Land Management,
etc. Based on discussions with cognizant organ-JzitlohS in the Phoenix
20, 21, 22, 23, 24, 25 ' , . , x UJ1
areaj a typical motorbike rldar was
assumed to travel about 45 miles per outing at an average rate of
15 miles per hour. The average trip length for a, four-wheel vehicle
was assume*1 tw be 150 miles at an average speed of 30 miles par hour.
Vehicle activity levels are generally several tlines greater for
end days as compared to weekdays.
Silt content of areas used for off-road travel mi\y be
by combining information from general soils maps and the results of
soils surveys available from the local branch of tte* U.S. Departซ)ent
of Agriculture Soil Conservation Service.
In documenting emissions estimates, a distinction should he roads
between weekend-day levels and weekday /levels. The weighted dally
/
average should be computed for consideration in air quality modeling
of annual TSP averagtt (SactfcM 4).
3.1.jSTunprnd Park** Lots *d Truck Sttft
The dust emission rate for vehlcles^'travtnng fh~ unpaved parking,
lots or truck stops 1s assumed to be the same as that for vehicles on
/*
unoaved roads. Based on an exponential increase 1n the emission rate
for vehicle speed from 0 to 30 miles per hour, the emission fac-
tor for a typical parking lot surface of 24% silt level would be 2.2
pounds/vehicle (4-wheel) mile at an average vehicle spead of 10 miles per
3-2n
-------
I
_ hour. For a gravel surface, the silt level is about 12%, and the parking
lot dust emission rate is about 1.1 pounds/vehicle mile at a speed of 10
I miles per hour.
' ti
Total parking lot dust emissionsปare estimated by (1) determining
I the average number of vehicles using the lot each day and the average
distance traveled by each of the vehicles, and (2) by calculating total
vehicle miles traveled daily and multiplying this rate by the ^em'tesion
t' %J
factors discussed above. In an alternative approach, average vehicle
I miles traveled may be related to parking lot size. For example, in one
* 4
IB recent study to characterize factors influencing fugitive dust emissions!,
, it has been assumed there are 190 VMT/year per 10,000 square feet
B of parking lot. Based on this assumption, unpaved parking lot emission
rates may be summarized as follows: ,
e = .21 (N/4) ton/yr. per 10,000 sq. ft. for parking lots with
surface silt content of 24%.
I e = .10 (N/4) ton/yr. per 10,000 sq. ft. for parking lots with
m surface silt content of 12% (gravel surface).
* Where N = average number of wheels for vehicles traveling in parking
lot.
The particle size distribution of the parking lot emissions is assumed
to be equivalent to that emitted off unpaved roads (see Section 3.1.1).
ซ 3.1.7 Aggregate Storage Piles
Based on field measurements^ of suspended dust arising from
aggregate storage operations, average emission factors for three categories
of process activity (active, inactive, and normal mix) are as shown in Table 3-4.
Sources of the aggregate process include loading and unloading to the storage
piles, traffic movement among the storage piles, and wind erosion. The factors
| shown are representative for storage piles in areas with climatic conditions
I similar to Cincinnati; however, the values may be adjusted by applying the
3-21
-------
TABLE 3-4 EMISSION FACTORS FOR AGGREGATE STORAGE PILES 17
Aggregate Storage Operation
Pile Status
Daily Activity3
Inactive
(wind-blown emissions only)
Normal activity mix b'c
Composition:
Loading onto piles
Vehicular traffic
Wind erosion
Loadout from piles
a8-12 hour activity/24 hour day
*C5 active days/week
Emissions:
Lbs/acre/day -or- Lbs/ton placed
in storage
13.2 0.42
3.5 0.11
10.4 0.33
0.04
0.13
0.11
0.05
total 0.33
A correction factor of
effect of regional climate.
2,should be applied to account for
3-22
-------
PE 2
correction factor V(YQQ-) to the total storage process emission factor, where
PE is the area-specific Thornwaite Precipitation-Evaporation Index.
17
Field tests that have been conducted have revealed the particle
size distribution for one of the representative operations (aggregate
loadout) to be as follows:
Particle Size Weight Percent
<1 y 30
1-2 y 46
2-3 y 16
3-4 y 6
>4 y 4
Estimation of total dust emissions resulting from aggregate storage
operations should be conducted using an appropriate emission rate selected
from Table 3-4. Activity of the storage operation is generally documented
through the permit system of the local air pollution control agencies.
Dust emissions are then calculated by combining the appropriate data and
emission rate selected from Table 3-4. For example, consider an aggregate
operation with a storage of 10 acres and a normal mix activity, located in
an area with a PE Index of 50. The rate of dust emissions arising from this
enterprise would be:
104
e = L^-L =41.6 Ibs/day/acre of storage
or 416 Ibs/day total emissions from the entire aggregate storage operation.
3.2 ESTIMATION OF BASEYEAR WIND EROSION EMISSIONS
This section includes procedures which may be used to estimate fugitive
dust emissions resulting from wind erosion of soil. Section 3.2.1 describes
the general emissions model and the data base required for calculation of
wind erosion emissions. Section 3.2.2 outlines specific considerations
involved when applying the emissions equation to various source categories.
3-23
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3.2.1 General Methodology
The exact mechanisms causing entrainment of the soils are not
yet fully understood. The quantification ur these mechanisms for
application in air pollution studies will not be availab"!a in the short
term. Presently it appears the most plausible approach for estimation
of wind-blown dust, is to assign a suspension rate to the horizontal
28
soil movement as determined by the established wind erosion equation
This approach has been used recently in studies concerning control
of fugitive dust emissions.
A simplified version of the basic wind erosion equation is
given by
Es = AIKCL'V
where Es = suspended participate fraction of wind erosion
losses of tilled fields, tons/acre/year
A = portion of total wind erosion losses that would
be measured as suspended particulate
I = soil credibility, tons/acre/year
K = surface roughness factor, dimensionless
C = climatic factor, dimensionless
L1 = unsheltered field width factor, dimensionless
V = vegetative cover factor, dimensionless.
The variable of greatest uncertainty in the adopted wind erosion
relationship is the suspension factor A. Only limited test data is
available to establish the relationship of the suspension ratio of
9
eroded soil with wind speed and soil type. A review of this data
has been conducted to establish best estimates of suspension ratios.'
3-24
-------
These estimates are listed in Table 3-5 for the major source categories.
The values serve as the current preferred basis for emissions compilation,
but should be considered tentative and subject to adjustment in the future.
TABLE 3-5 FRACTION OF TOTAL WIND EROSION LOSSES WHICH ARE
SUSPENDED (DUST SUSPENSION FACTORS)Jป15
Exposed Soil Surface Category Dust Suspension Factor
(Dimensionless)
Croplands 0.025
Unpaved dirt roads 0.38
Disturbed native soil (parking lots, 0.38
residence yards, excavation clearings)
The remaining terms of the wind erosion equation reflect parameters
of the basic wind erosion equation as a result of 30 years of research
to determine the primary factors that Influence erosion of soil by
wind. The data base used to assemble representative values of the
erosion equation parameters is discussed in Appendix A. When all terms
of the erosion model are quantified to reflect area-specific conditions,
the rate of soil erosion emissions is calculated for each definable
region of the emissions grid network. This rate is then applied to
the number of acres of soil subjected to erosion in each of the defin-
able regions.
3.2.2 Soil Erosion Emissions From Specific Source Categories
The major sources of wind-blown soil dust are unpaved roads and
parking areas, agricultural fields, undisturbed desert, tailings piles,
and disturbed soil surfaces. Specific aspects concerning the estimation
of these wind-blown soil sources are discussed briefly below.
3-25
-------
Dnpaved Roads
The erodibility (I) of soil surface of unpaved roads may be related
directly to the silt content of the road surface (Figure A-l). The silt
content of unpaved roads is determined by field tests (Section 3.1.1) or
by adjusting native silt content data available from USDA soil survey
results.
The surface roughness factor (K) for dirt roads was assumed to be
1.0. It is not expected that the limited number of ridges worn in dirt
roads would affect this overall estimate significantly.
The climatic factor (C) is calculated to reflect seasonal varia-
tions in temperature, precipitation, and average wind speeds for the
specific study area. Table 3-6 is an example illustrating the signif-
icant seasonal variation of the cUmajtic factor associated with long-
term historical and 1975 meteorology for the Phoenix area. These
differences are due to the transient moisture content of the soil and
the changing magnitude of wind speed. The Thornthwaite Precipitation-
Evaporation Index (PE Index) was formulated to express the net moisture
exchange between soil and atmosphere. The index is a measure of
cumulative moisture balance over the past 12-month period (See Table
3-6).
The unsheltered distance factor (L1), for a given road surface in
the prevailing wind direction varies continually. To assess an average
effective distance factor, 1t may be assumed that in the long-term,
wind direction is equally distributed for all roads. Any error attributed
3-26
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TABLE 3-6 SEASONAL CLIMATIC FACTOR, C, IN PHOENIX
AREA FOR J975 AND HISTORICAL LONG-TERM
AVERAGES.5
Period
1975
1st qtr.
2nd qtr.
3rd qtr.
4th qtr.
Historical
Averages
1st qtr.
2nd qtr.
3rd qtr.
4th qtr.
Quarterly
. PE* Average
8.8
8.8
7.7
5.3
9.4
9.4
9.4
9.4
Average Wind
Speed, w
7.2
8.4
8.3
7.3
5.6
6.7
6.5
5.2
C = .345 ฃ-*
(PEr
1.7
2.6
3.4
4.8
0.7
1.2
1.1
0.6
* PE ~ Thornthwalte's Precipitation Evaporation Index.
PE = 10
12
where
and
10
n.i
- precipitation-evaporation ratio
for month n
p ซ monthly rainfall (inches)
e - evaporation (inches)
T = average monthly temperature (ฐF)
n - month under consideration
3-27
-------
to this assumption would be minimized by the more probable assumption
that unpaved dirt roads are equally distributed in terms of direction.
For example, when the prevailing wind travtrser north-south roadways
at a 10ฐ angle, the net effect is to balance the various cases of
wind direction oblique to the road. Figure 3-4 shows the effect of wind
direction to unsheltered road distance for a typical unpaved road of
25 foot width. Figure A-2 relates the unsheltered distances to the un-
sheltered distance factor L1.
Q
ง
ง
Ul
CJ
0
s
ac
L25IJ
Road
Width
)1rect1or
30ฐ 45ฐ 60ฐ 75ฐ 90ฐ
ANGLE OF WIND WITH ROAD (9)
9
Figure 3-4. Effect of Wind Direction on Unsheltered Road Distance
L' 1s related to the distance 1n which maximum son movement Is reached,
and varies with soil erod1b1!1ty. The average value of L1 for road sur-
faces of specified credibility IK, is shown in Table 3-7. It is evident
that L1 varies only slightly for a relatively wide range of soil char-
acteristics. It should also be noted that L1 approaches zero from road
silt levels less than 40%.
o-t
-------
TABLE 3-7 UNSHELTERED ROAD DISTANCE
FACTOR L'
IK L1 AT Different Prevailing Wind Directions Average L'
e = 90ฐ e = 60ฐ e = 30ฐ e = 0ฐ
40 0.05 0.06 0.07 1.00 0.29
60 0.08 0.09 0.10 1.00 0.32
80 0.11 0.12 0.14 1.00 0.34
A suspension factor of 0.038 is applied to approximate the suspended
portion of the wind erosion soil losses. Table 3-8 summarizes the overall
computation procedure. Emission rates of suspended dust arising from wind
over unpaved dirt roads are calculated by assigning specific values, as
discussed previously, to the parameters of the wind erosion equation.
These rates are combined with the total acres of unpaved roads in each
district or grid square to calculate emission totals by grid. The emissions
are computed on a seasonal basis to reflect the significance of differences
in the climate.
Agricultural Fields
Wind-blown dust emissions from agricultural fields are estimated by
assigning area-specific values to the variables of the wind erosion equation
(Section 3.2.1). Except for the potential soil credibility (I), the emission
determinants depend on crop type. In the process of the development of the
wind erosion equation, the U. S. Department of Agriculture has assembled
sufficient data to parameterize soil surface preparations and agricultural
practices for various crops. These data should be employed to estimate crop-
specific soil losses in each identifiable district or grid square of the
study area.
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3-30
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An overall value for the soil erodibility (I), is determined for the
agricultural area of each township (or other convenient units of area) of
the study area. Soil silt measurements conducted by the U. S. Department
of Agriculture may be related to soil types identified on general soil maps.
Agricultural regions are then located on the soil maps with the use of
aerial photographs. An average silt content is estimated for cropland within
each geographical jurisdiction inventoried by weighting cropland acreage
and corresponding soil silt levels. Average erodibility of the croplands is
then determined by the silt content/erodibility relationship shown in Appendix
Figure A-l. This procedure may be simplified substantially if preliminary
analysis shows the study area is homogeneous in soil silt level.
Values for the soil surface roughness factor (K), the unsheltered field
length (L), and the vegetative cover, are relatively uniform for a specific
crop. The surface roughness factor accounts for resistance to wind erosion
due to ridges or clods in the field. An optimal ratio of ridge heights to
ridge spacing will reduce soil erosion by a factor of 0.5. Table A-l shows
typical roughness factors associated with soil preparation for various crops.
Average field sizes for relatively flat terrain devoid of tall natural
vegetation have been established for various crops as shown in Table*-!.
Soil losses from wind erosion across a field vary from the windward edge
of the field and increase proportionately with length until a terminal rate
of soil movement is attained. The distance required before attaining maxi-
mum erosion rate is influenced by the potential erodibility (I) and roughness
(K) of the soil. The relationship between the unsheltered field length (L),
the surface erosion potential (IK), and the field length factor (L1) is
shown in Figure A-2.
The amount of vegetative cover residue left on a field after the growing
season varies appreciably by crop (Table A-l). Cover residue reduces soil
wind erosion losses by the factor V as shown in Figure A-3. The degree of
3-31
-------
reduction attainable with the crop residue is related to the surface
erosion (IKCL1).
The climatic factor (C), is calculated to reflect seasonal variations
in temperature, soil moisture (including precipitation and irrigation
effects) and average wind speeds for the study area in the baseyear. Calcu-
lations of C were illustrated in Table 3-6. Regional values of C must be
adjusted for cropland soils to reflect additional soil moisture provided by
crop irrigation. Periodic Irrigation during the growing season maintains
soil moisture and aggregated state of the soil. The effects of the irriga-
tion are significant 1n the off-growing season, when disconsolidation of the
soil and exposure to winds would reduce resistance to soil erosion.
Based on area-specific irrigation schedules obtained from local agricul-
tural agencies for the major crops in the area along with monthly precipitation
and temperature data, a PE Index 1s calculated for each crop. (Irrigation
water is treated as equivalent to rainfall.) The PE values are then combined
with baseyear monthly average wind speeds to calculate climatic factors corres-
ponding to the non-growing or erosion-susceptible period (obtained from local
agricultural organizations). An example of the results of these calculations for
a study of the Phoenix area 1s shown in Table 3-9.
3-32
-------
1
1
1
1
1
mf
1
1
1
1
1
1
1
1
Table 3-9. CROP-SPECIFIC CLIMATIC FACTORS
IN PHOENIX AREA9
CROP PE INDEX NON-GROWING
OR EROSION
SUSCEPTIBLE PERIOD
Cotton 58.0 All Year
Alfalfa 113.0 None
Barley 52.8 May - December
Sorghum 40.2 November - July
Wheat 54.9 May - December
AVERAGE CLIMATIC FACTOR
(FOR PERIOD OF VULNERABILITY)
W3
C . .345-^ 2
.05
w
.06
.10
.06
Estimates of suspended dust arising from soil wind erosion losses
are calculated based on assignment of wind erosion equation parameters
as specified above. A suspension factor of
approximate the suspended portion of the soi
summarizes the overall computation procedure
0.025 is employed to
1 losses. Table 3-10.
for a series of five
example crops. The calculations should be computerized for convenience
in dealing with areas having numerous townships containing agricultural
fields. Values of the credibility index I,
length factor L1, and the vegetative factor
curves of Figures A-l, A-2, and A-3.
3-33
the unsheltered field
V may be extracted from the
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3-34
-------
I
I
Disturbed Soil Surfaces
Estimation of wind erosion emissions from vacant and cleared property
is conducted by assigning area specific values to the terms of the
equation. Area-specific values of the disturbed soil properties are likely
I to vary substantially from district-to-district, or from lot-to-lot. A
survey of vacant lots, parking lots, and dirt residence yards may be
I required to establish representative characterizations of these sources in
_ the various identifiable geographic areas. This survey may be accomplished
by field visits, use of aerial photos, or special summary data available
from local planning agencies or service organizations. The level of effort
associated with acquiring a representative data base should be dependent on
I the apparent impact of the sources on air quality in the area.
Tailing Piles
I
_ Tailing piles consist of deposits of earth removed during mining
" operations. For large mines, the tailing piles may expand over several
thousand acres. Generally the piles are composed of substantial pro-
portions of fines and are relatively susceptible to significant wind
erosion losses.
Only limited information is available concerning soil emissions from
I tailings piles. Recently, PEDCo 15 has developed an emission factor for
_ this fugitive source by employing the wind erosion equation. No field
testing was performed in the PEDCo analysis. Representative characteristics
were identified for tailings for use in the wind erosion equation. The
piles were described as being composed of sand and loamy sand soils with
I
I
3-35
-------
possible fines for surface cementation (I = 130), They are characterized
by a smooth, unridged surface (K = 1) and no vegetative cover (V - 1)..
Wind fetch over the piles is approximately 2000 feet. Ten percent of the
soil loss estimated by the wind erosion equation is assumed to become sus-
pended. The emissions are seasonally related to the climatic factor, which
may vary substantially during the year. The effect of climate on the emis-
sion rate 1s Illustrated in Table 3-11. Total emissions are calculated by
applying the emission factor to the number of acres of tailings pfies-.
Soil erod1bH1ty, vegetative cover, roughness factor5 and wind fetch
may be adjusted to reflect tailings piles of various characteristics,
However, typically it 1s difficult to obtain detailed Information t* cham
terize the piles. It is anticipated that a survey of individual inlnjs nTH
be required to obtain the needed data. This effort may be a 1 located accord-
1flg to the apparent signfftctnce of tfie tailings piles in ISP lev(*V,
3-36
-------
1
1
1
1
1
1
1
I
i
1
1
|
1
1
1
1
1
1
TABLE 3-11. EMISSION FACTORS FOR TAILINGS PILES
(NO VEGETATIVE COVER)
Emissions
Climatic Factor tons/acre/year
.30 4.0
.40 5.3
.50 6.6
.60 8.0
.70 9.5
.80 10.5
.90 12.2
1.00 13.3
1.20 16.0
It is assumed that the particles size distribution of tailings piles
emissions is equivalent to that of emissions from aggregate loadout opera
tions.
Particle Size (ji ) UQH^* pprrpnt_
<
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3.3 PROJECTION OF FUGITIVE DUST EMISSIONS
The extent and nature of fugitive dusi emissions depends on the
human activities which create or influence the.e sources. As the
community experiences development and reshaping, sources of fugitive
dust are being altered in magnitude, location, and type. If control
strategies are to be devised to correct air pollution problems, it is
essential that these air pollution problems be characterized to reflect
the future environment, when strategies would be implemented. There-
f
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Since the specific data base encountered for any study arpa win
vary significantly, the forecast indices which may be used to determine
S projected emission levels will also vary.
Unpaved Roads
I The parameters needed to calculate dust emissions off unpaved
_ roads are discussed in Section 3.1.1. Two of these parameters may
* change significantly in future years. They are 1) mileages and dis-
tributions of unpaved roads, and 2) average daily traffic.
The changing mileages of unpaved roads in various sectors of
| study area may be indicated by identifying trends in the historical
_ data. Additionally, plan forecasts and future objectives of the local
transportation department should be obtained. Road improvement pro-
JA grams will have significant impact on the status of unpaved road mile-
ages in many cities. Generally the target areas and schedules for
such improvement programs are outlined in detail, and can be employed
directly to adjust the baseyear parameters used in estimating the base-
jj year emissions (see Section 3.1.1).
m For many cities, improvements in county and city roads may be
occurring with some uncertainty, depending on the annual budget and
most pressing maintenance or new development requirements. In this
instance, average budget trends may be assumed to approximate the
| expected extent of roadway paving, each year, and location of these
improvements may be approximated by assuming tneir occurrence witm'n
3-39
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anticipated growth areas specified on city and county planning maps.
Distribution of the expected mileage of road paving throughout the
growth belt areas may be expediently tabu!:Led with the use of isoline
overlays depicting incrementally expanded development arฐas for the
period from the present to the years of interest. A detailed explan-
9
ation of this overall approach is documented in reference .
While road improvements may reduce dust emissions on unpaved roads,
Increasing traffic in future years will tend to offset this benefit.
The projected ADT for unpaved roads may be assumed to be directly
related to expected population growth for the area.
Agricultural Till ing
The most suitable index of agricultural growth 1s reflected by
the historical trend of cropland acreage. When agriculture exerts a
major Impact on the economy of an area, the trend rate will probably
remain fairly constant 1n the near term. Inspection of previous and
future land use maps for the area will Indicate the changing location
of croplands. Projections are made by comparing the present location
of croplands with the future expected locations on the land use maps.
If appropriate, available historical agricultural data may be
evaluated to Identify apparent trends in crop types. Changes in crop
type will affect the tillage season and would impact the temporal
distribution of emission levels from croplands. Local USDA officials
may be able to provide an assessment of any changes in projected
crop types.
3-40
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I
4.0 EMISSIONS/AIR QUALITY RELATIONSHIP
This section provides an outline of general procedures which may be
used as a guideline in formulating an appropriate source-receptor rela-
tionship for areas where fugitive dust sources are prevalent. The pro-
cedures presented here should be considered tentative and should not
fl inhibit incorporation of modifications and improvements. Section 4.1
concerns some important considerations affecting the choice of the source-
receptor relationship. Section 4.2 discusses several air quality models
that have been used for fugitive dust modeling and others that could be
adapted for use.
4.1 SOME FACTORS AFFECTING SELECTION OF THE SOURCE-RECEPTOR RELATIONSHIP
The evaluation of air pollution control strategies requires a detailed
understanding of the relationship between emissions and ambient air quality.
This subsection considers the importance ofiaveraging time and source config-
m uration for selection of models applicable to fugitive dust.
H 4.1.1 Averaging Time
An essential aspect in selecting a source-receptor relationship
concerns the averaging time of the air quality predictions. There is reason-
able cause to restrict the analysis to only the long-term averages. First,
I greater control is typically required to attain the primary annual standard
g than to attain the 24-hour standard (provided episodes due to dust storms
* and accidental industrial emissions are excluded from consideration, as
allowed by SIP regulations). A second reason for restricting the scope of
the model to long-term considerations concerns the uncertainties associated
I
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with the data base. Uncertainties are introduced at several stages of
the air monitoring measurements, the emissions inventory compilation, and
model formulation. The analytical limitations associated with the
detailed documentation of short-term particulate origins and their rela-
tionship to air quality levels would increase the uncertainties greatly,
making the substantial additional effort needed for this task impractical
and unwarranted at this time.
4.1.2 Source Configuration
The nature of the source 1s an Important criterion to be considered
in the selection of a source-receptor relationship. For conventional well-
controlled paniculate emission sources, where most of the partlculates
emitted are typically smaller than 10vW in diameter, the source-receptor
relationship may be established through the standard equations for atmos-
pheric transport awl dispersion.
However, the application of currently available models to the fugi-
tive dust problem 1s further complicated by the ill-defined nature of the
sources themselves. It is often difficult to characterize the sources in
the traditional classifications as: point, area or Hne. Also, certain
commonly used emission terms such as exit velocity and effluent tempera-
ture may become Inappropriate parameters in this context. These potential
ambiguities, of source type and emission characteristics, are Inherent to
the application of any currently available model. They must be dealt with,
by the user, on a case-by-case basis.
Unfortunately, typical Gaussian-type dispersion models may not
properly consider the physical characteristics or the emissions of unpaved
roads, storage piles, resuspended street dust or other fugitive dust
4-2
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I
I
3.3.2 Wind Erosion Sources
I The major sources of fugitive dust which are suspended by wind
are agricultural fields, unpaved roads, undisturbed desert, tailings
I piles, and disturbed soil surfaces.
Unpaved Roads
The procedure for estimation of projected wind erosion emissions
from unpaved roads is the same as that outlined in Section 3.2.2. The
adjustments which must be applied to the baseyear parameters used in
the wind erosion equation include: 1) the miles of unpaved roadways
in the various grid sectors, and 2) the climatic factor. The former
I item is obtained by the considerations outlined in Section 3.3.1. The
. climatic factor is calculated to reflect representative meteorology
' for the area, based on historical data for temperature, precipitation,
j and mean wind speed obtained from the National Climatic Service.
Agricultural Fields
Due to changes in location, acreage, crop types, and climate,
the estimates of agricultural wind erosion emissions performed for the
baseyear (Section 3.3.3) should be repeated for the selected future
_ years. The considerations outlined in Section 3.3.1 are applicable to
the issue here: crop type by grid sector, and acreage by grid sector
must be determined. These inputs are utilized to derive appropriate
values for the terms of the wind erosion equation. The climatic
factor is adjusted to a representative historical value for the area
if necessary.
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3-43
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Disturbed Soil Surfaces
The major consideration associated with the projection of emission
loadings from each of these sources involves changes in spatial distri-
bution and total source area. Projected development reflected by the
general plan will indicate acreage changes and location for undisturbed
desert areas and disturbed soil surfaces. Potential procedures for
approximating these changes are similar to those discussed under
construction (Section 3.3.1) emissions estimation.
3-44
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Construction Activities
Forecasted construction activities should be based on the general
future land use plan for the study area. Land areas involved in
construction for orojected years are assumed to be consistent with the
forecasts of the county general plan. Based on the annual area of
new urbanization development, and an assumed duration for active con-
I struction on this area, a total dust loading may be estimated for
m future years of interest. The location of the development will proceed
according to the scheme shown in the general plan. A geometric mapping
procedure may be used to estimate the projected location of the con-
struction activity. Isolines reflecting the constant rate of expanding
I development may be constructed for specific future years by interpo-
lating between the boundaries of the existing developed area and that
ฃ developed area forecasted by the Future General Land Use Plan. The
differential development in the years projected for example may
then assume to occur within a growth belt representing the expanded
urbanization over the specified 5-year period. The forecasted dust
emissions loadings are apportioned according to the relative area of
I the growth belt in each of the grid squares of the emissions grid
network.
Aggregate Storage Piles
Historical employment trends in the mineral industry are a relatively.
accurate index of Increasing area of aggregate storage piles. These employ-
K ment data are available from state economic organizations. Frequently, the
compilations arc presented with projections which can bo used directly in
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3-41
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adjusting the baseyear emissions levels to those forecasted for future years.
Potential relocation or new storage operations may be identified by consulta-
ion with cognizant local agencies such as the zoning and planning department,
the construction industry, or the mineral industry itself.
Entrained Street Dust
Roadway improvements, expected to be implemented over the next
ten years, will have significant impact on street dust loadings.
Improvements consist of upgrading currently paved streets, paving of
dirt roads, new road construction (both paved and unpaved), and curbing
and sidewalk construction. While all of these Improvements will result
in lower dun loads on existing streets, the Identifiable change
which will most affect street dust loadings from existing roads con-
cerns the decrease in number of miles of uncurbed roads. (The street
d'us-t loading* for roads with uncurbed road shoulders is four times less
than that observed for curbed streets.)
Projections of vehicle miles traveled (VMT) for future specific
years are assumed to be directly related to population projections.
These projections are used to adjust the VMT for the existing traffic
network to future year levels. The adjusted emission factor reflect-
ing newly curbed streets is calculated by weighting the emission factors
for uncurbed streets and curbed streets relative to the proportion
of each of these street configurations in those future years.
3-42
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t
sources. Nor do they normally consider gravitational settling or dry and
M wet deposition of participate matter; pollutants are typically treated as
though they were unreactive gases. Gravit'.tional settling and dry deposi-
m tion become increasinqly important as the diameter of the particles
m exceeds about 10 \m. Available data indicate that fugitive dust emissions
in some areas (for example, the anv southwest) may have a large proportion
W of mass in the range of 20-70+ vim. Therefore, application of conventional
Gaussian plume models may be inadequate for air quality evaluation where
fugitive dust sources predominate and where particle sizes are generally
large. These caveats notwithstanding, the following subsection outlines
8 some modeling techniques that should prove to be useful in assessing the
ซ fugitive dust problem.
4.2 DESCRIPTIONS OF SUGGESTED AIR QUALITY MODELS
The discussion in this section focuses on several models that have
been used or that may be adopted to evaluate the impact of fugitive dust
I
sources.
m 4.2.1 AQDM and CDM
Two models that are applicable and available for estimating the
1 annual impact of conventional sources on the ambient air quality are the
Air Quality Display Model (AQDM) and the Climatological Dispersion Model
| (CDM). (The format of the required input parameters and the necessary
2 3
. data base are documented in the AQDto and CDM User's Guides),
These models have been used for a number of years to relate parti-
cle emissions to ambient TSP concentrations. For the most part, because
of the lack of basic emission data with respect to fugitive dust sources,
I such sources were not directly considered in these models. Such sources
I
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have been considered in an indirect manner through the regression analysis
of observed and model-predicted concentrations. The Y-intercept resulting
from that analysis has generally been assumed to be the contribution of
those sources not directly input into the model, plus background. In
urban areas where smaller sized particles predominate, (e.g., Chicago,
Philadelphial AQDM and COM may still represent the best approach (at the
present time) for developing a source-receptor relationship.
In those areas where fugitive dust sources predominate, such as 1n
the west and the arid southwest (e.g., Phoenix, Las Vegas, etc.) AQDM and
COM are of limited value; other models outlined in following discussion
may be adapted for these cases.
29
4.2.2 The Atmospheric Transport and Diffusion Model (ATM)
The ATM 1s a receptor-oriented,mlcro-mesoscale (100m - 50km), clima-
tological, flat terrain, Gaussian plume model with a particle deposition
30
option. The dispersion coefficients a^-e calculated from Pasquill-Pifford
31 32 33
stability parameters or Hosker's formulation of Briggs - Smith
dispersion parameters using surface roughness. Plume rise is calculated
34
using Briggs' formula. At a given receptor, the model computes the con-
tribution, for time periods of one month or longer, from each source (point,
area and line) to the ambient air concentration (yg/m3). Also included in
2
the output are the dry deposition rate and the wet deposition rate (g/m /s)
for each source at each receptor. The wet deposition rate is a function of
the rainfall rate and frequency of occurrence. The dry deposition is com-
puted by assuming fractional, rather than complete, plume reflection at the
surface; the percent reflection depends on the type of ground cover. The
gravitational settling of the partlculates is accounted for by lowering the
effective height of emission, "tilting the plume", based on the distance to
4-4
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the receptor, the mean wind speed and the terminal velocity of the particle.
The meteorological input to the model consists of the usual stability-
wind rose frequency data, fraction of the time during the period of record
| that precipitation occurred and average rate of precipitation (in hundredths
fc of an inch per hour).
The point source data must include emission rates for all sources in
g/s, stack heights, exit gas temperatures, volume flow rate (or stack diame-
ters and exit velocity), and source locations in UTM coordinates.
f Line source data consists only of the emission rate in g/m/s, height
of the line source, and the UTM coordinates of the line end points.
Receptor locations, likewise, are specified in UTM coordinates.
Modeling of gaseous pollutants requires that the boundary layer
Ji thickness and gas diffusivity be specified while modeling of particulates
m requires specification of particle diameters and densities. This imposes
a potential limitation on the application of this model because reliable
ft particle size and particle density data are generally limited. The fact
that the model considers particle size and particle deposition makes the
| model appealing for use 1n areas with sources that emit larger-sized dust
particles. However, at the present time, severe restrictions over and
m above the basic data input limitation previously described exist which
ป. limit the general usefulness of this technique to the fugitive dust problem.
First, the model does not have the capability to handle a large number of
V sources or receptors, and hence, would be severely limited as a regional
scale model unless significant revisions were made. Second, if the detailed
particle density and particle size spectra are not available, the deposition
and gravitational settling modes of the model cannot be used. Finally, in
I its current form the model is of limited use for establishing control
I
I 4"5
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strategies because of the output format and lack of source contribution
tables.
4.2.3 Hanna-Gifford Model
The Hanna-Gifford model is an area source model that accepts a
gridded emissions inventory. The elements of the emission grid must be
square and they must be of uniform size; however, the specific size is vari-
able (a typical example would be a 2 km x 2 km grid). It is possible to
incorporate physical removal mechanisms (deposition) with minor modifica-
tions (see Appendix B for a detailed discussion of the model). In those
regions where conventional we 11-controlled point sources are present, the
Hanna-Gifford model must be supplemented by one of the models described in
4.2.1 or 4.2.* and the results superimposed.
jr -3C O7 OQ
The basic model has been used in several case studies ' '
in which the comparison of modeled and predicted concentrations has been
examined in detail.
4.2.4 Modified CDM/Rollback Model
A necessary but not sufficient feature of a fugitive dust model is
39
the requirement that it accommodate a range of particle sizes. TRW
developed a modeling procedure that uses the COM to model that portion of
the emissions comprised of particles smaller than 20 ซm and uses a propor-
tional (rollback) analysis to represent the contribution of the larger
particles. The rationale being that the COM is a suitable model for
describing the dispersion of particles smaller than about 10 ym diameter.
However, the COM 1s presently unable to account satisfactorily for the
dispersion-deposition behavior of larger particles characteristic of fugitive
dust sources because it does not contain techniques such as those developed by
40 41
Van der Hoven and Dumbauld, et al. or procedures such as those
4-6
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1
incorporated in the Atmospheric Transport Model.
In order to facilitate this modified modeling approach (see
Appendix C for model description and Appendix D for model input require-
ments), the gridded emissions inventory is prepared for four particle
m diameter ranges reflecting the cut-off points in dispersive behavior;
0 - 10 ym
10-20 ym
20 - 70 ym
greater than 70 urn.
The COM may be applied directly to the first two ranges since
| diffusion and atmospheric turbulence effects play a major role in the move-
ซ ment of these particles. However, for the 10-20jjn size range, the effect
* of gravitational settling is approximated with the assignment of a decay
constant in the COM. The explanation of the derivation of the decay con-
stant is given in Appendix D.
The emissions of particles greater than 70ymin size are ignored in
the air quality model. The fate of these particles will be determined
| almost exclusively by gravity effects. The range of horizontal travel of
^ these particles is only a few meters, generally not enough to impact the
air quality monitors, except for those cases where the local source is very
tf near the monitor.
This technique appears useful because it applies an atmospheric
transport and dispersion model to that portion of the fugitive dust emis-
sions that can be so treated and because it provides a technique for approxi-
jj mating the impact of the emissions of larger particles. The technique has
^ not been widely applied and should be used with caution. Appendix E pro-
vides a sample application of the CDM/Rollback Model.
I
1
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4.3 SUMMARY
At the present time, the consideration of fugitive dust sources in
diffusion models is limited. Continued use of AQDM and CDM appears to be
the most reasonable approach for those are?s where particles less than
10 micrometers predominate. Other techniques may be more useful in those
areas where larger sized particles are common (e.g., west and artd south-
west). The procedures included herein should not be considered inclusive
and should not inhibit the development and incorporation of various modi-
fications and Improvements.
4-8
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I
1
5.0 ALTERNATIVE CONTROL MEASURES
fl In areas where fugitive dust is the cause of high levels of TSP, the
major sources are typically unpaved roads, construction activities,
ff re-entrained street dust, and suspended soil eroded by wind off vacant
lots and disturbed soil surfaces. While the impact of these sources is
m generally localized in nature, they are typically found throughout a
_. given area and therefore may create widespread problems of high TSP concen-
* trations. However, several other sources of fugitive dust (i.e., tailing
piles) are generally less widespread and create more of a truly localized
limited Impact for a specific area.
In order to determine the impact of the sources most responsible for
the high TSP levels at various monitoring sites for the baseyear and
I projected years, 1t 1s necessary to review the emission inventory and
modeling results which have been previously discussed in Sections 3.0 and
4.0. A review of these results will establish the significant sources
ฃ for which alternative control options should be investigated. The control
options for various fugitive dust source categories are outlined below.
5.1 Control of Dust from Unpaved Roads
Control methods to reduce dust emissions from unpaved roads consist
I of (1) paving roads, (2) application of chemical stabilizers, (3) watering,
. and (4) traffic-related controls. Some communities have experimented with
these alternatives and may be considering the implementation of these
measures in the general plan for the area. Relevant county and city depart-
ments should be consulted to identify prospective planning efforts with
ป potential air quality impacts, and to obtain data which would help charac-
terize dust control applications for unpaved roads in the study area.
i
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42
A study was recently completed ir. wHch various chemical stabrH/vzers
were tested for dust control on unpaved rfK.ds. Th? stabilizers were
applied to sections of an unpaved roao wnh a;i average da-.'iy traffic
(ADT) of 140 vehicles and a surface soil si'U co-rc^ii; of ?J.s%- Sosno or
the chemicals were applied by spray, v^.ile cc.ws were mixed to a inreu-
inch depth after ripping the roacibsd survace, .-ii-vo'. ana dim: collector
measurements were utilized to evaluate -cha dust-suur^ssing abVircy or the
stabilizers with the rtat subject to '.v-^al trarnc i;o>r,Li;n:Ms. The
performance of the stabl 1 ', zev products '
-------
I
* Emulsion, which was controlling dust emissions by 84.4% after a 14-month
period. The main drawback to use of the effective stabilizers is cost.
Repeated applications of the chemicals, even at reduced rates, impose
I costs which approach or exceed the annualized cost of a paved road.
Paving of roads clearly offers the most effective long-term dust
| control. The most widely used low cost pavement is the bituminous
_. asphaltic chip seal over a granular base or a stabilized soil base.
Figure 5-1 shows a profile of this chip seal construction. A penetration
A stabilizer (liquid asphalt MC-250) is applied to the 6- to 8- inch
base, followed by a chip seal. Maintenance requirements depend on vehicle
traffic and locale, but generally include a second chip seal after one
year, followed by another seal in approximately 5 years.
ซ26
A study conducted by the city of Seattle Engineering Department
has shown the most cost effective method of dust control on Seattle road-
ways is a chip seal when the average dally traffic is over 100 vehicles.
This dust control option is also economically beneficial, considering the
estimated annual savings of $2,665/yr/mi in maintenance costs resulting
from the measure (annual maintenance costs of roadways diminishes apprec-
iably with the quality of the road surface) and numerous other cost benefits,
| such as reduced sewer costs, higher property values, lower vehicle operating
ซ> costs, lower health costs, and reduced cleaning costs.
* The cost of the various types of road paving and dust palliative
alternatives varies from one region to another. Construction, maintenance,
and material costs contrast significantly between regions. Typical cost
of initial installation and maintenance for various dust control alternatives
in Maricopa County (Arizona) is shown in Table 5-3. Actual costs for any
I given study region should be determined by inquiring with the local trans-
portation departments.
I 5-5
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IQ1L
Exfefina Base Material
Figure 5-1. Profile of Typical Section for Chip Seal Road
Surface Construction
5-6
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TABLE 5-3. INITIAL COST AND MAINTENANCE COST
fOF ALTERNATIVE ROAD SURFACES APPLIED &9 77
BY MARICOPA COUNTY HIGHWAY DEPARTMENT *' .
I
1
t
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ROAD SURFACE TYPE
Gravel Road
Oiled surface (low cost Applica-
tion)
Oiled surface dust control oil
Chip seal coat
3" asphalt
INITIAL COST PER MILE
$
$
$
$
$
16,000
2000-3000
5,300
35,000
55,000-100,000
ANNUAL MAINTENANCE t
1
$
$
$
$
$
600
2000-3000
5,300
800
160
U Control efficiency estimates for the various dust measures arc tabulated
by considering the effect of altering a road which is presently an unpaved
dirt surface having a silt content representative of the study area. Cost
m effectiveness is then estimated by considering the annualized cost of the
measure in the given study area and the resulting emissions reduction.
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Efficiencies and cost effectiveness estimates are shown in Table 5-4. The
chip seal surface appears to be somewhat more cost effective than the other
road surfacing dust control measures, and of those measures providing the
best control, the chip seal is significantly more cost effective. These
26
findings are consistent with the Duwamish Valley Study where it was
found that the least cost control was a chip seal surfacing when ADT is 150.
However, when ADT decreases to 15, lighter applications of the road dust
palliatives may be used to attain a certain level of dust control and cost
effectiveness of the palliative in this instance becomes competitive with the
5-7
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chip seal paving approach. It should be notod that the cost figures of
Table 5-4 are presented for illustrative pur, oses, and may vary greatly
depending on locale and existing construction and road maintenance practices.
TABLE 5-4. EFFECTIVENESS OF ALTERNATIVE ROAD SURFACES IN REDUCING
DUST EMISSIONS FROM AN UNPAVED ROAD IN MARICOPA COUNTY.
ARIZONA
ROAD TYPE
01 rt Surface
Gravel
011 Surface (Dust Control
011)
Oiled Surface (Low cost
Application)
Chip Seal
Asphalt
EMISSION RATE
LB/VEHICLE MI.
22a
lla
5f
11^
oe
oc
ANNUAL
EFFICIENCY
50%
75%
50%
100%
100%
COST EFFECTIVENESS0
$/TON OF DUST
11.0
19.5
13.5
10.8d
19. 6d '
b.
c.
44
and road silt content of 24% and
Based on AP-42 emission factor
average vehicle speed of 35 mph.
From reference
Computations based on assumption of ADT of 100, maintenance costs of
Table 5-3, and annuallzed cost for Indefinite period at 10% interest.
These figures do not Include the dust reductions attained by Inducement
of traffic off unpaved roads to the newly paved surface.
This emission rate does not Include entrapment of dust loadings off the
pavement. Entrained dust emissions are discussed 1n Section 3.1.2.
42
Based on field test conducted by Arizona Department of Transportation .
5-8
-------
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Traffic controls also offer potential for dust emission reductions
1 from unpaved roads. Dust emissions increase exponentially with vehicle
OC OT
ป speed up to 30 mph ' . Table 5-5 illustrates the dust emission
* rate at different speeds for a vehicle travelling over a dirt road.
Based on an average speed of 35 mph, the reduction achieved by restricting
vehicle speed to 20 mph would be 62 percent.
Restriction in use of unpaved roads may also be employed to reduce
ฃ dust emissions. Unpaved roads may be closed to travel when alternative
paved routes are available. The potential of this dust control measure
I is not encouraging since almost all roads provide needed access to at
least a limited segment of the population, and it is not plausible to
ฃ restrict traffic to only this limited sector. It should be noted, however,
that traffic volume on the remaining interior unpaved roads will be diverted
significantly after addition of paved routes to the road network. Such
m traffic inducement should be considered in assessing the total effectiveness
of the road-surfacing measures. For example, a plan to pave half the
ป section Hne roads in Maricopa County (Arizona) by 1985 would reduce
45
expected traffic on remaining Interior unpaved roads by 15 percent .
This analysis is made by considering the trip alternatives in a representative
section of the road network for the "before and after" paving control measure.
5-9
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TABLE 5-5. DUST EMISSION RATES MT DTFFERENT VEHICLE SPEEDS
SPEED OF
VEHICLE
35
30
25
20
EMISSION RATE3-
LB/VEHICLE MI.
22,0
19.0
13,0
8.5
DEGREE OF EMISSIONS
REDUCTION
14%
41*
62%
44
a. The emission rate is based on the, AP-42 emission factor for vehicle
speeds of *Q mph and over. For speeds from 0 to 30 mph the emission rate
increases exponentially with speed and is calculated as follows: e = .0211 SS
wnere e * emission rate (It/vehicle mi), and S ซ vehicle speed (mph). The
baseline emission rate (35 mph) was calculated assuming a typical dirt
road s1 It level of 24*.
5.2 CONTROL OF ENTRAINED STREET DUST
Various field studies have indicated that dust emissions from paved streets
46
are a major component of material collected by high-volume samplers. Re-
entrained traffic dust has been found to consist primarily of mineral matter
similar to common sand and soil, mostly tracked or deposited onto the roadway by
vehicles, but also including engine exhaust, from wear of bearing and brake
Itntngs, and from abrasion. These forms of dust may settle to the street sur-
face and become subsequently reentrained. The patterns of tiiaterl*! deposition
on the street suggest the control of entrained street dust by two principal
methods: 1) control of the street dust origins, and 2) street cleaning.
5-10
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Control of the Dust Origins
One obvious means of reducing street dust loadings is by controlling
its origins. Significant origins consist of carryout of dust from dirt
surfaces by motor vehicles, atmospheric fallout of airborne particulates,
and transport from adjacent exposed land areas. In areas experiencing
arid climates, the major sources of street dust originate from transport
of exposed soil from areas near the streets (i.e., unpaved road shoulders).
Dust from the exposed road shoulders is transported to the street surface
by turbulence from passing vehicles, wind erosion, tracking by pedestrians
and vehicles, and water runoff. Soil carryout by motor vehciles is also
a significant cause of street dust, particularly in areas with abundant
rainfall.
In many areas, roadway improvements anticipated in the next several
years will result in significant impacts on street dust loadings. These
improvements are important because dust loadings for streets with uncurbed
shoulders are estimated to be four times greater than that observed for
47
curbed streets The substantial portion of curbing and gutter
improvements will occur in the cities. Since the major portion of
vehicle miles traveled in any area are concentrated within the cities, the
urban street improvements will have far greater impact on TSP levels than
would similar improvements implemented in county road networks. Accordingly,
intensification of the street improvement plans should be considered as a
potential control for street dust emissions.
5-11
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To increase the effectiveness of street curbings as a dust control
measure, the adjacent soil should be stabilized or covered to prevent
wind erosion or tracking of this soil onto the street. Clearly, the
most effective means of soil protection at the curb is a sidewalk. A
typical and desirable city policy is to include sidewalks whenever curbs
are constructed on major streets. The effectiveness of this measure has
not been quantified, but 1t is expected that transfer of exposed soil to
adjacent road surfaces will be decreased significantly.
Typical city construction costs for street curbs are currently
about $5 per curb foot. The cost of sidewalk construction is $6 per
48
running foot of a standard 5 foot wide sidewalk
In cities where sanding 1s used on streets for snow and ice control,
modifications can betmade in the sanding operations to reduce air quality
impact without Increasing the hazard of vehicle accidents. Some of these
modifications are:
. replace the sand with salt or a salt/sand mix;
. plow streets instead of sanding;
. clear the sanding material from street as soon as possible after
each storm;
. apply material only at intersections and on hills and curves
(reduce the amount applied);
. use sand that has been washed and sized.
It 1s not possible to quantify the air quality Impact of each of these changes
or their combinations, but the simple assumption could be made that the impact
from sanding would be reduced proportionately to any reduction in the amount
of sand used on a street in a given area.
5-12
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Street Cleaning
There are three main types of machine street sweepers currently in use.
Broom sweepers utilize a rotating gutter broom to sweep material from the
gutter into the main pickup broom which rotates to carry the material into
the truck hoppers. The broom sweeper is by far the most commonly used class
of sweeper. A second type of sweeper, called the regenerative air sweeper,
uses an air blast to direct material into a collection hopper. A third type
of sweeper utilizes a broom and vacuum system to collect material. Each of
the sweepers employs a water spray to control dust emissions during sweep-
ing. In addition to machine street sweepers, various cities use flushers
which use a jet of water to move material to the gutter rather than actual
material pickup.
Broom sweeping has two operational characteristics that make its use
alone of doubtful value-it moves material from the gutter back into the
street for pickup and it is not efficient in removing fine particles that
aremost susceptible to re-entra1nment. Flushing probably shows the most
promise with regenerative air and vacuum sweeper somewhere in between for
reducing re-entrained dust. It wets the otreet, causing dust suppression until
the surface is completely dry, and moves material out of the traffic lanes to
the gutters. The only practical limitation on the use of flushers is in areas
where water availability is restricted. Flushers use 3,000 to 4,000 gallons
of water per mile of street, or up to 70,000 gal/day. Therefore, street flush-
ing could easily constitute 1 to 2 percent of a city's total water consumption.
14
In a recent field study performed by PEDCo for EPA in Kansas City and
Cincinnati, air quality impacts were measured using alternative street cleaning
techniques. In Kansas City, data indicated that air quality improved 8 to 18
ug/m3 with flushing, whereas broom cleaning showed no improvement
5-13
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For Cincinnati, the air quality impacts from flushing and broom sweeping
showed the reverse from that in Kansas City. Also, in Cincinnati where
vacuum sweeping was tested, it was not shovn to be effective in reducing
particulate concentrations. This finding was unexpected considering the
demonstrated efficiency of the vacuum units in removing small size parti-
cles from street surfaces and their overall street cleaning efficiency.
These cleaning efficiencies were determined from street loading measure-
ments taken before and after each cleaning operation.
Also, in the REDCo study, particulate air quality were obtained or
results were summarized from studies In five cities in which potential
control measures had been implemented (i.e., some type of street cleaning
program). Tht.,e cities or studies are: New York - New Jersey; Kansas City,
Kansas; Charlotte, North Carolina; Chicago, Illinois; and Twin Falls,
Idaho, The air quality data was reviewed to determine whether the programs
had a discernible effect on particulate concentrations. The findings were
inconclusive with regard to the effectiveness of improved street cleaning
as shown in Table 5-5.
Table 5-5
Cleaning method
Broom sweeping
Vacuum sweeping
Regenerative air sweeping
Flushing
Sweeping and flushing
Studies 1n
which method
was effective
1
0
0
2
0
Studies in
which method
was ineffective
2
2
1
2
1
5-14
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Intuitively, street cleaning as a control measure should reduce
re-entrained dust, but is still unproven as an effective method for
reducing ambient TSP concentrations, therefore, caution is advised in
undertaking control programs involving street cleaning. It is entire-
ly possible that changes in operating procedures (e.g., more frequent,
better operator training) or better designed equipment with environ-
mental concern in mind or other improvements in street cleaning methods
would reduce ambient concentrations. However, prior to any full scale
modification of a city's street cleaning program, a pilot study in-
corporating a sweeping project is recommended at least until more data
on the effectiveness of improved street cleaning methods become avail-
able. The interest and support of the public works department are
necessary in order for the measure to be successful. If the changes
are not supported or measured as important, an expanded or improved
cleaning program will probably not translate into an air quality improve-
ment.
Another reason for testing street cleaning modifications on a smal-
ler scale is that study data from one city may not be applicable in a-
nother due to great difference in street systems (storm drainage, curbs
and gutters, age and type of surface, etc.) and capabilities of street
departments.*
Refer to EPA-907/9-77-007 document, Control of Re-entrained Dust From
Paved Streets for more detailed information on street cleaning, con-
struction site control, and associated cost. Additional guidance is
currently being prepared for pilot street cleaning studies. This is
expected by November, 1977.
5-15
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5.3 CONTROL OF DUST EMISSIONS FROM CONSTRUCTION AND DEMOLITION ACTIVITIES
Construction activities are temporary and variable in nature. Fugitive
dust is emitted both during the activities (e.y., excavation, vehicle opera-
tion, equipment operations) and as a result of wind erosion over the
exposed earth surfaces. Earth moving activities comprise the major source
of construction dust emissions, but traffic and general disturbance of
the soil also generate significant dust emissions.
Wetting the surfaces of unpaved access trails for construction
vehicles and trucks is an effective control for dust emissions provided the
surface is ma..itained wet. In arid regions this generally requires an
appreciable amount of water. A study on the effect of watering on construction
sites indicates that extensive wetting of the soil may reduce emissions
from existing construction operations" Up to 60 to 70 percent The
study suggested that wetting of access roads twice a day with an application
of .5 gal of water per square yard will suppress dust emissions from
existing baseline construction practices by 50 percent. It was assumed
that a certain degree of dust control is currently achieved at most construc-
tion sites, due to typical local regulations requiring reasonable precautions
be exercised in these dust emissions.
A negative tradeoff associated with watering controls at construction sites
concerns the carryout of mud onto adjacent streets. The carried out mud later
becomes dust again and is susceptible to suspension by passing vehicles. If the
construction site is frequented by an appreciable amount of traffic and watering
controls are amply employed, mud carryout will be significant and should be con-
trolled, A practical means of removing the mud is cleaning the streets in the
vicinity of the construction site. Cleaning could be employed daily to clean
those paved roads within the proximity of the site and which are used by vehicles
5-16
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1
I
1
exiting off the site. The sweeping program could be conducted in cooperation
with the City Maintenance Department. It is not possible to generalize an
effectiveness for this action.
An additional dust source at construction sites consists of exposed
earth which is susceptible to wind erosion, and to dust emissions from infre-
quent traffic disturbance. While the suspended dust from this source is
generally insignificant, there are brief periods (i.e., during wind gusts or
traffic bursts) when the resulting dust levels may create a nuisance to
nearby inhabitants. Dust emissions from these sources may be reduced by
combining two control actions. First, a soil stabilizer, such as a chemical
palliative or vegetation cover may be applied. A second control action would
involve a stipulation that cleared earth be exposed for a limited period
before subsequent operations on this land commence. This would prevent the
frequent practice of clearance of vast plots of land where subsequent construc-
tion operations are not scheduled to begin for several months. Clearance
would be permitted only if accompanied by soil stabilization measures within
a certain period of the clearing. The method is quite effective in minimizing
the wind erosion impact of construction activities. However, there is little
definite information to quantify the impact from an overall % control effi-
ciency. However, one can apply the wind erosion equation to the conditions
I
1
I
I
I
I
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I
Cost estimates of the alternative dust control measures for construction
site emissions in the Phoenix area are shown in Table 5-6 for illustrative
purposes. These control costs will vary from region-to-region due to differ-
9 ences in water availability, street sweeping costs, and cost of dust pallia-
^ tives and their application. A region-specific study is needed to determine
the actual cost of the candidate measures in the region targeted for controls.
I
before and after control and obtain the % reduction in suspended soil. This
15
technique is outlined in Reference
5-17
I
-------
Dust emissions at demolition sites derive from essentially the same
source as those found on construction sites. These sources involve earth-
moving activities, and general disturbance of the soil. The control methods
available for these sources are the same as that employed at construction
sites (e.g., wetting of access roads). A significant portion of dust associ-
ated with demolition activities may also be generated by falling walls, and
an additional significant emission hazard concerns the release of asbestos
particles when demolition involves friable asbestos materials. The latter
hazard has resulted in the promulgation of demolition and renovation
49
standards for institutional, industrial, and commercial buildings con-
taining a specified amount of friable asbestos materials. These standards
require that asbestos materials must be removed prior to wrecking activities
by specified handling procedures, and that these materials be wetted prior
to removal and handling. The dust created by falling walls of brick, plaster
or concrete may be mitigated by spraying walls with water before teardown
and immediately after the fall. This control method may reduce emissions from
50
masonry demolition by 10 to 20% .
5-18
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5-19
-------
5.4 CONTROLS FOR AGRICULTURAL DUST EMISSIONS
Techniques for controlling fugitive dust from agricultural areas
include:
1. Continuous cropping with limited field exposure
2. Crop residue management and modified tilling operations
3. Limited Irrigation of fallow fields
4. Windbreaks and stripcropping
5. Chemical soil stabilizers
The effectiveness of each of the alternative control technqiues
can be determined by computing the influence of each control on the
wind erosion equation (E = AIKCL'V). Continuous cropping, crop
residue and stubble, and stripcropping will effect the vegetative factor
( V) of the equation; some aspects of modified tilling will affect the
roughness factor (K) and the climatic factor (C); windbreaks will
effect the unsheltered field length factor ( L'); and chemical soil
15, 17
stabilizers will affect soil credibility
5.4.1 Continuous Cropping
This technique, which attains maximum productivity from a cropland,
is one which also lessens the length of the period of barren field exposure
to wind erosion. Continuous cropping may be accomplished by repeated
plantings of a single specific crop, or may involve a complex process of
rotating various crop types on a given field throughout the year. Some
of the Important factors which Influence the fanners decision to plant a
certain type of crop within this rotational scheme are season, water
demand, water availability, market demand, and the length of time that is
required for the duration of the crop. The key limiting factors to
continuous cropping are the lack of rainfall and regulated water al-
locations to farmlands.
5-20
-------
In many agricultural areas, there are periods when fields are fallow
while preparations are being made for the next crop as well as periods
where fields are barren while in the seedling stage. For example,
consider the crops of cotton and sorghum. Assuming that the non-growing,
residue period for cotton is three months, and that during this time an
alternate crop is planted (such as a fast growing grain which takes about
a month to cover the ground, enough to eliminate wind erosion) the annual
fugitive emissions off the cotton field that would otherwise lie fallow
for three months could be reduced about 67 percent. For sorghum, the
non-growing residue period is November to July. Planting of wheat after
sorghum harvest in December would leave the sorghum field in residue
for only one month, resulting in a 78 percent reduction in annual
emissions on fields previously growing only a sorghum crop.
Cost of continuous cropping measures depend on numerous factors
such as water availability, additional manpower and equipment requirements,
crop resource requirements, and crop market value.
5.4.2 Crop Residue and Modified Tilling Operations
Protection from wind erosion can often be provided by leaving the
residue or standing stubble of a crop after it has been harvested. The
quantity and quality of stubble mulch which is required to prevent soil
blowing varies by crop type, soil characteristics, climate, and whether
the residue is standing or flattened. For instance, in a semi-arid area,
on a silt loam soil with 25 percent non-erodible fractions, 750 Ibs.
per acre of one foot standing wheat stubble or 1500 Ibs. per acre of one
foot flattened wheat residue is required for complete protection against
soil erosion, while on a loamy sand, 1750 Ibs. per acre of 12" standing
stubble or 3500 Ibs per acre of 12" flattened residue is required,
and, if sorghum is used instead of wheat, twice the weight of sorghum
5-21
-------
$2
is required . Fine residues provide better protection than
short crop residues. Modifying tilling and plowing operations to
create the most dust free condition on a given field is a complex
issue which depends on the type of crop being Harvested, the next
crop to be planted, the period between crops, and the manpower, equipment,
and time requirements of the farmer.
The length of time that the standing residue of wheat and barley 1s
left unaltered on fields 1s generally not regulated. Normally, the
farmer turns residue under when 1t is convenient. This might happen
very soon before the next planting or as much as a month before the next
planting. If tilling 1s postponed until just before it is necessary
to prepare the field for the next crop, wind-blown emissions are reduced
by the fraction of total soil exposure time saved by the postponement.
The potential emissions reductions w,h1ch can be achieved for an agri-
cultural region 1s difficult to determine because the exact chronology
of the various farmer's activities are not generally known.
No-tillage farming 1s currently being used as an advanced farming
method to prevent soil erosion, Increase cropland production, and to
53
reduce farming costs . Despite the economic benefits of no-till age
farming, there 1s substantial resistance by farmers to depart from
accepted practice. If tilling remains the accepted practice for crop
field preparations, and 1s delayed so that the residue can continue to
provide soil erosion control as long as possible, significant additional
expense will result from additional manpower and equipment required to
carry out tilling operations 1n a shorter period of time.
5-22
-------
Stripcropping consists of the inter-row planting of erosion-resistant
crops on fields with other crops which are erosion-susceptible. Small grains
which are closely seeded and cover the ground rapidly are erosion-resistant.
ฃ Cotton, sugar beets, peas, beans, and true' crops are generally erosion-
_ susceptible. The cost of grain Stripcropping varies with the grain type
" and the requirements of that grain and also according to the requirements
of the erosion-susceptible crop which is being protected. Modifications
in machinery may have to be made in order to tend the crop requirements of
I
I
I
a double-cropped field.
Stripcropping may be employed most effectively during the early months
of a crop development before foliage 1s sufficient to provide soil erosion
protection, "owever, the degree of protection provided by this method
would be minimal. As the main crop begins to develop, the reduction of soil
erosion caused by the accompanying Irrigation itself would probably exceed
the dust control benefits gained through Stripcropping.
| 5.4.5 Chemical Soil Stabilizers
While a field is 1n the seedling stage or is barren, wind erosion can
ป be reduced considerably with chemical stabilization. Investigation has shown
m that the liquid, petroleum res1n-in-water emulsion, 1s the most effective,
durable, and economical of the many available varieties of stabilizers for
1 this purpose. Use of herbicides 1s also required as the stabilizers provide
surface layer protection only, and normal weed removal practices would disturb
I the protective layer
Documentation of the effectiveness of the stabilizers in reducing dust
emissions is presently limited. Based on a recent study of soil stabilizers
42
conducted by the State of Arizona Department of Transportation , the
* wind-blown dust emissions from agricultural lands can be reduced by about
f90% provided the surface layer remains undisturbed. Cost of applying the
15
various stabilizers varies from about $100 to $650 per acre
I
5-24
-------
5.4.3 Limited Irrigation of Fallow Fields
The periodic irrigation of a barren field will provide control of
blowing soil by increasing soil moisture and crusting the soil surface.
The impact of irrigation on dust emissions may be estimated by determining
the change in climatic factor (C) and soil credibility (I) due to
additional surface crusting. The amount of water and the frequency
of each irrigation during fallow to maintain a desired level of control
would be a function of the season and of the crusting ability of the
soil. The main drawback to irrigation control concerns availability of
water, cost of water, and interference with farming activities on the
cropland
5.4.4 Windbreaks and Stripcropping
Both windbreaks and Stripcropping are intended to reduce wind erosion
by reducing the wind velocity over barren soil. The most effective
results are obtained when planting (or placement of physical barriers)
is done perpendicular to the prevailing wind direction. Windbreaks
occur around the field, while Stripcropping occurs within the field.
A windbreak provides lateral wind erosion control equal to ten
52
times the barrier height . A barrier 25 feet in height will control
erosion over 250 feet. Therefore, on a typical 2000 foot long field,
erosion can theoretically be reduced by about 12 percent. The most
severe drawback of windbreaks for erosion control is their very high
cost. Large scale application of windbreaks for erosion control is
generally considered unfeasible, particularly in arid areas where
water availability is limited.
5-23
-------
Table 5-7 summarizes the range of effectiveness and cost of various control
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15
measures for agricultural dust emissions
5.5 Control of Tailing Piles
Control methods for fugitive dust emissions from mineral waste heaps
| include: (1) physical control; (2) chemical binding; and, (3) vegetative
cover. The applicability and cost of these controls varies depending on
the type of mineral waste and the region in which it is located. Also,
applicability varies with other environmental control objectives, such as
" aesthetics, water pollution control, land use, etc.
Physical stabilization of tailings with a cover rock or smelter slag
can provide complete control of wigd-blown emissions. A mixture of soil
- I
and rock available from adjacent lands is a more widely used cover material.
Soil cover is subject to wind erosion to a lesser degree than the tailings,
|ง and permits a habitat for encroachment of local vegetation. The degree of
control provided by the soil cover is determined by the difference in erodi-
* bility of the soil and the more erodible tailings fines. The primary draw-
back to physical covers as erosion^controls 1s the high cost of application,
particularly when the cover materials are unavailable in the"immediate area.
Chemical stabilizers are commercially available and have been employed
15
in numerous applications to create a crusted erosion-resistant layer on
mineral waste piles. In applications where the tailings surface is not sub-
ject to disturbance, stabilization by crusting attains a control efficiency
of about 80% . Since chemical layers create only a thin skin of protec-
tion, they offer only temporary protection, and repeated applications are
required periodically to maintain the crust. Chemical stabilizers are typi-
V
cally used in combination with vegetation to form long-term erosion-resistant
surfaces over tailings piles. The chemicals promote vegetation growth and
protect seeds during the germination period. The effectiveness of the vege-
tation in reducing fugitive dust emissions depends on the density and nature
5-25
-------
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I o! '.he growth. In arotis, anrl for tailings piles which will support heavy
vegetation, wind erosion dust emissions may be virtually eliminated. However,
in areas less hospitable to plant growth, such as the arid southwest, only
native species may be grown (sagebrush, Indian rice grass, sand dropseed).
Assuming a moderate vegetation rate of 500 Ibs/acre v/as attained, fugitive
I dust emissions from the tailing piles would be reduced approximately 25%.
I
I
I
54
(see Section 3.2.2) .
Table 5-8 summarizes the range of effectiveness and cost of the control
measures to reduce tailing pile emissions.
5.6 Control of Unpaved Parking Lots and Truck Stops
The alternative controls for mitigating dust emissions from unpaved
parking lots are the same as those which may be applied for unpaved roads
| (see Section 5.1). The traffic surface may be improved by paving, gravel -
ing, or applying a dust palliative. Table 5-9 lists the efficiency and cost
of controls for parking lot dust emissions. Since no data are available to
characterize the effectiveness of the measures specifically for parking lots,
the figures of Table 5-9 are based on the assumption the measures are
equally effective for parking lots as for unpaved roads. The cost data are
the same as cost for applications for road surfacing discussed earlier. Actual
costs may vary significantly from region-to-region, and should be determined
specifically by inquiry with local transportation departments.
_
5.7 Control of Emissions from Disturbed Soil Surfaces
Feasible control methods to reduce wind-blown dust emissions from disturbed
soil surfaces are similar to those described for tailings piles (Section 5.5)
( and unpaved parking lots (Section 5.6). Control measures include chemical
stabilization, vegetation, and physical covers. For those soil surfaces which
receive periodic traffic, such as residence yards, playgrounds, and some vacant
A lots, application of chemical stabilizers must be intensified similar to that
required for control of unpaved road surfaces. Soil covers such as gravel may
5-27
-------
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5-29
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provide varying levels of dust protection depending on the application density.
For soil surfaces frequented by minimal traffic, combined vegetation and chemi-
cal stabilization generally provide the most cost effective control, particu-
larly in areas where rainfall is sufficient to support vegetation.
5-30
-------
I 6.0 INTEGRATION OF FUGITIVE DUST SOURCE IMPACTS
INTO THE STATE IMPLEMENTATION PLANNING PROCESS
" 6.1 INTRODUCTION
While considerable progress has been made in reducing ambient TSP concen-
trations in many locations, it is apparent that the primary National Ambient
Air Quality Standards (NAAQS) for TSP will not be attained on a nationwide
basis under the existing State Implementation Plans (SIPs). In light of this,
| States are required by Section 172 of the Clean Air Act of 1977 to submit
Implementation Plans by January 1, 1979 to attain the NAAQS for TSP as expedi-
tiously as practical, but no later than December 31, 1982. As part of this
revision process, the States must seriously evaluate the impact of all parti-
culate matter sources, including fugitive dust sources, and provide a revised
SIP to include its control within areas of non-attainment. If needed,
strategies for fugitive dust should be developed as a minimum for those areas
jp where the impact of these sources (by themselves or in combination with other
particulate matter sources) causes a significant impact upon the health and
welfare of the general population. An overall comprehensive control program
m for fugitive dust may not be realistic for all areas of the country, especially
for those areas where natural sources, independent of man's activity are the
8 predominate influencing factors (i.e., isolated rural areas).
All strategies developed with areas significantly impacted by fugitive
J dust sources should reflect the application of needed reasonable control
measures to those fugitive dust sources which are ttoe major contributors to
the fugitive dust problem. Such control measures should provide for control
of fugitive dust sources as expeditiously as practicable.
6.2 EVALUATION OF CONTROL STRATEGY
tt 6.2.1 Impact of Control Strategy on Emission Levels
The emission levels that will result after various control strategy
measures are implemented should be estimated for both the target years of
I
6-1
-------
attainment and projected years, considering growth of new emission sources.
Control efficiency information for various fugitive dust control measures,
(provided in Section 5) in addition to baseline and projected emissions inven-
tories, provide the data base needed for these estimations. The estimated
emissions that will result after control regulations are adopted and imple-
mented should be spatially resolved to the same level of detail as the base-
line inventory. In making such an analysis, a judgment must be made as to
emission reduction impact that will result for compliance with existing emis-
sion control regulations (e.g., stationary source as well as fugitive dust
control regulations). If the existing regulations are determined to be inade-
quate for the attainment of the NAAQS, additional emission control measures
will be needed.
Once a list of candidate measures has been identified, selection of
a control strategy 1s an iterative process accomplished by means of successive
.tests of alternatives usingซ;a source-receptor model to predict resulting air
quality levels (see Section 4.3.2). Through a series of iterative trial
judgments, a strategy should be established which attains the air quality
standard utilizing the most cost effective combination of control measures
available. The impact of controls for individual major source categories
should also be investigated as an aid in determining a reasonable mix of the
various controls for the overall attainment objective.
The control strategy should be selective for the major sources affect-
Ing air quality. The strategy may be widespread and/or site-specific depending
on the distribution of the major sources causing high TSP levels. An overall
areawlde strategy should be proposed to deal with the areawide TSP problem
Insuring attainment of air quality standards at all points within the area of
concern. As various trial alternative strategies are tested, it should become
clear which areas in the study region may need local controls. For example,
certain controls (such as street sweeping) are more effective within the center
6-2
-------
I
cable. An adequate documentation of the analysis should be prepared for future
reference.
city commercial areas, while others (e.g., road paving) are more effective in
m outlining suburban areas which are still developing.
The overall control strategy developed for fugitive dust sources
fl should reflect the degree of control necessary to attain the NAAQS from both
the short-term and annual average aspects. In most cases, the long-term area-
wide impact will be the binding constraint; however, in some cases, the short-
term or localized impact could be of some significance and it should be evaluated.
Once the strategy is finalized, enforceable regulations and compliance test
M methods must be developed to implement the strategy. The final control strategy
should provide for control of fugitive dust sources as expeditiously as practi-
I
I
6.2.2 Cost of Strategy
The cost of implementing the control measures will vary widely from
urban area to urban area. Local cost data should be obtained from those who
will be responsible for implementing the measures under consideration. The
g total cost of instituting the control strategy should be expressed in terms
of cost effectiveness and compared to other measures currently being enforced
by existing regulations. Control strategy cost should also be compared to
overall city and department budgets to assess the economic significance of the
proposed measures in comparison to existing expenditures and planned rates of
increase.
An important aspect in assessing the cost of the controls concerns the
| time frame outlined for implementation. A control plan should examine the
~ schedule for implementation to determine if significant cost impacts can be
minimized by extending the time frame a year or two to ease the economic burden
and allow for a more realistic program that can be implemented to demonstrate
I marked improvements in air quality.
I
6-3
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6.3 GUIDES FOR THE SELECTION OF REASONABLE CONTROL MEASURES
Reasonably available control technology (RACT) defines the lowest
emission limit that a particular source is capable of meeting by the
application of control technology that is reasonably available considering
technological and economic feasibility. RACT for source categories with
somewhat undefined emission points may represent relatively stringent
requirements which in many situations force the application of measures
not previously adopted or implemented in a given area. The technological
and economic feasibility of various controls will differ depending on
several factors indigenous to the area under consideration. General factors
affecting ',,'ie reasonableness of a control measure, and which may vary from
area-to-area include:
o The compatibility of the controls with the overall goals and plans
for the area
o The timetable for Implementation
o The degree of control required
o The financing mechanisms available for implementation
The extent to which the proposed control measures are compatible with
planned development affects the cost and technological feasibility of the
measure. For example, the paving of roads for dust control is entirely
compatible with long-term city development objectives to improve the transpor-
tation network. Similarly, the Improvement of road shoulders to reduce
street dust loadings and re-entra1nment of this dust to the ambient air is
completely consistent with city objectives to improve the quality of life in
the city. This compatibility lends to greater general technical and economic
feasibility for the dust control measures because of the other desirable
benefits they provide.
6-4
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I
Another consideration in the determination of reasonable measures
involves the degree of control which is sought. The ultimate goal of a
0 reasonable control strategy is the achievement of the national ambient
^ air quality standards. The higher the level of control needed for attain-
ment, the greater is the potential for technical and economic demands to
be the binding constraint when considering a control strategy to attain
the NAAQS.
The economic feasibility of any control alternative is greatly affected
by the extent and manner of funding available. Cost required for implemen-
g tation of different controls can be compared and expressed in terms of
the impact per capita. The source and ease of funding should be identified
9 and evaluated. Some controls (such as street sweeping, road surfacing) will
be funded by taxes or other governmental money-raising mechanisms, while
others will be paid by commercial enterprises.
It is clear that social acceptance is important to the success of the
implementation of a control strategy. Consequently, steps should be taken
| where appropriate to determine the social acceptability of the measures under
_ consideration. A demonstration project, as part of the first phase of imple-
9 mentation, may be used to generate public support when necessary. The elements
of the demonstration project, and its implications for resolving implementa-
tion difficulties, are considered in Section 6.4.
I A measure which is reasonable in one area may be unreasonable in another.
In general, most of the measures for control of fugitive dust are reasonable
| with a few exceptions, the major one being the widespread application of
chemical stabilizers to agricultural lands. While this method does have
application on a limited basis for dealing with short-term construction
projects, its overall environmental impacts are questionable if used without
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6-5
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care. This measure may have certain multi-media impacts which have not
been fully evaluated to date which may make its widespread application
nationwide for agricultural areas unreasor.ible. However, for the most part,
fugitive dust control measures are reasonable from a technical point of
view. Selection, therefore, involves a determination of the most cost effec-
tive measures which will provide the air quality improvements needed for
standards attainment. The timing for the application of control measures
is also an important factor when considering the economic feasibility
of a certain measure. For example, it may be necessary to pave a large
number of unpaved roads to bring about attainment, with any lesser degree
being inadequate. However, this may be unreasonable from an economic,
standpoint unless this paving program is done in phases over the next couple
of years. Thus, timing, economics and technical feasibility must be examined
in order to develop the types of controls necessary to provide an overall
comprehensive achievable strategy.
6.4 IMPLEHENTATION ASPECTS
The difficulty 1n Implementing the strategy depends on technical,
political, legal, and socloeconomic considerations associated with the various
control measures. The magnitude of these considerations depends on the
general Implementation approach of the strategy, that is, whether it is to
be enforced as a series of air pollution control regulations, or as in-line
actions to be taken by various agencies in the performance of related projects.
The direct regulatory approach 1s certainly required for several of the
source categories. This will be the only sure way to insure compliance for
a number of sources. However, in some cases the direct regulatory approach
may pose some difficulties and in fact may be less desirable than binding
agreements on the part of certain departments (i.e., public works, etc.) that
they will participate in and be responsible for the implementation of a cer-
tain portion of the strategy.
6-6
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This "so-called" alternative to the strict regulatory mechanism is an
app.-oach which provides for integration (where possible) of the control
measures into the on-line operations of various governmental agencies.
W This approach generates greater political and social acceptance in that
j these measures are viewed not only as air pollution controls, but as overall
planning and developmental improvements which will yield several tangible
I benefits in addition to air quality improvement. In view of the types of
major fugitive dust emission sources which are typically uncontrolled at
I present, the integral planning approach is particularly appropriate. Reason-
ably available controls for unpaved road dust and entrained street dust
emissions are entirely consistent with objectives of the local transportation
I and street maintenance departments and sbould be Incorporated into the overall
goals and objectives of these departments.
An example of this inter-governmental cooperation and implementation
is found in the current 208 Vffcter Planning process. At the present time,
| 208 Water Planning agencies are considering various techniques to minimize
_ water runnoff from "non-point sources" which are similar in many cases to
fugitive dust sources. Coordination of air management planners with water
planners may be mutually beneficial and is certainly encouraged, where
appropriate.
The major obstacle confronting implementation of a fugitive dust control
strategy, whether utilizing the integral planning approach or the direct
gj regulatory technique, concerns the sodฉeconomic acceptability of the proposed
_ actions. Appropriations for some major measures by the respective local agencies
require financial support of the citizenry, whether by taxes, bonds, or
assessment districts. While the funding needed to support implementation
of the strategy 1s generally relatively minimal, there is little chance that
I
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the additional expenditures associated with the strategy would be absorbed
in the annual budgets without clear justification. Such justification may
be facilitated by phasing in the controls with the implementation of a
demonstration project as the first phase to validate the benefits of the
proposed strategy.
Implementation difficulties anticipated for each of the control measures
comprising the strategy should be assessed and ranked to establish the
feasibility of successful execution of the proposed program. The assessment
should consider the approach in which various departments within the govern-
mental structure of the political jurisdiction are active participants in
carrying out the strategy. The assessment may be carried out with or without
the benefit of L demonstration project as the first phase of implementing
the areawlvia strategy. Such evaluations are necessarily somewhat speculative,
but should be consistent with the economic and technical characterization
of the strategy. Overall support for these measures should be generated by
providing the overall benefits and objectives of an integrated program to
control fugitive dust.
6.4.1 Demonstration Project
In some areas where control may meet with significant implementation
obstacles, demonstration projects may be planned as an integral part of
the control strategy to generate support and coordinate efforts within various
departments. Because the impact of fugitive dust sources istjjj^ically very
localized, a control demonstration project is particularly appropriate to
insure an achievable program in a timely manner. A demonstration strategy
is useful in a number of ways. First, the demonstration can be instrumental
in generating support for a more rapid implementation of the total strategy.
Second, the demonstration would enlist and promote coordination between
6-8
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I
I
agencies to achieve the overall objectives in a more complete and compre-
hensive way. Finally, the demonstration project might be essential as a
tool for further pollution control analysis as it will yield useful insights
for appropriate adjustments of the regionwide strategy over time. To attain
these objectives, the demonstration project should consist of the following
| elements:
ซ o Surveys to establish understanding of the overall goals of the
long-range plan for the area under consideration.
o A cooperative task force committee comprised of representatives from
the major affected departments. The committee would be responsible
for the planning of the strategy and carrying out phase one or the
_ demonstration phase.
o A field test to demonstrate the effect of the proposed control
measures in a limited area. This test would include institution of
all controls proposed for the)areawide strateay. A comprehensive
TSP field monitoring program would be implemented.
o An economic analysis to evaluate the cost benefits of the proposed
I control strategy.
o A public relations program to promote awareness of the benefits
of the proposed control plan and to generate support for further
I funding to implement the measures on a more accelerated scale.
The selection of the specific area for the demonstration would be depend-
| ent on several factors. First, receptibility of the various departments and
ฃ agencies to participate in the overall program should be assured. Second,
the area should be representative of major emission sources causlnguhigh
I levels of TSP throughout the problem area. Third, it would be preferable if
the selected area included a monitor of the existing air sampling network.
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6-9
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This would facilitate the comparison between before and after control and
would place the test program within the context of the data base used to
develop the strategy. Fourth, since a key to the utility of the project
is its effect on social acceptance, the area selection should reflect a
level of social acceptance typical of the characteristic of the entire
region which will eventually be affected by the plan. Another, but not neces-
sarily final, consideration in area selection is the planned development for
the area. Desirability for selection of the area is increased when scheduled
development is compatible with the specific controls comprising the demon-
stration project under consideration.
6/5 CONCLUSION
Statwj eปre encouraged to develep comprehensive reasonable control plans
to be implemented as expedHiously as practicable. In many areas, demonstra-
tion projects will not be necessary, and the program to control fugitive
dust can be carried out 1n a much quicker fashion. In other areas, control
efforts have already begun, and further complete enforcement of existing
regulations will go a long way in reducing TSP levels due to fugitive dust.
An adequate decumentation of the analysis of the strategy should be developed
to insure completeness. Once the strategy is finalized, enforceable regula-
tions and compliance test methods must be developed to implement the strategy.
The plan to control particulate matter should be a comprehensive one which
Integrates the control of fugitive dust, stack emissions, industrial process
fugitive particulate emissions and other area sources into a "well-oiled"
program to reduce ambient TSP concentrations as expeditiously as practicable
striving for overall acceptance, reasonableness and effectiveness.
6-10
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APPENDIX A
A-l
-------
Figure A-l. Soil rodibility ซK a tfunetioa of |ปareiciซ stsฎ
M - i '
A-2
-------
r
::J
! J _
."M
w.
*'ฃ
\rii
!(-i".i. .cni *k } :fT^^TTFl
-j-H-tJ;^:-f-|i|--i ซ'THr%- J V-4-
. ! 4iJW J84^'88Wll4j bWIUVS^iiK? &As ^St&SWd a
l:,Tfl tiar^-::n-! ;
a JH^4't8ski^l_bEjU^j|6Si_ &4^_: ,^iปjฃjgt} ItTg^M-lHJ'}:;-' iซ- -iilflL- k
I i", .| .J..1'JS" t 'Ws -1"'" i T i ii-^-r.SSJtaSrtT'Tvr,!, 'npi'." rr
! -I "H-'i-lJ. ! -4ป. j i f; I :-!}-. .p,.,_^.l.i .;4fi{-ซ.,.u v.<
tA
2riS---i:. > ! JU^
;ฃ;r.t:-re.,?ฃ::.ปซ ;[
i iVff> ' 4 {,<! j tf / $ * J ' -4
liAl. .>lH,n!-j i!' ;:jl-itl
CVJ
ซa;
( i! !
i-iJj -1.4 - L.JL: . .
A-3
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Table A-l. VALUES OF K. L AND V FOR OOMMOK FIELD CROPS
17
Crop
Alfalfa
Barley
Beans
Corn
Cotton
Grain Hays
Oats
Peanuts
Potatoes
Rice
Eye
Safflower
Sorghum
Soybeans
Sugar Beets
Vegetables
Wheat
K
1.0
0.6
0.5
0.6
0.5
0.8
0.8
0.6
0.8
0.8
0.6
1.0
0.5
0.6
0.6
0.6
0.6
L,ft.
1000
2000
1000
2000
2000
2000
2000
1000
1000
1000
2000
2000
2000
2000
1000
500
2000
V,lb/acre
3000
1100
250
500
250
1250
1250
250
400
1000
1250
1500
900
250
100
100
1350
A-4
-------
j-f-r-hfri
*ป4 - ,j^_ t-,'J^ Ii5iปrnnr-lป
rt f.r^tsT^
-rTnTK!rT^
^jHJEJ-JKJ^^^
-~ '""
A-5
-------
&
g
ซ
h
X 'boiovj esaNHonou
A-6
-------
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Appendix B: Detailed Description of the Hanna-Gifford Model
Analytically, this model may be formulated, for cases where emission
strength of the receptor grid is much less than that of the neighboring
grid squares, as follows:
x * (-)
* vir
1/2
1-b
u au-
N
Qo+ I
1=1
[(21+1 )]"b -(21-1
(B.I)
~ 1, 2, 3, ...,N
or for uniform emissions from all neighboring grid squares as
x = C (Q/u)
(B.2)
where
Q =
I
Qo = Source strength for the receptor grid (yg/m /s)
p
Q.J = Source strength for the ith grid square (yg/m /s),
u = Average wind speed (m/s) over the desired averaging time
(Greater than 20 minutes),
o
x = Average concentration for a suitably defined region (yg/m ),
AX = Grid width (m),
N = Number of grids in any one direction that analysis indicates
may have an impact on the receptor (usually limited to 4).
B-l
-------
The terms a,b are based on the assumption that the vertical dispersion
can be approximated by
= axb
3
where the "a" and "b" can be found in the COM User's Guide .
Physical removal mechanisms can be incorporated into the
model through the multiplicative factor
1/0 + C (vd/u))
where v . is the deposition velocity. As a first approximation to the
deposition velocity, the terminal velocity of the particles may be used,
40
The terminal velocity may be found in Meteorology and Atomic Energy >
if the particle diameter and density are known.
B-2
-------
Appendix C: Modified CDM/Rollback Model
The analytical formulation of the CDM/Rollback source-receptor
relationship is given by the relation
Xi = a^C. + a2.E. + B (C.I)
where
X. = Total suspended particulate concentraton, observed.
C. = COM calculated concentration of 0-10 and 11-20 ym particles.
E. = Emissions of particles >20 ym in the grid square of the
receptor.
B = Background TSP.
a-|. = Empirical coefficient to adjust COM air quality predictions.
a2. = Empirical coefficient relating emissions to air quality
for large particles.
i = Denotes the receptor under consideration.
With the magnitude of the assumed background and the particle
size distribution on the Hi-Vol filters known, it is a simple task to
determine o^ and c^ in the above equation. For example,
let F = Average fraction of particles greater than 20 ym on
Hi-Vol filter of monitor i (the larger F is, the greater
is the influence of fugitive sources on TSP.
and let FB = Average fraction of particles greater than 20 ym on
Hi-Vol filter of background stations.
Then it follows that
C-l
-------
i = a2. E. + FgB (C.2)
and (1-F) X. = a]1 C1 + (1-Fg)B (C.3)
Solving for the empirical coefficients,
(1-F) X. - (1-FB)B
-11
FX. - FRB
-1-. (C.5)
A sample calculation is presented in Appendix E.
C-2
-------
I
I
Appendix D: Information Required as Input to the CDM/Rollback Model
The specific format and description of the input procedures
relating to the source emissions data, meteorological data and receptor
locations are well-documented in the COM User's Guide and, hence, are
I not reproduced here. However, for continuity, a brief summary of the
required input to the model is given.
I Meteorology Data
M Meteorology data for the study area are obtained from the National
* Climatic Center (NCC) in Asheville, North Carolina. The NCC provides
I both the joint frequency function and mixing height data. The joint
frequency function is a combined frequency of occurrence for three
| meteorological parameters as defined by COM: six stability classes, six
m wind speed classes, and sixteen wind directions. The annual mixing
I 5'ฐ
" height and frequency functions should be obtained for the base year of
the study, and an additional distribution should be obtained for a more
extended period to reflect annual averages. The annual average will be
I used to forecast future air quality. Note that the COM requires a
m division of D stability into day-night frequencies and that E and F
stability frequencies are combined.
Determination of the Decay Constant
The pollutant half-life is required for the estimation of the decay
I term used in the COM diffusion model for the 10-20 ym range. Half-life
refers to the time elapsed before the ambient concentration of a given
I
-------
size particulate is reduced by one-half due to physical removal mecha-
nisms (e.g., dry deposition and gravitational settling). The following
39
derivation of half-life is based upon the Phoenix study ; however, the
procedure can be readily applied to other areas. The computational
technique is based on Van der Hoven's dry deposition formulation.
First, it is assumed that a 15 ym diameter particle is representative of
the 10-20 jam range. Then for an average wind speed of 2.41 m/s (mean
for Phoenix) and a terminal fall speed of 1.69 cm/s (corresponding to a
15 urn diameter particle), Van der Hoven's expression for reduction of
the source strength due to dry deposition may be used to determine the
distance at which the effective source strength has been reduced to half
its original value due to dry deposition. The time that it takes a
parcel of air, embedded in the mean flow, to travel that distance may
then be used as the half-life for particles in the 10-20 ym size range.
An appropriate half-life value may then be used in the exponential decay
term of COM.
The results of the calculations, using the technique outlined
above, are shown in Table D-l.
Because half-life (and the resulting decay term in COM) varies with
both stability and wind speed, the user must decide whether to use
separate values for the various wind speed/stability categories of
COM or to use a single composite value. For Phoenix, a single composite
value was used on the basis that this is only an approximation technique
and that a more complex analysis is not justifiable. The composite value
was derived from a weighted average of the half-life times given in
Table D-l.
D-2
-------
I
I
Table D-1. Half Life for Physical Removal
Mechanism in the COM for a 15ytn
Particle and a Mean Wind Speed of 2.4 m/s.
I
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*Not calculated, but can graphically be shown to be essentially infinite.
The weights used should be a function of two factors: (1) the
B percent frequency of each stability and (2) the relative contribution
to the predicted concentration given by the model for each stability clas:
The latter contribution to the weighting term can be approximated from
159
xu/Q curves (for example, those given by Turner ). Such an analysis
_ for Phoenix, shows that the weighted average only need be representative
" 39
of D, E and F stability. Sased on that calculation , the suggested
decay time is approximately 40 minutes.
Stability
A
B
C
D
E
F
Half Life (min.)
Q&
QQW
691.2
62.2
42.2
27.7
I
D-3
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Emissions Parameters
Emissions parameters required as inputs by the air quality model
include diurnal assignment of emissions, stack heights of sources, half-
life of pollutant and magnitude of emissions by particle size class and
grid sector.
The distribution of emissions between day and night is a required
input parameter to COM. To estimate this distribution, the emissions
patterns of the major sources should be evaluated.
Physical stack parameters required for model plume rise calculations
may be obtained from the National Emissions Data System. The source
emission heighc for the area sources must be assumed (10 m was used in
Phoenix).
Particle size distributions of the various emissions source cate-
gories should be used to express the gridded emission inventory (Section
3) in terms of the three particle size ranges (Section 4.2). Because of
the general lack of information available to characterize the particle
size of the various sources, substantial uncertainty is associated with
available distribution estimates. Figures D-l and D-2 summarize the
available data for particle size distributions of anthropogenic fugitive
dust sources and conventional sources. Distributions for fugitive
emissions caused by wind erosion approximate that of the parent soi-1
(Section 3.2.2), and must be determined from soils data for the specific
study area.
D-4
-------
CO
V
o
c
o
o-
o
(U
K-
O
C
o
(U
N
t
to
t-
-------
S-
4->
C C
o o
4J I/I
O C
3 0)
I- Q.
4J 10
to 3
C to
O Oป
O OC
O
4J
co
0)
$-
en
en
to
OJ
o
c
o
10
UJ
10
O
O)
o
a.
o
O
C
o
r
JQ
t-
$-
to
r
a
aป
N
r-
CO
at
o
CO
a.
CM
i
s_
0>
D-r
-------
I
I Appendix E: Sample Application of the CDM/Rollback Model
This appendix outlines the procedures which were used to adjust the
air quality model estimates and to generate baseline air quality pro-
jections for future years.
I
E.I Determination of Empirical Coefficients
Figure E-l is a schematic diagram portraying a single complete
run of the CDM/Rollback model. In the first step, the Emissions Simu-
lator Program produces a disaggregated gridded emission inventory. Next,
emissions from 0-10 and 11 -2oiiym ranges are combined with the meteorologi-
l
cal data and run through the C0M, The COM output and the emissions in
39
; the 21 -7Cin|fli range are input to a parameterization program." This program
I requires two additional inputs: (1) the average contribution of each of two
!
particle size ranges (0 to 20, and 20-70 pi) to TSP levels at a given recep-
tor, and (2) the background level of TSP in the study area. The source and
I procedure for tabulating these Inputs, plus the actual assignment of
empirical coefficients to the model, are discussed below.
I
Background Levels of TSP
A survey of monitoring sites located remotely from any urban area
of the study region should be undertaken to determine typical background
levels of TSP affecting the monitor measurements. The background level
I may be interpreted as an uncontrollable source comprised of particulate
I
I
E-l
I
-------
Raw Data
for Emission
Categories
Emissions Simulator
(Produce Emissions Grid)
Meteorology Data
Binary Output
of Emissions/grid
for 4 Particle Sizes
i
Emissions for
0-10 ami 11-20
micrometer
range
I
COM
(Calculate TSP for
0-10 and 11-20 micro-
meters).
Decay Constant
for 11-20
Micrometer
Range
Parametrlzatlon
(Assign Empirical
Coefficients and
Background)
A1r Quality
Estimates
Printed Output
of Emissions
1
Emissions for
21-70
micrometer
range
I
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Figure 1: Computer Modeling System
E-2
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I
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_ loading and originating from (1) natural sources in the area, and (2)
from suspended particulates transported from other areas. Background
O
Iparticulate levels typically vary from 20 to 40 yg/m throughout the
15, 60
United States
I Partlculate Size Distribution of Ambient TSP
Mechanical separators (e.g., cascade impactors) or microscopy
analyses of hi-vol filters serve as the basis for establishing the
average contribution of each particle size class to the TSP levels. In
areas with numerous fugitive dust sources, a substantial portion of the
I particulate mass found in hi-vol monitor filters is comprised of par-
ticles greater than 20 ym diameters. Particle size determinations
should be obtained for selected days of contrasting meteorology and TSP
levels at each of the various monitor sites. Distinguishable patterns
in the particle distributions at each of the monitors should be identi-
I fied, and an average distribution should be estimated over the range of
meteorology and TSP levels experienced in the baseyear. In the Phoenix
139
Fugitive Dust Study , the resulting particle distributions on the hi-
vol filters was relatively invariant for the particle classes considered
in the model parameterization. Although sampling was limited, the
I results showed about 70% of the particle mass to be comprised of
particles larger than 20 ym at all monitor sites examined, under both
| windy and calm conditions. In the Phoenix study, this finding simpli-
fied the assignment of empirical constants substantially.
E-3
-------
Assignment of Empirical Constants
Recall that the overall air quality model is expressed as:
Xi = ali Ci + a2i Ei + B (CJ)
The empirical coefficients are calculated after the COM has estimated
the ambient level of suspended particulates (C.) in the 0 to 20 pm
diameter size range using Equations (5) and (6). Table E-l illustrates
a systematic computation scheme for the empirical coefficients for
Phoenix where microscopic analysis gave an F value of 0.7. Column 1,
2, and 3 contain the COM predictions based on emissions from small
particles, column 4 the actual observed air quality, and column 5 the
emissions of particle 21-70 pm within the grid sque.re of each receptor.
Columns 7 and 9 are the contribution of TSP from particles 0-20 pm in
size and from particles 21-70 pm in size, respectively. The coeffi-
cients a-|.j and ซ2^ are shown in columns 6 and 8 and are computed from
the equations above. X. is found in column 11 and C- and E. are in
columns 3 and 5, respectively.
A brief statistical analysis of the observed and estimated concen-
trations in columns 3 and 4 can give some indication of the performance
of the COM. Figure E-2 shows the comparison between the COM model
results (for the 0-20 pm particles) and 30% (recall that the microscopic
analysis of the Hi-Vol filters indicated that 30% of the weight of the
particulates on the filter were 20 pm and smaller) of the observed
E-4
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concentration at each site. Also shown in Figure E-2 is the result of a
o
linear regression analysis of that data. The intercept (18.6 yg/m )
3
is very close to value assumed for background, 15.0 yg/m for the 0-20
ym range. The slope, 0.51, is a common result for Gaussian models. A
prior application of COM without modification for particle size (not
shown here), resulted in essentially no correlation between observed
and estimated concentrations. The regression analysis, therefore, gives
some indication that the modified COM substantially improves the treatment
of 0-20 ym particles. This is significant since nearly 70% of the emissions
are in this size range (for Phoenix).
An explanation that completely accounts for differences between the
COM resultfl estimates the observations is not possible, but the following
observations should be considered. First, there is probable bias of the
observed values from true representative concentrations due to variations
in monitor height, completeness of data, and representativeness of the
monitor site environment. Second, there is probable bias in the
emissions data base due to numerous uncertainties underlying the develop-
ment of the fugitive dust emissions inventory. Third, there is the
possibility of an inconsistent assumption regarding the particle size
distribution 1n the emissions data and the monitor data, Finally, there
are limitations associated with the assumptions of the model Itself.
While the Implications of any one particular limitation on the pre-
dictability achieved by the model may be assessed, the simultaneous
intervention of many influencing factors known to be affecting the model
results make any attempt to explain the variations very difficult. In
addition, the explanation is likely to be different for each of the
monitor sites.
E-7
-------
It must also be recognized that the relationship between local
emissions levels and TSP, as reflected in a2i, is distinctly unique for
each grid square because of the numerous variations of local source
distributions around the monitors. Accordingly, it was considered
appropriate to assign a separate empirical factor for application to
each of the monitor sites. This, of course, makes the interpretation
and application of this model highly site specific. It must be kept in
mind that the value of o^ will change according to future development
in the grid square and periodic revaluation is necessary.
E.2 A1r Quality Estimates
The base line emissons levels corresponding to the base year and
projected years are translated Into air quality descriptions using the
empirical source receptor relationship discussed previously. The model
is used to evaluate contributions of each of the source categories to
TSP levels, and the Impact of source changes on air quality.
Base Year Estimates
The empirical model should be employed to calculate suspended
particulate levels caused by each of the major emission sources sus-
pected to be affecting TSP levels significantly. For areas where TSP
levels are dominated by fugitive dust sources, it is likely that nearly
all the TSP level (excluding background) will be caused by emissions
from unpaved roads, entrained street dust, construction activities, or
wind erosion. Sites which are most dramatically affected by wind-
erosion emissions tend to be located in the rural areas presently under
E-8
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development. Other sites within cities may also be significantly
affected by wind-blown dust emissions. These sites are generally
surrounded by numerous vacant lots and/or dirt around residence yards.
Entrained street dust tends to impact air quality at sites located in
the city areas. Emissions from unpaved roads may contribute signifi-
cantly to TSP at each of the sites, but are generally particularly
dominant 1n the suburbs areas. Table E-2 illustrates the effect of
these major fugitive dust sources in the Phoenix area, as estimated by
the source-receptor model.
Projected Base Line TSP Levels
The projected emission levels for future years should be translated
into air quality estimates using the source-receptor model developed
earlier. These estimates are compared to base year levels for each of
the monitoring locations In the study area. Significant changes in air
quality are calculated and analysed. In many cases, air quality in
areas presently experiencing fugitive dust problems will improve sig-
nificantly in future years due to base line development planned for the
area. This development will change the distribution of emission sources,
eliminate local sources near the monitors, and diminish the magnitude of
many sources. While total dust emissions from unpaved roads may not
decrease, the distribution of these emissions may change substantially
owing to city roadway improvement programs. Wind erosion emissions may
decrease in future years due to reduction in wind erosion sources (i.e.,
vacant property), and may increase or decrease based on expectation of
E-10
-------
typical meteorology in future years. Contributions to TSP from entrain-
ment of street dust are expected to Increase with increasing vehicle
registration, especially at monitors located within the city areas.
Table E-3 is an example format useful for comparison of the base year and
\
projected base line source contributions to air quality.
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References
1. U.S. Environmental Protection Agency, "An Implementation Plan for Suspended
Participate Matter in the Phoenix Area" - Volume I, Air Quality Analysis,
EPA-450/3-77-02U, 1977.
2. TRW Systems Group, 1970. "Air Quality Display Model". Prepared for
National Air Pollution Control Administration under Contract No. PH 22-68-60
(NTIS PB 189194), DHEW, U.S. Public Health Service, Washington, D.C..
3. Busse, A. D. and J. R. Zimmerman. "User's Guide for the Climatological
Dispersion Model", Publication No. EPA-RA-73-024 (NTIS PB 227346/AS),
U.S. Environmental Protection Agency, Research Triangle Park, N.C. 27711,
December 1973.
4. Empirical Analysis Toward Total Suspended Particulate Source Classification
in Texas. University of Texas at Austin, Applied Research Lab.
ARL-TR-76-48. Page 12, October 1976.
5. National Assessment of the Particulate Problem. Volume V - Baltimore.
EPA-450/3-76-026c. Pages 21-29, June 1976.
6. National Assessment of the Particulate Problem. Volume XVI - Providence.
EPA-450/3-76-026n. Pages 15-17, June 1976.
7. National Assessment of the Particulate Problem. Volume I - National
Assessment. EPA-450/3-76-024. Pages 265-323, July 1976.
8. National Assessment of the Particulate Problem. Volume II - Particle
Characterization. EPA-450/3-76-024. Pages 1-25, July 1976.
9. U.S. Environmental Protection Agency, "An Implementation Plan for Suspended
Particulate Matter in the Phoenix Area" - Volume II, Emission Inventory,
EPA-450/3-77-021b* 1977.
10. U.S. Environmental Protection Agency, "Guidelines for Air Quality Maintenance
Planning and Analysis", September 1974.
11. U.S. Environmental Protection Agency, "Guide for Compiling a Comprehensive
Emission Inventory", March 1973.
12. Communication with Maricopa County (Arizona) Highway Department, March 1976.
13. Midwest Research Institute, "Quantification of Dust Entrainment from Paved
Roadways". Prepared for Environmental Protection Agency, March 1976.
14. PEDCo Environmental, "Control of Re-entrained Material from Paved Streets".
Prepared for U.S. Environmental Protection Agencyป 1977.
15. Jutze, George and Axetell, Kenneth - PEDCo Environmental Specialists, Inc.,
Investigation of Fugitive Dust". Volume I - Sources, Emissions and Control.
Prepared for U.S. Environmental Protection Agency, June 1974.
F-l
-------
16. Phoenix Newspapers, Inc., "Inside Phoenix 1976".
17. Cowherd, Chatten and Axetell , Kenneth Midwest Research Institute,
Development of Emission Factors for Fi"">itive Dust Sources", 1976.
18. Arizona Crop and Livestock Reporting Service, "1974 Arizona Agricultural
Statistics", Bulletin 5-10, Phoenix, Arizona, March 1975.
19. Maricopa County Planning Department, "A Report Upon Future General Land
Use For Maricopa County, Arizona", February 1975.
20. Tonto National Forest Service, Phoenix, Arizona, personal communication,
May 1976.
21. U.S. Forest Service, Phoenix, Arizona, personal communication, May 1976.
22. Bureau of Land Management, U.S. Department of Interior, personal communi-
cation, ?tey 1976.
23. Phoenix ("ity Parks and Recreation Department, personal communication,
May li/6.
24. Glendale City Parks and Recreation Department, personal communication,
May 1976.
25. PEDCo Environmental, "Nevada Particulate Control Study for Air Quality
Maintenance Areas, Factors Influencing Emissions from Fugitive Sources".
Prepared for U.S. Environmental Protection Agency, January 1976.
26. Roberts, J. W.; Matters, H. A.; Marigold, C. A.; and Rossano, A.T. -
"Cost and Benefits of Road Dust Control in Seattle's Industrial Valley",
Journal of the Air Pollution Control Association, September 1975.
27. Communication with Maricopa County Transportation Department, June 1976.
28. Hagen, L. J. and N. P. Woodruff, "Particulate Loads Cuased by Wind Erosion
in the Great Plains". Presentation at the 66th Annual Meeting of Air
Pollution Control Association, June 1973.
29. Culkowski, W. M. and M. R. Patterson, 1976: A Comprehensive Atmospheric
Transport and Diffusion Model. ORNL/NSF/EATC-17.
30. W. F. Hilsmeier and F. A. Gifford, Jr. - Graphs for Estimating Atmospheric
Dispersion, 'JSAEC Report ORO-545, Weather Bureau, Oak Ridge, Tennessee, 1962.
31. Hosker (Jr.), R. P., Estimates of Dry Deposition and Plume Depletion Over
Forests and Grassland, IAEA-SM-181/19, Air Resources Atmospheric Turbulence
and Diffusion Laboratory, November 1973.
32. G. A. Briggs, Diffusion Estimation for Small Emissions, U.S. Department of
Commerce, NOAA=ERL-ARATDL contribution no. 79 (Draft), Oak Ridge, Tennessee,
May 1973.
F-2
-------
33, F. B. Smith, "A Scheme for Estimating the Vertical Dispersion of a Plume
from a Source Near Gound Level", Chapter XVII, Proceedings of the Third
Meeting of the Panel on Air Pollution Modeling, N.A.T.O. Committee on the
Challenges of Modern Society, Paris, France, October 2-3, 1972, Proceedings
No. 14, Air Pollution Tech. Information Center, U.S. Environmental
Protection Agency, Research Triangle Park, North Carolina, 1973.
34. Briggs, Gary A. Plume Rise. USAEC Critical Review Series TID-25075,
National Technical Information Service, Springfield, Virginia. 1969.
35. Hanna, S. R. - A Simple Method of Calculating Dispersion from Urban Area
Sources. J. Air Poll. Cont. Assoc., Ij2, 774-777 (December 1971).
36. Gifford, F. A. and S. R. Hanna. Modeling Urban Air Pollution. Atmos.
Environ.. 7., 131-136 (1973).
37. Hanna, S. R. A Simple Dispersion Model for the Analysis of Chemically
Reactive Pollutants. Atmos. Environ., 7_, 803-817 (1973).
38. Nevada Particulate Control Study for Air Quality Maintenance Areas: Task D/E
Report, Emission Modeling and Control Strategy Development. PEDCo Environ-
mental Specialists, Inc., Cincinnati, Ohio. Prepared for the U.S. Environ-
mental Protection Agency, Region IX, under Contract No. 68-02-1375, Task
Order No. 29. December 1976.
39. U.S. Environmental Protection Agency, "An Implementation Plan for Suspended
Particulate Matter in the Phoenix Area - Volume III, Model Simulation of Total
Suspended Parti cul ate Matter Levels - EPA-450/3-77-02U, 1977.
40. Slade, D. H. (ed.), Meteorology and Atomic Energy 1968, U.S. Energy Research
and Development Administration, TID-24190, July 1968.
41. Dumbauld, R. K.; J. E. Rafferty; and H. E. Cramer. Dispersion-Deposition
from Aerial Spray Releases. Third Symposium on Atmospheric Turbulence
Diffusion and A1r Quality, Raleigh, N.C., October 1976.
42. Sultan, Hassen A. (Dr.) Arizona Transportation and Traffic Institute,
"Soil Erosion and Dust Control of Arizona Highways, Part IV, Final Report
Field Testing Program". Prepared for Arizona Department of Transportation,
November 1976.
43. Communication with Hawkins Company, Phoenix, Arizona, July 1976.
44. U.S. Environmental Protection Agency, "Compilation of Air Pollutant Emission
Factors", Supplement No. 5. December 1975.
45. U.S. Environmental Protection Agency, "An Implementation Plan for Suspended
Particulate Matter in the Phoenix Area" - Volume IV, Control Strategy
Formulation, EPA-450/3-77-021d, 1977.
46. Dunbar, D. R., "Resuspension of Particulate Matter", Standards Implementa-
tion Branch, Control Programs Development Division, U.S. Environemental
Protection Agency, Research Triangle Park, North Carolina, March 1976.
F-3
-------
47. American Public Works Association, "Water Pollution Aspects of Urban Runoff",
APWA, Chicago, 1969.
48. Communication with City Department of Transportation, Phoenix, June 1976.
49. U.S. Environmental Protection Agency, "Background Information on National
Emission Standards for Hazardous Air Pollutants", October 1974.
50. NATO Committee on the Challenges of Modern Society, "Air Pollution: Control
Techniques for Particulate Air Pollutants". Prepared for Environmental
Protection Agency, October 1973.
51. Communication with Phoenix Department of Transportation and Road
Maintenance, June 1976.
52. U.S. Department of Agriculture, "How to Control Soil Blowing", Farmer's
Bulletin No. 2169, July 1961.
53. "Farming Without the Plow", The Washington Post, Sunday, January 18, 1976.
54. Donovan, R. P.; Felder, R. M.; and H. H. Rogers, U.S. Environmental
Protection Agency, "Vegetative Stabilization of Mineral Waste Heaps",
April lb/6.
55. Dean, K. C. and R. Havens, "Stabilizing Mineral Wastes", Engineering Mining
Journal. April 1971.
56. "Chemical Treatment of Waste Tailings Puts an End to Dust Storms", Engineer-
ing Mining Journal, April 1971.
57. Dean, K. C. and R. Havens, "Reclamation of Mineral Milling Waste". Presented
at Annual AIME Meeting, San Francisco, California, February 1972.
58. National Oceanic and Atmospheric Administration, 1976. A Climatological
Analysis of Pasquill Stability Categories, National Climatic center, Federal
Building, Asheville, North Carolina 28801.
59. Turner, D. B., 1970. Workbook of Atmospheric Dispersion Estimates, PHS
Publication No. 999-AP-26 (NTIS PB 191482), Office of Technical Information
and Publications, U.S. Environmental Protection Agency, Research Triangle
Park, N.C. 27711.
60. U.S. Environmental Protection Agency, "Guidelines for Air Quality
Maintenance Planning and Analysis", September 1974.
61. U.S. Environmental Protection Agency, "Aerosol Sampling and Analysis,
Phoenix, Arizona", EPA-600/3-77-015, February 1977.
F-4
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
^ NO.
EPA-450/2-77-029
2.
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
Guideline for Development of Control Strategies in
Areas in with Fugitive Dust Problems -
IB. REPORT DATE _
1 October, i977
6. PERFORMING ORGANIZATION COOE
7. AUTHOR(S)
George Richard, TRW
Dallas Safriet, EPA
N~0
9. PERFORMING ORGANIZATION NAME AND ADDRESS
TRW
Environment Engineering Division
One Space Park
Redondo Beach, California
MO. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
! 68-01-3152
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Monitoring and Data Analysis Division
Research Triangle Park, North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
200/04
15. SUPPLEMENTARY NOTES
16. ABSTRACT
The document outlines a methodology for development of control strategies for areas
experiencing non-attainment problems due to fugitive dust emissions.
KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS jb. IDENTIFIERS/OPEN ENDED TERMS
Participate Matter
Total Suspended Parti cul ate
Emission Sources
Control Methods
Fugitive Dust
Air Quality Measurement
Air Quality Modeling
18. DISTRIBUTION STATEMENT
Release Unlimited
18. SECURITY CLASS (This Report)
Unclassified
20. SECURITY CLASS (This page)
Unclassified
u. COSATI Fiela/Group ]
21. NO. OF PAGES (
158 I
22. PRICE j
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
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