PB8 4-17 08 02
Improved Emission Factors Cor Fugitive
Dust from Western Surface Coal Mining Sources
TEDCo-Environmental, Inc., Kansas City, MO
Prepared for
Inducfcri^l Environmental Research Lad.
Cincinnati, OH
Mar 64
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PB84-17080 2
EPA-600/7-84-048
March 1984
IMPROVED EMISSION FACTORS FOR FUGITIVE OUST
FROM WESTERN SURFACE COAL MINING SOURCES
by
Kenneth Axetel1, Jr.
PEDCo Environmental, Inc.
2420 Pershing Road
Kansas City, MO 54108
and
Chatten Cowherd, Jr.
Midwest Research Institute
425 Volker Boulevard
Kansas City, MO 64110
Contract No. 68-03-2924
Work Directive flo. 1
Project Officers
Jonathan G. Herrmann
Energy Pollution Control Division
Industrial Environmental Research Laboratory
Cincinnati, OH 45268
and
Thompson G. Pace, P.E.
Monitoring and Data Analysis Divioion
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
TMs study was conducted in cooperation with
the U.S. Environmental Protection Agency
Region VIII Office in Denver, CO, and the
Office of Surface Mining in Washington, DC,
and Denver, CO.
INDUSTRIAL ENVIRONMENTAL RESEARCH LA30RAT0SV
OFFICE OF RESEARCH ANO DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OH 45268
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TECHNICAL REPORT DATA
(Pfectt mi l*un*cttuAi on tne m tru bffore
» *t*0*T NO J
EPA-600/7-84-048
J «ECI*HNTt ACCEMiO<»NO
PB8^-170802
J TITkt AND SutTITkC
Improved Emission Factors for Fugitive Dust from
Western Surface Coal Mining Sources —
Saspling Methodology & Test Results
& Bt'OH' DATE
March 1984
% fl RtOAMlNG ORGANIZATION CODE
J AUTHOnill
Kenneth Axetell, Jr. and Chstten Cowherd, Jr.
ft PLftFOAMiNG O*G*Ni2ATi0N SO
e pinroDU'NS organization name and address
PEDCc Environoental, Inc. Midwest Research Institute
2420 Perching Rd. 425 Volker Boulevard
Kansas City, MO 64106 Kansas City, MO 64110
10 PKOCAam itCMlNT NO
CBBS'IC
M CONTAAC/CAANI no
68-03-2924 (WD No. 1)
»1 t'ONJDOiNG AGENC» name ANDADDREU
Industrial Environmental Research Laboratory
Office of Research and Development
US Environmental Protection Agency
Cincinnati, OH 45268
i'j TYPE O' DEPORT AND KKiOD C3vCD[C
Final Report 3/79 - 3/81
14 SPONSORING AOENCT COOE
EPA/600/12
IS SUF'LlWtNTARV NOTES
* ^he primary purpose of this study was to develop emssion factors for significant
surface coat mining operations that are applicable at Western surface coal nines and are
based on state-of-the-art sampling and data Analysis procedures. Primary objectives
were 1) to develop emission factors for individual oining operations, in the form of
equations with several correction factors to account for eite-specific conditions, and
2) to develop these factors for particles less that 2.5yo (fine particulates), particles
leas than 15 ncn (inholable particulates), and total suspended particulates Secondary
objectives were I) to determine deposition rates over the 50- :o 100-ib distance downwind
froo the sources, and 2) Co estimate control efficiencies for certain source categories.
Emissions resulting from the following were ecopied at three nines during 1979 and 1980:
I drilling, blasting, coal loading, bulldozing, dragline operations, haul trucks, light-
and radium-duty trucks, scrapers, graders, and wind erosion of exposed areas. The
primary sampling methods w«s exposure profiling, supplemented by upwind/downwind,
ballon, wind tunnel, find quasi-otack saspling. The nusber of tests run totaled 265.
The report concludes with a eoeparison of the generated emission factors with previous
ones, a otateocnt regarding their applicability to mining operations with specific
caveats and collateral information which oust be considered in their use and reconi-
mendationo for Additional research in Western and other sines.
Hr ai* ros«os a a a oocuuiwr analysis
• * ot&caiPToeu
b ICSNTI>lt-P6'OPtN 3NOS0 TERMS
C COtATi 'Croup
1
1
B'O C.i1T4i5mTiON STaTiuawT
5 WUAJit TO PUBLIC
»0. 6»Cli»iT* CLASS
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NOTICE
This document has been reviewed in accordance with U.S. Environmental
Protection Agency policy and approved for publication. Mention oT trade
names or commercial products does not constitute endorsement or reconmen-
dation for use.
ii
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FOREWORD
When energy and material resources are extracted, processed, con-
verted, and used, the related pollutional impacts on our environment and
even on our health often require that new and increasingly more efficient
pollution control methods be used. The Industrial Envi rorrnental Research
Laboratory - Cincinnati, (IERL-Ci) ascists in developing and demonstrating
new and improved methodologies that will nwet these needs both efficiently
and economically.
This project involved the development of emission factors for oper-
ations at surface coal mines located in the western United States.
Operations sampled included, but were not limited to, haul road traffic,
scrapers, draglines, and blasts. Sampling techniques used included
exposure profiling, upwind-downwind and wind tunnel testing. Fron this
information, emission factors were developed which ta*.e into account such
characteristics as soil moisture and silt content. The data presented
in this study should aid both private industry and government agencies
in evaluating emissions from coal mining operations. If additional
information is needed, contact the Oil Shale and Energy Mining Branch
of the Energy Pollution Control Division.
Uavld G. Stephan
Di rector
Industrial Environmental Research Laboratory
Cincinnati
111
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ABSTRACT
Since 1975 several sets of emission factors have evolved for esti-
mating fugitive dust emission from surface cojI mines. The diverse values
of available enission factors, obvious sampling problems, and questions of
applicability over a range of mimng/meteorological conditions have under-
mined confidence in air quality analyses performed to date. Ry early 1979,
these problems led to a ground swell of support, from both regulatory and
mining industry personnel, for the development of new emission factors.
This study began in mid-March of 1979. The primary purpose of this
study was to develop emission factors for significant si/rface coal mining
operations that are applicable at Western surface coal mines and are
based on state-of-the-art sampling and data analysis procedures. Tne
primary objectives have been 1) to develop enission factors for individual
mining operations, fn the form of equations v.ith several correction factors
to account for site-specific conditions; and 2) to develop these factors
in three particle size ranges—less than 2.5 am (f>ne particulates), less
tnan 15 um (inhalable particulates), and total suspended particulates.
Secondary objectives were 1) to determine deposition rates over the 50-
to 100-m distance downwind from the source, and 2) to estimate control
efficiencies for certain source categories.
Sampling was performed at three mines during 1979 and 1980. Emissions
resulting from the following were sampled: drilling (overburden), blasting
(cocl and overburden), co»l loading, bulldozing (coal and overburden),
dragline operations, haul trucks, light- and med'.um-duty trucks, scrapers,
graders, and wind erosion of exposed areas (overburden 2nd coal). The
primary sampling method was exposure profiling. When source configuration
made it necessary, chls method was supplemented by upwind/Hownwind, balloon,
wind tunnel, and quasi-stack sampling. A total of 265 tests were rur,.
ExtensWe quality assurance procedures were implemented internally for this
project and were verified by audit.
S1ze-spec1f1c emission factors and correction parameters were developed
for all sources tested. Confidence Intervals and probability limits were
also calculated. Additional data for determination of deposition rates
were gathered, but no algorithms could be developed. Two control measures
for unpaved roads were tested.
iv
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The report concludes with a comparison of the generated emission
factors with previous ones, a statement regarding their applicability
to mining operations with specific caveats and collateral information
which must be considered in their use, and recommendations for addi-
tional research in Western and other mines.
v
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CONTENTS
Pa£e
Foreword iii
Abstract iv
Figures ix
Tables xi
Abbreviations of Units xvi
Acknowledgement xvi 1
1. Introduction 1
Pre-contract status of mining emission factors 1
Purpose of study 2
Technical review group for the study 3
Contents and organization of this report 6
2. Selection of Mines and Operations to be Sampled 7
Geograohical areas of most concern 7
Significant dust-producing operations 9
Potential mines for sampling 13
Schedule 15
3. Sampling Methodology 17
Techniques available to sanple fugitive dust
emissions 17
Selection of sampling methods 18
Sampling configurations 19
Source characterization procedures 42
Adjustments made during sampling 42
Error ar.^lyses for SAnpling ri.ethod<; 46
S.jmmary of t«sts performed 46
4. Sample Handing and Analysis 50
Sample handling SO
Analyses performed 52
Laboratory analysis procedures 52
Quality assurance procedures ond results 55
Audits 56
5. Calculation and Data Analysis Methodology 62
Number of tests per source 62
Calculation procedures 65
Particle size corrections 88
Combining results of Individual samples
and tests 91
Procedure for development of correction factors 93
vl
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Page
94
94
96
116
126
126
131
144
150
150
152
170
172
172
174
174
178
178
181
193
194
194
196
196
199
199
200
204
211
214
214
222
222
232
CONTENTS (continued)
Results of Simultaneous Exposure Profiling and
Upwind-Downwind Sampling
Description of comparaoility study
Results of comparabi1 *ty study
Deposition rates by alternative measurement
methods
Results for Sources Tested by Exposure Profiling
Summary of tests perforated
Results
Problems encountered
Results for Sources Tested by Upwind-Downwind Sampling
Summary of tests performed
Results
Problems encountered
Results for Source Tested by Balloon Sampling
Summary of tests performed
Results
Problems encountered
Results for Sources Tested by Wind Tunnel Method
Summary of tests performed
Resul ts
Problems encountered
Results of Source Tested by Quasi-Stack Sampling
Summary of tests performed
Results
Problems encountered
Evaluation of Results
Emission rates
Particle size distributions
Deposition
Estimated effectiveness of control measures
Development of Correction Factors and Emission
Factor Equations
Multiple linear regression analysis
Emission factor prediction equations
Confidence and prediction Intervals
Emission factors for wind erosion sources
vl 1
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CONTENTS (continued)
Page
14. Evaluation of Emission Factors 242
Comparison with previously available
emission factors 232
Statistical confidence in emission factors 244
Particle size relationships 247
Handling cf deposition 248
15. Conclusions and Recommendations 250
Summary of emission factors 250
Limitations to application of emission factors 253
Remaining research 255
16. References 257
Appendix A Stepwise Multiple Linear Regression A-l
Appendix B Calculations for Confidence and Prediction
Intervals B-l
vl 11
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FIGURES
Number Pagp
2-1 Coal Fields of the Western U.S. 8
2-2 Operations at Typical Western Surface Coal Mines 10
2-3 Schedule for Coal Mining Emission Factor
Development Study 16
3-1 Exposure Profiler 21
3-2 Upwind-Dowr.-..;nd Sampling Array 26
3-3 Wind Tunnel 29
3-4 Quasi-Stack Sarnpling--Temporary Enclosure for
Drill Sampling 30
3-5 Blast Sampling with Modified Exposure Profiling
Configuration 33
3-6 Coal Loading with Upwind-Downwind Configuration 34
3-7 Dragline Sampling with Upwind-Downwind
Configuration 36
3-8 Haul Road Sampling with Exposure Profiling
Configuration 38
3-9 Scraper Sampling with Exposure Profiling
Configuration 39
3-10 Wind Erosion Sampling with Wind Tunnel 41
5-1 Illustration of Exposure Profile Extrapolation 74
5-2 Example Ground-Level Concentration Profile 81
5-3 Example Vertical Concentration Profile 81
5-4 Plot of the 50 Percent Cut Point of the Inlet
Versus Wind Speed 89
1 x
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FIGURES (continued)
Number Page
6-1 Sampling Configuration for Comparability Studies 97
6-2 Particle Size Distribution from Comparability
Tests on Scrapers 100
6-3 Particle Size Distributions from Comparability
Tests on Haul Road 101
6-4 Deposition Rates as a Function of Time 117
6-5 Average Measured Depletion Rates 119
6-G Depletion Rates by Vieorstical Deposition
Functions 122
6-7 Average Measured Depletion Rates Compared to
Predicted Tilted Plume Depletion 124
13-1 Confidence and Prediction Intervals for Emission
Factors for Coal Loading 229
x
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TABLES
Number Page
1-1 Technical Review Group for Mining Study 5
2-1 Determination of Significant Dust-Producing
Operations 12
2-2 Characteristics of Mines that were Sampled 14
3-1 Sampling Devices for Atmospheric Particulate
Matter—Exposure Profiling 22
3-2 Basic Equipment Deployment for Exposure Profiling 23
3-3 Special Equipment Deployment for Exposure
Proflling--Comparabi1ity Tests 24
3-4 Sampling Configurations for Significant Sources 31
3-5 Source Characterization Parameters Monitored
During Testing 43
3-6 Summary of Potential Errors in the Exposure
Profiling Method 47
3-7 Summary of Potential Errors in the Upwind-
Downwind Sampling Method 48
3-8 Summary of Tests Performed 49
4-1 Laboratory Analyses Performed 53
4-2 Quality Assurance Procedures for Mining Emission
Factor Study 57
4-3 Quality Assurance Results 59
4-4 Audits Conducted and Results fin
5-1 Evaluation of Correction Factors with Partial
Data Set 66
x1
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TABLES (continued)
Number Page
5-2 Calculated Sample Sizes using Tv,o-St*.)e Method 67
5-3 Sample bizes Proposed and Obtained
5-4 oq Method of Determining Atmospheric Stability
Class 76
6-1 Con^arison of Particle Size Data Obtained by
Different Techniques 98
6-2 Ratios of Net Fine and Inhalable Particulate
Concentrations to Net TSP Concentrations 104
6-3 Concentrations Measured at Collocated Samplers 107
6-4 Test Conditions for Comparability Studies 109
6-5 Calculated Suspended Particulate (TSP) Emission
Rates for Comparabl11ty Tests 110
6-6 Calculated Inhalable Particulate (<15 urn) Emission
Rates for Comparability Tests 112
6-7 Analysis of Variance Results 113
6-8 Multiple Classification Analysis (ANOVA) 114
6-9 Depletion Factors for Comparability Tests 121
7-1 Exposure Profiling Site Conditions - Haul Trucks 127
7-2 Road and Traffic Characteristics,- Haul Trucks 129
7-3 Exposure Profiling Site Conditions - Light and
Medium Duty Vehicles 132
7-4 Road and Traffic Characteristics - Light and
Medium Duty Vehicles 133
7-5 Exposure Profiling Site Conditions - Scrapers 134
7-6 Road and Traffic Characteristics - Scrapers 135
7-7 Exposure Profiling Site Conditions - Graders 136
xl 1
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TABLES (continued)
Number Page
7-8 Road and Traffic Characteristics - Graders !37
7-9 Test Results for Haul Trucks 133
7-10 Test Results for Light- and Medium-Duty Vehicles 140
7-11 Test Results for Scrapers 141
7-12 Test Results for Graders 142
7-13 Dustfall Rates for Tests of Haul Trucks 145
7-14 Dustfall Rates for Tests of Light and Median
Duty Vehicles 147
7-15 Dustfall Rates far Tests of Scrapers 148
7-16 Dustfall Rates for Tests of Graders 149
8-1 Test Conditions for Coal Loading 151
¦J-2 Test Conditions for Dozer (Overburden) 153
8-1 Test Conditions for Dozer (Coal) 154
8-4 Test Conditions for Draglines J5S
8-5 Test Conditions for Haul Roads 156
8-6 Apparent Emission Rates for Coal Loading Htgh-
Volume (30 ion) 157
8-7 Apparent Emission Rates for Dozer (Overburden)
Hig>i-Volume (30 um) 15*>
8-8 Apparent Emission Rates for Oozer (Coal) High-
Volume (30 um) 159
8-9 Apparent Emission Rates for Dragline High-Voluny*
(30 um) 160
8-10 Apparent Emission Rates for Haul Road High-
Volume (30 un) 161
8-11 Emission Rates for Upwind-Downwind Test: 163
xllt
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TABLES (continued)
Number Pane
8-12 Emission Rates for Coal Loading, Hichotofrous
(15 urn and 2.5 um) 165
8-13 Emtssion Rates for Dozer (Overburden), Dichotomous
(15 um and 2.5 um) lf>6
8-14 Emission Rates for Dozer (Coal), Dichotoreous (15 um
and 2.5 um) 167
8-15 Emission Rates for Dragline, Dicnotomou'* (15 um and
2.5 um) lfiB
8-16 Emission Rates for Haul Roads, Dichotor.ajus (15 um and
2.5 um) 169
9-1 Test Conditions for Blasting 173
9-2 Apparent Emission Rates for Blasting, High Volume
(30 um) 175
9-3 Apparent Emission Rates for Blasting, 0ichoto">ous
(15 um and 2.5 um) 176
10-1 Wind Erosion Te»t Site Parar;«tcr» - Coal
Storage P1les 179
10-2 Wind Tunnel Test Conditions - Coal Storage Piles 182
10-3 Wind Erosion Surface Conditions - Coal
Storage Piles 184
10-4 Wind Erosion Test Site Parameters - Exposed
Ground Areas 186
10-5 Hind Tunnel Test Conditions - Exposed Ground
Areas 18H
10-6 Wind Erosion Surface Conditions - Exposed
Ground Areas 189
10-7 Hind Erosion Test Results - Coal Storage Piles 190
10-8 Wind Erosion Test Results • Exposed Ground
Areas 192
1.1-1 Test Conditions for Drills 195
*1 v
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TABLES (continuPd)
Number Page
11-2 Apparent Emission Rates for Drilling 197
12-1 Comparison of Sample Catches on Greased and
Ungreased Impactor Substrated 201
12-2 Particle Size Distributions Based on Net
Concentrations 205
12-3 Depletions Factors Calculated from Dustfall
Measurements 207
12-4 Depletion Factors for Upwind-Downwind Tests 209
12-5 Calculated Efficiencies of Control Measures 212
13-1 Variables Evaluated as Correction Factors 216
13-2 Results of First Multiple Linear Regression
Runs (TSP) 217
13-3 Changes made in Multiple Linear Regression
Runs (TSP) 219
13-4 Results or" Final Multip^ Linear Regression
Runs (TSP) 220
13-5 Results of F1r-t Multiple Linear Regression
Runs (IP) 223
13-6 Changes made in Multiple Linear Regression
Runs (IP) 225
13-7 Results of Final Multiple Linear Regression
Runs (IP) 226
13-8 Prediction Equations for Median Emisison Rates 227
13-9 Typical Values for Correction Factors 228
13-10 Emission Factors, Confidence'and Prediction
Intervals 231
13-11 Calculated Erosion Potential Versus Wind Speed 233
13-12 Surface and Emission Characteristics 238
xv
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TABLES (continued)
Number Page
13-13 Hypothetical Monthly Wind Data Presented in
LCj Format 239
14-1 TSP Emission Factor Comparison 243
14-2 Half-Width of Confidence Intervals Compared to
Median TSP Ennsison Factor 245
14-3 Evaluetion of Widely-Used ParticulateEmission
Factors from AP-42 246
15-1 Summary of Western Surface Coal Mining Emission
Factors 251
xv1
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ABBREVIATIONS OF UNITS
ABBREVIATIONS
ug/nP micrograms per standard cubic meter
pig milligrams
SCFM standard cubic feet per minute
mi n minutes
°C degrees celslus
in. Inches
ACFM actual cubic feet per minute
ft feet
fpm feet '^er minute
sfpm standard feet per minute
cm centimeters
m meters
lb pounds
VMT vehicle miles traveled
s seconds
degrees Jcelvln
3 grams
yd-* cubic yards
BTu British Thermal Units
gal gallons
ml miles
CFH cubic feet per minute
stph miles per hour
xvil
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ACKNOWLEDGEMENT
This report was prepared for the Industrial Enviromnenta1 Research
Laboratory of tne U.S. Environmental Protection Agency (EPA). Mr.
Jonathan Herrnunn served as Project Officer and Mr. Thompson Pace and
Mr. Edward LiHis from the Air Management Technology 3ranch of FPA
provided him »ith technical and policy assistance. Also assisting Mr.
Herrmann wer
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SECTION 1
INTRODUCTION
PRE-CONTRACT STATUS OF MINING EMISSION FACTORS
Over the past 4 or 5 years, several sets of emission tactors for
estimating fugitive dust emissions from surface coal mining have evolved.
The first of these were primarily adaptations of published emission fac-
tors from related industries, such as construction, aggregate handlinq,
taconite mining, and travel on unpaved roads (Monsanto Research Corporation
1975; Environmental Research and Tc^nnology 1975; PEDCo Environmental 1975;
Chalekode 1975; PEDCo Environmental 1976; Wyoming Department of Environmental
Quality 1976, Appendix B; U.S. Environmental Protection Agency 1977a;
Colorado Department of Health 1978; Midwest Research Institute 1978).
The concept of developing emission factors by operation rather than
for the entire mine has been widely accepted from the beginning. This
approach recognizes the large variation in operations from mine to mine.
As demand for emission factors specifically for surface coal mining
Increased, some sampling studies at mines were undertaken. The first of
these, sponsored by EPA Region VIII in the summer of 1977, sampled 12
operations'at 5 mines in a total of 213 sampling periods (U.S. Environ-
mental Protection Agecny 1978a). Emission factors were reported by
operation and mine, but no attempt was made to derive a general or
"universal" emission factor equation for each operation that could be
applied outside the five geographic areas where the samplng took place.
Also, several problems with the upwind-downwind sampling method as
employed in the study were noted in the report and by the mining industry
observers. An industry-sponsored sampling study was conducted at mines
in the Powder River Basin in 1978-1979. No information or proposed
emission factors, from that study have been released yet.
i EPA Region VIII and several state agencies have evaluated the avail-
able emission factors and compiled different lists of recommended factors
for use in their air quality analyses (U.S. Environmental Protection
Agency 1979; Wyoming Department of Environmental Quality 1979; Colorado
Department of Health 1980). Some of Oie alternative published emission
factors vary by an order of magnitude. 1 Part of this variance is from
actual difference In average emission rates at different mines (or at
different times or locations within a single mine) due to meteorological
conditions, mining equipment/techniques being used, control techniques
being employed, and soil characteristics.
1
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The diverse values for available emission factors, the obvious pro-
blems encountered in sampling mining sources, and questions of applicability
over a range of mining/meteorological conditions have all underlined
confidence in air quality analysis done to date. Ttr?se problems led to a
ground swell of support from regulatory agency personnel in early 1979 Jor
new emission factors.
The major steps in an air quality analysis for a mine are estimating
the amount of emissions and modeling to preoict the resulting ambient
concentrations. The preamble to EPA's Prevention of Significant Deter-
ioration (PSD) regulations notes the present inability to accurately
model the impact of nines and indicates that additional research will be
done. However, problems in modeling of mines have been overshadowed by
concern over the emission factors. Advancement in this entire area seems
to be contingent on the development of new emission factors.
PURPOSE OF STUDY
The purpose of this study is to develop emission factors for signi-
ficant surface coal mining operations that are applicable at all Western
mines and that
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The study is also intended to determine deposition (or plume depletion)
rates over the 50 to 100 m distance immediately downwind of the sources.
Although it is recognized that deposition continues to significant for
distances of a few kilometers, a large percentage of the fallout occurs in
the first 100 m and estimates of the additional deposition can be made
more accurately from particle size sampling data than from measurements
associated with the emission factor development.
A secondary purpose is to estimate the efficiencies of commonly used
dust control techniques at mines, such as watering and chemical stabili-
zation of haul roads. This aspect of the study received less emphasis
as the study progressed as better information indicated that more test
periods than ortginally anticipated woulo be needed to determine the basic
emission fa'_tors with a reasonable margin of error.
The study was designed and carried out with special effort to encourage
input and participation by most of the expected major users of mining
emission factors. The intent was to obtain suggestions for changes and
additions prior to developing the emission factors than criticism of the
techniques and scope of the study afterward.
TECHNICAL REVIEW GROUP FOR THE STUDY
Participants
EPA's Office of Air Quality Planning and standards (PAQPS) took the
Initial lead in planning for a study to develop new emission factors.
Their staff became aware of the amount of concern surrounding the avail-
able inning factors when they considered including surface mining as a
najor source category under proposed regulations for Prevention of Signi-
ficant Deterioration.
EPA Region VIII Office, which had directed the first fugitive dust
sampling study at surface mines and published a compilation of recommended
mining emission factors, Immediately encouraged such a study and offered
to provide partial funding. The new created Office of Surface Mining
(OSM) in the Department of Interior also offered support and funding. At
that time, OS, had just prooosed regulations pursuant to the Surface Mining
Control and Reclamation Act (SMCRA) requiring air quality analyses for
Western mines of greater than 1,000,000 tons/yr production (this
requirement was dropped 1n the final regulations).
EPA's Industrial Environmenlal Research Laboratory (ICRL) soon became
Involved as a result of Its responsibilities for the agency's research
studies on mining. This group already had planned some contract work on
3
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fugitive dust emissions from surface coal mines in its FY/1979 budget, so
its staff assumed the lead in contractual matters related to the study.
All the early participants agreed that even broader representation
would be desirable in the technical planning and guidance for the stuly.
Therefore, a technical review group was established at the outset of the
study to make recommendaitons on study design, conduct, and analysis of
results. The agencies and organizations represented on the technical
re"iew group are shown in Table 1-1. This group received draft materials
for comnient and iTst periodically throughout the study. Other groups that
expressed an interest in the study were provided an opportunity to commenf
on the draft report.
Study Design
The study design was the most important component of the study from
many perspectives. It was the.primary point at which participants could
present their preferred approaches. The design also had to address the
problems that had plagued previous sampling studies at mines and attempt
to resolve them. Most of the decision making in the study was done during
this phase.
The first draft of the study design report was equivalent to a
detailed initial proposal by the contractors, with the technical review
group then having latitude to suqgest modifications or different approaches.
The rationales for most of the design specifications were documented In the
report so members of tne technical review group would also have access to
the progression of thinking leading to recommendations..
The scope of the full study was not fixed by contract prior to the
design phase. Some of the options left open throughout the design phase
were number of mines, geographical areas, different mining operations, and
the seasonal range to ba sampled. In some cases, the final decision on
recommended sampling methods was left to the results of comparative testing-
alternative methods were both used Initially until the results could be
evaluated and the better method retained.
Several major changes were made from the f
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TABLE 1-1. TECHNICAL REVIEW GROUP FOR MINING STUDY
Organization
Representative
Alternate
Bureau of Land Management
Stan Coloff
Bureau of Mines (U.S.)
H. Wi11iam Zeller
Consolidation Coal Company
Richard Kerch
Department of Energy,
Policy Analysis Division
Suzanne WeiIborn
Bob Kane
Environmental Protection Agency
Industrial Environmental Research Lab.
Monitoring and Data Analysis Division
Region VIII
Source Receptor Analysis Branch
Jonathan Herrmann
Thun>pson Pace
E. A. Rachal
James Dicke
J. Southerland
David Joseph
Edward Burt
Forest Service, U.S. Department of
Agriculture
Douglas Fox
National Coal Association
Charles T. Drevna
National Park Service
Phil Wondra
J. Christiano
New Mexico Citizens for Cean Air
and Water
Michael D. Williams
North American Coal Corporation
Bruce Kranz
Office of Surface Mining
Headquarters
Region V
Robert Goldberg
Floyd Johnson
Peabody Coal Company
Steven Vardiman
Wyoming Department of Environmental
Quality
Randolph Wood
Chuck Collins
5
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Quality Assurance Procedures
October 1979
Example Calculations for Exposure
Prof 11i ng
November 1979
Calculations Procedures for Uowind-Downwind
Sampling Method
October 1979
Statistical Plan
November 1979
Statistica Plan, Second Draft
May 1980
The above reports were being prepared while sampling proceeded at ths
first two mines. The contents of these reports are summarized in this
report in appropriate sections.
CONTENTS AND ORGANIZATION OF THIS REPORT
This report contains 16 sections and is bound m one volume. The
first five sections describe the methodologies used in the study; e.g.,
sampling (Section 3), the sample analysis (Section 4), and data analysis
(Section 5). Sections 6 through 11 present resjlts of the various
sampling efforts.
Sections 12 through 15 describe the evaluation and interpretation
of results and the development of emission factor equations. The specific
topics covered by section are:
12 Evaluation of Results
13 Development of Correction Factors and Emission
Factor Equations
14 Evaluation of Emission factors
15 Summary and Conclusions
Section 16 Is the list of references
6
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SECTION 2
SELECTION OF MINES AND OPERATIONS TO BE SAMPLED
GEOGRAPHICAL AREAS OF MOST CONCERN
The contract fo this study specified that sampling be done at Western
surface coal mines. As a result of comments and recommendations made by
members of the technical review group during the study design preparation,
this restriction in scope was reviewed by the sponsoring agencies. The
decision was made to continue focusing the study on Western mines for at
least three reasons:
1. The Western areas are more arid than Eastern of Midwestern
coal mining regions, leading to a greater potential for
excessive fugitive dust emissions.
2. Western mines in general have larger production rates and
therefore would be larger individual emission sources.
3. Most of the new mines, subject to analyses for environmental
Impacts, are in the West.
The need for emission factors for Eastern and Midwestern surface mines
Is certainly acknowledged. Consequently, an effort was made in the pre-
sent study to produce emission factors that are applicable over a wide
range of climatic and mining conditions.
There are 12 major coal field in the Western states (excluding the
Pacific Coast and Alaskan fields), as shown in Figure 2-1. Together,
they account for more than 64 percent of the surface-mineable coal reserves
In the U.S. (U.S. Bureau of Mines 1977). The 12 coal fields have different
characteristics which may influence fugitive dust emission rai.es from
mining operations, such as:
Overburden and coal seam thickness and structure
Mining equipment commonly used
Operating procedures
Terraln
Vegetation
Precipitation and surface moisture
Wind speeds
Temperatures
7
-------
COAL TYPE
LIGNITE ES3
SUBBITUMINOUSCZ3
BITUMINOUS KS3
1978 production, Strlppable
Coal f
-------
Mines In all 12 Western coal fields could not be sampled in this study.
The dual objectives of the emission facto- development program were to
sample representative, rather than extreme, emission rates and yet saitple
over a wide range of meteorological and mining conditions so that the
effects of tnese variables on emission rates could also be determined.
Therefore, diversity was desired in the selection of nines (in different
coal fields) for sampling.
No formal system was developed for quantifying diversity between
the Western fields. Instead, three fields with hi<; reduction from sur-
face mines and distinctly different characteristics were identified by
the project participants: Fort Union (lignite). Powder River Basin, and
San Juan River. Sampling at mines in each of tnese fields was to be the
first priority. If sampling in a fourth field were possible or a suitable
pine could not be located in one of the three primary areas, the Green
River field was the next choice.
SIGNIFICANT DUST-PRODUCING OPERATIONS
All of the dining operations that Involve movement of soil, coal, or
equipment or exposure of erodible surfaces generate sonse amount of fugitive
dust. Before a stapling program could be designed, it was first necessary
to identify which of the many emission-producing operations at the mines
would be sampled.
The operations at a typical Western surface nine are shown schemati-
cally in Figure 2-2. The initial raining operation is rewova? of topsoil
and subsoil with large scrapers. The topsoil is carried by the scrapers
to cover a previously mined and regraded area (as part of the reclamation
process) or placed in temporary stockpiles. Tne exposed overburden Is
then leveled, drilled, and blasted. Next, the over&urden material is
renoved doan to the coal seam, usually by dragline or shovel and truck
operation. It is placed in the adjacent mined cut and forms a spoils
pile. The uncovered coa' seara is then drilled ami biased. A shovel or
front-end loader loads the borken coal into haul trucks. The coal Is
transported out of the pit along graded haul roads to the tipple, or
truck dump. The raw coal nay also be diw^ad on a temporary storage
pile and later rehandled by a front-end loader or dozer.
At the tipple, the ccal is dumped Into a hopper that feeds the pri-
mary crusher. It is then moved by conveyor through additional coal pre-
paration equipment, such as secondary crushers and screens, to the storage
area. If the mine has open storage piles, the crushed ccal passes through
a coal stacker onto the pile. The piles are usually worked by dozers,
and are subject to Mind erosion. From the storage area, the coal is
conveyed to the train loading facility and loaded cnto rail cars. If the
alne is captive, coal goes from the storage pile to the power plant.
9
-------
v» o»M
To FnpinHni tad
Shipping Facilitin
^ UnHts1«fh«l Af#i
Figure 2-2. Operations at typical western surface coal mines.
-------
During mine reclamation, which proceeds continuously throughout the
life of the mine, overburden spoils piles are smoother and shaped to
predetermined contours by dozers. Topsoil is placed on the graded spoils
and the land is prepared for revegetation by furrowing, mulching, etc.
From the time an area is disturbed until the new vegetat'on emerges, the
exposed surfaces an; subject to wind erosion.
These operations could not be ranked directly in order of their
impact on particulate air quality because reliable emission factors to
estimate their emissions do not exist. Also, any specific mine would
probably not have the same oeprations as the typcial mine described above,
and the relative rragnitudes of the operations vary greatly from mine to
mine (e.g., the average haul distance from the pit to the tipple).
In the study design phase, two different analyses were done to
evaluate the relative impacts of the emission sources (PEDCo Environmental
and Midwest Research Institute 1979). In the first analysis, several
alternative emission factors reported in the literature were used to cal-
culate estimated emissions from a hypothetical mine having all the pos-
sible mining sources described above. The second analysis used a single
set of enission factors, judged to be the best available for each source,
combined with activity data from seven actual surface mines in Wyoming
and Colorado. The resulting rankings from the two analyses were similar.
The ranges of perceitages of total mine emissions estimated by the two
analyses are summarized in Table 2-1. The sources
-------
TABLE 2-1. DETERMINATION OF SIGNIFICANT DUST-PRODl'-'NG OPERATIONS
Primary
Range in % of
erission
total mine
Operation
composition
emissions
Significant sources
Haul truck
soil
18-85
Light and medium duty vehicles
soil
<1-27
(unpaved access roads)
Shovel/truck loading, evfe
soil
4-12
Shovel/truck loading, coal
coal
<1-11
Dozer operations
either
4-11
Wind erosion of exposed areas
soil
<1-10
Scraper travel
soil
<1- 8
Blasting, ovb
soil
<1- 5
Blasting, coal
coal
<1- 4
Drilling, ovte rvc
sol 1
<1- 4
Front-end loader
coal
1- 3
Grader
soil
1- 3
Oragline
soil
<1- 2
Wind erosion of storage piles
coa!
<1- 2
Insignificant sources
Truck dumping,
soil
<1
Truck dumping, coal
coal
<1
Scraper pickup
soil
<1
Scraper spreading
soil
<1
Coal stacker
coal
<1
Train loading
coal
<1
Enclosed storage leading
coal
<1
Transfer/conveying
coa1
<1
Vehicle traffic on paved roads
soil
<1
Crushing, primary
coal
<1
Crushing, secondary
coal
<1
Screening and sizing
coal
<1
Drilling, coal
coal
<1
12
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POTENTIAL MINES FOR SAMPLING
The number of mines to be sampled was set at three in the study
design. This was based on a compromise between sampling over the widest
range of mine/meteoroloqical conditions by visiting a large number of
mines and obtaining the most tests within the ouJget and time limits by
sampling at only a few nines. The criteria for selection of appropriate
mines were quite simple:
1. The three mines should have the geographical distribution
described above, I.e., one each In the Fort Onion, Ponder
River Basin, and San Juan River fiplds.
2. Each mine should have all or almost all of the 14 sign'fl-
cant dust-producing operations listed in Table 2-1.
3. The mine personnel should be willing to cooperate in tho
study and provide access to all operations for sampling.
4. The mines should be relatively large so that there are
several choices of locations for sampling ejch of the
operations.
Using their industry contacts, tne National Co*l Association (NCA)
members did preliminary screening to find appropriate mines and Jiade
contacts to determine whether suitable mines were interested in parti-
cipating In the sampling program.
The three mines finally selected were each obtained in a different
manner. The first, 1n the Powder River Basin, volunteered before any
contacts were made with mining companies. Thr* second mine was operated
by a company with a representative on the technical review group. This
mine was m the Fort Union field In North Da«ota. By coincidence, these
first two mines were among the five where sampling had been done in «.he
previous EPA-sponsored emission factor;development study (EPA 1978a).
Several mines In the San Juan River field were contacted by NCA and
by PEDCo to participate. After falling to obtain a volunteer, provisions
of the Clean Air Act were invoked to obtain access. Personnel at the
third mine cooperated fully wttu the sampling teams and were very helpful.
The names of the three mines are not mentioned in this report.
Pertinent information on the three mines Is summarized 1n Table 2-2.
13
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TABLE 2-2. CHARACTERISTICS OF MINES THAT WERE SAMPLED
Parameter
Units
Mine 1
Mine 2
Mine 3
Powder River
Location
Basi n
North Dakota
Four Corners
Production
105 tons
9-12
1-4
5-8
Stratigraphic data
Typical overburden depth
ft
75
35
80
Typical coal seam
ft
23
2, 4. 9
8
thickness
Typical parting thickness
ft
-
2, 15, 30
35
Typical pit depth
ft
98
80
145
Av overburden density
lb/yd3
3000
3350
5211
Operating data
No. of active pits
-
3
2
7
Typical haul distance
mi
1.6
3.5
2.5
(one way)
103 tons
Av storage pile size
72
15
300
Equipment
Draglines
No.;yd3
3; 60
2: 33. 65
4; 38-64
Shovels
No.;yd3
4; 17, 24
2; 15
J; 12
Front-end loaders
No.;yd3
4; 5-12.5
i: 12
6; 23.5
Haul trucks
No,;tons
13; 100, 120 6; 170
11; 120, 150
Hater trucks
No. ;103 gal
5; 8, 10
3; 1, 8
2; 24
Scrapers
No.;yd3
6; 22
12; 33> 40
3; 34
Dozers
No.
9
8
9
Av coal analysis data
Heat value
Btu/lb
8600
1C61Q
7750
Sulfur content
%
0.8
0. 7j
0.75
Moisture conterit
%
25
37
13
Information in this table provided by respective mining companies.
14
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SCHEDULE
A task order was issued in mid-March, 1979, to prepare a preliminary
study design for development of surface coal mining emission factors.
The time period for the task order was 8 weeks (to mid-May). If the
resulting sampling methods and analytical approach were acceptable to
the sponsoring agencies and the technical review group being convened
to guide the study and assure its wide applicability, another contract
to perform the sampling and data analysis was to follow immediately so
that field work could be completed during the summer and fall of 1979.
The first mine was sampled on schedule, from July 23 through August
24, 1979. However, delays in obtaining approval to sample at a second
mine; requests for f.rther documentation of calculation procedures, error
analyses, and quality assurance procedures; and preparation of a
detailed statistical plan caused a slip in the schedule at this point.
The second mine was sampled from October 10 through November 1, 1979,
precluding a sampling period at a third mine during the dusty season.
The winter sampling at the first mine took place from December 4 through
13, 1979.
Sampling at the third mine, rescheduled for the spring of 1980, was
postponed on several occasions for such reasons as: lapse of the primary
contract with the need to find an alternative contracting mechanism;
unresolved issues regarding the statistical approach; and need for several
contacts to gain access to a mine for the sampling. The third mine was
finally sampled from July 21 to August ,14, 1980.
The actual «chedule for the study is shown in chart form in Figure 2-3.
The distribution of sampling periods by season should be noted. Two
occurred during July-August, when emission rates would be expected to be
near their maximum. One of these mines was also sampled in December, when
fugitive dust rates would normally be relatively low in the Pov/der River
Basin. The fourth sampling period was In October, a season during which
potential for dust generation would be near the annual average.
15
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—t—i—r
STUDY DSN
TASK ORDER
t—I—r
i i r
FIRST TASK OROER
FOR FIELD WORK
i—i—T
i—i—i—i—i—i—i—r
TASK ORDER TO FINISH FIELD
WORK AND WRITE REPORT
i—i—T
t3i 66-
E ET
-AA-
ET
PI
-O-
P2
-e|
mni, mine 2
1 2
LEGEND:
P3
REPORTS
t a
T ¦
P »
EPA AND OSH HTG hi/ CONTRACTORS
WTG OF TECHNICAL REVIEW GROUP
PRESURVEY TRIP TO MINE
PROJECTED DATE OF EVENT
MEETINGS
¦FIELD
MINE 3
6
KEY TO REPORT NUMBERS:
1. STUDY DSN, DRAFT 1
2. STUDY DSN, DRAFT 2
3. STUDY DSN, ORAFT 3
4. FIVE INTERIM TECHNICAL RPTS
5. STATISTICAL PLAN, DRAFT 2
bbCONTRACTS
TESTING-
10
6. PRELIMINARY DATA RPT
7. FIRST DRAFT PROJECT RPT, VOL I
8. FIRST DRAFT PROJECT RPT, VOL II
9. SECOND DRAFT PROJECT RPT
10. FINAL PROJECT RPT
J I I S I I I L
l
1 I I I J I I I I I L
J I L
:«AR APR MAY OUN JUL AUG SEP OCT NOV DEC JAN FE3 MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR APR
1979 1980 1981
Figure 2-3. Schedule for coal mining emission factor development study.
-------
SECTION 3
SAMPLING METHODOLOGY
TECHNIQUES AVAILABLE TO SAMPLE FUGITIVE DUST EMISSIONS
Five basic techniques have been used to measure fugitive dust emissions.
These are quasi-stack, roof monitor, exposure profiling, upwind-downwind and
wind tunnel. Several experimental sanpling methods are in developmental
stages.
In the quasi-stack method of sampling, the missions from a well-
defined process are captured in a trmporary enclosure and vented to a
duct or stack of regular cross-sectional area. The emission concentration
and the flow rati of the air stream in the duct are measured using standard
stack sampling or other conventional methods.
Roof monitor sampling is 'jsed to measure fugitive emisssions entering
the ambient air from buildings or cthfr enclosure openings. This type of
sampling is applicable to roof vents, doors, windows, or numerous other
openings located in Such fashion that they prevent the installation of
temporary enclosures.
The exposure profiling technique employs a sinqle profile tower with
multiple sampling heads to perform simultaneous multi-point isokinetic
sampling over the plu.ne cross-section. The profiling tower Is 4 to 6
meters in height and is located downwind and as ciose to the source as
possible (usually meters). This method uses monitors located directly
upwind to determine the background rontritmtlon. A modification of this
technique employs balloon-suspended samplers.
With the upwind-downwind technique, an array of samplers 1s set up
both upwind and downwind of the source. The source contribution 1s
determined to be the difference between the upwind and downwind concen-
trations. The resulting contribution Is then used In standard dispersion
equations to back-calculate the source strength.
The wind tunnel method utilizes a portable wind tunnel with an open=
floored test section placed directly over the surface to be tested. A1 r
1s drawn through the tunnel at controlled velocities. A proble Is located
at the end of the test section and the air Is drawn thorugh a sampling
]tra1n.
17
-------
Several sampling methods using new sampling equioment or sampling
arrays are 1n various stages of development. These include tracer studies,
lidar, acoustic radar, photometers, quartz crystal impactors, etc.
SELECTION OF SAMPLING METHODS
Each of the five basic techniques used to measure fugitive dust
emissions has inherent advantages, disadvantages, and limitations to
its use.
The quasi-s^ack mpthod is the most accurate of the airborne fugitive
emission sampling techriques because it captures virtually all of the
emissions from a given source and conveys them to a measurement location
with minimal dilution {Kalika et al. 1976). Its use is restricted to
emission sources that can be isolated and are arranged to permit the
capture of the emissions. There are no reported uses of this technique
for sampling open sources at mines.
The roof mor.itor method is net as accurate as the quasl-stack method
because a significant portion of the emissions escape through other
openings and a higher degree of dilution occurs before measurement. This
method can be used to measure many indoor sources where emissions are
released to the ambient air at low air velocities through large openings.
With the exception of the preparation plant and enclosed storage, none of
the sources at mines occur within buildings.
The exposure profiling technique is applicable to sources where the
ground-based profiler tower can be located vertically across the plume
and where the dlstence from the source to the profiling tower can remain
fixed at about 5 meters. This limits application to point sources and
line sources. An example of a line source that can be sampled with
this technique is haul trucks operating on a haul road. Sources such as
draglines cannot be sampled using this technique because the source works
in a general area (distance between source and tower cannot be fixed),
and because of sampling equipment end personnel safety.
The upwind-downwind method is the least accurate of the methods
described because only a small portion of the emsslons are captured 1n
the highly diluted transport air stream (Kallka et al. 1976). It is,
however, a universally applicable method. It can be used to quantify
emissions from a variety of sources where the requirements of exposure
profiling cannot be met.
The wind tunnel method has been used to meausre wind erosion of soil
surfaces and coal piles (Gillette 1978; Cowherd et al. 1979). It offers
the advantages of measurement of wind erosion under controlled wind
conditions. The flow field in the tunnel has been shown to adequately
18
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simulate the properties of ambient winds which entrain particles from
erodible surfaces (Gillette 1978).
Experimental sampling methods present at least three problems for
coal mine applications. First, none have been used in coal mines to date.
Second, they are still in experimental stages, so considerable time would
be required for testing and development of standard operating procedures.
Thfd, the per sample costs would be considerably higher than for currently
available sampling techniques, thus reducing the number of samples that
could be obtained. Therefore, these techniques were not considered
applicable methods for this study.
After review of the inherent advantages, disadvantages and limitations
of each of the five basic sampling techniques, the basic task was to
determine which sampling method was most applicable to the specific
sources to be sampled, and whether that method could be adapted to meet
the multiple objectives of the study and the practical constraints of
sampling in a surface coal mine.
Drilling was the only source which coul be sampled with the quasl-
stack method. No roof monitor sampling could be performed because none
of the sources to be sampled occurs within a building. It was decided
that the primary sampling method of the study would be exposure profiling.
The decision was based primarily on the theoretically greater accuracy
of the profiling technique dS opposed to upwind-downwind sampling and
its previous use in similar applications. Where the constraints of
exposure profiling could not be met (point sources with too larqe a
cross-sectional area), upwind-downwind would be used. The wind tunnel
would be used for wind erosion sampling.
SAMPLING CONFIGURATIONS
Basic Configuration
Exposure Profillng--
Source strength--The exposure profiler consisted of a portable tower,
4 to 6 m in neight, supporting an array of sampling heads. Each sampling
head was operated as an Isokinetic exposure sampler. The air flow stream
passed through a settling chamber (trapping particles larger than about
50 um In diameter), and then flowed upward through a standard 8 In. x
10 In. glass fiber filter positioned horizontally. Sampling Intakes were
pointed Into the wind, and the sampling velocity of each Intake wan
adjusted to match the local mean wind speed as determined prior to each
test. Throughout each test, wind speed was monitored by recording
anemometers at two heights, and the vertical wird speed profile was
determined by assuming a logarithmic distribution. This distribution
19
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has been found to describe surface winds under neutral atmospheric stability,
and is a good approximation for other stability classes over the short
vertical distances separating the profiler samplers (Cowherd, /'xetell,
Guenther, and Jutze 1974). Sampling time was adequate to provide sufficient
particulate mass 10 mg) and to average over several units of cyclic
fluctuation in the emission rate (e.g., vehicle passes on an unpaved road).
A diagram of the profiling tower appears in Figure 3-1.
The devices used in the exposure profiling test to measure concentrations
and/or fluxes of airborne particulate matter are listed in Table 3-1. Note
that only the (isokinetic) profiling samplers directly measure particulate
exposure (mass per unit intake area) as weil as particulate concentration
(mass per unit volume). However, in the case of the other sampling devices,
exposure may be calculated as the product of concentration, mean wind speed
at the height of the sampler intake, and sampling time.
Two deployments of sampling equipment were used in this study: the
basic deployment descnbed in Table 3-2 ana thu special deployment shown
in Table 3-3 for the comparability study.
Particle size-- Two Sierra dichotomous samplers, a standaro hi-«ol,
and a Sierra cascade impactot were used to measure particle sizes downwind.
The dichotomous samplers collected fine and coarse fractions with upper
cut points (50 percent efficiency) of 2.5 /m and approximately 15 um.
(Adjustments for wind speed sensiti-. ity of the 15 /en cut point are discussed
in Section fc; limitations of this sampling technique are describea in Section
1 *9
1 U m
The high-volume parallel-slot cascade impactor with a 20 cfm flow con-
troller was equipped wit'i a Sierra cyclone preseparator to remove coarse
particles that otherwise would tend to bounce off the glass fiber Impaction
substrates. The bounce-through of coarse particles produces an excess of
catch on the backup filter. This results in a positive b'as in the measure-
merit of fine particles (see Page 6-3). The cyclone sampling intake was
directed into the wind and the sampling velocity adjusted to mean wind speed
by fitting the intake with a nozzle of appropriate size, ''esulting in
isokinetic sampling for wind speeds ranging rrom 5 to 15 mph.
Deposition-- Particle deposition was measured by placing dustfall buckets
along a 1 ine downwi nd of the source at distances of 5 m, 20 m, and 50 m from
the source. Greater distances would have been desirable for establishing the
deposition curve, but measurcable weights of dustfall could not be obtained
beyond about 50 m during th 1-hour test periods. Dustfall buckets were col-
located at each distance. The bucket openings were located 0.75 m above
ground to avoid the impact of saltating particles generated by wind erosion
downwind of the source.
20
-------
Figure 3-1. Exposure profiler.
-------
TABLE 3-1. SAMPLING DEVICES FOR ATMOSPHERIC
PARTICULATE MATTER—EXPOSURE PROFILING
Particulate
matter
category
Air sampling device
Type
Quantity
neasured
Operating flow
rate
Flow
Calibrstor
TP
Exposure profiler
head
Exposure and
concentration
Variable (10-50
SCFH) to
achieve iso-
kinetic
stnplin,,
Anemoraeter
calibra-
tor
Cyclone with inter-
changeable probe
tips and backup
filter
Exposure and
concentration
20 ACFM
Orifice cal-
brator
TSP
Standard hl-vol
Concentration
40-60 ACFM
Orifice cal"
ibrator
IP
Oichotomous sampler
Concentration
0.59 ACFM
Dry test
eseter
FP
Dichotosious sampler
Concentration
0.59 ACFM
Dry test
eeter
TP = Total particulate «= All particulate Batter in pluee
TSP = Total suspended particulate 0 Particulate matter In size range collected
by hl-vol, estimated to be lees than about
30 (is* diaaeter
IP = Inhalable particulate ** Particulate less than 15 pa diuseter
FP = Fine particulate 3 Parti-ulate less than 2.5 pm diameter
22
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TABLE 3-2. BASIC EQUIPMENT DEPLOYMENT FOR EXPOSURE PROFILING
Oistance
frco
Intake
Source
Height
Location
(o)
Equipment
(c)a
Upwind
5
1 Dfchotomous t-aapler
2.5
1 Standard hi-vol
2.5
2 Dustfall buckets
0.75
1 Continuous wind conitor
4.0
Downwind
5-10
1 HRI exposure profiler with 4
1.5 (1.0)
sampling heads
3.0 (2.0)
4.5 (3.0)
6.0 (4.0)
1 Standard hi-vol
2.5 (2.0)
1 Hi-vol with cascade irapactor
2.5 (2.0)
2 Dichotooous samplers
1.5
4.5 (3.0)
2 Dustfall buckets
0.75
2 Wans wire anejsoawftfirs
1.5 (1.0)
4.5 (3.0)
Downwind
20
2 Duttfal' buckets
0.75
Downwind
50
2 Dustfall buckets
0.75
A
Alternative heights for sources generating lower piuse heights are given
in parentheses.
23
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TABLE 3-3. SPECIAL EQUIPMENT DEPLOYMENT FOR EXPOSURE
PROFILING—COMPARABILITY TESTS
Locat-ion
Distance
from
Source
(o)
Equipment
Intake
Height
(m)
Upwind
5 to 10
1 Standard hi-vol
1.25
1 Standard hi-wol
2.5
2 Oustfall buckets
0.75
1 Continuous wind monitor
4.0
Downwind
«>
1 MRI exposure profiler with 4 sampling
1.5
heads
3.0
4.5
6.0
1 Standard hi-vol
2.5
2 Hi-vols with cascade inspactors
1.5
4 Oichotoaous samplers
1.5
3.0
4.5
6.0
2 Oustfall buckets
0.75
2 Ware wire sneroaeters
1.5
4.5
Downwind
20
1 Hi-vol with cascade icpactor
2.5
2 Dustfall buckets
0.75
Downwind
50
2 Oustfall buckets
0.75
24
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Exposure Profiling Modification for Sampling Blasts--
Source strength-- The exposure profiler concept was modified for
sampling blasts. The large horizontal and vertical dimensions of the
plumes necessitated a suspended array of samplers as well as ground-based
samplers in order to sampler over the plume cross-section in two dimensions.
Five 47 mm PVC filter heads and sampling orifices were attached to a
line suspended from a tethered balloon. The samplers were located at
five heights with the highest at 30.5 m (2.b, 7.6, 15.2, 22.9, and 30.5 m).
Each sampler was attached to a wind vane so tnat the orifices would face
directly into the wind. The samplers were connected to a ground based
pump with flexible tubing. The pump maintained an isokinetic flow rate
for a wind speed of 5 mph. In order to avoid equipment damage from the
blast debris and to obtain a "-epresentative sample of the plume, the
balloon-suspended samplers were located about 100 m downwind of the
blast area. This distance varied depending on the size cf the blast and
physical constraints. The distance was measured with a tape measure.
The balloon-supDorted samplers were supplemented with five hi-vol/dichot
pairs located on an arc, at the same distance as the balloon from the
edge of the blast area. These were spaced 20 m apart on the arc.
Particle size-- The five ground-based dichotomous samplers provided
the basic particle size information.
Deposition--There was no measurement of deposition with this sampling
method. Dustfall samples would have been biased by falling debris from
the blast.
Upwi nd-Downwi nd- -
Source strength-- The total upwind-downwind array usei for sampling
point sources included 15 samplers, of which 10 were hi-vols and 5 were
dichotomous samplers. The arrangement is shown schematic?Ily 1n Figure
3-2. The downwind distances of the samplers from point sources were
nominally 30 m, 60 m, 100 m, and 200 m. Frequently, distances in the
array had to be modified because of physical obstructions (e.g., highwall)
or potential interfering sources. A tape measure was used to measure
source-to-sampler distances. The upwind samplers were placed 30 to 100
m upwind, depending on accessibility. The hi-vol and dichotomous samplers
were mounted on tripod stands at a height of 2.5 m. This was the highest
manageable height for this type of rapid-mount stand.
This array was modified slightly with sampling line sources. The
array consisted of two h1-vol/dichot pairs at 5 m, 20 m, and 50 m with
2 hi-vols at 100 m. The two rows of samplers were normally separated by
20 m.
25
-------
I /
plume
centerline
Figure 3-2. Upwind-downwind sampling array.
26
-------
Particle size-- In addition to the dichotomous samplers located upwind
of the source and at 30 m and 60 m distances downwind of the source, milli-
pore filters were exposed for shorter time period during the sampling at
different downwind distances. These filters were to be subjected to micro-
scopic examination for sizing, but most of this work was suspended because
of poor agreement of microscopy with aerodynamic sizing methods in the
comparability study.
Deposition-- The upwind-cownw1nd method allows indirect meas"rement
of depsttion through calc^ation of apparent emission rates at different
downwind distances. The ""c-'uction m apparent emission rates as a function
of distance is attributed iu doposition. At distances beyono about 100 m,
deposition rates detemined by this method would probably be too small to
be detected separate fron< plume dispersion.
Wind Tunnel--
Source strenqth--For the measurement of dust emissions gene'rced by
wind erosion of exposed areas and storage piles, a portable wind ti.nnel
was used. The tunnel consisted of an inlet section, a test section, and
an outlet diffuser. As a modification to previous wind tunnel desions,
the working section had a 1 foot by 1 foot cross section. This enlarge-
ment was made so that tiie tunnel could be used with rougher surfaces.
The open-floored test section of the tunnel was placed direct'iy on the
surface to be tested (1 ft x 8 ft), and the tunnel air flow was adjusted
to predetermined values that corresponded to the means of the upper NOAA
wind speed ranges. Tunnel wind speed was measured by a pitot tube at
the downstream end of the test section. Tunnel wind speeds were related
t) wind speed at the standard 10 m height by means of & loyrithmic profile.
An airtight seal was maintained along the sides of the tunnel by
rubber flaps attached to the bottom edges of the tunnel sid's. These
were covered with material from areas adjacent to the test urface to
eliminate air infiltration.
To reduce the dust levels in the tunnel air intake stream, testing
was conducted only when ambient winds were well below the threshold
velocity for erosion of the exposed material. A portable high-volume
sampler with an open-faced filter (roof structure removed) was operated
on top of the inlet section to measure background dust levels. The
filter was vertically oriented parallel to the tunnel Inlet face.
An emission sampling module was used with the pull-through wind tunnel
in measuring particualte emissions generated by wind erosion. As shown
1n Figure 3-3, the sampling module was located between the tunnel outlet
hose and the fan inlet. The sampling train, which was operated at 15-25 cfm,
27,
-------
consisted of a tapered probe, cyclone precollector, paral lei->>lot cascade
impactor, backup filter, and high-volume motor. Interchangeable probe
tips were sized for isokinetic sampling over the desired tunnel wind
speed range. The emission sampling train and the portable hi-vol were
calibrated in the field prior to testing.
Particle size--The size distribution for 30 jure and smaller particles
was generated frcT the cascade impactor used as the total particulate
sampler. The procedure for correction of the size data to account for
particle bounce-through is described in Section 5.
Deposition--f{o r,ethod of measuring the deposition rate of particles
suspended by wind erosion m the test section could be incorporated into
the design of the wind tunnel.
Quasi-Stack--
Source strength--An enclosure was fabricated consisting of an ad-
justable metal frame covered with plastic. The frame was 6 feet long
with maximum openings at the ends of 5 x 6 feet. Due to problems with
the plastic during high winds, the original enclosure was replaced with
a wood enclosure with openings 4x6 fett, as snown in Figure 3-4. For
each test, the enclosure was placed downwind of the drill base. Hie
outlet area was divided into four rectangles of area, anj the vind velocity
was measured at the center of each rectangle with a hot wire anemometer
to define the wind profile inside the frame.
Four exposure profiler samplers with flow controller* were used to
Sffliple the plume. Using the wind profile data, the sampler flow rates
were adjusted to 2 to 3 minute intervals to near-1 soUnetic conditions.
Particle size--The only particle size measurements made with this
sampling method was the split between the filter catch and settling chamber
catch in the profiler heads.
Deposition--There was no direct measurement of deposition with this
saraplTng method.
Sampling Configuration by Source
The basic s
-------
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nd
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-------
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Hl-Wl HOTOR
ostna
scnuRs m
^scmiwi chwbw
Willi
PlMfOG"
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F1,ure 3.4. Q».sl-s«* SOTpUn9-«»Por»ry
enclosure for drill sampling-
-------
TABLE 3-4. SAMPLING CONFIGURATIONS FOR SIGNIFICANT SOURCES
Source
Point,
line, or area
Sampling configuration
Drilling (overburden)
Point
Quasi-stack
Blasting (coal and overburden)
Area
Exposure profiling
(modification)
Coal loading (shovel/truck and
front-end loader)
Point or area
Upwind/downwind
Dozer (coal and overburden)
Line or point
Upwi nd/downwi nd
Drag! "¦ ne
Point or area
Upwi nd/downwi nd
Haul trurV
Line
Exposure profiling
Light- and medium-duty vehicles
Line
Exposure profiling
Scraper
Line
Exposure profiling
Grader
Line
Exposure profiling
Wind erosion of exposed areas
Area
Wind tunnel
Wind erosion of storage piles
Area
Wind tunnel
A
Several of these sources could be operated as a line, point, or area source.
Where possible, the predominant method of operation was used. In other
cases, sampling requirements dictated the type of operation.
31
-------
B1asting--
The plume from a blast Is particularly difficult to sample because
of the vertical and horizontal dimensions of the plume and the inability
to place sampling equipment near the blast. Further, the plume is sus-
pp'-ted to be non-Gaussian because of the way in which the plume is
ift ially formed. Therefore, upwind-downwind sampling is not appropriate.
To sample blasts, a modification of the exposure profiling technique was
developed. This modification was discussed previously. Atypical sampling
array is shown in Figure 3-5. The same sampling procedure was used for
overburden blasts and coal blasts.
Coal Loading with Shovels or Front-End Loaders--
The exposure profiler could not be used for this source because of
movement of the plume origin. Therefore, the upwind-downwind configura-
tion for point sources was used. There are many points at which dust
Is emittpd during truck loadln-j—pul ling the truck into position,
scooping the material to be loaded, lifting and swinging the bucket,
dropping the load, driving the truck away, and cleanup of the area by
dozers or front-end loaders. Dropping of the load into the truck was
generally the largest emission point so its emissions were used as the
plume centerline for the sampling array, with the array spread wide enough
to collect emissions from all the dust-producing points. Bucket size was
recorded for each test, as well as the number of bucket drops.
Wind conditions and cne width of the pit dictated the juxtaposition of
the source and sampler array. When the winds channeled through the p't and
the pit was wide enougn to set up the sampling equipment out of the way of
haul trucks, the samp'ors were set up downwind and in the pit. When winds
were perpendicular to the pit, the sampling array was set up on a bench
If the bench was not more than 5 to 7 meters high. With this configuration,
the top of the haul truck was about even with the height of the bench;
emissions frori the shovel drop point cou'd be very effectively sampled in
this manner. Two coal loading sampling arrays are shown in Figure 3-5.
Dozers-
Dozers are difficult to test because they may operate either as a line
source or in a general area as large as several acres over a 1-hour test
ji»r1od. When a dozer operated as a line source, the upwind-downwind con-
figuration for a line source was used. The samplers were located with the
assumed plume centerline perpendicular to the line of travel for the dozer.
The number of times the dozer passed the samplers was recorded for each test.
Since dozers could not always be found operating as a line source, captive
dozers were sometimes used so that test conditions could be more accurately
controlled. To sample dozers working in an area, the upwind-downwind point
source configuration was used. The location and size of the area was recorded
along with dozer movements.
32
-------
Figure 3-5. Blast sampling with modified exposure profiling configuration
-------
Sampling array in the pit
Sampling array on a bench
Figure 3-6. Coal loading with uDwind-downwind configuration.
34
-------
Dragli ne--
Sampling of this source was performed with the upwind-downwind con-
figuration because of the large initial dimensions of the plume and
because of the impossibility of placing samplers near the plume originc
There are three emnsion points--pickup of the overburden material,
material lost from the bucket during the swing, and overburden drop. It
was not always possible to position samplers so they were downwind of all
three points. Therefore, sketches were made ot each setup and field notes
were recorded as to which points were included in the test. The number of
drops, average drop distance, and size of the dragline bucket were also
recorded.
Location of the samplers relative to the dragline bucket was determined
by wind orientation, i^ze of the pit (width and length) and pit accessi-
bility. When winds were parallel to the pit, the array was set up in the
pit if there was sufficient space and the plumes from all three emission
points passing over the samplers. When winds were perpendicular to the
pit, draglines were only sampled if samplers could be placed on a bench
downwind at approximately the same height as the spoils pile where the
overburden was being dropped. Figure 3-7 shows the two typical dragline
sapling configurations.
Haul Trucks-
Most sampling periods for haul trucks at the first mine were performed
as part of the comparability study {see Section 6), employing both expo-
sure profiling and upwind-downwind configurations. Haul trucks were used
to perform the comparative study because they are a uniformly-emitting line
source and because haul road tiaffic is the largest particualte source In
most mines. At subsequent mines, exposure profiling was used to sample
this source. For each test, the wind was approximately perpendicular to
the road, the air intakes of the samplers were pointed directly into the
wind, and the samplers extended to a height of 6 m to capture the vertical
extent of the plume. In a few cases, more than |
-------
Sampling array 1n the pit
Sampling array at about the saot height as the spoils pile
Figure 3-7. Dragline sampling with upwind-downwind confIguratton
36
-------
specifically for lighter vehicles were u^ed to testing. However, sere
sampling for light- and inettiusn-duty vehicles was aone on haul roads.
Samples of the road surfaces were taken so that differences due to road
properties could be evaluated (a full discussion of source characterization
fs included in the next subsection). A light- and medium-duty vehicle
sampling array is shown in previously cued Figure 3-8.
Scraper--
This source was sampled by the etposure profiling method. Scrapers
were sampled while traveling on a temporary road so that the emissions could
be tested as a line source. Neither the loading nor the emotying operations
were sampled, since both had been estimated to have insignificant emissions
compared to scraptr travel. The profiler was extended to 6 m to sample
the vertical extent of the plurae. In order to secure a suitable setup in
a location with interference fron other sources, it was iften necessary
to use captive equipment. A typical sampling array for scrapers is shown
in Figure 3-9.
Graders--
Exposure profiling was used to sample qraders. Graders operate In a
fairly constant manner; only the speed and travel surface (on road/off
road) vary over a time. It was asiuned that the travel surface could be
considered as a correction fsctor rather than requiring two separate
emission factors. As with dozers, captive equiprant was soviet *'Res
necessary to sample tnts source because graders did not normally rfrive
past the sarae location repetitively. Even if there were regarding a short
stretch of road, thay would tie at a different location on the road cross
section with each pass, making it difficult to reposition the profiler.
Therefore, captive equipment allowed better control of test variables.
bind Erosion of Exposed Areas and Storage P1les--
The wind tunnel was used to sample these two sources. In measuring
emissions with the portable wind tunnel, it was necessary to place the
tunnel on a flat, nearly horizontal section of surface. Care was taken
rot to disturb the natural crust on the surface, with the exception of
removing a few large clumps that prevented the tunnel test section from
making *n airtight seal with the surface.
Th« threshold velocity for wind erosion And emission rates at se .ral
predetermined wino speeds above the threshold were measured on each test
surface. Wind erosion of exposed surfaces had been shown to decay In
tine for velocities welt above the threshold value for the exposed surface.
Therefore, some tests of a given surface were performed sequentially to
trace the decay of the erosion rate over time at high test velocities. A
typical wind tunnel sampling configuration Is shown in Figure 3-10.
37
-------
Haul truck travel
Light- *nd medius-duty truck
Figure 3-8. Haul road sampling with exposure profiling configuration.
38
-------
Figure 3-9. Scraper sampling with exposure profiling configuration
-------
Changes Made In Res »nse Comments
Tha basic sampling designs presented above represents tne combined
efforts of the two contractors as well as comments received from the tech-
nical review group. Specific changes made in response to technical review
group comments are summarized b?low.
1. Dichotomous samplers were added to the exposure profiling
sampling method. They were placed at four heights cor-
responding to the Isokinetic sampling heights during the
comparability study, and at two heights for the remainder
of the tests. With this arrangement, dichotomous samplers
replaced the cascade impactor as the primary particle
size sanpler In exposure profiling.
2. A fourth row of downwind sampler was added to the upwind-
downwind array. Two hi-vols were placed at 200 m from the
source to aid In the measurement of deposition.
3. The quasi-stack sampling method was adopted for sampling
ove"burden drilling and an enclosure was designed and
fabricated.
4. The modification of the exposure profiling method to sample
blasts was devised.
5. Provisions were made to sample scrapers, and other sources
as required, ^s captive equipment 1n locations not subject
to other dust interferences.
SOURCE CHARACTERIZATION PROCEDURES
In order to determine the parameters that affect dust generation from
an Individual source, the suspected parameters must be measured at the
time of the emission test. These parameters fdll Into three categories:
properties of the materials being disturbed by wind or machine^, operating
parameters of the mining equipment involved, and meteorological conditions.
Table 3-5 lists the potential parameters by source that were quantified
during the study.
Representative samples of materials (topsoll, overburden, coal, or road
surface) were obtained at each test location. Unpaved and paved roads were
sampled by removing loose material of road surface extending across the
travel portion. Loose aggreqate materials being transferred were sampled
with a shovel to a depth exceeding the size of the largest aggregate pieces.
Erodlble surfaces were sampled to a depth of about 1 centimeter. The samples
were analyzed to determine moisture and silt content.
40
-------
Figure 3-10. Wind erosion sampling with wine tunnel.
41
-------
Mining equipment travel speeds were measured by radar gun or with a
stop watch over a known travel distance. Equipment specifications and
traveling weights were obtained from mine personnel. For several sources,
it was necessary to count vehicle passes, bucket drops, etc. These counts
were usually recorded by two people during the test to ensure the accuracy
of the results. Frequent photographs were taken during each test to
establish the sampling layout (to supplement the ground-measured distances),
source activity patterns, and plume characteristics.
Micro-meteorological conditions were recorded for each test. Host of
these data were used in the calculation of concentrations or emission rates
rather than as potential correction factors for the emission factor equations.
During the test, a recording wind instrument measured wind direction and
wind speed at the sampling site. A pyranograph was used to measure solar
intensity. Humidity wa*. determined with a sling psychrometer. A barometer
was used to record atmo^, neric pressure. The percent of cloud cover was
visually estimateu.
In addition to monitoring micro-meteorological conditions, a fixed
monitoring station at che mine monitored parameters affecting tne entire
area. Data were receded on temperature, humidity, wind speed and direction,
and precipitation.
ADJUSTMENTS MADE DURI"J SAMPLING
The sampling comIgurations detailed in this section were the result
of a careful study design process completed prior to actual field sampling.
Actual field conditions forced chanyed to elements of the study design.
A modification to the upwind-downwind sampling array was required.
Whereas the study design called for two hi-vo's at 200 m downwind of the
source, this setup could not be adapted to field conditions. Three major
.reasons for the deviation from the study designs were: (a) the difficulty
of locating the- samplers where they were not sjbjected to other dust In-
terferences; (b) the olfficulty of extending power to the samplers; and
, (c) In many sampling locations, there was not 200 m of accessible ground
downwind of the source. Therefore, only 1 hi-vol was routinely placed
at the 200 m distance and in some cases no sampler was located at that
distance.
Four modifications were made to the exposure profiling sampling array.
First, it was impractical to mount dlchoto-nous samplers at all four heights
on the profiling tower as called for 1n the original study design. Dicho-
tomous samplers were placed at two heights. Second, the study design called
for an exposure profiling test to be terminated It the standard deviation
of the wind direction exceeded 22.5° during test period. Because unstable
atmospheric conditions were encountered at Mine 1 during the summer season,
42
-------
TABLE 3-5. SOURCE CHARACTERIZATION PARAMETERS
MONITORED DURING TESTING
Source
tt
Parameter
Quantification technique
All tests8
Wind speed and direction
Temperature
Solar intensity
Humidity
Atmospheric pressure
Percent cloud cover
Anemometer
Thermometer
Pyranograph
Sling psychrometer
Barometer
Visual estimate
Overburden drilling
Silt content
Moisture content
Depth of hole
Dry sieving
Oven drying
Drill operator
Blasting
Number of holes
Size of blast area
Moisture content
Visual count
Measurement
From mining company
Coal loading
Si It content
Moisture content
Bucket capacity
Equipment operation
Dry sieving
Oven drying
Equipment specifications
Record variations
Dozer
Silt content
Moisture content
Speed
Blade size
Dry sieving
Oven drying
T ime/distance
Equipment specifications
Dragline
Silt content
Moisture content
Bucket capacity
Drop distance
Dry sieving
Oven drying
Equipment specifications
Visual estimate
Haul truck
Surface silt content
Vehicle speed
Vehicle weight
Surface loading
Surface moisture content
Nunber of wheels
Dry sieving
Radar gun
Truck scale
Mass/area of collected
road sample
Oven d^ing
Visual observation
Light- and Kediua-
duty vehicles
Same parameters and quantif
haul trucks
cation techniques as for
(continued)
43
-------
TABLE 3-5 (continued).
Source
Parameter®
Quantification technique
Scraper
Grader
Wind erosion of
exposed areas
Wino erosion of
storage piles
Same parameters and quantif
haul trucks
Same parameters and quantif
haul trucks
Surface credibility
Surface sill content
Surface moisture content
Surface roughness height
Same parameters and quantif
wind erosion of exposed are
icaticn techniques as for
ication techniques as for
Dry sieving
Dry sieving, before and
after test
Oven drying, before and
after test
Measurement
ication techniques as for
P5
Most of the meteorological parameters monitored during all tests are needed
to estimate emission rates, and are not considered to be potential correc-
tion parameters in the emission factor equations.
44
-------
it was necessary to relax this restriction. However, this change had no
effect on tne direction-insenstive dichotornous sampler which served as
the primary sizing device. At the third mine, a second cascade impact.or
and hi-vol were added alongside the profiler at the heigf.t of the third
profiling heid. This was to provide backup data on particle size distri-
bution in the upper portion of the plume and on the TSP concentration
profile. Finally, greased substrates were used with the cascade lm-
pactors at the third nine to test whether particle bounce-through observed
at the first two mines would be diminished.
A modification was required to the balloon sampling array. The study
design specif ie-1 that the five ground-base:! sampler pairs be located
10 m apart and that the balloon samplers be located on the blast plume
centerline. This was found to be impractical under field conditions.
The location of the plume centerline was very dependent on the exact wind
direction at the time of the blast. Because the balloon sampling array
required at least one hour to set up, it was impossible to anticipate
the exact wind direction one hour hence. There'ore, the ground-basrd
samplers were pieced 20 to 30 m apart when the wind was variable so
that some of the samplers were in the plume. The balloon sometimes could
not be moved to the plume centerline quickly enouyh after the blast.
Rapid sequence photography was used during the test to assist in deter-
mining the plume centerline; the emission factor calculation procedure
was adjusted accordingly.
ERROR ANALYSES FOR SAMPLING METHODS
Separate error analyses were prepared ror the exposure profiling
and upwind-downwind sampling methods. These analysis were documented
in Interim technical reports and will be summarized here (Midwest
Research Institute 1979; PEDCo Environmental 1979}.
A sunmary of potential errors {lo) 1n the exposure profiling Rethod
Initially estimated by MRI Is shown in Table 3-6. Potential errors
fall in the categories of sample collection, laboratory analysis, and
emission factor calculation. For particles less than 15 jum, the
error in the technique was estimated by MRI to range from -14 percent
to +8 percent. Subsequent field experience on this project indicated
that actual error was 30 to 35 percent in that size range and higher
for the less than 30 (suspended particulate) size range.
45
-------
Potential errors Initially estimated by PEDCo for the upwind-
downwind sampling method are summarized in Table 3-7. A delineation
was made between errors associated with line sources and point/area
.ources. The estimated errors were +_30.5 percent and +50.1 percent,
respectively.
SUMMARY OF TESTS PERFORMED
Sampling performed is shown In Table 3-8. The number of samples
are shown by source and mine. A total of 265 tests were completed.
46
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TABLE 3-6. SUMMARY OF POTENTIAL ERRORS IN THE EXPOSURE PROFILING METHOO
Bcurco or error
Crror typo
Action to ninlalie error
[•tlutal error
Sasole collection
1. lMtnscot error
Bandoa
Planned aaintenance, periodic calibration
and frequent flew checko
»X*
S. MdsoHittatic tcvllo(
a. wind direction fluctuation
Byotcaatic
V"-5*
Indicated that the dichotoaoue eanpier inatruaont error woe at
Wot 2S percent, producing a total error ((or particles leas than 15 pa) of 30 to IS percent.
-------
TABLE 3-7. SUMMARY OF POTENTIAL ERRORS IN THE UPWIND-DOWNWIND SAMPLING METHOD
Estimated
error
Point/area
Source of error
Data restraints to limi*. error
Line source
source
Measurement
1. High volume sampler
Orientation of roof within
18.8%
18.8%
measurements
average wind direction
2. Wind speed measurement
Average wind speed >1.0 mph
4.6%
4.6%
3. Location relative to the
source
«. Distance from source
Measure from downwind edge of
1.7%
1.7%
source
b. Distance from plume
Samplers should be within 2a
-
5.8°
1 in y dimension
of centerline ^
c. Distance from plume
Sampler^ should be within 2a
0.5 hi
1.0 m
1 in z dimension
of centerline
Atmospheric dispersion equation
4. Initial plume dispersion
Horizontal
-
0.2 m
Vertical
0.2 m
0.5 m
5. Dispersion coefficients
Empirical values
3.2%
5.8/3.2%
Estimation of stability
15.9%
21.1/15.9%
class
6. Subtraction of a background
This error will be higher
18.8%
18.8%
concentration
when the wind reverses
briefly or upwind samplers
are biased by nearby sources
7. Gaussian plume shape
cannot quantify
8. Steady state dispersion
Marginal passes <12% of good
6.0%
6.0%
passes
Total
30.5%
50.1%
-------
TABLE 3-8. SUMMARY OF TESTS PERFORMED
Sources
Mine 1
Mine 2
Mine 1W3
Mine 3
Total
Drill (overburden)
11
-
12
7
30
Blasting (coal)
3
6
7
16
Blasting (overburden)
2
3
5
Coal loading
2
8
15
25
Dozer (overburden)
4
7
4
15
Dozer (coal)
4
3
5
12
Dragline
6
5
8
19
Haul truck
7b
9
10
9
35c
Light- and medium-duty truck
5
5
3
13d
Scraper
5b
5
2
2
14
Grader
6
2
8
Exposed area (overburden)
11
14
3
6
34e
Exposed area (coal)
10
7
6
16
39
Total
70
75
33
87
265
^ Winter sampling period.
Five o* these tests were comparability tests,
j Nine of these were for controlled sources.
Two of these were for controlled sources.
Three of these were for controlled sources.
49
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SECTION 4
SAMPLE HANDLING AND ANALYSIS
SAMPLE HANDLING
Several different types of particulate samples were collected during
the field work: hi-vol glass filters, filters and setting chamber
catches fran exposure profilers, cascade 'upactor stages, cyclone pre-
collector catches, l£fion filters from dichotomous samples, Millipore
filter cartridges frum microscopic analysis, PVC filters frov tne balloon
sampling system, and dustfall samples. These samples all required
slightly different handling procedures.
At the end of each run, the collected samples were transferred
carefully to protective containers. All transfer operations except
removal of cartridges from the instruments were done in a van or in
the field lab to minimize sample losses and contamination. Sample media
were carried ano transported locally in an upright position, and covered
with temporary snap-on shieios or covers where appropriate. H1-*:>1
and profiler filters were folded and placed'ln Individual en/elopes.
Dust collected on interior surfaces of profiler probes and cyclone
precollectors was rinsed with distilled water into containers with t*e
settllno chamber catches.
In oMer to reduce the amount of material di&lodced from the taut
dichotomous filters during handling, the preweighed filters t*ere placed
1n plastic holders than were then kept In individual petri dis'.es throughout
the handling process. The petri Uls ies were sealed with tape before being
returned to the laboratory and stacked 1n small carrying coses so that
they would not be Inverted. Many of the dlchotomous filters were hand-
carried back to the laboratory by air travel rather than returning with
the sampling equipment and other samples in the van.
In spite of the special hanmlny proceuures adopted for the dlcho-
, tomnus filters, loose particulate materials was observed in sons of the
petri dishes and material could be seen migrating across the filter
'surfaces with any bumping of the filter holder. Sevpral corrective
actions were investigated by PEDCo arid MR I throughout the study, but
this remained an unresolved handling problem. First, ringed Teflon filters
were substituted for the mesh-backeu niters Initially used in an attempt
to reduce movement or vibration of the exposed filters. Next, the possi-
bility of weighing the filters In the field was reviewed. However, a
50
-------
sensitive micobalance an" strict filter equilibration procedures were
required because of the snail weights involved--f1Iter tare weights less
than 100 mg and nvjy upwind and fine part'cle fraction sample weighs less
than 50 ug. (See Section 12 for further discussion of dic'iotonous samplers.)
P\C filters for the balloon samplers ar.d Willipore filters for
particle size analysis were sent to the field in plastic cartridges.
These cartridges were uncapped and affixed to thj air pumps during sampling,
then reseated and returned to the laboratory for gravimetric or microscopic
analysis. Loss of material from these filter surfaces was not observed
to be a problem as it was with the Teflon filters.
Alt samples except the dichotomoas filters were labeled with the name
of the mine, date, operation, sampler, and a unique sample number
(dichotcmous simple holders had only the sample numDer). This sane
Information was also recorded on a field data sheet at the time of
sampling. Copies of the field data sheets were shown m the study
design report.
To minimize the problem of particle bounce, the glass fiber cascade
impactor substrates were greased for use at H1ne 3. The grease solution
was prepared by dissolving 100 grams of stopcock grease in 1 liter of
reagent grade toluene. A low pressure spray gun was used to apply this
solution to the impaction surfaces. No grease was applied to the borders
and backs of the substrates. After treatment, the substrates were
equilibrated and weight using standard procedures. The substrates were
handled, transported and stored In specially designed frames which pro-
tected the greased surfaces.
After samples were taken at the mines, they were kept in the field
lab until returned to the main laboratory. All samplei *ere accounted
for by the field crew by checking against the field data sheet records
prior to leaving the field location. Photocopies of the data sheets
were made and transported separately from the samples. Upon reaching
the tab, the chain of custody was maintained by Immediately logging 1n
the sample numbers of all samples received. No sample were known to have
been lost through misplacement or inadequate labeling during the entire
study.
Non-filter (aggregate) sample were collected during or immediately
following each stapling period and labeled with identifying information.
The samples were kept tightly wrapped In plastic bags until they were
split and analyzed for moisture consent. Dried samples were then re-
packaged for shipraent to the main laboratories for sieving.
51
-------
analyses performed
Laboratory analyses were performed on particulate samples and on
aggregate samples. All monitoring of source activities and rateoro-
logical conditions was done with on-site measurements and did not result
in the collection of samples for later analysis. The analyses performed
are sunnarized in Table 4-1.
All particulate samples were analyzed in the lab of the by the con-
tractor who took the samples. However, almost all of the aggregate
sample analyses were done in the MRI lab beca-jse of their extensive
past experience with aggregate analyses and to naintain consistency in
methods. Aggregate samples for PEDCo's tests were taken by their field
crew and mo'sture contents wer<; determined in the field lab. Most of the
labeled, dried aggregate samples were then turned over to MRl for all
other analyses.
PEDCo performed all microscopy analyses. Initial'y, microscopy
samples were to be used to deteraine full particle size distributions.
After the canparability study results showed that mtscroscopy data
did not agree with that obtained frois sampling devices that measured
aerodynamic particle sizes, the microscopy work was limited to determination
of largest particles in the plume downwind of sources.
LABORATORY ANALYSIS PROCEDURES
Filters
Particulate staples wsre collected on four different types of f11 tors:
glass fiber. Teflon, polyvinyl chloride (PVC) and cellulose copolytner
(Nilllpore). The procedure for preparing and analyzing glass fiber filters
for high volume air sampling Is fully described In Quality Assurance Handbook
for Mr Pollution Measurement Systs than 50 percent relative
hunldlty In a special weighing roora. The filters were weighed to the
nearest 0.1 mg. The balance was checked at frequent Intervals with
standard weight* to assure accuracy. The filters remained In the same
controlled environment for another 24 hours, after which a second analyst
rewelghed 10 percent of them as a precision check. All the filters In
each set in which check weights varied by more than 3.0 rag frora Initial
weights were rewelghed. After weighing, the filters were packed flat,
alternating with onionskin paper, for shipment to the field.
52
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TABLE 4-1. LABORATORY ANALYSES PERFORMED
Sample
Analysis perfonned
Particulate
Hl-wol fiiter
Weigh, calculate concentration
Exposure profiler filter
Weigh
Settling chamber catch
Filter, dry, weigh
Cyclone precollector catch
Filter, dry, weigh
Cascade iopactor stages
Weigh
Quasi-stack filter
Weign
Settling chasiber catch
Transfer, tfry, weigh
Teflon filter
Weigh, calculate concentration
PVC filter
Weigh
ttillipore filter
Microscopic examination for size
distribution and max size
Oustfill
Filter, dry, weigh
Anqreqate
Raw sod sample
Moisture content
Oried sample
Mechanical sieving
knft«
-------
When exposed filters were returned from the field, they were equili-
brated under the same condn.ons as the initial weighing. They were weighed
and check weighed in the same manner.
Teflon filters from dichotomous samplers were dessicated for 24 hours
over anhydrous calcium sulfate (Driente) before weighing, both before and
after use. The. filters were weighed ir\ same constant temperature and
humidity room as the glass fiber filters. They were weighed to the nearest
0.01 ng and the check weighing had to agree within O.iO -
-------
All filters, both tared and exposed, were weighed to +5 119 with
a 10 percent audit of tared and exposed filters. Audit limits were _^100
yg. Blank values were determined t>y washing "clean" (unexposed) settling
chambers and dustfall buckets m the field and following the above pro-
cedures.
Aggregate Samples
Samples of r
-------
but others were set more stringent than normal requirements. Wo quality
assurance procedures for operating or maintaining dichotomous samplers
had been recommended yet by EPA, so considerable project effort was
expended in developing and testing these procedures.
Meteorological equipment and monitoring procedures are not covered
in Table 4-2. Approved equipment vi*s used and it was operated and
maintained according to manufacturer's instructions. Meteorological
instruments had been calibrated in a laboratory wind tunnel prior to the
field woik.
Adherence to the specified quality assurance procedures was checked
periodically by the Project Officer and other members of the technical
review group, by intercontractor checks, and by external independent audits.
Results of the quality assurance program for flow races and weighing are
sunmarized in Table 4-3. Results of the audits are descrmed in the
following section.
AUDITS
In addition to the rigorous internal quality assurance program and
the review procedures set up with the technical .'eview group, several
independent audits were carried out during this study to further increase
confidence in results. Two different levels of audits were employed:
Intercontractor - HRI audited PEDCo and vice versa
External - Performed by an EPA Instrument or laboratory
expert or a third EPA contractor
The audit activities and results of audits are summarized in Table 4-4.
Although there are no formal pass/fail criteria for audits such as
these, all of the audits except the collocated samplers in the comparabil'ty
study and filter weighings seemed to Indicate that measurements were being
made correctly end accurately. The collocated sampler results are discussed
further In Section 6 and 12. A11 the filters that exceeded allowable
tolerances upon rewelghlng (10 percent of audited filters) lost weight.
In the case of the hi-vol filters, loose material was observed trj the
filter folders and noted on the MRI data sheet. The amounts lost from the
dlchot filters would not be as readily noticeable In the petrl dishes. The
several extra handling steps required for auditing the filters, Including
their transport from Cincinnati to Kansas City, could have caused loss of
material from the filters.
In addition to the external flow calibration audit at the third mine
(shown In Table 4-4), another one was conducted at the second mine. However,
results of this earlier audit were withdrawn by the contractor who performed
56
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TABLE 4-2. QUALITY /.SSURAN^E PROCEDURES FOR MINING EMISSION
FACTOR STUDY
Activity
QA check/requirement
Sampling flow rates
Calibration
Profilers, hi-vols,
and impactors
Calibrate flows in operating ranges using calibration
orif;-e, once at each mine prior to testing.
Uichotomous samplers
Calibrate flows in operating ranges with displaced
volume test meters once at each mine prior to testing.
Single-point checks
Profilers, hi-vols,
and impactors
Check 25% of units with rotameter, calibration orifice,
or electronic calibrator once at each site prior to
testing (different units each time). If any flows
deviate by mo»*e than 7%, check all other units of same
type and recalibrate non-complying units. (See al-
ternative check below).
Oichotomous samplers
Check 25% of units with calibration orifice once at
each site prior to testing (different units each
time). If any flows deviate by more than 5%, check
all other units and recalibrate non-coroplying units.
Alternative
If flows cannot be checked at test site, check all
units every two weeks and recalibrete units which
deviate by more than 7% (5% for dicnots).
Orifice calibration
Calibrate agains-t displaced volume test meter ant-.-ally.
Sampling media
Preparation
Inspect and imprint glass fiber media with ID
numbers.
Inspect and place Teflon media (dichot filters) 1n
petrl dishes labeled with ID numbers.
Conditioning
Equilibrate media for 24 hours in clean controlled
room with relative humidity of less than 50% (varia-
tion of less than *5%) and with temperature between
20°C and 25°C (variation of less than ±3%).
Weighing
Weigh h1-vol filters and impactor substrates to nearest
0.1 eg and weigh dichot filters to nearest 0.01 rag.
(continued)
57
-------
TABLE 4-2 (continued).
Activity
QA check/requirement
Auditing of weights
(tare and final)
Independently verify weights of 7% of filters and
substrates (at least 4 from each batch). Reweigh
batch if weights of any hi-vol filters or substrates
deviate by more than ±3.0 mg or if weights of any
dichot filters deviate by more than rO.l mg.
Correction for
handling effects
Weigh and handle at least one blank for each 10
filters or substrates of each type for each test.
Prevention of
handling losses
Transport dichot filters upright in filter cassettes
placed in protective petri dishes.
Calibrat ion of
balance
Balance to be calibrated once per year by certified
manufacturers representative. Check prior to each
use with laboratory Class S weights.
Sampling equipment
Maintenance
All samplers
Check motors, gaskets, timers, and flow measuring
devices at each mine prior to testing.
Dichotomous samplers
Check and clean inlets and nozzles between nr'nes.
Equipment siting
Separate collocated samplers by 3-10 equipment widths.
Operation
Isokinetic sampling
(profilers only)
Adjust sajnpling intake orientation whenever mean (15
ain average) wind direction changes by more than
30 degrees.
Adjust sampling rate whenever mean (15 min average)
wind speed approaching sampler changes by more than
20%.
Prevention of static
oode deposition
Cap sampler inlets prior to and immediately after
sampling.
Data calculations
Data recording
Use specially designed data forms to assure all nec-
essary data are recorded. All data sheets must be
initialed and dated.
Calculations
Independently verify 10% of calculations of each type.
Recheck all calculations if any value audited deviates
by more ±3%.
58
-------
TABLE 4-3. QUALITY ASSURANCE RESULTS
Activity
QA results
Calibration
Profilers, hi-vols,
and impactors
PEDCo calibrated hi-vols a total of 6 tioes in the 4
visits.
MRI had flow controllers on all 3 types of units
These set flows were calibrated a total of 4 times
for profilers, 7 tines for hi-vols and iirpactors.
Dichotomous samplers
PEDCo and MRI calibrated their 9 dichots a total of 6
times, at least once at each mine visit. Actual flow
rates varied as touch as 9.1% between calibrations.
Single point checks
Profilers, hi-vols,
and impactors
Out of a total of 29 single point checks, only 2
PEDCo hi-vols were found to bo outside the 7%
allowable deviation, thus requiring recalibration.
For MRI, L'O single point checks produced no units
out of compliance.
Dichotomous samplers
The dichotomous samplers were recalibrated with a test
meter each time rather than checking flow with a
calibrated orifice.
Weijjhings
Tare and final
weights
PEDCo reweighed a total of 250 unexposed and exposed
hi-vol filters during the study. Three of the re-
weighings differed by more than 3.0 mg. For 238 dichot
filter reweighings, only four differed by more than
0.1 mg.
MRI reweighed a total of 524 unexposed and exposed
glass fiber filters during the study. Four of the
reweighings differed by more than 3.0 mg. For 43
dichot filter reweighings, only one differed by more
than 0.1 og.
Blank filters
PEDCo analyzed 88 blank hi-vol and 69 blank dichot
filters. The average weight increase was 3.4 mg
(0.087%) for hi-vols, 0.036 mg (0.038%) for dichots.
The highest blanks were 26.3 and 0.22 mg, respectively.
MRI analyzed 67 hi-vol and dichot filter blanks.
The highest blanks were 7.05 mg and 0.52 mg,
respectively.
59
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TABLE 4-4. AUDITS CONDUCTED AND RESULTS
Activity
lnter-
contractoi
or external
audit
Contractor
audited
Date
No and
type of
unlti
Rtsults
ri0»
ta Iibration
I
PEDCo
HRI
PEDCo
8-21-79
8-27-79
10-12-79
2 hl-vol
1 hi-vol
1 fnpactor
2 dichot
2 hi-vot
Each 4% fros cal curve
hi-*ol and impactor wttnin
i\ of curv*. dichot within
n
One within IX. other out
by 12 6X
mi
10-12-79
2 M-vol
1 dichot
Both «UMn 7%
Within SX
E
(EPA. OAQPS)
E
(contractor)
PEDCo
MM
HR!
PEOCo
eEDCo
8-01-79
8-01-79
8-06-80
8-05-80
8-06-80
7 dichot
^ dtcnot
10 ni-vol
S Jfchot
All set 5 to 11* high
One within IX, other ojt
Dy 10X
7 within 5%. 2 within 7%,
one 8 3% from cal curve
Total flows all within St.
2 coarse flows differed
Dy 6.2 and 9 ZZ
Filter
weighing
1
PEDCo
KRI
1-02-80
39 hl-vol
31 dichot
Three hi-vo) filters
varied by asm than 5 0
eg, all tost weight and
loose naterial in folder
was noted four dichots
exceeded the 0 10 ng
tolerance and all lost
weight
Hltert not tudaltted
yet
laboratory
procedures
E
(EPA, EMSI.)
PEOCo
HRI
10-30-79
11-13-79
Coepreh
review
Cospreh
review
Ko probleas found
No probleas found
Collocaud
tsep'tri
I
Both
7-26-79
to 8-09-79
18 hi-vol
10 dichot
Paired hl-vol values
differed by an av of 34%,
IP value* by 35X.
Syttni
audit
E
(£PA. OAQPS)
Both
8-01-79
All
r».;;kaij siting, calibration,
filter handling, end
Mint, procedures. Few
ofnor problems founi but
concluded that operations
should provide reliable
data.
60
-------
It after it was learned that some critical steps, such as the auditee being
present and current calibration curves being provided at the time of the
audit, had not been followed. However, the preliminary results of that
withdrawn audit showed generally acceptable performance of almost all the
sampling equipment.
Some of the calculations of each contractor were repeated by the other
as an audit activity. In general, the data were found to be free of cal-
culation errors, but differences in assumptions and values read from curves
led to frequent differences in T1na1 emission rates. No effort was made to
estimate the average difference in independently calculated emission rates.
,61
-------
SECTION 5
CALCULATION AND DATA ANALYSIS METHODOLOGY
NUMBER OF TESTS PER SOURCE
The study design proposed the number of samples to be collected for
each operation, but these initial numbers were based primarily on avail-
able sanpling time and the relative importance of each operation as a
dust source. Several members of the technical review group requested
a statistical analysis to determine the appropriate number of samples to
be taken.
After sampling data were obtained from the first two mines/three
visits, the total sample size needed to achieve a specified margin of
error and confidence level could be calculated by 'mowing the variability
of the partial data set. This method of estimating required sample size,
in which about half of the preliminarily-estimated sample size is taken
and its standard deviation is used to provide a final estimate of sample
size, is called the two-stage or Stein method. The two-stage method,
along with two preliminary data evaluations, constituted the statistical
plan finally preparer* for the study.
The steps in estimating total sample sizes and remaining samples
1n the statistical plan were:
1. Determine (by source) whether samples taken in different
seasons and/or at different mines were from the same
population. If they were, total sample size could be
calculated directly.
2. Evaluate potential correction factors. If samples were not
from a single distribution, significant correction factors
could bring than into a single distribution. If they were
from populations with the sane mean, correction factors could
reduce the residual standard deviations.
3. Calculate required sample sizes using residual standard
deviations.
4. Calculate remaining samples required to achieve the desired
margin of error and confidence level and recommend the number
of samples for each source to be taken at the third mine.
62
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Two-Stage Method fcr Estimating Sample Size
If samples a^p to be taken from a single normal population, the
required total sample size can be calculated with the following equation
based on the two-stage sampling method (Natrella 1963):
t2S2
n = 1
~3r~ (Eq. 1)
where n = rumber of samples required for first and second stages
combi ned
sj = estimate of population standard deviation ba^ed on ni
samples
t = tabled t-value for risk a and n^-l degrees of freedom
d = margin of error in estimating population mean
The margin of error, d, and the risk, a, that the estimate of the
mean will deviate from the population mean b;y an amount d or greater are
specified by the user. A relative error (d/x) of 25 percent and a risk
level of 20 percent have been specified for the calculations presented
herein based on the intended use for the results, the measurement errors
involved in obtaining the samples, and the accuracy of emission factors
currently being used for other sources. Having specified d (or d/x) and
a, the only additional value needed to calculate n for each source is
the estimate of population standard deviation, sj (or s^/x), based on
the partial sample obtained to date, nj.
Samples from the Same Normal Population
One important restriction on the use of Equation 1, as noted above,
is that samples (from different mines) must be from a single normal
distribution. If average emission rates for a specific source at three
different mines are 2, 10, and 50 lb/ton, and the three samp^s have
relatively low variability, the combined data cannot be assumed to be
normally distributed with a common mean. Regardless of how many samples
were taken at each mine, the data would be trimcdal ly distributed.
Therefore, before Equation l can be used to calculate the total
sample size, a check should be performed to determine whether the avail-
able data from different mines are from populations with the same mean
and variance. If not, the mines would need to be treated separately
and thus require a calculation of required sample size for each mine,
using the analogue of Equation \ (n = number of samples at a single mine).
The total sample size would then be the total of the three sample sizes
calculated for the respective mines.
63
-------
A statistical test can be performed on the data to evaluate whether
two or more sets of samples taken at different mines or in different
seasons are from distributions (populations) having the same means and
variances (Natrella 1963; Halrl 1952).* This test was performed in the
statistical plan and indicated that all sources at the first two mines/
three visits except coal dozers, haul roads, and overburden drills were
from the same populations. Therefore, with the exceptions rioted, total
sample sizes could be determined directly.
Correction Factors
This approach on which this study has heen based is thct the final
emission factors will be mean emission rates with correction factors
attached to adequately account for the wide range of mining and meteoro-
logical conditions over which the emission factors must be applied. The
use of correction factors may affect required sample sizes, in that
correction factors which reduce •"he uncertainty (standard deviation)
in estimating ar, emission factor also reduce the sample size necessary
to attain a desired precision with a specified confidence. Therefore, the
partial data from two mines were analyzpd for significant correction factors
that could reduce the sample standard deviations and thus possibly reduce
required sample sizes. It should be pointed out that some additional
samples are needed to adequately quantify the effect of each correction
factor on the emission factor, so a small reduction in sample size due to
the use of a correction factor would be offset by this need for extra data.
Independent variables thought to be candidates for correction factors
were measured or monitored with each sample of emission rate. The potential
correction factors arp listed in Table 5-1.
The approach for evaluation of correction factors described later in
this section, multiple linear regression, was used to identify sign^icant
correction factors in the partial data set. However, analysis was not
as thorough (e.g., did not include transformations) because it was being
done only to get a slightly better estimate of the optimum sample size.
The independent variables considered and their effects on standard
deviation are summized in Table 5-1. Using appropriate values of s
(standard deviaiton) in Equation 1, the sample sizes consistent with the
previous-discussed relative error of 25 percent and risk level of 20
percent were calculated. These numbers are shown in Table 5-2, which
* Another test, the test for goodness of fit, may be more appropriate
for determining whether data are from a population with a normal
distribution, but it was not used in the original statistical plan.
64
-------
was taken from the statistical plan. Some x and s values in this table
may not agree exactly with values reported later in the results sections
because of minor changes in calculation procedures between the time the
statistical plan (e.g., method of extrapolating to 30jum SP emission rate)
was released and the final report was prepared.
These sample sires were calculated after 2 mines/3 visits, leaving
only one mine visit to obtain all the additional samples. It was not
possible to comolete the sampling requirements specified in Table 5-2
at the third mine within available project resources. Therefore, an
attempt was made to get relative errors for all sources clown to 0.31 and
major sources {naul trucks, scrapers, and draglines) down to 0.25 by
slightly reallocating the number of samples required for several of tre
sources. Table 5-3 compares four different i^ts of sample sizes:
1. Originally proposed in study design.
2. Calculated after 2 mines/3 visits to achieve a relative
error of 25 percent at risk level of 0.20.
3. Proposed 1n statistical plan as feasible totals after
third mine.
4. Actually collected at 3 mines/4 visits.
CALCULATION PROCEDURES
Exposure ProfiHng
To calculate emission rates using the exposure profiling technique,
a conservation of mass approach is used. The passage of airborne parti-
culate, i.e., the quantity of emissions per unit of source activity, is
obtained by spatial integration of distributed measurements of exposure
(mass/area) over the effective cross section of the plume. Th exposure
is the point value of the flux (mass/area-time) of airborne particulate
•Integrated over the time of measurement. The steps in the calculation
procedure are presented in the paragraphs below.
Step 1 Calculate Weights of Collected Sample--
In order to calculate the total weight of particulate matter collected
by a sample, the weights of air filters and of intake wash filters (profiler
Intakes and cyclone precollectors only) are determined before and after
use. The weight change of an unexposed filter (blank) is used to adjust
for the effects of filter handling. The following equation is used to
1 calculate the weight of particulate matter collected.
65
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TABLt 5-1. EVALUATION OF CORRECTION FACTORS WITH PARTIAL DAT- SET
Source/
Potential
Mult.
Relative std
samples
correction factor
R
Significance
deviation
0.838
Overburden
Silt
0.58
0.004
0.699
drilling/23
Depth of hole
0.63
0.161
0.681
% moisture
0.63
0.809
0.697
1.037
Blasting
No. of holes
0.47
0.199
0.977
(coal)/9
X moisture
0.48
0.860
1.C53
1.149
Coal
Bucket capacity
0.39
0.264
1.122
loading/10
0.784
Oozer
Speed
0.61
0.048
0.657
(«vW)/ll
Silt
0.69
0.239
0.636
% moisture
Die
not improve
reg
•ession
0.695
Dozer
Speed
0.84
0.019
0.416
(coal)/7
Silt
Did
not improve
regression
% moisture
Die
not improve
reg
ression
1.446
Dragline/11
Drop distance
0.88
0.000
0.733
% moisture
0.91
0.120
0.662
Bucket capacity
0.92
0. 334
0.659
Operation
0.96
0.048
0.500
Silt
Did
not improve
.
reg
•ession
1.470
Haul
Silt
0.40
0.048
1.377
truck/18
No. of passes
0.46
0.074
1.364
Control
0.47
0.148
1.387
Moisture
0.48
0.258
1.419
Lt.- and med.-
Veh. weight
0.54b
0.280
1.076b
duty
(added to above)
vehicles/6
0.888
Scraper/
Silt
0.15
0.649
0.922
12
% moisture
0.20
0.827
0.961
No. of passes
0.28
0.877
1.000
Grader/5
Not enough data
b Interrelated with drop distance, so not used as a correction factor.
The four variables for haul roads all explained more variance than vehicle
weight, and It did not reduce residual coefficient of variation for com-
bined haul road/access road data set.
66
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TABLE 5-2. CALCULATED SAMPLE SIZES USING TWO-STAGE METHOD
Single
First
a
h
n, per
n.
Source
pop.
est.
nl
~ a
'0.8
sb
X
s/x
mine
total
Drilling
no
40
11
1.38?
From Table 5-1
0.70
15
45
12
1.37?
From Tc
ble 5-1
0.70
15
Blasting
yes
12
9
1.397
18.7
18.0
1.04
34
(coal)
Coal
yes
30
10
1.383
0.031
0.027
1.15
41
loading
Dozer
yes
18
11
1.383
From Ti
ble 5-1
0.66
14
(ovbd)
Dozer
no
18
4
1.638
897b
25.4
0.35
6b
(coal)
3
1.886
3.01
6.54
0.46
12
27
Dragline
yes
18
11
1.383
From Te
ble 5-1
0.73
17
Haul truck
no
30
5
1.533
4.54
9.67
0.47
9
(PEDCo est.)
6
1.476
10.37
19.20
0.54
11
30
Haul truck
no
30
6
1.476
3.99
6.68
0.60
13
IP (MRI est.)
6
1.476
0.62
1.56
0.40
6
29
It - and med.-
yes
15
5
1.533
T.30
2.87
1.15
50
duty vehicles
Scraper
yes
18
1?
1.363
13.99
15.75
0.89
24
Grader
?
9
5
1.533
0.90
1.7
0.53
11
Degrees of freedom (d.f.) for calculating t are n,-l unless there are
correction factors, in which case d f. are reducea by 1 for each correction
. factor.
Smaller sample sizes are required without use of correction factor for
speed.
67
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TABLE 5-3. SAMPLE ilZtS PROPOSED AND OBTAINED
Source
Samples
proposed in
study dsn
Samples
required by
2-stage method
Samples
proposed in
stat plan
Rel. error
for samples
in stat plan
Samples
actually
collected
Dril1 ing
40
45
30
0.20
30
Blasting
(coal)
12
34
16
0.36
1G
Coal
loading
3D
41
24
0.32
25
Dozer
(ovbd)
18
14
16
0.31
15
Dozer
(coal)
18
27
10
0.31
12
Dragline
18
17
19
0.21
19
Paul truck
30
30
40
0.19
36
Lt.- ant! med
duty vehicle.
- 15
s
50
12a
0.45a
12
Scrapers
18
24
24
0.24
15
Graders
9
11
8
0.27
7
a Expected to be combined with haul roads in a single emission factor.
68
-------
Particulate Final Tar Fianl Tare
sample = filter - filter - blank - blank
weight weight weight weight weight
(Eq. 2)
Because of the typically small factions of finds in fugitive dust
plumes and the low sampling rate of the ihchotomous sampler, no weight
gam may be detected on the fine filter of this instrument. This makes
it necessary to estimate a minimum detectable FP concentration corresponding
to fhe minimum weight gain which can be detected by the balance (0.005 mg).
Since tour individual ta^e and final weights produce the particualte
sample weight (Equation 2), the minimum detectable weight on a filter 1s
0.01 mg.
To calculate the minimum FP concentration, the sampling rate (1 m^/h)
and duration of sampling must be taken into account. For example, the
minimum concentration which can be detected for a one-hour sampling period
1s lO/jg/m^. jhe actual sampling time should be used to calculate the
minimum concentration.
Step 2 Calculate Particulate Concentrations--
The concentration of particulate matter measured by a sampler, expressed
in units of micrograms per standard cubic meter (>(jg/scm), is given by the
following equation.
where Cs = particulate concentration, jug/scm
m = particulate samele weight, mg
Qs = sampler flow rate, SCFM
t = duration of sampling, m1n
The coefficient 1n Equation 3 1s simply a conversion factor. To be con
sistent with the National Ambient Air Quality Standard for TSP, all
concentrations are expressed in standard conditions (25°C and 29.92 1n.
of Hg).
The specific particulate matter concentrations are determined from
the various particulate catches as follows:
C,
s
= 3.53 x 104 _m_
qst
(Eq. 3)
TP -
Profiler: filter catch + intake Catch
or
Cyclone/cascade impactor: cyclone catch + substrate
catches + backup filter catch
69
-------
TSP - Hi-vol sampler: filter catch
SP - Calculated: sub-30jum fraction determined by extrapolation
of sub-2.5 and sub-15yum fraction? assuming a
lognormal size distribution
IP - Size-selective inlet: filter catch
Dichotomous sampler: coarse particualte filter catch +
fine particulate filter catch
FP - Dichotcmous sample: fine particle filter catch multiplied
by 1.11
The dichotomous sampler total flow of 1 m3/h is divided into a coarse
particle flow of 0.1 m^/h and a fine particle flow of 0.9 m^/h. The
mass collected on the fine particle filter is adjusted for fine particles
which remain in the air stream destined for the coarse particie filter.
Upwind (background) concentrations of TP or any of the respective
size fractions are substracted from corresponding downwind concentrations
to produce "net" concentrations attributable to the tested source. Upwind
sampling at one height (2.5 meters) did not allow determination of vertical
variations of the upwind concentration. Because the upwind concentration
at 2.5 meters may be greater than at the 4 to 6 meter height of the net
downwind profiling tower, this may cause a downward bias of the net con-
centration. Upwind TP is preferably obtained with an isokinetic sampler,
but should be represented wall by the upwind TSP concentration measured
by a standard hi-vol, If there are not nearby sources that would ' ave a
coarse particle impact on the background station.
Step 3 Calculate Isokinetic Flow Ratios—
The isokinetic flow ratio (IFR) is the ratio of the sampler intake air
speed to the wind speed approaching the sampler. It is given by:
Q Qs
IFR = =
(Eq. 4)
aU aUs
where Q = sampler flow rate, ACFM
Qs » sampler flow rate, SCFM
a = Intake area of sampler, ft^
(J » approaching wind speed, fpm
Us ° approaching wind speed, sfpm
70
-------
IFR is of interest in th« sampling of TP, since isokinetic sampling assures
that particles of all sizes are sampled without bias.
Step a Calculate Downwind Particle Size Distributions--
The downwind particle size distribution of source--contribated parti-
culate matter at a given height may be calculated from net TP, IP, and rp
concentrations at the same height (and distance from the source). Normally,
the TP value from the exposure profiler head would be used, unless a cascade
impactor operates much closer to isokinetic sampling conditions than the
exposure profiler nead.
The proper inlet cut-point of each dichotomous sampler must be determined
based on the mean wind speed at the height of the sampler. The concentration
from a single upwind dichotomous sampler shoulc he adequately representative
of the background contribution to the downwind dichotomous sampler concen-
trations. The reasons are: (a) the background concentration should not
vary appreciably with height; (b) the upwind sampler, which is operated
at an intermediate height, is exposed to a mean wind speed which is within
about 20 percent of the wind speed extremes that correspond to the range
of downwind sampler heights; and (c) errors resulting from the above
conditions are small because of the typically small contribution of back-
ground in comparison to the source plume.
Independent particle size distributions may be determined from a
cascade impactor using the proper 50 percent cutoff diameters for the
cyclone precollector and each impaction stage. Corrections for coarse
particle bounce are recommended.
If it can be shown that the FP and apparent IP fractions of the net TP
concentrations do not va,y significantly with height in the plume, i.e.,
by more than about 10 percent, then the plume can be adequately characterized
by a single particle size distribution. This size distribution is developed
from the dichotomous sampler net concentrations. The fine particle cutpoint
of the dichotomous sampler (2.5/jm) corresponds to the midpoint of the
normally observed bimodel size distribution of atmospheric aerosol. The
coarse mode represents particles produced by a single formation mechanism
and can be expected to consist of particles of lognonmally distributed
size. The best fit lognormal line through the data points (mass fractions
of TP) is determined using a standard linear regression on transformed data
points as described by Reider and Cowherd (1979). This best fit line is
extrapolated or interpolated to determine SP and IP fractions of TP.
Step 5 Calculate Particulate Exposures and Integrate Profiles-
71
-------
For direction samplers operated isokinetically, particulate exposures
may be calculated by the following equation:
E = M = 2.83 x 10-5 CsQst
(Eq. 5)
a
a
+ 3.05 x 10"8 CsUst
(Eq. 6)
where E = particulate mass collected by sampler, mg
M - net particulate mass collected by sampler, mg
a = sar.pler intake area, cm2
Cs = net particulate concentration, ^g/sm^
Us = approacnlng wind speed, sfpm
Qs - sampler flow rate, SCFM
t =» duration of sampling, min
The coefficients of Equations 5 and 6 are conversion factors. Net mass or
concentration refers to that portion which Is attributable to the source
being tested, after subtraction of the contribution from background.
Notii that the above equations may also be written In terms of test
parameters expressed In actual rather than standard conditions. As
mentioned earlier, the MRI profiler heads and warm-wire anemometers
give readings expressed at standard conditions.
The integrated exposure for a given particle size range is found by
numerical Integration of the exposure profile over the height of the plume.
Mathematically, this 1s stated as follows:
H
(Eg. 7)
A °
Edh
0
where A = Integrated exposure, m-mg/cm?
E a part1culate exposure, m-mg/cm2
h = vertical distance coordinate, m
H » effective extent of plume above ground
72-
-------
Physical^, A represents the total passage of airborne particulate matter
downwind of the source, per unit length of line source.
The net exposure must equal zero at the vertical extremes of the pro-
file, i.e., at the ground where the wind velocity equals zero and at the
effective height of the plume where the net concentrations equals zero.
The maximum TP exposure usually occurs below a height of 1 m, so that there
is a sharp decay in TP exposure near the ground. The effective height of
the plume is determined by extrapolation of the two uppermost net TSP
concentrations.
Integration of the portion of the net TP exposure profile that
extends above a height of 1 m is accomplished using Simpson's Rule on
an odd number of equally spaced exposure values. The maximum error in
the integrated exposure resulting from extrapolation above the top sampler
Is estimated to be one-half of the fraction of the plume mass which lies
above the top sampler. The portion of the profile below a height of 1 n
1s adequately depicted as a vertical line representing uniform exposure,
because of the offsetting effects of the usual occurrence of maximum
exposure and the decay to zero exposure at ground level (see Figure 5-1).
Step 6 Calculate Particulate Emission Rates--
The T? emission rate for airborne particulate of a given particle
size range generated by vehicles traveling along a straight-line road
segment, expressed in pounds of emissions per vehicle-mile traveled (VMT),
is given by:
e = 35.5 A (Eq. R)
IT
where e = particulate emission rate, lb/VMT
A = integrated exposure, m-mg/cm2
N = number of vehicle passes, dlmensionless
The coefficient of Equation 8 Is simply a conversion factor. The metric
equivalent emission rate is expressed In kilograms (or grams) of parti-
culate exissions per vehicle-kilometer traveled (VKT).
The SP, IP, and FP emission rates for a given test are calculated by
multiplying the TP emlss.on rate by the respective size fractions obtained
in Step 4.
Dustfall flux decays with distance downwind of the source, and the flux
distribution may be integrated to determine the portion of the TP emission
which settles out near the source. Although this effect has been analyzed 1n
-------
8
7
• Measured Data Point
O Extrapolated Data Point
6
5
4
3
2
0
NET EXPOSURE, mo/cm
Figure 5-1. Illustration of exposure p."0f1le extrapolation
procedures (haul truck run J-9).
7-
-------
previous studies, it is not essential to the reduction of profiling data.
Consequently, no such analysis is being performed in the present study as
part of the profiling calculations.
Upwind-Downwind
The basis for calculation of emission rates in the upwind-downwind
sampling method is conversion of ambient concentration data into corres-
ponding emissio.i rates by use of a Gaussian dispersion equation. Two
different forms of the Gaussian disnersion enuation were used—one for
line source and the other for point sources. In both cases, net downwind
(downwind minus upwind) concentrations were substituted into the equation
along with appropriate meteorological and distance data to calculate
apparent source strengths. The eight to 10 samplers in the downwind array
;esulted in that number of estimates of source strength being produced for
each sampling period.
In an interim technical report, the calculation procedures for the
upwind-downwind n^thod were explained in slightly greater detail than has
beer allocated in this report. A step-by-step calculation procedure was
presented in the Interim report and is summarized below:
1. Determine stability class by method.
2. Calculate Initial plume dispersion, tfy0 and &zo.
3. Determine virtual discance x0.
4. Determine source-to-sampler distances.
5. Calculate plume dispersion (oy and o2) at each downwind
sampling distance.
6. Correct measured concentrations for distance of sampler away
form plume centerllne (for point sources only).
7. Calculate source strength with Gaussian dispersion equation.
8. Convert source strength to an emission rate.
These steps are discussed briefly below.
Step 1 Determine the Stability Class-
Stability class was calculated using the method. A oft value was
determined for each test period by the method described on the following
page. Stability class was then estimated as presented in Table 5-4. An
alternate method oestimating stability, based on wind speed and cloud
cover, always agreed within half a stability class with the org methou value.
75
-------
TABLE 5-4. ofl MFTHOD OF DETERMINING ATMOSPHERIC
B STABILITY CLASS
°e
Stability cTass
17 5 22.5°
<22.5
<17.5
<12.5
A
B
C
0
(<% <7.5° would be E stability, but 0 would be used because all sampling
occurred during daytime and E is only a nighttime stability class).
Source: Mitchell 1979.
Steps 2 through 5 Calculate Plume Dispersion Coefficients (oy and oz)-~
Value of Oy and oz are a function of downwind distance, x, and
stability class. For distances greater that 100 m, Pasquill's dispersion
curves can be used to determine values of oy and o2 (Turner 1970, pp-8-9).
For distances less than 100 m, and the following equations were utilized:
°y » 00 + °y0 (*!• 9)
5 / • 3
02 = a(x + X0)b (Eq. 10)
The variables In Equations 9 and 10 were determined as follows:
cfg - The 00 value 1s the standard deviation of horizontal wind direction
end was obtained ty dividing the wind direction strip chart recording
for the test psriod Into increments of 1 min each, specifying an
average direction each Increment, and calculating the standard
deviation of the resulting set of readings. The upper limit of
-------
Stabi1ity class
a
b
A
B
C
D
0.180
0.145
0.110
0.085
0.945
0.932
0.915
0.870
x0 - The virtual distance term, x0, is used to simulate the effect of
initial vertical plume dispersion. It is estimated from the
initial vertical plume dispersion value, Cz0, which in turn is
the observed initial plume height divided by 2.15 (Turner 1970):
Step 6 Correct Concentrations for Distance of Sampler Away from Plume
Centerline—
The dispersion equations assume that scmpling 1s done along the plume
centerline. For line sources, this is a reasonable assumption because
the enissions occur at ground level and have an initial vertical dispersion
(
-------
Step 7 Calculate Source Strength with Gaussian Dispersion Cquation--
The line source equation was used for haul road, scraper, and some
dozer sources. The equation is:
x = (£q 13)
sin $ \2rt oz u
where x = plume centerline concentration at a distance x down-
wind from the mining source, g/m3
q = line source strength, g/s-m
$ = angle between wind direction and line source
oz = the vertical standard deviation of plume concentra-
tion distribution at the downwind distance x for
the prevailing atmospheric stability, m
u = mean wind speed, m/s
The point source dispersion equation was used in conjunction with
dragline, coal loading, and other dozer operations. This equation is:
The point source dispersion equation was used in conjunction
with dragline, coal loading, and other dozer operations. This
equation is:
X = ^— (Eq. 14)
y z
where Q = point source strength, g/s
a = the horizontal standard deviation of plume concen-
y tration distribution at the downwind distance x for
the prevailing atmospheric stability, m
X, a , u = same as Equation 14
z
Step 8 Convert Source Strength to an Emission Rate--
The calculated values of q were converted to an emission rate per
vehicle (haul roads and scrapers) or per hour. For the per vehicle unit,
the q value 1n g/s-m was divided by the traffic volume during the sampling
period. For the per hour unit, the q value was converted to lb/h at normal
operating spe~d. Similarly, point source Q values were converts to emission
rates per ton of material handled or per hour.
In summary, upwind-downwind emission rates were calculated using either
a point source or line source version of the Gaussian dispersion equation.
The point source equation utilized two additional factors to acccount for
78
-------
inability to sample on the plume centerline in the horizontal and vertical
dimensions. Each sampler produced a separate estimate of emission rate for
the test, so eight to 10 values associated with different downwind distances
were generated for each test.
IP and FP emission rates could have been calculated by using the pro-
cedure described above. However, at any specified point within the plume,
the calculated emission rate is directly proportional to measured con-
centration. Therefore, ratios of measured IP and FP concentrations to TSP
concentrations were calculated for each pair of dichotomous and hi-vol
samplers. The resulting fractions were multiplied by the calculated TSP
emission rate for the corresponding point in the plume to get IP and F°
emission rates.
If particle deposition is significant over the distance of the downwind
sampler array, apparent emission rates should decrease with distance from
the source. Therefore, upwind-downwind sampling provided an implicit
measure of the rate of deposition. In addition, the possible decrease in
apparent emission rat»* with distance meant that the eight to 10 different
values for a test could not simply be averaged to obtain a single emission
rate for the test. The procedure for combining the values is explained
in a following subsection.
Balloon Sampling
This calculation procedure combines concepts used in quasi-stack and
exposure profiling sampling. However, it is less accurate than either of
the^e two methods because the sampling pquipment does not operate at
isokinetic flow rates.
The balloon samplers were preset to a flow rate that was isokinetic
at a wind speed of 5 mph. Since wind speed only approached this speed in
two of the 18 tests, the sampling rates were normally super-isokinetic.
The other two types of equipment in the array, hi-vols and dicnotomous
samplers, sample at a relatively constant air flow. In spite of this
limitation, it was judged that a calculation involving integration of
concentrations would yield better results than could be obtained by using
a dispersion equation.
Step 1 Plot Concentration Data in Horizontal and Vertical Dimensions--
Concentration data from the ground-based hi-vols and balloon-suspended
samplers yield a concentration profile of the plume in both the horizontal
and vertical directions. By combining these profiles with visual observa-
tions and photographs, it was possible to determine the plume boundaries.
Conceptually, the next step was to approximate the volume of air that passed
the sampling array by multiplying the product of wind speed and sampling
duration by the cross-sectional area of the plume. The concept is similar
to the procedures used in the quasi-stack calculations. Quasi-stack
calculations are discussed in the next subsection.
79
-------
The calculation procedure is essentially a graphical integration
technique. Concentrations measured by the ground-level hi-vols (2.5 m
height) were plotted against their horizontal spacing. Bu using visual
observations, photographs taken m the field, and the curve itself, the
profile was extrapolated to zero concentration at both edges of the plume.
The resulting curve was assumed to represent the concentration profile at
ground level and was graphically integrated. This concept is demonstrated
in Figure 5-2.
Step 2 Estimate the Volume Formed by the Two Profiles--
The balloon samplers were suspended at five specific heights of 2.5,
7.6, 15.2, 22.9, and 30.5 m. Since concentrations measured by these
samplers were not directly comparable to those from hi-vols, concentrations
at the four heights about 2.5 m were expressed as ratios of the 2.5 m
concentration. The resulting curve of relative concentration versus
height was extrapolated to a height of zero concentration, as shown in
Figure 5-3. The next step was to multiply each of the ratios by the area
under the ground level concentration profile. This produced an approxima-
tion of the relative integrated concentration at each of the five heights.
By using a trapezoidal approximation technique, an estimate of the volume
formed by tne two profiles was obtained.
Step 3 Calculate the TSP Emission Rate--
The final emission rate calculation was made with the following equation:
E = 60 V(u)t (Eq. 15)
where E = total emissions from blast, mg
V = volume under the two profiles, mg/m
u = wind speed, m/s
t = sampling duration, min
The final result was then converted to lb/blast. This value was recorded as
the TSP emission rate.
The next sti- was to calculate IP and FP emision rates. The unadjusted
IP and FP concen' rations for each dichot were expressed as fractions of their
associated hi-vo* concentrations. Then, the averages of the five unadjusted
IP fractions and the five FP fractions were calculated and the 50 percent
cut point for IP was adjusted to account for the inlet's dependence on wind
speed. A more detailed discussion of the correction for wind speed 1s
presented 1n a later subsection. The resulting fractions were multiplied
by the TSP emission rate and the results reported as IP and FP emission rates.
80
-------
cn
n
o
o
HI-VOL 4
HI-VOL 3
HI-VOL 2
HI-VOL 5
Hi-VOL
s
\
/
^ I I
DISTANCE PERPENDICULAR TO PLUME, m
Figure 5-2. Example ground-level concentration profile.
30.5
22.9 -
ID
x 15.2
7.6 -
2.5 "
x
RELATIVE CONCENTRATION
Figure 5-3. Example vertical concentration profile.
81
-------
The procedure outlined above incorporates a critical assumption
concerning particle :>ize distribution. Due to a lack of particle size
data at each height, the assumption has been made that the fractions of
the concentration less than 15 and 2.5/jm are the sane throughout the
plume as they are at 2.5 m height. Since particle size distribution
measured at ground level was applied to the entire plume, the reported
IP and FP emission rates are Drobably underestimates.
Wind Tunnel
To calculate emission rates frotr wind tunnel data, a conservation of
mass approach is used. The quantity of airborne participate generated by
wind erosion of the test surface equals the quantity leaving the tunnel
minus the quantity (background) entering the tunnel. Calculation steps
are described below.
Step 1 Calculate Weights of Collected Sample--
The samples are all collected on filters. Weights are determined
by subtracting tare weights from final filter weights.
Step 2 Calculate Particulate Concentrat ions--
The concentration of particulate matter measured by a sampler,
expressed in units of micrograms per cubic meter (/jg/m^), is given by
the following equation:
C = 3.53 x 10* ~~ (Eq. 16)
s
where C = particulate concentration, vg/m3
m = particulate sample weight, mg
Q = sampler flow rate, ACFM
5
t = duration of sampling, min
The coefficient in Equation 16 is simply a conversion factor.
The specific particulate matter concentrations determined from the
various sampler catches are as follows:
TP - Cyclone/cascade impactor: cyclone catch + substrate
catches + backup filter
catch
TSP - Hi-Vol sampl-jr: filter catch
82
-------
To be consistent with the National Ambient Air Quality Standard for TSP,
concentrations should be expressed at standard conditions (25° and 2^.92
in. of Hg.).
Tunnel inlet (background) concentrations of TP or any of the respective
particulate size fractions are subtracted from corresponding tunnel exit
concentrations to produce "net" concentrations attributable to the tested
source. The tunnel inlet TP concentration is preferably obtained with an
isokinetic sampler, but should be represented well by the TSP concentration
measured by the modified hi-vol, if there are no nearby sources that would
have a coarse parties impact on the tunnel inlet air.
Step 3 Calculate Tunnel Volume Flow Rate--
During testing, the wind speed profile along the vertical bisector of
the tunnel working section is measured with a standard pitot tube and
included manometer, using the following equation:
u(z) = 6.51 H(2) T
P
where u(z) = wind speed, m/s
H(z) = manometer reading, in. H^O
z = height above test surface, cm
T = tunnel air temperature, °K
P = tunnel air pressure, in. Hg
The values for T and P are equivalent to ambient conditions.
A pitot tube and inclined manometer are also used to measure the center-
line wind speed in the sampling duct, at the point where the sampling probe
is Installed. Because the ratio of the centerline wind speed in the sampling
duct to the centerline wind speed in the test section is independent of flow
rate, it can be used to determine isokinetic sampling conditions for any
flow rate in the tunnel.
The velocity profile near the test surface (tunnel floor) and the walls
of the tunnel is found to follow a logarithmic distribution (Gillette 1978):
u(z) = U*_ In |_ (Eq. 18)
o
where u* = friction velocity, cm/s
zQ = roughness height, cm
83
-------
The roughness height of the test surtace is determined by extra-
polation of the velocity profile near the surface to z=0. Tlie roughness
height for the plexiglas walls and ceiling of the tunnel is 6 x 10" cm.
These velocity profiles are integrated over the cross-sectional area
of the tunnel (30.5 cm x 30.5 cm) to yield the volumetric flow rate
through the tunnel for a particular set of test condition.
Step 4 Calculate Isokinetic Flow Ratio--
The isokinetic flow ratio (IFR) is the ratio of the sampler intake air
speed to the wind speed approaching the sampler. It is given by:
IFR = ?s_ (Eq. 19)
aUs
where Q = sampler flow rate, ACFM
6
a = intake area of sampler, ft2
U = wind spped approaching the sampler, fpm
5
IFR is f interest in the sampling of TP, since isokinetic sampling assures
that d.3 tides of all sizes are sampled without bias.
Step 5 Calculate Downstream Particle Size Distribution--
The downstream particle size distribution of source-contributed parti-
culate rnatter may be calculated from the net TP concentration and the net
concentrations measured by the cyclone and by each cascade impactor stage.
The 50 percent cutoff diameters for the cyclone precollector and each
impaction stage must be adjusted to the sampler flow rate. Corrections
for coarse particle bounce are recom„iended.
Because the particle size cut point of the cyclone is about 11 um,
the determination of suspended particulate (SP, less than 30 um) concen-
tration and IP concentration requires extrapolation of the particle size
distribution to obtain the percentage of TP that consists of SP (or IP). A
lognormal size distribution is used for this extrapolation.
Step 6 Calculate Particulate Emission Rates--
84
-------
The emission rate for airborne particulate of a given particle size
range generated by wind erosion of the test surface is given by:
(Eq. 20)
whore e = particulate emission rate, g/m2-s
Cn = net particulate concentration, g/m3)
Qt = tunnel flow rate, m3/s
A = exposed test area = 0.918m2
Step 7 Calculate Erosion Potential--
If the emission rate is found to decay significantly (by more than
about 20 percent) during back-to-back tests of a given surface at the
same wind speed, due to the presence of non-erodible elements on the
surface, then an additional calculation step must be performed to
determine the erosion potential of the test surface. The erosion
potential is the LOt^l Quantity of erodible particles, in any specified
particle size range, present on the surface (per unit area) prior to
the onset of erosion. Because wind erosion is an avalanching prov.ass,
it is reasonable to assume that the loss rate from the surface if pro-
portional to the amount of erodible material remaining;
where = quantity of erodible material present on the surface
at any time, g/m2
Mq = erosion potential, i.e., quantity of erodible material
present on the surface before the onset of erosion,
g/m2
-kt
(Eq. 21)
k = constant, s"1
t = cumulative erosion time, s
85
-------
Consistent with Equation 21, the erosion potential may be calculated
from the measured losses from the test surface to two erosion times:
L2 = measured loss during t.ime period 0 to t2, g/m2
The loss may be back-calculated as the product of the emission rate from
Equation 20 and the cumulative erosion time.
Quasi-Stack
The source strengths of the drill tests are determined by multiplying
the average particulate concentration in the sampled volume of air by the
total volume of air that passed through the enclosure during the test.
For this calculation procedure, the air passing through the enclosure is
assumed to contain all of the particulate emitted by the source. This
calculation can be expressed as:
where E = source strength, g
X = concentration, g/m3
V = total volume, m3
Step i Determine Particle Size Fractions--
As described in Section 3, isokinetic samplers were used to obtain
total concentration data for the particulate emissions passing through
the enclosure.. Originally, these data were to be related to particle
size, based on the results of microscopic analyses. However, the incon-
sistent results obtained from the comparability tests precluded the use
of this technique for particle sizing. Consequently, the total concen-
tration data were divided into suspended and settleable fractions. The
filter fraction of the concentration was assumed to be suspended parti-
culate and the remainder was assumed to be settleable particulate.
(Eg. 22)
where = measured loss during time period 0 to t^
g/m2
E = XV
(Eq. 23)
86
-------
Step 2 Determine Concentration for Each Sampler--
Rather than traverse the enclosure, as is done in conventional source
testing, four separate profiler samplers were used during each test. These
samplers were spaced at regular intervals alonj the horizontal centerli'p
of the enclosure. Each sampler was set to approximate isokinetic sampling
rate. This rate was determined from the wind velocity measured at each
sampler with a hot-wire anemometer. The wind »elocity was checked at
each sampler every 2 to 3 minutes and the samphno rates were adjuster
as necessary.
Step 3 Calculate volume of Air Sampled by Each Vofiler--
In order to simplify the calculation of source strenqth, it was
assumed that the concentration and wind velocity measured at each sappier
were representative of one-fourth the cross-cectional area of the enclosure.
Thus, the total volume of air associated with each proffer concentration
was calculated as follows:
V± = (a/4)(t) (Eq. 24)
where V = total vclirae of air associated with sampler i, ir.3
= mean velocity measured at sampler i, m/min
a = cross-sectional area of enclosure, m2
t = sampling duration, min
Step 4 Calculate the Total Emissions as Sum of Four Partial Emission Rates-
Separate source strengths, E, are calculated for the total concentration
and the fractioi captured on the filter. The^quation is:
4
E = 1^1 V± Xi (SQ' 25)
These source strengths, in grams, were converted to pounds per hole drilled
ana a'-e reported Section 11.
PARTICLE SIZE CORRECTIONS
Several different size fraction measurements require a mathematical
calculation to correct for some deficiency In the sampling equipment from
ideal size separation. Three of the calculation procedures are described
hera:
87
-------
Correction of cMchotoinoiis samples <"0 15 yum values
Conversion of physical diameters measured microscopically to
equivalent aerodynamic diameters
Correction of cascade impactor data to account fc~ particle
bounce-through.
Correction of Dichotomous Data
Recent research indicates that the collection efficiency of the
dichotomo':s sampler inlet is dependent on wind speed (Wedding 19^0). As
shown in Figure 5-4, the 50 percent cut point that is nominally 15 jurr,
actually varies from 10 to 22 jum over th? rarge of w'nd speeds tested.
The procedure developed in the pressnt study to correct dichot con-
centrations to a 15 um cut point was to:
1. Determine the average wind speed for each test period.
2. Estimate the actual cut point for the sample from Figure 5-4.
3. Calculate nit concentrations for each stage by subtracting
upwind oichot concentrations.
4. Calculate the total concentration less thar the estimated
cut point diameter by summing the net concentrations on the
two stages.
5. Adjust the fine fraction (<2.5jum) concentration by multiplying
by 1.11 to account for fine part'cles that re-nain in the portion
of the air stream that carries the coarse fraction particles.
6. Calculate the ratio of fine fraction to net TSP concentration
and the ratio of total net dichot concentration to net TSP
concentration.
7. Plot (on log-prnbabi 1 ity paper) two data points on a graph of
particle size versus fraction of TSP concentration. The two
points are the fraction less than 2.5 jum and the fraction less
than the cut point determined in step 2.
8. Draw a straight line through the two points and interpolate or
extrapolate the fraction less than 15jum. (Steps 7 and 8 are
a graphical solution that may be replaced by a calculator
program that can perform the linear interpolation or extra-
polation with greater precision.)
88
-------
30
25
or
THEORY
§ 20
O
o
EXPERIMENT
§ 15
o
10
5
40
10
20
30
0
WIND SPEED, km/h
Figure 5-4. Plot of the 50 percent cut point of the inlet
versus wind speed.
89
-------
9. Calculate the net concentration less than 15 ;um from this
fraction and the known net TSP concentration.
A relatively small error is involved in the assumption of a log
linear curve between the two points because the 15 um point is so near
the point for the actual upper limit particle size. The largest un-
certainty in applying this correction is probably the accuracy of the
research data in Figure 5-4.
Conversion of Microscopy Data to Aerodynamic Diameters
Three calculation procedures for converting physical particle diameters
into equivalent aerodynamic diameters were found in the literature (Hesketh
1977; Stockham 1977; and Mercer 1973). One of these was utilized in
calculations in a recent EPA publication, so this procedure was adopted
for the present project (U.S. Environmental Protection Agency 1978b).
The equation relating the two measurements of particle size is:
d = particle physical diameter, pm
p = particle density
C = Cunningham factor
= 1 ~ 0.000621 T/d
T = temperature, °K
Ca = Cunningham correction for dft
This equation requires a trlal-and-error solution because Ca Is a
function of d. The multiple Iterations can be performed by a computer
or calculator program (U.S. Environmental Protection Agency 1978b).
In practice, Ca Is approximately equal to C so the aerodynamic diameter
(da) 1s approximately the physical dlamter (d) times p. An average
particle density of 2.5 was assumed with the microscopy data from this
study, thus yleldirg conversion factors of about 1.58. It 1s questionable
whether the trlal-and-error calculation of Ca in Equation 26 1s warranted
when density values are assumed.
(Eq. 26)
where d = particle aerodynamic diameter, m®
90
-------
Correction of Cascade Impactor Data
To correct for particle bounce-through, MRI has developed a procedure
for adjusting the size distribution data obtained from its cascade
impactors, which are equipped with cyclone precollectors. The true size
distribution (after correction) is assumed to be lognormal as defined
by two data points: the corrected fraction of particulate penetrating
the final impactior stage (less than 0.7 jum) and the fraction of particulate
caught by the cyclone (greater than about 10 jjm). The weight of matt.ial
on the backup stage was replaced (corrected) by the average of weights
caught on the two preceding impaction stages if the backup stage weight
was higher than this average.
Because the particulate matter collected downwind of a fugitive dust
source is produced primarily by a uniform physical generation mechanism,
it was judged reasonable to assume that the size distribution of airborne
particulate smaller than 30/jm is lognormal. This in fact 1s suggested
by the uncorrected particle size distributions previously measured by
MRI.
The isokinetic sampling system for the portable wind tunnel utilizes
the same type of cyclone precollector and cascade Impactor. An identical
particle bounce-through correction procedure was used with this system.
COMBINING RESULTS OF INDIVIDUAL SAMPLES AND TESTS
Combining Samples
In the quasl-stack and exposure profiling sampling methods, multiple
samples were taken across the plume and the measurements were combined
in the calculations to produce a single estimate of emission rate for
each test. However, In the upwind-downwind method, several (eight to
10) Independent estimates of emission rate were generated for a single
sampling period. These Independent estimates were made at different
downwind distances and therefore had differing amounts of deposition
associated with them.
The procedure for combining upwlnd-downwlnd samples was based on
comparison of emission rates as a function of distance. If apparent
emission rates consistently decreased with distance (not more than two
values out of progression fcr a test), the average from the front row
samplers was taken as the initial emission rate and deposition at suc-
ceeding distances was reported as a percent of the initial emission rate.
If apparent emission rates did not have a consistent trend or increased
with distance, then all values were averaged to get an emission rate for
the test and deposition was reported as negligible. Since deposition
cannot be a negative value, Increases in apparent emission rates with
distance were attributed to data scatter, non-Gaussian plume dispersion,
•or Inability to accurately locate the plume centerllne (for point sources).
91
-------
The amount of deposition from the front row to the back row of samplers
is related to th» distance of these samplers from the source, i.e., if
the front samplers are at the edge of the source and back row is 100 m
downwind (this was the standard set-up for line sources), a detectable
reduction in apparent emission rates should result. However, if the
front row is 60 m from the source and back row is 100 m further downwind
(typical set-up for point sources due to safety considerations), the
reduction in apparent emission rates with distance is likely to be less
than the average difference due to data scatter.
These dual methods of obtaining a single estimate of emission rate
for each test introduce an upward bias into the data; high levels on the
front row in general lead to their retention as the final values, while
low levels in general lead to averaging with higher emission rates from
subsequent rows. This bias is thought to be less than the errors that
would result in applying either of these methods universally for the
different deposition situations described above. It should also be
noted that other types of deposition measurements are possible.
Any single estimate more than two standard deviations away from the
average of the remaining samples was considered an outlier and not included
In calculating the average emission rate.
Combining Tests
Emission rates for three particle size ranges were reported for all
tests, along with data on the conditions under which the tests were taken.
These data were first subjected to multiple linear regression (MLR) analysis,
as described below. Of the three size- ranges, only the TSP and IP data were
used in the MLR analysis. This analysis identified significant correction
parameters for each source.
Next, adjusted emission rates were calculated for each test with the
significant correction parameters. From this data set, average emission
rates (base emission factors) and confidence intervals were calculated.
The emission factor equation is this average emission rate times the cor-
rection factors determined from the MLR analysis.
PROCEDURE FOR DEVELOPMENT OF CORRFCTION FACTORS
The method used to evaluate Independent variables for possible use as
correction factors was stepwise MLR. It was available as a compute program
as part of the Statistical Package for the Social Sciences (SPSS). The
MLR program outputs of interest in evaluating the data sets for each source
were the multiple regression coefficient, significance of the variable,
and reduction 1n relative standard deviation due to each variable. The
stepwise MLR technique is described in moderate detail 1n Appendix A.
Further information on it can be found In the following references:
92
-------
Statistical Methods, Fourth Edition (Snedecor 1946); Applied Regression
Analysis (Draper 1965); and SPSS Second Edition (Nie 1975).
Because of the high relative standard deviations (s/3T) for the data
sets and the desire to have correction factors in the emission factor
equations multiplicative rather than additive, all independent and de-
pendent variable data were transformed to natural logarithms before being
entered in the MLR program.
The stepwise regression program first selected the potential correction
factor thdt was the best predictor of TSP emission rate, changed the
dependent variable values to reflect the impact of this independent vari-
able, then repeated this process with remaining potential correction factors
until all had been used in the MlR equation or until no improvements in
the predictive equation was obtained by adding another variable. Not all
variables included in the MLR equation were necessarily selected as cor-
rection factors.
A detailed description of correction factor development procedures
is given in Section 13 of Volume II.
93
-------
SECTION 6
RESULTS OF SIMULTANEOUS EXPOSURE PROFILING ANO
UPWIND-DOWNWINO SAMPLING
The exposure profiling and upwind-downwind samplers were run or a
common source for several tests so that simultaneous measurements by these
methods could be compared. This complex undertaking was essential to
establish that the methods were yielding similar results. Tne simultaneous
sampling, called the comparability study, was performed before any of the
other testing so that any major discrepancies could be resolved or the
study design reevaluated prior to sampling at the second and third mines.
The original intent was to prepare a technical report on the results
of the comparability study and any recommended sampling modifications
for distribution between the first and second mine visits. However, a
series of changes in the method of calculating the suspended particu'ate
fraction of the total profiler catch and the temporary nonavailability of
an EPA-recommended computer program for particle size interpolation
prevented the exposure profiling values from being determined. Preliminary
calculations for six of the 10 tests, presented at a September 13, 1979
meeting of the technical review group after completing the last compara-
bility test on August 9, indicated good agreement between the two methods:
The average ratio for 14 pairs of simultaneous measurements
was reported to be 0.92, with only two of the paired values
differing by more than a factor of 2.0.
Therefore, sampling was conducted as specified in the study design report
at the other twc mines. By the time the calculations for suspended
particulate from profiler tests were finalized, the need for a separate
comparability study report had passed.
DESCRIPTION OF COMPARABILTY STUDY
The two sources selected for testing in the comparability study were
haul roads and scrapers. They are ground-level moving point sources (line
sources) that emit from relatively fixed boundaries, so th<» alternative
sampling inethods are both appropriate and the extensive sampling array could
be located without fear of the source changing locations. Also, haul roads
and scrapers were suspected to be two of the largest fugitive dust emission
sources at most surface coal mines.
94
-------
Five tests of each source were conducted over a 15-day period, fine
additional haul road test was attempted but aborted because ot wind
direction reversal shortly after the beginning of the test. The individual
tests were of about one hour duration. All five tests of each source were
performed at a single site; only two sites and one mine were involved in
the comparability study.
Profiling towers were placed at three distances from the source--5,
20, and 50 m--in order to measure the decrease in particulate flux with
distance, and indirectly the deposition rate. The relatively large dis-
tances of the back profiler from the source created one problem: these two
profilers had to be significantly taller than the first tower because the
vertical extent of the plum? expands with distance from the source. The
towers were fabricated to be 9 and 12 m higi;, respectively, for the 20 and
50 m setbacks.
Hi-vols and dichotomous samplers for the upwind-downwind configuration
were located at the same three downwind distances as the profiling towers.
Two samplers of each type were placen at these distances. In addition,
two hi-vols were located at 100 m downwind of the source.
Duplicate dustfall buckets were placed at the 5, 20, and 50 m distances
to measure deposition rates directly, for comparison with the calculated
plume mass depletion rates from the profiler and upwind-downwind samplers.
Some sampli.ig equipment was also set out to obtain independent particle
size distribution measurements. Cascade impactors were placed at two heights
at 5 m setback and at one height at 20 m. Millipore fiHers for micro-
scopic examination were exposed briefly during each sampling period ac five
different heights (corresponding to profiler sampling head heights) at the
20 m di stance.
Upwind samplers consisted of three hi-vols and a dichotomous sampler,
all located 20 m from the upwind edge of the source. Two of these were
operated by PEDCo as part of the upwir.d downwind array, and the other two
(hi-vols at 1.5 and 2.5 m height) were operated by MR I as the background
samplers at the 5 m downwind distance as parts of their separate arrays,
but which also served as quality assurance checks for the sampling and
equipment.
Finally, wind speed and direction were continuously recorded during
the tests by separate instruments operated by PEDCo and MR I. Profile
samplers on each tower were kept at isokinetic flow rates by frequency
monitoring hot-wire anemometers at the heights of each of the samplers
and adjusting flows to match measured wind speeds. Therefore, wind speeds
from five different locations 1n the sampling array and two wind direction
charts were available for comparison.
95
-------
The sampling configuration used in the comparability study is shown
schematically in Figure 6-1. T^ese sampling periods involved much extra
equipment, so it was-not feasible to use this configuration throughout
the project.
RESULTS OF COMPARABILITY STUDY
Particle Size Data
Particle size data were generated by three different rr ¦ ,hods in the
comparability study: dichotomous sampler, cascade impactor and microscopy.
These three methods all have some shortcomings; corrections to the data
were required in all three cases. The cut pount for the coarse stage of
the dichotomous sampler was adjusted to eliminate the wind speed error
of the inlet design. The batkuo filter weight of the cascade impaccor was
reduced'to correct for particle bounce-through; this weight reduction
averaged 4.2 percent of the total particulate sample for the ten compara-
bility tests shown in Table 6-1. Physical particule sizes measured under
the microscope were converted to equivalent aerodynamic diameters for
comparison with the other stze data. The procedures for these corrections
were described in Section 5.
The particle size data for collocated samplers are presented in Table
6-1. For better visual comparison, the size distributions are also shown
-jraphically in Figures 6-2 and 6-3. In order to reduce the curves on each
graph to a manageable number, the duplicate samples taken by the same
metnod at each distance (see Tabel 6-1) have been averaged to create a
single curv. All of the dichot and impactor curves are straight lines
because they . re based on two data points and an assumption of lognormal
distribution of particles by weight.
Microscopy produced the widest variations between samples—some showed
that less thanlO percent of the particles were sub-30 xm and others showed
all particles in the sample to be less than 15 jum. It was concluded that
the relatively small number of particles counted manually on each filter
(300 to 500) precluded the samples from being representative of the actual
size distribution. This is particularly evident when the number of large
particles counted is considered. Each particle of tO/jm diameter observed
has 6A,n00 times the mass of a 1 ^im particle and 6* times the mass of a
lOxjm particle. Therefore, if two particles larger than 40 ;um are found in
the fields selected, this could result in 30 percent by weight being in
that size range; whereas, a sample with one particlo larger than 40jum
would have only about 17 percent of its weight in that size range. Thus,
one extra large particle shifts the entire distribution by 13 percent in
fiis example.
This evaluation is not an indictment of optical microscopy as a
pa-ticulate assessment technique. In cases where there ire different
96
-------
MR I
PEDCo
HI-VOL
A
A
DICH0T0M0US SAMPLER
o
4%
PROFILER HEAD
-a
-a
CASCADE IMPACTOR
o
DUSTFALL
u
190 m
wo
10 m
Figure 6-1. Sampling configuratlon for comparability studies.
-------
TABLE 6-1. COMPARISON OF PARTICLE SIZE DATA OBTAINED BY DIFFERENT TECHNIQUES
Cumulative percent smaller than stated size
Aero-
dynamic
size
Test pm
At 5 m dist
At
20 m dichot, 2
5 m ht
At 50 m,
2.5 m ht
Dichot
Imoactor
Dichot
Impactor
Micro-
scopy
Dichot
3.0 m
6.0 m
1.5 m
4.5 m
Left
Right
Left
Right
J1 2.5
0.5
1.3
2.2
2.7
0.6
0.6
7.2
a
a
a
5.0
2.1
3.2
4.1
5.4
3.2
4.0
12.3
a
a
a
10.0
6.3
7.3
7-4h
9.8.
11.9
16.0
19-7h
a
a
a
15.0
11.0
11.0
10.0b
13. 5b
21.4
29.1
25. lb
a
a
a
20.0
15.5
14.4
33.2
40.7
a
a
a
30.0
23.7
20.3
44.9
67.8
a
a
a
J2 2.5
1.0
1.2
2.1
19.9
0.8
0.6
1.3
a
4.4
2.8
5.0
1.6
3.3
4.3
35.7
2.1
2.8
2.6
a
8.2
5.5
10.0
2.5
7.8
82h
54.3.
5.0
9.6
49h
a
14.1
10.0
15.0
3.3
12.1
11.5b
65. lb
7.7
17.1
6.8
a
18.7
13.6
20.0
3.9
16.0
10.2
24.2
a
22.4
16 6
30.0
5.0
22.7
14.8
36.4
a
28.3
21.5
J3 2.5
0.7
5.6
5.7
4.6
0.9
0.7
4.7
9.6C
2.0
1.6
5.0
2.3
11.2
11.2
9.1
3.4
4.0
8.6
21.3
5.7
4.9
10.0
6.4
20.1
19.6.
16.3.
10.1
15.0
14.6.
33.4
13.2
12.3
15.0
10.6
26.8
26. lb
21.8b
17.0
26.8
19.2b
44.9
19.9
19.1
20.0
14.6
32.1
23.3
37.3
68.8
25.8
25.2
30.0
21.8
40.3
34.2
53.2
100.0
35.4
35.1
J4 2.5
0.4
1.5
2.7
4.4
2.2
2.2
6.2
<0.1C
3.7
3.7
5.0
1.3
3.2
4.9
8.2
4.6
5.3
11.5
0.2
7.8
7.4
10.0
3.7
6.:
8-4h
14
8.6
11.1
19.2.
0.7
14.6
13.2
15.0
6.1
7.0
11.2b
18.7b
12.0
16.1
24.9b
2.0
20.1
17.9
20.0
8.5
11.4
14.8
20.5
4.4
24.7
21.7
30.0
13.0
15.4
19.7
27.6
8.8
31.9
27.9
J5 2.5
1.8
2.5
6.5
5.5
2.7
3.1
6.6
2.3C
7.8
7.6
5.0
4.3
4.6
11.6
10.0
4.8
7.4
11.9
11.6
13.8
13.3
10.0
9.1
7.8
3.9.1.
16.7.
8.0
15.2
19.7
44.9
22.3
21-4
15.0
13.2
10.4
24.6b
21.8b
10.5
21.7
25.4b
100.0
28.3
27.2
20.0
16.9
12.6
12.5
27.1
33.1
31.7
30.0
23.0
16.1
15.9
35.8
40.3
38.6
J9 2.5
0.9
2.7
2.3
2.7
1.4
1.6
3.2
2.6C
1.8
1.8
5.0
3.0
7.1
4.9
5.3
5.3
8.7
6.7
12.9
6.3
7.0
10.0
8.5
15.6
95h
14.8
28.4
12.4
54.4
16.8
19.7
15.0
13.9
22.9
13.4b
12.8b
24.9
45.5
16.9b
69.7
26.5
31.2
(continued)
98
-------
TABLE 6-1 (continued).
Cumulative percent smaller than stated size
Aero-
dynamic
size
Test pm
At 5 n dist
At 20 m dichot, 2.
5 m ht
At 50 m,
2.5 m ht
Dichot
ImDactor
Pichot
Impactor
Micro-
scopy
Dichot
3.0 m
6.0 m
1.5 m
4.5 m
Left
Right
Left
Right
20.0
19.1
29.0
31.9
58.0
87.6
34.7
40.8
30.0
28.0
38.8
44.7
74.6
100.0
47.5
54.7
J10 2.5
1.2
3.5
7.3
4.7
3.4
1.7
9.8
<0.1C
4.0
2.0
5.0
4.1
11.2
13.0
9.3
14.1
9.9
17.0
0.3
10.0
5.9
10.0
11.2
27.0
21.3.
167h
37.1
32.3
27.0
1.2
20.9
14.0
15.0
18.0
39.8
27.3b
22.4b
53.9
50.6
33.9°
4.2
29.6
21 4
20.0
24.3
49.6
65.8
64.1
6.3
36.7
27.7
30.0
34.7
63.4
80.1
80.1
9.4
47.4
37.9
J12 2.5
1.5
6.8
5.4
13.5
3.5
2.8
11.5
0.8C
3.6
4.5
5.0
4.5
14.1
10.2
22.7
10.0
7.7
IS. 6
19.5
8.9
11.8
10.0
11.1
25.4
17.7.
34.7.
22.6
17.4
30.5
88.7
18.4
24.8
15.0
17.3
33.6
23. 3b
42.6b
32.9
25.6
37.8
100.0
26.2
35.0
20.0
22.8
40.1
41.2
32.5
32.6
43.0
30.0
31.9
49.6
53.0
43.3
42.5
54.3
b20 2.5
0.5
0.4
3.7
3.9
7.7
5.0
5.8
a
2.5
2.9
5.0
2.7
2.2
6.7
7.2
15.5
12.5
S.9
a
7.0
9.3
10.0
10.6
8.9
11.3b
i2.4.
27.2
25.5
16.0b
a
15.9
22.6
15.0
19.6
16.8
14.9b
16.4b
35.7
35.6
20.5b
a
23.6
33.8
20.0
28.2
24.6
42.2
43 5
30.2
42.8
30.0
42.7
33.2
51.2
54.4
40.6
55.6
J21 2.5
0.6
0.4
7.7
9.0
2.8
4.5
10.0
a
8.7
5.4
5.0
2.6
1.4
14.3
16.2
8.3
11.0
18.5
a
17.1
15.2
10.0
8.3
3.8
23.8h
26.4.
19.4
22.4
30.5.
a
29.4
32.6
15.0
14.5
6.2
30.6b
33.5b
28.8
31.3
38.8b
a
38.2
45.6
20.0
20.3
9.1
36.6
38.5
44.7
54.6
30.0
30.7
14.0
48.5
49.2
53.8
67.5
b No data.
Extrapolated from 10 pm and 0.7 pro data.
Extrapolated assuming a lognormal distribution below 5 |jm.
99
-------
100
50
30
20
10
5
2.5
1.0
50
30
2C
10
5
2.5
1.0
50
30
20
10
5
2.5
1.0
TE >T c
**iL
ST
J2
E
TEST v
1ST
J4
i
'J
I-
l
a
TEST ,
v1
1
.1 1 5 20 50 80 95 99 99.9
IMPACTOR DATA, 5 m
20 in
D1CH0T0M0US DATA, 5 m
20 m
50 m
MICROSCOPY DATA, 20 m
.1 1 5 20 50 80 95 99 99.9
PERCENT 8Y WEIGHT SMALLER THAN STATED SIZE
re 6-2. Particle size distributions from comparability tests on scrapers
100
-------
TOO
TEST v
TEST
TEST ,112
TEST .
ST 121
IMPACTOR DATA, 5 m
20 m
DICHOTOMOUS DATA, 5m —
20 m -
50 m •-
MICROSCOPY DATA, 20 m
1 1 5 20 50 80 95 99 99.9
PERCENT BY WEIGHT SMALLER THAN STATED SIZE
Figure 6-3. Particle size distributions from comparability tests on hai.l roads.
101
-------
particle types present and the primary purpose is to semiquantitative^'
estimate the relative amounts, microscopy io usually fhe fcesc analytical
tool a/ailable. However, as a pure particle sizing method, microscopy
appears to be inadeqjai.e compared to available aerodynamic techniques.
In contrast, the dichotomous samplers and cascade impactors produced
fairly consistent size distributions from test to test (as would :>e ex-
pected) and reasonably good agreement between methods. Tiie cascade impactor
data always indicated higher percentages of particles less than 2.5 Air .
but approached the cumulative percentages of the ..ichot method for the
10 to 15 um sizes. This may reveal that the corr-ctions fo i.,ipactor dat?
for particle bouncf-through were r X large enough.
Data from the dichots at 3 and 6 m heights and th* impactors at 1.5
and 4.5 m heights had similar variations in size distribution w'th height.
For both types of samplers, most of the tests (6 out of 10) showed more
large particles on the lower sampler, but several tests showed Tarqer
particles on the upper sampler. This provides evidence that the plume is
still not well formed at the 5 m distance from the source.
Comparison ofsize distributions taken at successive distances from
the sou-ce revealed that the percentage of small particles increased from
5 m samples to 20 m samples in all but two cases out of 20. This finding
is consistent with the premise of fallout of la^ar particlps. However,
reduction in mean particle size was not obvious in the comparison of
corresponding data from 20 m and 50 m; only half the tests showed a further
decrease in average particle size and some actually had larger average
particle sizes.
Th dichotomous samplers appeared to give the most reliable results,
either by comparing the distributions tak_,. at different distances in
the same test or by evaluating the eff. cts of corrections made to the
raw data. As indicated in Section 4, handling problems with the d^chot filter
and light loadings on the fine particle stages prevented this froi being
a completely satisfactory sizing method for the large numbers of samples
generated in the full study. Sampling preci3ion errors resulting from
these factors are quantified in the following subsection. These proulems
are discussed further in Section 12, Volume II.
i The ratios of net fine part culate (less than 2.5 jum) and inhalable
particulate to net TSP arc also sizing measures of interest. These data
for collocated samplers in the comparability study are presented in Table
6-L. Tlie average ratio for all the fine particulate (FP) samples was
0.039, indicating a very low percentage of small particles in the plumes.
As expected, this ratio mcrased with distance from the soiree due tc fallout
of larger particles but not of the fine particles. The average ratios at
5, 20, and 50 m downwind were 0.016, 0.042, and 0.062, respectively.
Inhalable particulate constituted a much larger fraction of TSP--an average
ratio of 0.52. Again, the differential effect of fallout on large particles
10?
-------
was evident. The average 1S/TSP ratios at the three sampling distances were
0.36, 0.48 and 0.73.
Simultaneous Sampling
Samplers located at the same di'lance from the line sources (but not
collected) showed only fair agreement in their measured concentrations.
The average absolute relative difference in the measured TSP values was
17.8 percent; the average (signed) relative difference was 10.fi percent.
The average absolute and signed relative differences at the three distances
were:
Distance Av. diff., % Signed diff..—%
5 25.3 17.7
20 13.5 11-5
50 13.7 2.7
Absolute relative difference for each pair is calculated as the absolute
difference between values divided by the mean of the two values, expressed
as a percent: Absolute rel. diff. = I a-bI
(a+b)/2
xlOO. Signed relative difference employs the same calculations, but the
algebraic rather than absolute difference is used.
For IP and FP, the corresponding average absolute relative differences
were 25.3 and 29.1 percent. Average signed differences were 8.9 and 17.7
percent, respectively. The IP and FP differences at the three sampling
distances were:
Avg. abs Avg. signed
rel. diff, % rel. diff, %
ristance IP FP IP —EE
5 19.4 37.9 3.6 26.9
20 36.6 25.7 30.4 10.1
50 19.9 2j.6 0.1 16.2
These differences provide an estimate of sampling precision, althouqh
they could be attributed partially to actual differences 1n source strength
at various locations along the line source, since the samplers were not
collocated. The larger differences In TSP concentrations at the 5 m distance
iould be due to highly erratic concentrations in the Immediate area of plume
formation. No explanation was found for the large IP differences at the
20 m dlstance.
103
-------
TABLE 6-2. RATIOS OF NET FINE AND 1NHALABLE PARTICULATE
CONCENTRATIONS TO NET TSP CONCENTRATIONS
Test
Downwjnd
distance,
m
Net TSP
cone, fjg/m3
Ratio of FP
(<2.5 pm) to
TSP
Ratio of IP
(<15 pm) to
TSP
Left
Right
Left
Right
Left
Right
Scrapers
J1
5
3,389
4,377
0.01
<0.01
0.34
0.23
20
2,573
3,081
0.01
<0.01
0.28
0.32
50
1,032
1,264
0.01
0.01
0.56
0.29
02
5
10,402
14,174
<0.01
0.01
0.22
0.20
20
4,877
4,997
0.01
0.01
0.13
0.31
50
947
1,107
0.13
0.06
0.50
0.37
J3
5
16,884
21,347
0.G2
0.01
0.48
0.33
20
5,331
-
0.01
-
0.24
-
50
1,542
1,656
0.02
0.01
0.39
0.34
J4
5
2,267
2,529
0.02
0.01
0.20
0.17
20
1,107
1,278
0.01
0.01
0.14
0.19
50
484
462
0.03
0.03
0.35
0.30
J5
5
2,894
5,496
0.02
0.01
0.42
0.22
20
1,767
-
0.01
-
0.07
-
50
417
250
0.03
0.04
0.25
0.40
Haul roads
J9
5
4,736
3,554
0.01
0.01
0.54
0.46
20
1,942
2,957
0.02
0.02
0.52
0.73
50
1,280
1,033
0.01
0.01
0.30
0.49
J10
5
4,579
3,920
0.02
0.01
0.57
0.40
20
2,210
1,946
0.04
<0.01
0.85a
0.88
50
470
485
0.26
0.06
1.92®
l.lld
J12
5
1,757
1,772
0.03
0.01
0.21
0.15
20
1,142
1,188
0.04
0.03
0.35
0.21
50
432
378
•
0.05
0.17
J20
S
1,911
2,883
0.01
0
°.75b
0.45
20
902
1,051
0.28
0.14
1.4 2?
1.26*
50
361
361
0.09
0.13
1.93
3.20
(continued)
104
-------
TABLE 6-2 (continued).
Test
Downwind
distance,
m
Net
cone,
TSP
pg/m3
Ratio of FP
(<2.5 pm) to
TSP
Ratio of IP
(<15 pm) to
TSP
Left
Right
Left
Right
Left
Right
J21
5
4,511
7,114
0.07
0.03
0.45
0.40
20
2,658
3,548
0.04
0.05
0.44
0.36
50
1,076
2,086
0.16
0.04
0.65
0.42
? 13.0 pm cut size rather than 15 pm.
19.0 pm cut size rather than 15 pm.
105
-------
The previous discussion was based entirely on data generated by PEDCo.
Both PEDCo and MRI operated equipment upwind of the sources. Measurements
made by PEDCo and MRI samplers are compared in Table 6-3. The average
absolute relative difference in upwind TSP concentrations was 19.9 percent,
while the average absolute relative difference in measured TSP concentrations
at 5 m downwind was 57.9 percent. These differences appeared to he pri-
marily random, in that some were positive and others were negative and their
signed averages were only 2.5 and 17.6 percent, respectively. The additional
difference above 25.3 percent at 5 m downwind was attributed to such factors
as different flow rates, nonuniform source strength, and slightly offset
sampllng times.
The measured IP concentrations at 5 m downwind had a 48.4 percent
average absolute relative difference, also much higher than the simultaneous
PEDCo IP samples, and the concentrations measured by the two groups had
a systematic bias. PEDCo's values were consistently higher than MRI's.
Both sets of units were calibrated and audited for flow rates, so the
difference was suspected to be in the sample handling procedures, which
were previously noted to be a major problem. Also, different sampling
media were used dun no the comparability study--PEDCo used mesh-backed
Taflon filters and MRI used ringed filters.
The precision of the basic measurement techniques, as evaluated in
side-by-side sampling, do not agree with values used in the error analyses
cited in Section 3, especially at the 5 m sampling distance. The pre-
cision of the hi-vol appears to be +25 percent or more at 5 m from the
source, improving to about +15 percent at greater distances from the
source. The precision of tTTe dichotomous sampler for measuring the IP
fraction appears to average +25 percent or more at all distances. For
the error analysis of exposure profiling, this changes tie random instru-
ment error from 5 percent to at least 25 percent. For upwinu-downwind
sampling, the 18.8 percent estimate for hi-vol sampler measurements would
still be appropriate if it were applied to samples taken at 20 m or more
away from the source.
Comparative Emission Rates
The comparability study was conducted over a 2 week period. The
meteorological, source activity, and soil conditions for each test are
shown 1n Table 6-4. This table Includes all the variables identified
that might influence particulate emission rates.
The most important results of the comparability study, emission rates
from simultaneous testing by exposure profiling and the upwind-downwind
technique, are presented In Tables 6-5 and 6-6. Table 6-5 shows TSP
emission rates and Table 6-6 the inhalable particulate (less than 15^m)
fraction, both in units of lb/VMT.
106
-------
TABLE 6-i CONCENTRATIONS MEASURED AT COLLOCATED SAMPLERS
Measured concentration, pg/m3
Rel
Sampler/
PEDCo
Second
MR I
Second
diff,
location
Test
sampler
PEDCo sampler
sampler
MRI sampler
%t
Hi vol
Upwi nd
J1
235
254
296
+16
J2
13999
13803
14163
-0
J3
8222
3620
10636
-14
J4
184
226
176
+9
J5
344
264
124
-56
J9
285
339
440
+31
J10
1106
1129
913
-8
¦J12
821
1192
1064
+31
J20
1201
1012
1020
-17
J21
1060
780
1009
-17
signed avg
-2.5
absolute avg
19.9
5 m dwn
J1
3661
4649
-
-
J 2
10635
14407
b
-
J3
17117
21580
24230
+22
J4
2457
2719
2194
-16
J5
3130
5732
1599
-94
J9
5108
3926
7188
+46
J10
5668
5009
10057
+62
J12
2122
2137
819
-89
J20
3042
4014
4833
+31
J21
5145
7747
2051
-103
signed avg
-17.6
absolute avg
57.9
Dichet, IP
5 m dwn
J1
1254
1119
1033
-14
J 2
3659
4427
388
-165
J3
9689
8761
5191
-56
J4
724
742
529
-32
J5
1750
2010
1446
-26
J9
2842
1929
1102
-74
J10
2748
1771
1825
-21
J12
801
701
760
+1
J20
2036
2222
1425
-40
J21
2653
3764
1828
-55
signed avg
-48.3
absolute avg
48.4
a Some loose material In filter folder, concentration may be higher,
b Sampler only ran 12 of 34 min, concentration Invalidated,
c See Page 103 for procedure to calculate relative difference.
107
-------
The data in Tables 6-5 and 6-6 were examined for relationships between
sampling methods, sources, and downwind distance. A standard statistical
technique was used to determine whether statistically significant. This
technique, called Analysis of Variance (ANOVA), was available as a computer
program as part of the Statistical Package for the Social Sciences (SPSS).
The basis of ANOVA is the decomposition of sums of squares. The total sum
of squares in the dependent variable is decomposed into independent compo-
nents. The program can bo used to simultaneously determine the effects
of more than one independent variable on the dependent variable. Much has
been written about this technique, so further discussion has not been
included here. Further information on it can te found in many standard
statistical textbooks.
One of the assumptions upon which ANOVA is based is that input data
are normally distributed. The TSP and IP emission rates in Tables 6-5 and
6-6 were both found to be skewed, so ANOVA was also run on the data after
they were transformed to their natural logarithms. The relationships
between emission rates and sampling methods, sources, and downwind distance
were the same for the untransformed and transformed data. Therefore, the
results with untransformed data are presented herein because they relate
directly to the data m Table 6-5 and 6-6.
The outputs from the program are shown Tables 6-7 and 6-8. They consist
of the ANOVA results and a multiple classification analysis (MCA). The
MCA table can be viewed as a method of displaying the ANOVA results.
The data in Table 6-7 sftow that sampling method and downwind distance
are significant variables for both TSP and IP (A = 0.20). Source was not
a significant variable and one of the interrelationships were significant.
Table 6-8 shows the deviation from the total sanple mean for the three
variables. Also shown are deviations after the effects of the other
independent variables are accounted for. The minor changes 1n these
deviations indicate that there are no significant relationships between
variables.
The average percent difference between sampling methods (profiling versus
upwind-downwind) was calculated from the data in Table 6-8 for both TSP
and IP. The resulting differences were 24 and 52 percent, respectively, with
profiling producing the higher values 1n both cases.
Both methods of sampling showed large overall reductions In TSP
emission rates with distance. However, the profiling samples at 5 m did
not fit the pattern of fairly regular reductions displayed at the other
distances and with the upwind-downwind data. In six of ten tests, emission
rates by profiling at 5 m were much lower than the corresponding rates at
20 m. These six pairs of Inverted values were attributed to the systematic
bias documented earlier in this section between PEOCo and MRI inhalable
particulate concentrations, in which PEOCo's values were consistently
108
-------
TABLE 6-4. TEST CONDITIONS FOR COMPARABILITY STUDIES
Test
Oate
Start
time
Sampling
duration,
minutes
Source
characteristics
Soil properties
Meteorological
conditions
Passes
Mean
speed,
mph
Mean
weight,
ton
Silt,
%
Moisture,
%
Temp,
°F
Wind
speed,
m/s
Stab
class
J1
7/28/79
16:49/16:45a
87/84a
63/63a
19
55
8.9
5.7
74/75a
2.8/3.7a
C
J2
7/27/79
13:45/13:40
34/38
18/18
19
58
23.4
2.3
77/79
1.4/3.7
A
J3
7/27/79
16:38/16:33
51/54
35/35
24
59
15.8
4.1
85/89
1.3/2.2
B
J4
7/28/79
11:22/11:06
52/63
25/25
20
40
14.6
1 5
68/83
1.1/1.3
A
05
7/28/79
14:29/14:20
60/62
12/12
18
77
10.6
0.9
85/90
1.4/1.5
A
J9
8/01/79
10:21/10:21
51/59
41/44
19
72
9.4
3.4
83/83
4.8/3.8
8
J10
8/01/79
14:08/14:02
52/47
43/43
19
66
9.4
2.2
88/89
4.4/4.8
C
J12
8/02/79
10:50/10:49
49/49
18/20
15
109
14.2
6.8
80/81
0.8/1.1
A
J20
8/09/79
14:10/14:lv
49/46
23/23
17
138
11.6
8.5
73/73
2.5/2.1
B
J21
8/09/79
16:51/16:52
26/21
13/13
15
121
11.6
8.5
79/79
1.6/2.2
B
a MRI value/PEOCo value.
-------
TABLE 6-5. CALCULATED SUSPENDED PARTICULATE EMISSION RATES
FOR COMPARABILITY TESTS
Test
Downwi nd
distance,
Rl
Emission rate, lb/VMT
Relative
differgnce,
By profiler
By uw-dw
TSP
Total
particulate
<30 pm
fraction
Scrapers
J1
5
41.4
8.6
10.6
+21
20
29.1
15.4
11.4
-30
50
7.8
100
2.4
J2
5
66.5
9.4
18.6
~66
20
59.9
15.9
16.8
+6
50
40.0
8.3
7.2
-14
100
5.3
J3
5
125.0
50.2
35.6
-34
20
52.6
24.5
17.8
-32
50
23.5
0.2
9.8
+18
100
2.2
J4
5
27.5
3.9
5.7
+38
20
22.4
4.8
5.2
t8
50
15.6
4.0
4.0
0
100
2.4
J5
5
96.7
17.7
20.0
+12
20
46.6
11.5
15.6
+30
50
15.2
4.5
5.7
+24
100
1.2
Haul roads
J9
5
51.4
15.2
14.1
-8-
20
35.7
22.5
13.6
-49
50
17.8
8.3
11.1
+29
100
5.1
J10
5
54.1
33.0
12.0
-93
20
20.3
18.5
8.8
-71
50
7.1
3.4
3.2
-6
100
neg
J12
5
16.5
12.9
3.5
-115
20
5.5
1.9
4.4
+79
50
2.0
0.3
2.9
+162
100
0.5
(continued)
110
-------
TABLE 6-5 (continued).
Test
Downwind
distance,
m
Emission rate, lb/VMT
Relative
differgnce,
By profiler
By uw-dw
TSP
Total
particulate
<30 pm
fraction
J20
5
36.6
12.3
6.4
-63
20
31.3
17.7
4.3
-122
50
20.6
10.7
2.8
-117
100
neg
J21
5
76.4
14.2
15.0
+5
20
40.9
19.2
13.8
-33
50
25.0
15.2
12.8
-17
100
8.5
Mean
5
59.2
17.7
14.2
-22
20
34.4
15.2
11.2
-30
50
18.5
7.0
6.8
-3
Std dev
5
33.0
13.8
9.3
(difference
20
16.3
7.2
5.2
signed)
50
10.9
4.5
3.6
a See Page 103 for procedure to calculate relative difference.
Ill
-------
TABLE 6-6. CALCULATED INHALABLE PARTICULATE (<15 pm)
EMISSION RATES FOR COMPARABILITY TESTS
Test
Oownwind
distance,
m
IP emission rate, lb/VMT
Relative
difference,
%c
By profiler
By uw-dw
Scrapers
J1
5
4.2
3.1
-30
20
7.2
3.5
-69
50
3.2
J 2
5
4.0
2.5
-46
20
6.8
2.4
-96
50
5.2
2.0
-89
J3
5
26.1
14.0
-60
20
11.0
4.2
-89
50
4.1
3.6
-13
J4
5
1.7
1.0
-52
20
2.4
0.9
-91
50
2.2
1.3
-51
J5
5
10.0
5.8
-53
20
5.4
1.1
-132
50
2.5
1.4
-56
Haul roads
J9
5
7.4
7.2
-3
20
11.8
8.9
-28
50
3.7
4.4
+17
J10
5
17.7
6.0
-99
20
12.4
7-6a
-49
50
1.8
4.9
~93
J12
5
7,9
0.6
-172
20
1.1
1.2
+9
50
0.2
0.5
+86
020
5
5.4
3.B.
-35
20
12.0
5-7E
-71
50
5.8
7.1
+20
J21
5
6.0
6.3
+5
20
11.4
5.5
-70
50
10.3
6.3
-48
Mean
5
9.0
5.0
-57
20
8.1
4.1
-66
50
4.0
3.5
-13
Sid dev
5
7.4
3.9
(signed
20
4.2
2.8
di fference)
50
2.9
2.2
a This dichotomous sampler value could not be corrected to a 15 um cut point
to reflect the wind speed bias of the sampler inlet. The uncorrected cut
point is about 13.6 um.
b These dichotomous sampler values could not be corrected to a 15 um cut point
to reflect the wind speed bias of the sampler inlet. The uncorrected cut
point Is about 19.0 um
c See Page 103 for procedure to calculate relative difference.
112
-------
TABLE 6-7. ANALYSIS OF VARIANCE RESULTS
TSP BY
METHOD
SOURCE
DIST.
SUN OF
BEAN
SIGNIF
SOURCE OF VARIATION
SQUARES
or
SQUARE
F
OF F
HAIN EFFECTS
994.413
4
248.603
3.563
.012
HETHOIi
117.001
1
119.001
1.717
.196
SOURCE
5?.492
1
57.492
.830
.367
DIST
817.920
2
408.960
5.?02
.005
2-UAY INTERACTIONS
186.270
5
37.254
.538
.747
HETHOI' SOURCE
95.011
1
95.011
1.371
.248
HETHOD DIST
44.826
2
22.413
.323
.725
SOURCE DIST
55.749
2
27.874
.402
.671
3-UAT INTERACTIONS
21.643
2
10.821
.156
.85c
nETHOU SOURCE DIST
21.643
2
10.821
.156
.656
EXPLAINED
1202.326
11
109.302
1.577
.'37
RESIDUAL
3256.810
47
49.294
TOTAL
4459.136
58
76.882
IP BY
METHOD
SOURCE
DIST.
sun of
MEAN
SIGNIF
SOURCE OF VARIATION
SQUARES
DF
SQUARE
F
OF r
MAIN EFFECTS
269.278
4
47.319
3.499
.014
METHOD
129.377
1
129.377
6.724
.013
SOURCE
28.422
1
28.422
1.477
.230
DIST
111.478
2
55.739
2.897
.065
2-UAV INTERACTIONS
76.587
5
15.317
.796
.558
METHOD SOURCE
.825
1
.825
.043
.B37
METHOD DIST
41.533
2
20.767
1.079
.348
SOURCE DIST
33.984
2
16.992
.883
.420
3-UAf INTERACTIONS
1.833
2
.917
.048
.954
HETHDD SOURCE DIST
1.833
2
.917
.048
.954
EXPLAINED
347.697
11
31.609
1.643
.118
RESIDUAL
904.308
47
19.241
TOTAL
1252.005
SB
21.586
113
-------
TABLE 6-8. MULTIPLE CLASSIFICATION ANALYSIS (ANOVA)
ADJUSTED FOR
INDEPENDENTS
•» COVARIATES
DEVN BETA
METHOD
Profiler ' " 1.44 1.37
Uw-dw 2 30 -1.40 -i.33
.16 .16
SOURCE
Scrapers i 2? .98 .91
Haul trucks2 30 -.95 -.86
.11 .10
DIST
5 m 1 20 3.87 3.83
20 m 2 20 1.10 1.06
50 m 3 19 -5.23 -5.15
.43 .43
MULTIPLE ft SQUARED .223
MULTIPLE R .472
TSP BY 6RAND MEAN « 12.08
METHOD
SOURCE
DIST. VARIABLE ~ CATEGORY
ADJUSTED FOR
UNADJUSTED INDEPENDENTS
N DEV'N ETA DEV'N BETA
ADJUSTED FOR
INDEPENDENTS
~ COVARIATES
DEV N BETA
METHOD
Profiler 1 29 1.51 1.46
Uw-dw 2 30 -1.46 -1.41
.32 .31
SOURCE
Scrapers I 29 -.73 -.74
Haul trucks 2 30 .71 .72
.16 .16
DIST
5 TO I 20 1.38 1.37
20 Rl 2 20 .47 .46
50 m 3 19 -1.95 -1.92
.30 .30
MULTIPLE b SQUARED .215
MULTIPLE R .464
IP BY GRAND MEAN = 5.66
METHOD
SOURCE
DIST. VARIABLE ~ CATEGORY
ADJUSTED FOR
UNADJUSTED INDEPENDENTS
N DEV 'N ETA DEV N BETA
114
-------
higher and the average difference was 48.4 percent. MRI generated the
the 5 m profiling data; PFDCo generated the 20 and ^0 m data. This
difference was important because th*> IP and FP concentration data are
used to extrapolate the less than 30 /im fraction in profiling calculation?.
The IP emission data by both sampling methods displayed almost as
much reduction with distance as the TSP data. This is a surprising
finding, in that very little deposition of sub-15jtim particles would be
expected over a 50 m interval.
The reason for the relatively opr comparisons between emiss^n rates
obtained by the two sampling/calculation methods can be traced pr irily
to the precision of the sampling methods. MRI and PEPCo s ilers -cated
at the same distances from the source and operated simultar.ously p'Oduced
TSP concentrations that differed by an average of 58 percent, greater than
the average difference of 24 percent in the resulting TPS emission rates.
Similarly, a 48 percent average difference in IP concentrations explains
much of the 52 percent difference in IP emission rates.
Both methods are entirely dependent on the measured IP and or/TSP
values for calculating emission rates. The accuracy of the methods can
improve on the precision of individual measurements to the extent that
multiple measurements are used in the calculation of a single emission
rate. Both profiling and upwind-downwind techniques as employed in the
comparability study utilized two IP measurements, and upwind-downwind
used two TSP measurement to obtain final emission rates at each distance.
Results from the two sampling methods were compared with each other
rather than a known standard, so it is impossible to establish from the
data which is more accurate. If the error analyses described in Section
3 were revised to reflect the sampling precisions reported above,
exposure profiling would show lower total error levels than uowind-downwind
sampling at the same distance from the source. For the distances
routinely used for the respective methods in the reminder of the field
work, upwind-downwind sampling would have lower indicated total error.
Whichever sampling method is used, it appears from the modified error
analyses that the current state-of-the-art in fugitive dust emission
testing is +25 to 50 percent accuracy.
DEPOSITION RATES BY ALTERNATIVE MEASUREMENT METHODS
Analytical Approaches
Four different approaches for describing the deposition rate for each
test were considered:
1. Reduction 1n apparent emission rate per unit distance
form the source (deposition = dg/dx)
115
-------
2. Reduction in apparent emission rate per unit time
(deposition = -dg/dt); also, this deposition rate
plotted as a function of total travel time away from
source
3. Qustfall measurements at successive distances expressed
as percentages of the calculated total particulate
emission rate
4. Total percent reduction in apparent emission rate over
50 or 100 m compared with percent of emissions greater
than 15 jum diameter (under the assumption that most
large particles settle out and few small ones do)
In the first approach above, deposition rate is the slope of a curve
of TSP or IP emission rate versus distance, applied to either profiling
or upwind-downwind data. Deviations from a smooth, idealized deposition
curve wars magnified by this method of determining the slope of a curve
at different points. With the scatter in the emission data of Tables 6-5
and 6-fi, calculated deposition rates varied tremendously, including many
negative values.
Converting the deposition data to a time rather than distance basis
in the second approach was an attempt to remove the effect of wind speed
variation on deposition r<-tes. The table of time deposition rates and
plot of deposition rate versus total travel time had almost as much
scatter as the data fra.i the first approach. When the deposition rates
were normalized to percents of the initial emission rate for that test,
the data showed a perceptible relationship, as presented in Figure 6-4.
Dustfail, a direct measurment of particle deposition, could not be
equated with the calculated TSP or IP values described above because
dustfail contains deposition of all particle sizes, not just that in the
TSP or IP size range. Net dustfail rates were compared with reductions
in total particulate (TP) emission rates from the 5 m profiler to the
50 m profiler. However, the same scatter noted above in the profiling
data combined with similar scatter in v.he dustfail data obscured any
pattern in deposition rates.
All dustfail measurements were taken by collocated duplicate readings.
The average difference for downwind duplicate measurements in the 10
tests was 40.5 percent, even greater than differences ir. '-oncurrent TSP
and IP measurements. In addition, several (13 out of 57) ot +he net
dustfail readings were negative because the upwind value was higher than
the downwind one. Allowing for the scatter in the data, dustfail rates
appeared to agree better in magnitude with the TSP deposition rates cal-
culated by the first approach than with TP deposition rates.
116
-------
TRAVEL TIME, S
Figure 6-4. Deposition rates as a function of time.
117
-------
The fourth approach evalutated for describing deposition in the
comparability tests was to relate the measured deposition to the percent
of particles in the plume susceptible to deposition. Particles greater
than 15 /tm were assumed to be highly susceptible to deposition, partially
because this fractional value was readily available from the test data.
However, none of the correlations between deposition rates and particles
greater than 15/jm in the plume were found to be significant (at the 0.05
to 0.20 level):
Distance
Size meas. method Ho. tests
5 m Impactor 10 0 29
20 m Imp£Cr>r 10 -0-36
20 m Dichot AU
No reason was identified for these low correlations.
Average Deposition
Although the approaches evaluated above did not provide a usable
relationsmp for estii.
-------
1.2
Legend
1.0
uw-dw
0.8
0.6
0.4
100
80
60
40
20
0
DOWNWIND DISTANCE, m
Figure 6-5. Average measured depletion rates.
119
-------
The input conditions for all three functions were: wind speed = 1.0 m/s,
gravitational settling velocity of monodisperse particles = 0.1 m/s, emission
height = 2.0 m, and stability class as indicated on the figure.
One observation that can be made from the curves, and that would be
more obvious if the curves were extended beyond 200 m, is that much of the
total deposition occurs within this first 200 m. However, these are
theoretical curves a.nd it should not be implied that the field study
measurements at 100 m account for the bulk of deposition or provide, a rough
estimate of fully depleted emission rates. This could only be determined
with actual measurements of deposition at distances of \ km and beyond.
The tilted pluine curve was closest of the three theoretical function1;
to the average deposition rates from the comparability study (plotted in
Figure 6-5). There is no assurance that this function continues to provide
the best fit at distances in the range of 1 to 20 km that are of greatest
concern in dispersion modeling. Not that the tilted plume depletion is not
very dependent on stability class; the test data did not appear to be
closely realted to stability class either.
The depletion factor in thj tilted plume function is given in the
following equation:
QxQo " 1 - 1 tfq. 27)
(l-n/2)(h u/xvd-l) * 2
where n = Sutton's diffusion parameter, which varies by stability class:
A
B
C-D
E-F
ri
UHT
0.26
0.48
0.57
h = emission height, m
u = wind speed, m/s
x = downwind distance, m
V(j ° deposition velocity, 10"^ m/s
The average deposition rates from Figure 6-5 are plotted together with
tilted plume curves representing average test conditions (B stability, u =
2.6 m/s, and h0 = 2.0 m) for four different vj values in Figure 6-7. It was
assumed that v
-------
TABLE 6-9. DEPLETION FACTORS FOR COMPARABILITY TESTS
Test
TSP depletion
factor
IP
depletion
Stabi1ity
class
Wind
speed, m/s
Init. partic.
size
20 m
50 m
100 m
20 m
50 in
% >15 pm
X >3C pm
J1
1.08
0.74
0.23
1.13
1.03
C
3.7
89
78
J2
0.90
0.39
0.28
0.96
0.80
A
3.7
92
86
J3
0.50
0.28
0.06
0.30
0.25
8
2.2
81
69
J4
0.91
0.70
0.42
0.90
1.30
A
1.3
93
86
J5
0.78
0.28
0.06
0.19
0.24
A
1.5
88
60
J9
0.96
0.79
0.36
1.24
0.61
B
3.8
82
67
J10
0.73
0.27
0
1.27
0.82
C
4.8
71
51
J12
1.26
0.83
0.14
2.00
0.83
A
1.1
75
59
J20
0.67
0.44
0
1.25
1.11
B
2.1
82
60
J21
0.*>2
0.85
0.57
0.87
1.00
B
2.2
90
78
121
-------
0.9
o
x
Legend
Source
depletion
A STABILITY
Surface
depletion
1.0
T
T i1 ted
plume
0.8
o
X
0.6
D STABILITY
For all curves
P
T
vg - 0.01 m/s
0.9
o 0.8
Or
X
0.7
v
0.6
F STABILITY
••
•••
0.5
160
40
120
200
80
DOWNWIND DISTANCE, m
Figure 6-6. Depletion rates by theoretical deposition functions.
122
-------
v0, cm/s
D, urn
Test curve best matched
2
5
15
30
16
26
45
63
^uw"dw» IPp
30 ^unip
Actually, deposition rates for small particles onto the ground have
been observed to be greater than can be explained by gravitational
settling velocity, and the concept of a deposition velocity vum
emission rates in 50 m and 79 percent reduction in upwind-
downwind TSP emisiion rates in 100 m. Deposition rates 1n indi-
vidual tests were obscured by data scatter, so an empirical
function could not be developed. However, the average deposition
rates expressed as depletion factors (Qx/Q0) agreed reasonably
well with theoretical deposition functions. Of the three theo-
retical functions examined, the test data appeared to agree best
with the tilted p'ume model (subjective evaluation).
Dustfall data had less precision than the ambient measure-
ments on which the e.nission rate depletion factors were based.
Subsequently evaluation of dustfall data from tests other than the
123
-------
1.2
1.0
0.8
0.6
0.4
0.2
A I ' 1 T
Legend
B Stability
y = 2.6 m/s
hg = 2.0 m
t I I L
0 40 80 120 160 200
DOWNWIND DISTANCE, m
Figure 6-7. Average measured depletion rates compared to
predicted tilted plume depletion.
124
-------
comparability tests showed that this method is reproducible as
long as there are not wind direction reversals during the samplinq
period. A full discussion of dustfall measurement as a method
for quantifying deposition rates is presented in Section 12. A
summary discussion of deposition is incljded in Section 14.
125
-------
SECTION 7
RESULTS FOR SOURCES TESTED BY EXPOSURE PROFILING
SUMMARY OF TEbTS PERFORMED
As previously discussed, exposure profiling was used to test parti-
cualte emissions from haul trucks, light-duty and medium djty vehicles,
scrapers (travel mode) and graders. These sources were tested at three
mines during the period July 1979 through August 1980.
A total of 63 successful exposure profiling tests were conducted
at the three mines/four visits. They were distributed by source and by
mine as follows:
Number of tests
Controlled/
Source uncontrolled Mine 1 Mine 2 Mine 1W Mine 3
Iiaul trucks U 6 6 3 4
C 0 4 0 5
Light- and med.- U 3 4 0 3
duty vehicles C 2 0 0 0
Scrapers U 5 6 2 2
Graders U 0 5 0 2
Light and variable wind conditions were encountered at Mine 1 during
the test period July-August 1979, with winds occasionally reversing and
traffic-generated emissions Impacting on the upwind sampling station.
These events were termed "bad passes."
Table 7-1 lists the site conditions for the exposure profiling tests
of dust emissions generated by haul trucks. The comparability tests are
indicated by an asterisk after the run number. In addition to the
testing of uncontrolled sources, watering of haul roads was tested as a
control measure.
Table 7-2 gives the road and traffic characteristics for the
exposure profiling tests of haul trucks. This source category exhibited
a wide range of road and traffic characteristics, Indicating a good
126
-------
TABLE 7-1. EXPOSURE PROFILING SITE CONDITIONS - HAUL TRUCKS
Prof i le.*
Meteorology
Start
time
Sampling
duration
(min)
Vehicle passes
Temp.
(°c>
Wind
speed
(m/s)
Mine/Site3
Run*1
Date
Good
Bad
Mine 1/Site
2
J-6
7/30/79
16:03
67
?
37
24.5
0.9
J-9*
8/01/79
10:21
51
41
0
28.3
4.8
J-10*
8/01/79
14:08
52
43
2
31.0
4.4
J-lld
8/01/79
17:39
48
40
0
30.5
4.2
J-12*
8/02/79
10:50
49
18
1
26.7
0.8
J-20*
8/09/79
14:10
49
23
0
23.0
2.5
J-21*
8/09/79
16:51
26
13
1
25.0
1.6
Mine 2/Site
1
K-l
Wll/79
10:21
b6
65
0
14.6
6.2
Mine 2/Site
(Watered)
3
K-6
10/15/79
11:03
177
£4
0
17.8
3.4
Mine 2/Site
3
K-7
10/15/79
14:50
53
57
0
23.5
2.6
Mine 2/Site
(Watered)
3
K-8
10/16/79
11:02
105
43
0
10.3
5.7
Mine 2/Site
3
K-9
10/16/79
13:18
89
63
0
12.0
5.0
K-10
10/17/79
10:37
65
«
0
10.6
5.0
!C-11
10/17/79
12:05
64
50
0
12.5
5.2
K-12
10/17/79
13:38
58
43
0
15.5
5.4
Mine 2/Site
(Watered)
3
K-13
10/23/79
10:47
73
78
0
4.0
3.7
Mine 1/Site
5
L-l
12/07/79
14:04
92
57
0
0.7
1.9
(continued)
-------
TABLE 7-1 (continued)
Profiler
Meteorology
Start
time
Sampling
duration
(min)
Vehicle passes
Temp.
(°C)
Wi nd
speed
(m/s)
Mine/Site3
Runb
Date
Good
Bad
Mine 1/Site
6
L-2
12/08/79
13:12
4e
23f
0
12.2
6.9
L-3
12/08/79
13:45
48
26
0
13.2
6.5
L-4
12/08/79
15:04
47
32
0
13.6
6.1
Mine 3/Sitr
1
P-l
7/25/80
16:28
57
15
0
35
3.8
Mine 3/Site
2
P-2
7/26/80
10:25
95
10
2
27
1.8
P-3
7/27/80
9:10
89
18
0
27
3.8
Mine 3/Site
(Watered)
2
P-4
7/28/80
8:41
135
48
0
27
3.7
Mine 3/Site
2
P-5
7/29/80
7:32
108
38
0
32
2.8
Mine 3/Site
(Watered)
2
P-6
7/30/80
7:12
112
48
0
29
2.2
P-7
7/31/80
7:27
95
35
0
29
2.F.
P-8
7/31/80
9:22
103
49
.0
29
3.0
P-9
8/01/80
7:51
142
48
0
27
3.7
a Mine 1/Site 2 - Mine B tipple road (haul road to crusher)
Mine 2/Site 1 - 250m west of haul truck unloading station.
Mine 2/Site 3-1 mile west of haul truck unloading station.
Mine 1/Site 5 - About 100m east of haul road sites for summer testing.
Mine 1/Site 6 - About 250bi northeast of haul road sites for summer testing.
Mine 2/Site 1 - Near Ramp 5 east of lake.
Mine 2/Site 2 - Between Ramps 2 and 3.
b Asterisk Indicates comparability test.
c Value at 3m above the ground, interpolated from 1.5 and 4.5m warm wire anemometer
data using a logarithmic profile,
d MRI comparative equipment run; PE0C0 did not test.
e Represents total time that the profiler ran properly; there was a prior period for
which Isokinetic flows could not be obtained,
f Represents the total number of passes during the attempted run (while the equipment,
other than the profiler, was operating).
128
-------
TABLE 7-2. ROAD AND TRAFFIC CHARACTERISTICS - HAUL TRUCKS
Road surface
properties
Mean
vehicle
speed
(km/h)
Mean
vehicle
weight
(tons)
Mean
No of
vehicle
whee1s
Run
Loading
(g/m2)
Silt
W
Moist.
(*)
Vehicle mix
J-6
7.9a
c -a
5.*»
-
-
-
J-9*
40
9.4
3.4
About 2/3 haul trucks;
rest light duty trucks
31
65
8.0
J-10*
130
9.4
2.2
About 2/3 haul trucks;
rest light duty trucks
31
60
7.7
J-ll
82
8.2
4.2
Mostly unloaded haul
trucks
32
60
9.9
J-12*
235
14.2
6.8
Mostly haul trucks
24
99
9.5
J-20*
330
11.6
8.5
Mostly loaded haul trucks
27
125
10.0
J-21*
330
b
b
Mostly haul trucks
Z'"
110
9.3
K-l
780
7.7
2.2
Combination of heavy and
light duty trucks
53
63
6.1
K-6
354
2.2
7.9
Combination haul trucks
and light duty trucks
56
89
7.4
K-7
361
2.8
0.9
Mostly light duty trucks
55
24
4. S
K-8
329
3.1
1.7
Combination haul trucks
and light duty trucks
58
65
6.3
K-9
470
4.7
1.5
Combination haul trucks
and light duty trucks
47
74
6.7
K-10
290
7.7
2.0
Combination haul trucks
and light duty trucks
58
69
6.6
K-ll
290
8.9
2.0
Combination haul trucks
and light duty trucks
48
73
6.5
K-12
290
11.8
2.3
Combination haul trucks
and light duty trucks
58
95
7.3
(continued)
129
-------
TABLE 7-2 (continued)
Road surface
properties
Mean
vehicle
speed
(km/h)
Mean
vehicle
weight
(tons)
Mean
No. of
vehicle
wheels
Run
Loading
lg/m2)
Silt
(%)
Moist.
(%)
Vehicle mix
K-13
67
1.8
2.7
Combination haul trucks
and light duty trucks
51
64
6.5
K-26
67
b
b
Combination haul trucks
and light duty trucks
51
84
6.8
L-l
450
13.0
7.7
Mostly haul trucks
42
95
8.8
L-2
104
b
b
Mostly haul trucks
39
96
9.8
L-3
550
13.8
4.9
Mostly haul trucks
32
107
9.3
1-4
1410
18.0
5.1
Mostly haul trucks
32
86
8.3
P-l
489
4.7
0.4
Mostly haul trucks
43
79
8.5
P-2
489
4.7
0.4
About 1/2 haul trucks; rest
light/medium vehicles
42
42
7,2
P-3
580
4.1
0.3
Haul trucks
50
94
9.7
P-4
200
2.0
0.3
About 1/2 haul trucks; rest
light/medium vehicles
51
55
7.6
P-5
131
3.1
c
About 1/2 haul trucks; rest
light/medium vehicles
50
47
7.1
P-6
489
2.8
2.9
Mostly light/medium
vehicles
51
25
5.6
P-7
458
2.4
1.5
About 1/2 haul trucks; rest
light/medium vehicles
50
61
7.6
P-8
680
7.7
15.3
About 1/2 haul trucks; rest
light/medium vehicles
47
47
7.5
P-9
438
1.6
20.1
About 1/2 faul trucks; rest
light/medium vehicles
50
58
8.7
aAverage of more than one sample.
bNo sample taken.
cMo1sture below detectable limits.
~Comparability test
130
-------
potential for identifying a:id quantifying correction parameters. Most
tests involved a blend of vehicle types dominated by haul trucks. Silt
and moisture values were determired by laboratory analysis of ,-oad surface
aggregate samples obtained from the test roads. Mean vehicle speeds and
weights are arithmetic averages for the mixes of vehicles which passed
over che test roads during exposure profiling.
Table 7-3 lists the site conditions for tht exposure profiling tests
of dust emissions generated by light- and medium-duty vehicles. In
addition to the testing of uncontrolled roads, the application of calcium
chloride to an access road was tested as a control measure.
Table 7-4 gives the road and traffic conditions for the exposure
piofil.ng tests of light- and medium-duty vehicles. Small variations
1n mean vehicle weight and mean number of vehicle wheels were observed
for this source category. No access roads were available at Mine 2, so
light-duty vehicles were tested at a haul road site.
Table 7-5 lists the site conditions for the exposure profiling tests
of dust emissions generated by scrapers (favel mode). Table 7-6 gives
the road and traffic conditions for the exposure profiling tests of
scrapers. All scrapers tested were four-wheeled vehicles, which excluded
this parameter from consideration as a correction factor.
Table 7-7 lists the site conditions for the exposure profiling tests
of dust emissions generated by graders. Table 7-8 gives the road and
traffic conditions for the exposure profiling tests of graders. All
graders tested were six-wheeled vehicles and weighed 14 tons. Therefore,
mean vehicle weight and rcean number of vehicle wheels were excluded frc*s
consideration as correction factors.
RESULTS
The measured emission rates are shown In Tables 7-9 through 7-12
for haul trucks, light- and medium-duty vehicles, scrapers, and graders,
respectively. In each case, emission rates are given for TP, SP, IP,
and FP.
For certain runs, emission rates could not ba calcolated. For haul
truck L-2, the profiler samples did not maintain a consistent flow rate.
Haul truck run J-6 was not analyzed because of the predominance of bad
passes, the emissions from run J-7, the access road treated with calclun
chloride, were to low to be measured. Scraper run P-15 produced only a
TP emission factor; questionable results from a single dlchotomous sampler
prevented calculation of reliable emission rates for SP, IP, and FP.
131
-------
TABLE 7-3. EXPOSURE PROFILING SITE CONDITIONS - LIGHT AND KDIUH DUTY VEHICLES
Mine'Site3
Profiler
Meteorology
Run
Date
Start
time
Sampling
duration
(lain)
Veh i c1e
passes
Temp.
(°C)
V»indb
speed
(o/s)
Good
Bad
Mine 1/Site 3
J-7
7/31/79
14:09
59
87
17
28.3
1.1
(CaCl,treated)
J-8
7/31/79
15:47
68
95
65
30.0
1.6
Mine 1/Site 4
J-13
8/08/79
11:29
26
59
0
25.5
2.9
J-18
8/08/79
13:43
21
34
0
26.5
3.7
J-19
8/08/79
1^:53
31
70
0
26.8
3. f
Mine 2/Site 2
K-2
10/13/79
12:23
55
150
0
8.3
5 5
K-3
10/13/79
15:21
58
150
0
12.1
4.8
K-4
10/14/79
11:45
67
150
0
16.2
3.1
K-5
10/14/79
13:19
68
150
0
20.4
4.3
Mine 3/Site 3
P-10
8/02/80
Aborted
test
P-ll
8/04/80
13:07
73
100
0
35
5.8
P-12
8/04/80
15:33
60
125
0
35
5.2
P-13
8/04/80
17:14
55
100
0
29
4.2
Mine 1/Site 3 - Mine access road treated with calcium chloride.
Wne 1/Site 4 - County access road.
Mine 2/S1te 2 - 50 a west of haul truck unloading station.
. Mine 3/Site 3 * Hear Ramp 14 north of pit.
Value at 3 q above the ground, interpolated from 1.5 and 4.5 to wans wire
aneroooeter data using a logarithmic profile.
132
-------
TABLE 7-4. ROAD AND TRAFFIC CHARACTERISTICS - LIGHT AND MEDIUM DUTY VEHICLES
Run
Road surface
properties
Vehicle mix
Mean
vehicle
speed
(km/h)
Mean
vehicle
weight
(tons)
Hear
No. of
vehicle
wheels
Loading
(g/m2)
Silt
<*)
rtoist.
<*)
J-7
700
3.0
3.6
Mostly light duty vehicles
40
7
4.2
J-8
700
3.0
3.6
Mostly light duty vehicles
40
3
4.0
J-13
138
10.1
1.0
Light duty vehicles
40
2.2
4.0
J-18
540
8.8
1.1
Light duty vehicles
40
2.0
4.0
J-19
540
8.2
0.9
Light duty vehicles
40
2.3
4.1
K-2
120
4.9
1.6
Light duty vehicles
56
2.3
4.C
K-3
120
4.9
1.6
Light duty vehicles
56
2.4
4.0
K-4
909
5.3
1.7
Light duty vehicles
56
2.4
4.0
K-5
909
5.3
1.7
Light duty vehicles
56
2.4
4.0
P-ll
108
5.5
0.9
Mostly pickups
68
2
4.0
P-12
108
5.5
0.9
Mostly pickups
69
2
4.0
P-13
108
5.5
0.9
Mostly pickups
69
2
4.0
J33
-------
TABLE 7-5. EXPOSURE PROFILING SITE CONDITIONS - SCRAPERS
Source8
Profiler
Meteoroloq/
Run**
Date
Start
time
Sampling
duration
(mi n)
Vehicle
passes
Temp.
(°C)
Wind
speed
(m/s)
Good
Bad
Mine 1/Site 1
J-l*
7/26/79
16:49
87
63d
23.3
2.8
J-2*
7/27/79
13:45
34
18
15e
25.0
1 4
J-3*
7/27/79
16:38
51
35
29.4
1.3
J-4*
7/28/79
11:22
52
25
5
20.0
1.1
J-5*
7/28/79
14.24
60
12
2
29.5
1.4
Mine 2/3ite 4
K-15
10/25/79
11:54
13
6
0
5.0
3.9
K-16
10/26/79
11:07
41
10
0
8.8
2.6
K-17
10/26/79
15:22
18
31
0
12.0
4.0
K-18
10/26/79
15:59
37
30
0
13.1
2.6
K-22
10/29/79
9:08
110
20
0
5.0
3.0
K-23
10/29/79
13:23
43
20
0
6.1
4.6
Mine 1/Site 7
L-5
12/12/79
10:40
14
20
0
3.5
8.6
L-6
12/12/79
11:22
22
15
0
4.2
9.4
Mine 3/Site 4
P-14
8/06/80
Abortec
1 test
P-15
8/08/80
14:02
43
4
1
32
1.6
P-18
8/10/80
16:18
33
18
0
27
3.9
Mine 1/Stte 1 - Temporary scraper road at reclamation site.
Mine 2/Site 4 - 250 a north of north pit area.
Mine 1/Site 7 - About 1 Bile northeast of haul road sites for summer testing.
. Mine 3/Site 4 - 100 a south of pit.
Asterisk indicates comparability test.
Value at 3 0 above the ground, Interpolated froa 1.5 and 4.5 o wartn wire
d aneooseter data using a logarithmic profile.
Represents total passes; pass quality was not recorded.
Combination of oarginat and bad passes.
134
-------
TABLE 7-6. ROAD AND TRAFFIC CHARACTERISTICS - SCRAPERS
Runl
Road surface
properties
Vehicle mix
Mean
vehicle
speed
(km/h)
Mean
vehicle
weight
(tons)
Mean
No. of
vehicle
wheels
Loading
(g/m2)
Silt
(%)
Moist.
(%)
J-l*
121
8.9a
5.7a
Mostly scrapers
31
50
4.1
J-2*
313
23.4a
2.3a
Mostly scrapers
31
53
4.0
J-3*
310
15.8
4.1
Mostly scrapers
39
54
4.1
J-4*
55
14.6a
1.5a
Unloaded scrapers
32
36
4.0
J-5*
310
10.6a
0.9a
Loaded scrapers
29
70
4.0
P-15
b
b
b
Mostly unloaded scrapers0
45
46
4.0
K-16
384
25.2d
6.0
All scrapers
48
64
4.0
K-17
384
25.2d
6.0
Mostly scrapers
37
57
4.1
K-18
384
25.2d
6.0
All scrapers
40
66
4.0
K-22
301
21.6
5.4
All unloaded scrapers
51
45
4.0
K-23
318
24.6
7.8
All scrapers
45
54
4.0
L-5
238
21.0
e
All scraDers
34
53
4.0
L-6
238
21.0
e
All scrapers
32
50
4.0
P-15
f
7.2
1 0
Mostly scrapers
26
42
4.0
P-18
f
7.2
1.0
Scrapers
16
64
4.0
^Average of more than one sample.
hNo sample taken.
JjTest stopped prematurely; scraper drivers quit for lunch.
aAverage silt of Runs K-29 to K-23.
^Unrepresentative sample taken after grader pass; sample not analyzed.
'Sample not analyzed for loading.
9Aster1slc indicates comparability test.
135
-------
TABLE 7-7. EXPOSURE PROFILING SITE CONDITIONS - GRADERS
Profiler
Meteorology
Start
time
Sampling
duration
(min)
Vehicle
passes
Temp.
(°C)
Wind,
speed
(m/s)
Mine/Site3
Run''
Date
Good
Bad
Mine 2/Site 4
K-19
10/27/79
10:24
57
40
0
10.2
5.2
K-20
10/27/79
11:46
59
40
0
13.4
4.5
K-21
10/27/79
13:34
49
40
0
17.4
4.3
Mine 2/5ite 5
K-24
10/30/79
10:16
35
30
0
6.5
4.4
K-25
10/30/79
11:16
39
30
0
7.8
4.6
Mine 3/Site 4
8/10/80
17:45
129
9
0
27
3 5
P-17
8/10/80
13:28
67
15
0
27
1.9
Mne 2/Site 4 - 250 in north of north pit area.
Mine 2/Site 5 - 250 m northwest of haul truck unloading station.
b Mine 3/Site 4 - 100 m south of pit.
Value at 3 m above the ground, interpolated from 1.5 and 4.5 re warm wire
anemometer data using a logarithmic profile.
136
-------
TABLE 7-8. ROAD AND TRAFFIC CHARACTERISTICS - GRADERS
Run
Road surface
properties
Vehicle mix
Mean
vehicle
speed
(km/h)
Mean
vehicle
weight
(tons)
Mean
No. of
vehicle
wheels
Loading
(g/m2)
Silt
<%)
Moist.
(%)
K-19
328
23.1
9.1
All graders
8
14
6.0
K-20
535
29.0
8.8
All graders
10
14
6.0
K-21
495
27.8
7.2
All graders
10
14
6.0
K-24
597
17.6
4.0
Mostly graders
10
13
5.9
K-25
776
24.5
5.4
All graders
10
14
6.0
P-lfi
a
7.2
1.0
Graders
19
14
6.0
P-17
a
7.2
1.0
Graders
16
14
6.0
a Sample not analyzed for loading.
137
-------
TABLE 7-9. TEST RESULTS FOR HAUL TRUCKS
Particulate emission rates
Run8
TP.
lb/VMT
SP,
lb/VMT
IP.
lb/VMT
KP.
lb/VMT
J-9*
51.4
15.2
7.4
0.41
J-10*
54.1
33.0
17.7
0.54
J-11
67.2
30.2
15.4
0.69
J-12"
16.5
12.9
7.9
0.26
J-20*
36.6
12.3
5.4
0.14
J-21*
76.4
14.2
6.0
0.21
K-l
23.2
8.2
3.3
0.05
K-6
8.0
2.2
1.1
0.07
K-7
4.6
3.9
2.5
0.07
K-B
9.2
2.5
1.3
0.10
K-9
13.4
6.4
3.3
0.15
K-10
18.1
4.4
2.3
0.18
K-ll
17.5
4.5
2.3
0.19
K-l 2
24.3
6.0
3.2
0.23
K-13
2.4
0.60
0.40
0.10
K-26
5.7
3.4
1.8
0.06
L-l
7.9
0.71
0.32
0.02
L-2
b
b
b
b
L-3
76.9
67.2
42.1
1.65
L-4
107
73.1
38.1
0.57
(continued)
138
-------
TABLE 7-9 (continued)
Particulate emission rates
Runa
TP,
lb/VMT
SP,
lb/VMT
IP,
lb/VMT
FP.
lb/VMT
P-l
31.4
20.6
14.7
2.88
P-2
45.0
6.3
3.2
0.29
P-3
43.6
24.1
11.5
0.20
P-4
14.0
5.1
2.2
0.05
P-5
34.2
14.1
e-3
0.14
P-6
5.1
1.8
1.0
0.11
P-7
20.5
8.4
4.1
0.16
P-8
14.6
4.3
2.1
0.10
P-9
16.5
5.6
2.5
0.07
^ Asterisk indicates comparability run.
Profiler samplers malfunctioned.
139
-------
TABLE 7-10. TEST RESULTS FOR LIGHT- AND MEDIUM-DUTY VEHICLES
Particulate emission rates
TP,
SP.
IP.
FP.
Run
lb/VMT
lb/VMT
lb/VMT
lb/VMT
J-7
a
a
a
a
J-8
0.55
0.35b
0.34b
0.09b
J-13
7.0
5.5b
4.5b
0.50b
J-18
9.5
8.2b
6.6b
1. 5b
J-19
7.1
6.7b
5.2b
0.22b
K-2
5.0
0.64
0.33
0.03
K-3
3.1
0.76
0.39
0.03
K-4
3.0
o.en
0.34
0.04
K-5
2.7
0.93
0.52
0.05
P-ll
12.6
8.5
4.5
0.10
P-12
12.8
9.0
5.1
0.13
P-13
9.7
7.8
4.1
0.15
. Emissions too low to be measured.
ERC dichotomous samplers.
140
-------
TABLE 7-11. TEST RESULTS FOR SCRAPERS
Particulate
emission rates
Run8
TP.
Id/VMT
SP,
lb/VMT
IP.
lb/VMT
FP.
lb/VMT
J-l*
41.4
8.6
4.2
0.27
J-2*
66.5
9.4
4.0
0.19
J-3*
125
50.2
26.1
1.5
J-4*
27.5
3.9
1.7
0.09
J-5*
96.7
17.7
10.0
1.4
K-15
126
16.2
7.2
0.39
K-16
206
29.2
15.6
1.8
K-17
232
74.3
35.6
1.6
K-18
179
43.0
19.3
0.81
K-22
58.4
10.3
4.8
0.29
K-23
118
24.5
11.1
0.54
L-5
360b
355b
217b
0.72b
1-6
184
163
94.0
1.0
P-15
383
c
c
c
P-18
18.8d
4.0d
«•
a.
0.02d
A
. Asterisk indicates comparability test.
Profiler samplers malfunctioned
0 Only one dichotomous sampler and only four good passes.
Only two profilers operational.
141
-------
TABLE 7-12. TEST RESULTS FOR GRADERS
Particulate emission rates
TP,
SP.
IP.
FP,
Run
Ib/VMT
Ib/VMT
Ib/VMT
lb/VMT
K-19
31.3
4.0
2.3
0.33
K-20
29.0
4.3
1.7
0.46
K-21
22.5
1.3
0.89
0.08
K-24
13.1
3.2
1.9
0.29
K-25
19.5
7.3
4.1
0.38
P-16
53.2
34.0
15.4
0.09
P-17
73.9
8.6
2.9
0.04
-------
The means, standard deviations ,and ranges of SP emission rates for
each source category are shown below:
SP emission rate (lbs/VMT)
Source No. tests Mean Std. dev. Range
Haul trucks
Uncontrolled 19 18.8 20.2 0.71-67.2
Controlled 9 4.88 3.44 0.60- 8.4
Light- and medium-
duty vehicles
Uncontrolled 10 4.16 3.73 0.64- 9.0
Controlled 2 0.35a a a
Scrapers
Uncontrolled 14 57.8 95.3 3.9 -355
Graders
Uncontrolled 7 9.03 11.2 1.8 -34.0
a On one of two tests, the emissions were below detectable limits.
As expected, the SP emission rates for controlled road sources were sub-
stantially lower than for uncontrolled sources. The mean emission rate
for watered haul roads was 26 percent of the mean for uncontrolled haul
roads. For light- and medium-duty vehicles, the mean emission rate for
roads treated with calcium chloride was 8 percent of the mean for uncon-
trolled roads.
Tha average ratios of IP and FP to SP emission rates are:
Average ratio of IP to Average ratio of FP to
Source SP emission rates SP emission rates
Haul trucks 0.50 0.033
Light- and medium-
duty vehicles
Scrapers
Graders
0.63
0.112
0.49
0.026
O.A9
0.055
As indicated, SP emission from light- and medium-duty vehicles contained
a much larger proportion of small particles than did the other source
categories.
143
-------
The measured dustfall rates are shown in T&bles 7-14 through 7-16
for haul trucks, light- and medium-duty vehicles, scrapers, and graders,
respectively.
Flux data from collocated samplers are given for the upwind sampling
location and for three downwind distances. The downwind dustfall flukes
decay sharply with distance from the source.
PROBLEMS ENCOUNTERED
Adverse meteorology created the most frequent difficulties *n
sampling emissions from urpaved roads. Isokinetic sampling cannot be
achieved with the existing profilers when wind speeds are less than
4 mph. Problems of light winds occurred mostly during the summer testing
at Mine 1. In addition, wind direction shifts resulted in source plume
impacts on the upwind samplers on several occasions. These events,
tenned "bad passes," were confined for the most part co summer testing
at Mine 1.
Bad passes were not counted in determining source impact on down-
wind samplers. Measured upwind particualte concentrations were adjusted
to mean observed upwind concentrations for adjoining sampling periods
at the same site when nc bad passes occurred.
Another problem encountered was mining equipment breakdown or
reassignment. On several occasions sampling equipment had been de-
ployed but testing could not be conducted because the mining vehicle
activity scheduled for the test road did not occur.
144
-------
TABLE 7-13. DUSTFALL RATES FOR TESTS OF HAUL TRUCKS
Run
Flux (mg/m2-min. )
Upwind
Downw^ nd
5 K
20 m
50 m
J-6
16
a
6.1
a
17
a
d
a
J-9
4.0
131
29
13
3.9
91
36
6.7
J-10
7.5
126
54
5.2
5.9
126
45
8.9
J-11
3.3
274
75
16
1.9
285
56
27
J-12
0.9
19
8.2
1.4
6.4
14
9.2
3.4
J-20
0.8
31
8.1
10.0
1.2
33
9.1
7.9
J-21
7.1
19
17
2.0
19
22
7.6
30
K-l
2.5
34b
16
8.0
3.5
25
51
17
K-6
0.7
12
3.0
2.9
0.6
12
3.0
4.1
K-7
0.6
12
11
7.2
0.5
16
12
8.0
(C-8
1.6
7.1
8.1
3.7
5.3
14
1.1
3.1
K-9
2.0
21
6.1
5.2
6.6
16
7.0
6.2
K-10
07c
25
25
8.1
0.8
34
18
8.1
K-!l
07c
33
26
8.2
0.8
42
18
8.1
(continued)
145
-------
TABLE 7-13 (continued)
Run
Flux (mg/m2-min.)
Upwind
Downwind
5 m
20 m
50 m
K-12
°"7c
20
24
7.6
0.8
22
16
7.5
K-13
0.3
6.6
1.9
0.6
0.3
d
1.6
d
K-26
0.6
18
2.7
2.3
0.7
24
3.0
2.1
L-l
12
6.2
3.7
0.7
2.4
9.3
7.5
2.5
L-2
t o
5.4
97
27
10
L J
L-4
3.7
61
28
14
P-l
2.8
13
8.6
6.0
3.8
24
6.4
6.6
P-2
28
23
24
18
2.7
20
7.6
d
P-3
e
e
e
e
P-4
2.2
b
3.1
3.6
1.0
4.1
2.2
1.9
P-5
0.7
8.0
4.3
1.2
0.9
3.0
2.7
4.7
P-6
0.4
4.3
4.0
1.4
0.4
2.3
2.2
4.2
P-7
1.5
5.9
1.7
0.8
0.6
2.2
5.7
1.4
P-8
0.3
2.3
0.7
0.6
1.1
1.9
0.6
0.8
P-9
1.1
7.8
0.7
1.4
4.7
3.4
4.1
1.2
a Negative net wsfght when blank was Included,
b At 10a.
c Same buckets used for K-19, K-ll, K-12.
d No final weight,
e Sample not taken.
146
-------
TABLE 7-14. DUSTFAIL RATES FOR TESTS OF LIGHT AND MEDIUM DUTY VEHICLES
Run
Flux (mg/m2-rain.)
Upwind
Downwind
5 m
20 m
50 m
J-7
a
a
a
a
a
a
a
a
J-8
3.8
2.0
0.8b
0.0C
a
a
a
a
J-13
a
23
3.0
5.6
a
30
6.5
2.6
J-18
a
20
0.9
1.2
0.7
20
0.2
1.2
J-19
a
21
3.5
0.7
a
21
4.2
1.0
K-2
0.2
d „
7.7
6.1
0.4
22
6.8
4.2
K-3
0.2
d A
6.0
5.4
3.8
6.8
f
3.7
K-4
0.9
9.8
8.9
2.9
0.4
**
9.3
8.9
K-5
0.9
9.2
8.4
2.8
0.4
14
8.8
8.4
P-ll
0.6
d
8.6
20
0.3
47
4.3
3.5
P-12
f
48
11
8.1
f
130
25
5.7
P-13
r
f
f
f
a Negative net weight when blank was included,
b At 18 b.
c At 35 a.
d Mo final weight,
e At 10 o.
f Sa^>le not taken.
147
-------
TABLE 7-15. DUSTFALL RATES FOR TESTS OF SCRAPERS
Run
Flux (ng/mJ-(nin.)
Upwind
Downwi nd
5 m
20 m
50 m
J-i
4. B
33
8.5
a
3.'
32
8.2
a
J-2
51
26
13
b
54
34
1.3
b
J-3
27
39
b
7.9
7.1
39
2.7
b
J-4
5.8
14
6.4
1.3
6.0
12
6.3
6.5
J-5
2.0
16
3.0
2.0
2.9
12
3.3
1.3
K-15
3.6
84
69
34
3.9
180
24
360
K-16
11
44
16
52
9.2
46
13
52
K-17
4.2
3100
370
40
3.5
2800
490
40
K-18
4.1
860
171
25
3.5
760
140
25
K -22
0.9
39
21
11
1.3
34
30
7.3
K-23
0.9
99
S3
26
1.3
87
74
19
1-5
8.1
200
33
6.2
1-6
8.2
100
69
40
P-15
a
a
a
a
P-18
a
a
a
a
a Samp1® not taken.
b Negative not weight when blank was Included.
C Sanplc Included nondust aaterial.
148
-------
TABLE 7-16. D'JSTFALL RATES FOR TESTS OF GRADERS
Run
Flux (rog/iT2-n)in.)
Upwind
Downwind
5 n
20 si
50 m
K-19
2.5
46
52
28
2.6
75
36
18
K-20
2.6
20
53
28
2.7
25
37
19
K-21
2.6
65
62
34
2.7
56
*3
22
K-24
2.7
64
49
23
4.5
48
40
16
K -2b
2.8
61
46
22
4.7
46
39
15
P-16
a
22
2.9
0.2
a
22
9.8
6.6
P-17
a
21
6.1
6.6
a
27
10
9.9
a Sample not taken.
149
-------
SECTION 8
RESULTS FOR SOURCES TESTED BY UPWIND-DOWNWIND SAMPLING
SUMMARY OF TESTS PERFORMED
Five different sources were tested by tie upwind-downwind method—
coal loading, dozers, draglines, haul roaas, and scrapers. However,
haul roads and scrapers were tested by upwind-downwind sampling only
as part of the comparability study, wU.h the exception of six additional
upwind-downwind haul road tests during the winter sampling period.
Test conditions, net concentrations, and calculated emission rates for
the comparability tests were presented in Section 6. Test conditions
and emission rates for haul road tests are repeated nere for easier
comparison with winter haul road tests, but scraper data are not shown
again. Haul roads were tested by the upwind-downwind method during the
winter when limited operations and poor choices for sampling locations
precluded sampling of dozers or draglines, the two primary choices.
A total of 87 successful upwind-downwind tests were conducted at
teh three mines/four visits. They were distributed by source and by
mine as follows:
Source
Coal loading
Dozer, overburden
Dozer, coal
Draglines
Haul roads
Scrapers
Test conditions for the coal loading tests are summarized In Table
8-1. Correction factors for this source may be difficult to develop:
bucket capacities and silt contents did not vary significantly during
the tests, nor did drop distances (not shown In the table). One
variable not inlcuded in the table Mas type of coal loading equipment.
At the first two mines, shovels were used; at the third mine, front-
end loaders were used.
Mine 1
2
4
4
6
5
5
Number of tests
Mine 2 Mine 1W
8
7
3
5
Mine 3
15
4
5
8
150
-------
1
1
2
2
1
2
3
4
5
6
7
6
3
1
2
3
4
5
6
1
8
9
10
11
12
13
14
15
TABLE 8-1. TEST CONDITIONS FOR COAL LOADING
Date
Start
tima
Samp H rig
duration,
minutes
Source
characteristics
Ho. of
trucks
Ducket
capacity,
yd3
Soil properties
Silt,
%
Moisture,
%
Meteorological
conditions
Temp,
°F
Wind
speed,
m/s
8/11/79
8/11/79
10/16/79
10/16/79
10/16/79
10/16/79
10/18/79
10/18/79
10/18/79
10/30/79
7/26/80
7/26/eO
7/25/80
7/30/80
7/30/80
7/30/80
8/05/80
8/07/80
8/07/80
8/07/80
8/07/80
8/12/80
8/12/80
8/12/80
8/12/80
12:35
13:45
9:45
12:45
16:00
17:00
9:40
12:50
15:30
16:00
8:34
9:26
10:27
10:35
11:50
12:58
10:15
9:17
10.02
12:00
12:48
8:42
10:03
10:42
11:30
43
39
72
80
45
30
42
40
36
35
35
44
24
23
52
65
54
34
46
28
47
22
18
13
22
10
3
4
3
3
2
2
5
2
3
2
4
10
8
2
3
2
3
4
4
2
3
3
17
17
14
14
14
14
14
14
14
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
No
data
No
data
3.6
3.6
3.6
4.2
4.2
4.2
3.9
4.0
4.0
4.0
4.0
3.7
3.7
3.7
3.7
22
22
38
38
38
38
38
38
38
38
11.9
11.9
11.9
18.0
18.0
18.0
12.2
11.1
11.1
11.1
11.1
6.6
6.6
6.6
6.6
87
91
46
55
56
56
50
57
60
38
74
80
82
94
95
95
93
82
83
100
100
79
89
89
89
1.0
1.0
4.3
4.3
2.9
2.6
2.1
4.8
4.9
5.0
1.7
1.0
1.0
1.1
1.1
2.9
1.3
1.0
1.3
1.2
1.9
2.0
1.9
1.8
2.5
-------
Test conditions for dozers are summarized in Tables 8-2 and 8-3 for
dozers working overburden and coal, respectively. These two source
categories exhibited a wide range of operating and soil characteristics
in their tests—speed varied from 2 to 10 mph, silt contents from 3.8 to 15.1
percent, and moisture contents from 2.2 to 22 percent. This indicates a
good potential for correction factors. Also, there is a possibility of
producing a single emission factor for the two dozer operations.
Dragline test conditions are shown in Table 8-4. Bucket sizes for
the different tests were all nearly the same, but large differences in
drop distances (5 to 100 ft), silt contents (4.6 to 14 percent), an-1
moisture contents (0.2 to 16.3 percent) were obtained. One dragline
variatle used in the preliminary data analysis for the statistical plan,
operator skill, was not included in Table 8-4 because it was judged to be
too subjective and of little value as a correction factor for predicting
emissions from draglines. Also, it was not found to be a significant
variab'e 1n the preliminary data analysis.
Test conditions for haul roads tested by upwind-downwind sampling are
summarized in Table 8-5. Most of the te?ts for this source were done by
exposure profiling, so this subset of tests was not analyzed separately
to develop another emission factor. Instead, the calculated emission
rates and test conditions for these tests were combined with the exposure
profiling test data in the data analysis and emission factor development
phase.
RESULTS
The apparent TSP emission rates calculated from the concentrations
at each h1-vol sampler are shown in Tables 8-6 through 8-10 for coal
loading, dozers (overburden), dozers (coal), draglines, and haul roads,
respectively. These reported emission rates have not been adjusted for
any potential correction factors. The individual emission rates are
shown as a function of source-sampler distances in these tables. Distance
Is an important factor 1n the evaluation of deposition.
When the samples were evaluated for deposition as described 1n
Sectior. 5, only 21 out of the 87 upwind-downwind samples (including scrapers)
demonstrated distinct fallout over the three or four distances. The
percentage of tests showing fallout was much higher for sources sampled
as line sources than for sources samples as point sources: 13 out of 25
(52 percent) for line sources compared to 8 out of 62 (12.9 percent) for
point sources.
It was concluded that some problem exists with the point source
dispersion equation because its results rarely indicate
152
-------
TABLE 8-2. TEST CONDITIONS FOR DOZER (OVERBURDEN)
Test
Date
Start
time
Sampling
duration,
minutes
Source
characteristics
Soil
properties
Meteorological
conditions
Speed,
mph
Passes
Silt,
%
Moisture,
%
Temp,
°F
Wind
speed,
m/s
Stab
class
Mine 1
1
8/22/79
13:10
59
4
30
15.1
8.8
79
2.9
B
2
8/22/*9
14:30
63
4
32
15.1
8.8
86
1.8
A
3
8/22/79
16:15
71
2
17
15.1
8.8
79
3.2
B
4
8/23/79
13:25
133
2
33
7.5
8.2
80
2.0
A
Nine 2
1
10/15/79
11:00
46
7
20
4.1
16.8
65
5.0
D
2
10/20/79
12:45
64
7
42
3.8
15.6
44
8.5
D
3
10/23/79
13:00
97
7
52
4.4
15.3
42
4.9
C
4
10/23/79
15:05
54
7
22
4.4
15.3
51
3.2
B
5
10/23/79
16:20
55
7
7
4.4
15.3
52
1.8
C
6
10/27/79
12:50
145
7
82
5.4
13.6
53
3.3
C
7
10/27/79
16:08
55
7
60
5.4
13.6
65
2.7
C
Mine 3
1
7/29/80
8:28
60
2
30
7.0
3.6
78
1.5
A
2
7/29/80
9:54
43
2
21
7.0
3.6
85
1.3
B
3
8/11/80
9:24
49
2
14
6.9
2.2
83
1.1
A
4
8/11/80
12:30
23
2
10
6.9
2.2
85
1.9
8
-------
Test
Mine 1
1
2
3
4
Mine 2
1
2
3
Mine 3
1
2
3
4
5
TABLE 8-3. TEST CONDITIONS FOR DOZER (COAL)
Date
Start
time
Sampling
duration,
minutes
Source
characteristics
Speed,
mph
Passes
No. of
dozers
Soil
properties
Silt,
%
Moisture,
Meteorological
conditions
Temp,
°F
Wind
speed,
m/s
8/18/79
8/18/79
8/18/79
8/18/79
10/26/79
10/26/79
10/26/79
8/10/80
8/10/80
8/10/80
8/10/80
8/10/80
10:15
12:45
13:50
14:50
14:20
15:00
16:08
16:02
16:40
17:25
18:05
18:45
60
46
37
30
25
47
43
15
17
12
18
14
8
8
6
8
7
7
7
8
10
12
5
5
n/a
n/a
n/a
n/a
24
22
26
17
21
19
19
15
2
2
1
1
2
1
1
1
1
1
1
1
8.0
8.0
8.0
8.0
6.0
6.0
6.0
11.3
11.3
11.3
11.3
11.3
20.0
20.0
20.0
20.0
22.0
22.0
22.0
4.0
4.0
4.0
4.0
4.0
83
86
88
85
53
53
54
92
93
95
91
90
1.5
3.4
2.3
2.2
3.6
4.1
2.7
5.7
6.0
5.2
3.8
3.0
-------
1
1
2
3
4
5
6
2
1
2
3
4
5
3
1
2
3
4
5
6
7
8
TABLE 8-4. TEST CONDITIONS FOR DRAGLINES
Date
Start
time
Sampling
duration,
minutes
Source
characteristics
Buckets
Bucket
capacity,
yd3
Drop
dist,
ft
Soil properties
Silt,
%
Moisture,
%
Meteorological
conditions
Temp,
°F
Wind
speed,
m/s
8/08/79
8/08/79
8/08/79
8/17/79
8/17/79
8/17/79
10/13/79
10/13/79
••0/13/79
10/21/79
10/24/79
7/31/80
7/31/80
7/31/80
7/31/80
8/02/80
8/02/80
8/02/80
8/02/80
11:15
14:09
16:40
11:00
14:40
16:00
12:15
14:28
16:00
12:48
14:45
10:19
11:35
12:40
13:28
10:30
11:35
12:34
13:45
49
62
60
44
49
31
68
72
74
52
83
41
53
35
55
29
40
26
55
32
46
44
54
49
5
63
71
66
46
6
30
37
40
22
22
24
18
23
60
60
60
60
60
60
32
32
32
32
32
55
55
55
55
65
65
65
65
10
32
20
28
30
82
40
40
5
10
30
100
60
100
30
10
20
25
25
6.4
6.4
6.4
6.4
6.4
6.4
11.4
11.4
11.4
12.6
5.0
14.0
14.0
14.0
4.6
5.0
5.0
5.0
5.0
8.4
8.4
8.4
8.4
8.4
8.4
15.6
15.6
15.6
16.3
14.9
2.7
2.7
2.7
1.2
0.2
0.2
0.2
0.2
78
83
88
84
86
84
47
52
53
38
54
85
93
94
96
88
88
88
90
2.4
3.1
3.9
2.0
1.0
1.8
4.7
4.1
3.6
.1.9
2.7
1.0
1.9
2.2
2.1
6.2
7.4
4.1
3.6
-------
TABLE 8-5. TEST CONDITIONS FOR HAUL ROADS
Test
Date
Start
time
Sampling
duration,
minutes
Source
characteristics
Soil properties
Meteorological
conditions
Passes
Mean
speed,
mph
Mean
weight,
ton
Silt,
%
Moisture,
X
Temp,
°F
Wi nd
speed,
m/s
Stab
class
Mine 1
J9
8/01/79
10:21
59
44
19
72
9.4
3.4
83
3.8
8
J10
8/01/79
14:02
47
43
19
66
9.4
2.2
89
4.8
C
J12
8/02/79
10:47
49
20
15
109
14.2
6.8
81
1.1
A
020
8/09/79
14:10
46
23
17
138
11.6
8.5
73
2.1
B
J21
8/09/79
16:52
21
13
15
121
11.6
8.5
77
2.2
8
Nine 1W
1
12/04/79
10:54
64
14
64
5.7
0
2
12/08/79
12:40
38
28
24
106
15.9a
5.0a
53
6.2
0
3
12/08/79
13:50
54
24
20
118
13.8
4.9
56
5.8
D
4
12/08/79
15:00
52
31
20
95
18.0
5.1
56
5.4
D
5
12/09/79
9:15
55
20
52
2.0
C
6
12/09/79
10:30
63
22
59
5.0
D
8 Average or other samples this day.
-------
faAJ6SS
-------
TABLE 8-6. APPARENT EMISSION RATES FOR COAL LOADING
High-Volume (30 pm)
Test No.
Apparent emission rates at specified distances,
lb/ton
Distances
from source, m
First
Second
Third
Fourth
Mine 1
1
0.006
0.005
0.005
0.005
0.006
0.008
0.010
0 010
25
50
80
2
0.005
0.004
0.010
0.008
0.010
0.017
O.OiS
0.031
20
45
75
Mine 2
1
0.030
0 057
0.050
0.048
0.034
0 043
0.081
0.045
34
65
131
2
0.043
0.089
0.071
0.121
0.067
a
a
a
65
96
162
3
0.014
0.023
0.019
0.017
0.011
0.017
0.045
0.002
57
82
183
4
0.013
0.018
0.013
0.012
0.010
0.016
0.026
0.012
80
105
206
5
0.005
0.007
0.007
0.008
0 015
0.004
0.013
0.017
0.013
30
62
101
199
6
0.022
0.025
0.039
0.012
0.021
0.013
0.017
0.033
10
28
62
170
7
0.030
0.008
0.011
0.018
0.038
0.012
0.027
10
28
62
170
8
0.005
0.004
0.005
0.004
0.005
0.009
0.010
0.010
30
60
110
Mine 3
1
0.128
0.113
0.168
0.018
0.072
0.088
0.015
0.025
111
132
148
166
2
0.115
0.049
0 008
0.061
0.043
0.053
0.036
0.043
0.055
31
58
96
150
3
0.060
0.067
0.055
0.038
0.035
0.056
0.057
0.051
0 042
29
56
94
148
4
0.005
0.016
0.011
0.012
0.019
0.009
0.010
12
24
31
45
5
0.006
0.005
0.007
0.007
0.013
0.014
0.019
16
27
34
50
6
0.008
0.014
0.010
0.016
0.021
0.015
0.029
16
27
34
50
7
0.005
0.026
a
0.041
0.036
0.056
0. Oi.7
10
20
35
8
0.041
0.051
0.069
0.070
0.079
0.104
60
90
130
9
0.042
0.047
0.059
0.064
0.066
0.070
45
75
115
10
0.194
0.100
0.200
0.133
0.214
0.222
45
65
105
11
0.041
0.029
0.130
0.045
0.191
0.134
29
49
89
12
0.039
0.034
0.049
0.051
0.036
0.077
35
65
95
13
0.364
0.842
0.912
1.271
1.218
1.214
35
65
95
14
0.165
0.282
0.291
0.356
0.352
0.507
35
62
92
15
0.177
0.161
0.131
0.123
0.265
0.267
35
62
92
a Interference from truck traffic.
157
-------
TABlE 8-7. APPARENT EMISSION RATES FOR DOZER (OVERBURDEN)
High-Volume (30 ym)
Tesi No.
Apparent emission rates at specified distances, lb/h
Distances
from source, m
First
Second
Third
Fourth
Mine 1
1
14.3
18.2
11.6
9.0
7.8
10.3
10.5
a
4.5
15
44
78
180
2
12.0
13.0
17.0
17.9
7.9
22.2
15.7
8.9
8.2
20
49
83
185
3
2.5
2.6
2.3
0.8
S.2
1.8
a
2.4
1.5
25
54
88
190
4
3.4
5.5
4.9
1.3
2.3
0.5
a
8.1
13.1
25
52
78
138
Mine 2
1
0.8
0.3
2.0
0.6
6.1
25
56
2
2.1
0.6
a
0.7
3.0
2.4
1.8
5.3
20
46
81
151
3
1.8
2.2
2.3
1.8
2.1
3.7
3.5
3.5
6.3
25
58
100
162
4
3.0
2.9
0.8
0.0
1.9
0.0
0.0
0.0
3.2
25
58
100
162
5
1.6
4.8
0.0
3.6
8.6
17.3
19.8
17.6
25
58
100
162
6
0.8
0.7
0.8
0.4
1.2
2.4
2.7
6
23
53
103
7
1.0
1.5
0.7
1.3
1.5
3.5
0.0
1.0
31
66
90
146
Hine 3
1
4.5
5.2
4.6
5.5
8.0
3.8
7.0
8.8
4.a
25
45
75
lib
2
2.5
4.8
5.0
4.3
5.0
6.4
4.9
5.0
6.3
20
40
70
110
3
21.0
14.9
18.0
17.8
14.4
16.7
25
41
63
4
25.9
20.1
15.9
17.7
23.9
43
59
81
A
Used as upwind concentration.
158
-------
TABLE 8-8. APPARENT EMISSION RATES FOR DOZER (COAL)
High-Volume (30 p1*)
Test No.
Apparent enission rates at specified distances, Ib/h
Ofstances
from source,
ro
First
Second
Third
Fourth
Mine 1
1
13.4
16.7
12.1
15.4
20.1
16.8
14.1
23.5
20.4
125
155
193
292
2
47.1
34.9
40.9
34.3
23.1
34.8
50.8
37.9
a
125
15b
193
292
3
8.3
38.5
12.1
12.5
19.0
b
31.2
45.0
11.6
125
155
193
292
4
11.9
22.0
16.5
25.0
30.8
b
18.4
4G.8
24.3
125
155
193
292
Kin* 2
1
9.7
8.0
10.4
8.6
6.4
11-5
13.4
30
42
53
2
3.0
5.8
5.2
6.6
8.4
4.6
9.5
40
67
78
3
l.G
2.5
3.8
3.4
4.2
1.0
4.4
40
67
78
Nine 3
1
281
284
303
229
340
283
300
30
60
91
133
2
298
234
217
153
164
217
250
242
30
60
91
133
3
300
453
533
427
540
540
526
670
30
60
91
133
4
255
255
324
368
306
414
366
293
30
60
91
133
5
160
152
243
193
239
245
300
261
30
60
91
133
? Less then upwind concentration.
Used as upwind concentration.
-------
TABLE 8-9. APPARENT EMISSION RATES FOR DRAGLINE
High-Volume (30 fjra)
Test No.
Apparent emission rates at specified distances,
lb/yd3
Distances
from source, m
First
Second
Third
Fourth
Mine 1
1
0.023
0.023
0.023
0.021
0.021
0.023
0.028
0.039
0.028
60
90
130
220
2
0.009
0.010
0.021
0.022
0.023
0.050
0 043
0.054
0.068
20
50
90
180
3
0.003
0.005
0.001
0.007
0.003
0.0C3
0.003
0.009
0.007
20
50
90
180
4
0.042
0.055
0.032
0.051
0.051
0.016
0.031
0.060
0.007
90
122|156
246
5
0.074
0.067
0.073
0.074
0.074
0.046
0.052
0.107
0.026
i;o
172 '205
296
6
0.355
0.446
0.314
0.302
0.442
0.047
0.049
0.197
a
80
112
146
236
Mine 2
1
0.034
0.052
0.043
0.068
0.025
0.024
0.046
40
67
97
203
2
0.019
0.026
0.031
0.016
0.024
0 039
0.017
0.035
0.027
31
61
69
168
3
0.001
0.002
0.004
0.001
0.001
0.005
0.003
0.002
0.005
31
51
89
163
4
0.01?
0.012
0.019
0.016
0.019
0.021
0.017
0.013
0.025
150
177
216
310
5
0.065
0.071
0.051
0.035
0.014
0.025
0. 033
0.030
0.000
110
139
172
230
Mine 3
1
0.188
0.181
0.142
0.138
0.138
0.120
0.077
0.067
94
121
148
*
C
0.122
0.142
0.102
0.120
0.202
0.204
0.181
0.130
94
121
1«8
3
0.196
0.205
0.185
0.179
0.191
0.245
0.194
0.192
94
12i
148
4
0.080
0.062
0.111
0.102
0.115
0.157
0.021
0.125
94
121
148
5
0.063
0.057
0.064
0.053
0.066
0 356
0.05?
0.06/
140
166
196
6
0.081
0.070
0.065
0.049
0.072
0.069
0.06?
0.134
0.138
98
124
154
234
7
0.122
0.075
0.079
0.131
0.087
0.101
0.088
0.114
0.136
98
124
134
234
8
0.101
0.097
0.103
0.113
0.106
0.101
0.111
0.1CC
0.104
140
166
196
276
A
Concentration less than upwind.
160
-------
TABLE 8-10. APPARENT EMISSION RATES FOR HAUL ROADS
High-Volume (30 pts)
Test No.
Apparent emission rates at specified distances,
lb/VHT
Distances
from source, a
First
Second
Third
Fourth
Mine 1
J9
16.1
12.1
10.8
16.5
12.3
10.3
3.8
6.4
5
20
50
100
J10
13.0
11.1
9.3
8.2
3.2
3.3
a
a
5
20
50
100
J12
3.5
3.5
4 3
4.4
3.1
2.7
1.1
a
5
20
50
100
J20
5.1
7.7
4.0
4.6
2.8
2.8
a
a
5
20
50
100
J21
11.7
18.4
11.8
15.8
8.7
16.8
6.8
10.2
5
20
50
100
Mine 1W
1
11.6
11.6
12.1
9.6
13.6
13.1
13.9
14.6
5
20
50
80
2
19.1
13.1
13.3
13.3
11.2
8.5
10.6
5
20
50
80
3
28.3
21.8
15.6
15.2
7.7
4.5
4.8
5
20
50
60
4
36.0
38.3
32.8
21.6
29.8
25.6
20.0
21.7
5
20
50
30
5
11.5
15.1
9.3
14.4
13.9
6.2
5
23
50
80
6
47.8
40.9
31.1
31.0
31.5
28.8
40.6
5
20
50
30
a Downwind concentration less than calculated upt»ind.
161
-------
deposition, although the same type and size distribution of emissions are
involved as with the line source dispersion equation. The sensitivity
of calculated emission rates to several inputs to the point source
equation (such a«. initial plunp width, initial horizontal dispersion, dis-
tance from plume centcrline, and stability class) were examined, but no
single input parameter could be found that would change the emission data
by distance to show deposition.
The single-value ISP emission rates for each test determined from
the multiple emission rate values are summarized in Table 8-11. The
means and standard deviations for these tests are shown below:
Source
No. tests
Units
Hean
Std dev
Ranqp
Ccal loading
25
lb/ton
0.105
0.220
0.0069-1.09
Oozer, overburden
15
lb/h
6.8
6.9
0.9-20.7
Dozer, coal
12
lb/h
134.3
155.6
3.0-439
Oragline
19
lb/yd3
0.088
0.093
0.003-0.400
Haul road
11
lb/VMT
17.4
10.9
3.6-37.2
Scraper
5
lb/VMT
18.1
11.4
5.7-35.6
It should be emphasized that the mean values reported here are not
emission factors; they do not have any ccisideration of correction
factors Included in them.
Emission rates for coal loading varied over a wide range, from
0.0069 to 1.C9 lb/ton. Rates at the third mine averaged an order
of magnitude higher than at the first two mines. Since a front-end
loader was used at the third mine and shovels at the first two, the
wide differences in average emission rates may Indicate that separate
emission factors are required for these two types of coal loading.
Emissions from dozers working overburden varied over a moderate
range. Much of that variation can probably be explained by the soil
characteristics of the overburden being regraded: soil at the second
mine, which in general had the lowest emission rates, had the highest
moisture contents and lowest silt contents; soil at the third mine,
which had the highest emission rates, was driest. The evaluation of
these two correction parameters is described in Section 13.
Coal dozer emissions were grouped very tightly by mine. The
averages, standard deviations, and ranges by mine show this:
162
-------
TABLE 8-11. EMISSION RATES FOR UPWIND-DOWNVINO TESTS
Coal loading
Dozer,
overburden
Oozer, coal
Dragline
Haul road/scraper
Test
Emission
Test
Emission
Test
Emission
Test
Emission
Test
Emission
No.
rate, lb/ton
No.
rate, Wh
No.
rate, lb/h
No.
rate, ib/yd3
No.
rate, lb/VMT
Haul road
Mine 1
Mine 1
Mine 1
Mine 1
Mine 1
1
0.006S
1
16.2
1
16.1
1
0.024
J9
14.1
2
0.0100
2
12.6
2
40.1
2
0.029
J10
12.0
Mine 2
3
2.6
3
19.0
3
0.004
J12
3.6
1
0.044
4
3.0
4
21.3
4
0.048
J20
6.4
2
0.068
Mine 2
Mine 2
5
0.070
J21
15.0
3
0.0147
1
0.9
1
9.1
6
0.400
Mine 1W
4
0.0134
2
1.8
2
6.2
Mine 2
1
12.9
5
0.0099
3
2.6
3
3.0
1
0.042
2
16.1
6
0.0228
4
1.3
Mine 3
2
0.026
3
25.0
7
0.0206
5
9.2
1
289
3
0.003
4
37.2
8
0.0065
6
1.0
2
222
4
0.016
5
12.8
Mine 3
7
1.0
3
439
5
0.068
6
36.0
1
0.120
Mine 3
4
323
Mine 3
Scraper
2
0.082
1
5.4
5
224
1
0.184
Mine 1
3
0.051
2
5.2
2
0.133
J1
10.6
4
0.0105
3
18.0
3
0.192
J2
18.6
S
0.0087
4
20.7
4
0.C99
J3
35.6
6
0.0140
5
0.060
J4
5.7
7
0.035
6
0.068
J5
20.0
8
0.062
7
0.104
9
C.058
8
0.105
10
G.193
11
0.095
12
0.042
13
1.09
14
0.358
IS
0.188
-------
Mine Mean Std dev Range
1
2
3
24.1
6.1
299
10.9
3.0
89.2
16 1-40.1
3.0- 9.1
222-439
Coal characteristics are also expected to explain part of this variation,
but it is doubtful that the very high emission rates at the third mine
can be explained with just those parameters. Dozers working coal had
considerably higher emission rates than dozers working overburden. The
two sources probably cannot be combined into a single emission factor with
available data unless some correction parameter reflecting the type of
material being worked is incorporated.
Dragline emissions had greater varlatior within each m
-------
rABLE ft-12. EMISSION RATfS FOR COAL LOADING
Dichotomous (1 L> jjid, 2.5 pm)
Test No.
Apparent IP emission rates at specified
distances, lb/ton
Avg
IP
tmis
rate,
lb/ton
Avg
FP
em is
rate,
lb/ton
Dist from
source, m
First
Second
Mine 1
1
2
Mine 2
1
2
3
4
5
6
7
8
Mine 3
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0.002
0.001
0.005
0.013
0.003
0.002
0.001
0.005
0.013
0.004
0.112
0.003
0.001
0.001
0.002
0.011
0.012
0.051
0.003
0.012
0.575
0.116
No dicl
0.001
0.001
0.006
0.050
0.002
0.008
0.004
0.011
0.001
0.003
0.035
0.008
0.001
0.009
0.002
0.000
0.012
0.029
0.011
0.006
0.182
0.093
tot data
0.002
0.002
0.002
0.018
0.005
0.005
0.002
0.039
0.005
0.023
0.011
0.039
0.001
0.001
0.011
0.011
0.018
0.021
0.040
0.056
0.015
0.404
0.152
for te«
0.001
0.007
0.005
0.009
0.003
0.005
0.006
0.004
0.020
0.013
0.036
0.009
0.010
0.352
0.122
0.002
0.0C6
0.008
0.01*
0.011
0.005
0.004
0.005
0.001
0.003
0.003
0.C12
0.002
0.003
0.005
0.022
0.003
0.005
0.000
0.017
0.008
0.004
0.044
0.008
0.016
0.002
0.001
0.006
0.008
C. 012
0.014
0.038
0.020
0.011
0.378
0.121
0.0001
0.0002
0.0002
0.0008
0.0001
0.0018
0.0007
0.0029
0.0008
0.0002
0.0038
0.0005
0.0022
0.P002
0.0001
0.0001
0.0012
0.0012
0.0005
0.0033
0.00C5
0.0021
0.0054
0.0035
25
20
34
65
57
80
30
10
10
30
111
31
29
12
16
16
10
60
45
45
29
35
35
35
50
45
65
96
82
105
62
28
28
60
132
58
56
24
27
27
20
90
75
65
49
65
05
62
165
-------
TABLE 8-13. EMISSION RATES FOR DOZER (OVERBURDEN)
Dichotomous (15 pm, 2.5 pin)
Apparent IP emission rates at specified
distances, lb/h
Test No.
First
Second
Mine 1
1
2
3
4
3.39
1.68
3.86
b
1.75
2.78
1.58
b
2.43
2.02
3.18a
b
2.71
2. 22.
3.17®
b
5.66
2.48
b
Mine 2
1
2
3
4
5
6
7
00 e
3.74®
2.39
0.846
0.0 h
1.00h
0.885
0.91d
13.9
0.0
n
419 s
0.92?
0.513
1.13
1.62
0.561
0.375
0.632
2.82
0.129
0.646
6.43d
0.0
0.0
0.521
0.0
Mine 3
1
2
V
0.488
0.701
6.48
33.4
0.679
0.912
0.842
0.600
5.22
32.6
1.91
0.913
2.00J
31.8'
Avg
Avg
IP
FP
er.n s
emis
rate,
rate,
Oistances
lb/h
lb/h
from
source,
3.18
0.436
15
44
2.18
0.322
20
49
2.85
1.010
25
54
c
c
25
52
2.12
0.583
25
56
5.88
0.091
20
46
1.00
0.790
25
58
0.48
0.065
25
58
1.14
0.680
25
56
0.68
0.421
8
23
1.22
0.536
31
66
0.98
0.356
25
45
0.781
0.089
20
40
4.57
0.925
25
41
63
32.6
1.73
43
59
81
b
c
d
e
f
S
h
1
j
k
1
This dichotomous sampler value could not be corrected to a 15 pm cut
to reflect the wind speed bias of the sampler inlet. The uncorrected
point is about 16.2 pra.
Downwind concentration less than upwind.
Insufficient data.
See footnote a; represents 13.4 pm cut point.
See footnote a; represents 10.4 pra c*Jt point.
See footnote a; represents 13.5 pa cut point.
See footnote a; represents 20.2 pa cut point.
See footnote a; represents 16.0 cut point.
See footnote a; represents 17.4 Mm cut point.
Actually at 63 m distance.
See footnote a; represents 19.8 cut point.
Actually at 8 m distance.
point
cut
166
-------
TABLE 8-14. EMISSION RATES FOR DOZER (COAL)
Dichotomous (15 (jm, 2.5 pm)
Apparent
IP emission rates at specified
distances, lb/h
Avg
IP
emis
rate,
lb/h
Avg
FP
emis
rate,
lb/h
Test No.
First
Second
uisi Trom
source, m
Mine 1
1
2
3
4
3.94
38.0
7.91
6.49
3.94
42.0a
1.49
6.48
4.18
67.2a
2.44
11.5
3.89
21.1
3.89
13.4
6.91
31.2a
7.94
27.0
4.49
39.9
4.73
13.0
0.243
0.730
1.000
2.68
125
125
125
I?5
155
155
155
155
Mine 2
1
2
3
1.73
2.08
0.82
3.58
1.03
0.43
1.02
2.94
0.57
2.71
2.98
1.86
2.26
2.26
0.92
0.252
0.199
0.138
30
40
40
42
67
67
Mine 3
1
2
3
4
5
214
254
229
161
70
223
273
157
78
96
119
259
18J
109
222
113
185
204
72
177
178
236
176
82.2
3.50
2.25
4.49
3.28
3.50
30
30
30
30
30
60
60
60
60
60
This dichotomous sampler value could not be corrected to a 15 pm cut point
to reflect, the wind speed bias of the sampler inlet. The uncorrected cut
point is about 15.8 fjm.
167
-------
TABLE 8-15. EMISSION RATES FOR DRAGLINE
Dichotomous (15 pm, 2.5 pm)
Test No.
Apparent IP emission rates at specified
distances, lb/yd3
Avg
IP
emis
rate,
lb/yc!3
Avg
FP
emis
rate,
lb/yd3
Dist from
source, m
First
Second
Mine 1
1
0.003
0.004
0.002
0.006
0.010
0.0C6
0.0009
60
90
2
0.008
0.004
0.008
0.021
0.021
0.012
0.0002
20
50
3
0.001
0.001
0.002
0.004
0.002
0.002
0.0001
20
50
4
0.007
0.007
0.003
0.008
0.007
0.006
0.0001
90
120
5
0.010
0.006
0.016
0.025
0.021
0.016
0.0009
140
170
6
0.060
0.038
0.060
0.042
0.104
0.061
0.0087
80
110
Mine 2
1
0.002
0.003
0.003
0.003
0.0002
40
67
2
0.009
0.009
0.002
0.008
0.007
0.0008
31
61
3
0.001
0.001
0.002
0.001
0.001
0.0003
31
61
4
0.026
0.010
0.005
0.020
0.015
0.0010
150
177
5
0.022
0.028
0.038
0.052 '
0. 03d
0.0110
110
139
Mine 3
1
0.008
0.028
0.015
0.024
0.018
0.0017
94
121
2
0.013
0.017
0.017
0.017
0.016
0.0011
94
121
3
0.058
0.052.
0.06 ^
0.058
0.006
94
121
4
0.044
0.063d
0.039
0.026
0.043
0.005
94
121
5
0.038
0.055
0.034
0.025
0.038
0.0001
140
166
6
0.034
0.029
0.011
0.040
0.028
0.0017
98
124
7
0.036
0.022
0.019
0.020
0.024
0.0023
98
124
8
0.028
0.003
0.014
0.023
0.017
0.0004
140
166
This dichotomous sampler value could not be corrected to a 15 pm cut point
to reflect the wind speed bias of the sampler inlet. The uncorrected cut
^ point is about 17.4 pm.
See footnote a; represents 19.0 pm cut point.
168.
-------
TABLE 8-16. EMISSION RATES FOR HAUL ROADS
Dichotomous (15 |jm, 2.5 pm)
Test No.
Apparent IP emission rates at specified
distances, lb/VMT
Avg
IP
emis
rate,
lb/VMT
Avg
FP
emis
rate,
lb/VMT
Distances
from source, m
First
Second
Third
Mine 1
J9
8.71
5.61
5.65
12.13
3-74^
5.08
o. 82
0.141
5
20
50
J10
7.42
4.50
7.91
7.24
3.55
6.17
6.13
0.300
5
20
50
J12
0.74
0.52
!.50b
0.96
0.00
0.53.
0.71
0.095
5
20
50
J20
3.81
3.80
5.63
5.83
5.37
8.92
5.5b
0. 101
5
20
50
J21
5.22
7.41
5.26
5.72
5.65
7.01
6.04
0.758
5
20
50
Mine 1W
1
4.28
5.91
7.32
6.59
6.02
0.192
5
20
2
7.18
11.69
9 11
9.33
0.062
5
20
3
17.12
13.33
8.57
8.97
12.00
0.804
5
20
4
5.41
3.80
8.06
4 62
5.47
0.620
5
20
5
2.2 6
1.57
1.00
1.42
1.56
0.217
5
20
6
10.78
12 36
10.25
34.36
11.94
0.165
20
This dichotomies sampler value could not be corrected to a 15 pra cut point
to reflect the wind speed bias of the sampler inlet. The uncorrected cut
b point is about 13.6 mm.
See footnote a; represent 19.0 pm cut point.
169
-------
These values are different than the average ratios of net concentrations
because of the effect of deposition on calculation of the single-val:
TSP emission rates.
The overburden dozer IP/TPS ratios are much higher than for other
sources because five of the 15 tests had IP concentrations much higher
than TSP concentrations. When the IP concentration exceeds the TSP
concentration, correction of the IP value to 15 um size from the actual
(wind speed dependent) cut point canrot be performed by the method
described on Page 83. For s-jch cases in Table 8-13 (and TaL.le 8-14
through 8-16), the uncorrected IP value were reported along with their
estimated cut points. If the five tests with uncorrected IP data were
eliminated, the average IP/TSP ratio would be 0.28, much clober to that
other sources. No explanation was found for the high IP concentrations
compared to TPS concentrations for overburden dozers.
For all sources except overburden dozers, the IP and FP emission rate
variabilities (as measured by tse relativp standard deviation) were
about the same as TSP emission rate variabilities. Due to the four
high dichotomous sample values, the IP and FP emission rates for
overburden dozers h3d abcut twice the relative standard deviation as
the TSP emission rates.
PROBLEMS ENCOUNTERED
The most common problem associated with upwind-downwind sampling was
the long time required to set up the complex array of 16 samplers and
auxiliary equipment. On many occasions, the wind direction would change
or the mining operation would move while the samplers were still being
set up.
Another frequent problem was mining equipment breakdown or reassign-
ment. At various times, the sampling team encountered these situations:
pwer loss to dragline; front-end loader broke down while loaning first
truck; dozer broke down, 2 hours until replacement arrived; dozer
operator called away to operate frontend loader; and brief maintenance
check of dragline leading to shutdown for the remainder of shift for
repair.
A third problem was a typical operation of the mining equipment
dragline sampling. One example was the noticeable difference 1n dragline
operators' ability to lift and swing the bucket without losing material.
Sampling of a careless operator resulted In emission rates two to five
times as high as the previous operator working in the same location.
The dragline presented other difficulties 1n sampling by the upwind-
downwind method. For safety reasons or because of topographic
obstructions, 1t was often Impossible to place sailers 1n a regular
170
-------
array downwind of the dragline. Therefore, many samples were taken well
off the plume centerline, resulting in large adjustment factor values in
the dispersion equation calculations and the potential for larger errors.
Estimating average source-*"o-sampler distances for moving operations
such as dtagllnes was also difficult.
Sampling of coal loading operations was complicated by the many
related dust-producing activities that are associated with it. It is
impossible to sample coal loading by the upwind-downwind method without
also getting some contributions from the haul truck pulling Into position,
form a frontend loader cleaning spilled coal from the loading area, and
from the shovel or frontend loader restacking the loose coal between
trucks. It can be argued that all of these constitute necessary parts
of the overall coal loading operation and they are not a duplication of
emissions Included In other emission factors, but the problem arises
1n selecting loading operations that have typical amounts of this
associated activity.
Adverse meteorology also created several problems in obtaining
samples. Weather-related problems were not limited to the upwind-
downwind sampling method or the five sources samples by this method,
but the large number of upwind-downwind tests resulted In more of these
test periods being Impacted by weather. Wind speed caused problems
most frequently. When wind speeds were less than 1 m/s or greater
than about 8 m/s, sampling could not be done. Extremely low and high
winds occurred on a surprisingly large number of days, causing lost
work time by the field crew, delays m starting some tests, and pre-
mature cessation of others. Variable wind directions and wind shifts
were other meteorological problems encountered. In addition to
causing extra movement and set up of the sampling equipment, changes
1n wind direction also ruined upwind samples for some sampling periods
in progress. Finally, several sampling days were lost due to rain.
171
-------
SECTION 9
RESULTS FOR SOURCE TESTED BY BALlOON SAMPLING
SUMMARY Of TESTS PERFORMED
Blasting was the only source tested by the ball loon sampling method.
Overburden and coal blasts were both sampled with the same procedure,
but the data were kept separate during the data analysis phase so that
the option of developing separate emission factors was available. A
total of 18 successful tests were completed--14 for coal blasts and 4
for overburden blasts. Three more blasts were sampled, but the balloon
was hit and broken in one and the plumes missed the sampler arrays in
two others; no attempt was made to calculate emission rates for these
three tests.
The overburden was not blasted at *.he mine in North Dakota (second
mine), so overburden blast tests wer«? «.un fired to the first and third
mines. The resulting sample size of four is not large enough for
development of a statistically souno cmisrion factor.
The sampling array consisted of balloon-supported samplers at five
heights plus five pairs of ground-based hi-vols and dichots to establish
the horizontal extent of the plume. No measure of deposition rate was
made with this configuration because all samplers were at the same dis-
tance from the source.
Samplers at Mine 2 were located 1n the pit for coal blasts, but
samplers at Mines 1 and 3 were located on the hlghwall above the pit.
Therefore, some (prior) deposition 1s included in the emission rate
measured at the latter mines. These ars the only emission rates in
the study that are not representative of emissions directly from the
source.
Test conditions for the blasting tests are summarized in Table 9-1.
An extremely wide range of blast sl2es was sampled—from 6 to 750 holes
and from 100 to 9600 m2. The variation 1n moisture contents was also
quite wide. ¦ The only potential correction factor with a limited range
during testing was the depth of thejholes. All the holes for coal
blasts were about 20 ft deep. Overburden holes had a range of 25 to
135 ft, but there are not enough data points to develop a correction
factor.
172
-------
TABLE 9-1. TEST CONDITIONS FOR BLASTING
A —
Soi 1
prop-
Meteorological
Sampling conditions
Source characteristics
erties
conditions
Samplers
Wind
Start
Duration,
in or out
No. of
Area,
Tons of
Depth of
Moisture,
Temp,
speed.
Stab
Test
Oate
time
minutes
of pit
holes
m2
explosive
holes, ft
%
°F
m/s
class
Mine 1
Coal 1
8/10/79
15:00
5
out
33
1100
1.0
22
22
82
1.1
A
2
8/10/79
15:30
3
out
6
100
0.2
22
22
82
1.0
A
3
8/14/79
12:00
7
out
42
1600
1.3
20
22
62
1.4
B
„ Mr 1
8/14/79
14:30
16
out
33
3400
12.0
70
7.2
66
5.1
D
2
8/20/79
14:45
8
out
20
2200
10.0
60
7.2
76
2.0
A
Mine 2
Coal 1
10/25/79
11:28
6
in
195
1100
20
38
45
2.6
C
2
10/26/79
11:00
8
in
210
1J00
20
38
43
1.6
C
3
10/29/79
9:33
3
in
180
1000
20
38
43
1.8
C
4
10/29/79
12:07
6
in
150
800
20
38
43
1.0
B
5
10/29/79
14:30
7
in
110
1100
20
38
38
3.2
D
6
10/30/79
14:35
6
in
96
600
20
38
47
5.4
0
Mine 3
Coal 2
7/28/80
14:20
13
out
250
4100
20
11.1
99
1.7
B
3
7/29/80
14:10
21
out
750
6800
20
11.1
104
1.2
B
4
8/01/80
13:10
25
out
200
3400
20
11.1
90
2.0
A
5
8/04/80
14:15
7
out
150
2400
20
11.1
95
2.7
C
6
8/06/80
10:45
12
out
160
2700
20
11.1
82
1.3
B
^ ^ 1
8/06/80
14:35
10
out
50
9600
135
8.0
93
1.7
A
Ovvlc^it*2
8/12/80
15:05
10
out
60
5000
25
8.0
95
1.0
A
-------
RESULTS
TSP emission rates are snown in Table 9-2. The emission rates varied
over a wide range, from 1.1 to 514 lb/blast. Blasting emssions at the
first two nines were reTativley low; those at the third mine were quite
high. Some of the differences are expected to be explained by test
conditions, which also varied ever a correspondingly wide range. The
values in Table 9-2 are as measured, and have not been adjusted for any
potential correction factors.
The data subsets by mine were too small for statistics such as
standard deviation to be meaningful. If the data are divided into sub-
sets of coal and overburden blasts, the TSP emission rates are as
fol1ows:
Type blast No. samples Mean, lb Sid dev Range
Coal 14 110.2 161.2 1.1-514
Overburden 4 106.2 110.9 35.2-270
The only sample tnat was more than two standard deviations away from the
mean was the 514 lb value. However, this blast had more than three
times as many holes as any other blast sampled, so it would not be
considered an outlier.
Inhalable and fine particulate emission rates ara presented in Table 9-3..
The IP emission rates ranged from 0.5 to 142.8 lb/blast and from 1/ to 138
percent of TSP. The IP emission rates for blasts averaged 46 percent of
the TSP rates, about the same ratio as the haul roads. Fine particulate
averaged 5.0 percent of TSP, higher than for any other source. Coal
blasts and overburden blasts did not have any obvious distinctions in their
respective particle size distributions.
PROBLEMS ENCOUNTERED
Balloon sampling represented a substantial modification of the exposure
profiling method and therefore a somewhat sxperimental technique. It
was particularly difficult to apply blasting because technical limitations
of the technique combined with the infrequency of blasting resulted in
very few opportunities to perform the sampling.
This sampling method could not be used when ground lpvel winds were
greater than about 6 m/s because the balloon could not be controlled on
Its tether. At wind speed less than about 1 m/s, wind direction tended
to vary and the sampling array could not be located with any confidence
of being in the plume. Also, at low wind speeds, the plume from the
blast frequently split or rose vertically from the blast site. There-
fore, sampling was constrained to a fairly narrow range of wind speeds.
174
-------
TABLE 9-2. APPARENT EMISSION RATES FOR BLASTING
High-Volume (30 pm)
Pound/
Distance
Pound/
Distance
Test No.
blast
from source, m
Test No.
blast
from source, m
Mine 1
Mine 1
Coal
Overburden
1
32.5
96
1
40.4
100
2
2.7
96
2
79.4
100
3
51.7
37
Mine 2
Coal
1
8.8
130
2
1.1
213
3
10.7
130
4
1.6
160
5
40.3
170
6
11.8
180
Mine 3
Mine 3
Coal
Overburden
2
401
90
1
35.2
110
3
514
160
2
270
200
4
148
128
5
113
53
6
206
82
175
-------
TABLE 9-3. APPARENT EMISSION RATES FOR BLASTING
Dichotomous (15 pm, 2.5 |jm)
Pound/blast
Distance
Pound/blast
Distance
Test No.
IP
FP
from source, m
Test No.
IP
FP
from source, m
Mine 1
Mine 1
Coal
Overburden
1
44.9a
3.62
9fi
1
32.9
0.79
100
2
1.56
0.32
96
2
48.9
0.09
100
3
17.3
1.23
37
Mine 2
Coal
1
1.55
0.10
130
2
0.62
0.06
213
3
3.57
0.80
130
4
0.45
0.10
160
5
15.30
1.27
170
6
1.99
0.01
180
Mine 3
Mine 3
Coal
Overburden
2
123.4
10.4
90
1
16.9
3.5
110
3
142.8
12.3
160
2
93.9
16.2
200
4
87.9
13.0
128
5
35.3
2.1
53
6
71.3
19.8
82
a Dichotomous concentrations are greater than hi-vol, value represents 20.5
tim cut point for IP.
176
-------
For safety masons, a source-sampler distance of 100 m or more
was usually required. At this distance, the plume could disperse
vertically above the top sampler inlet under unstable atmospheric
conditions.
Even though sampling was done at very large mines, only one or
two bl.ists per day were scheduled. This often created difficulties
in obtaining the prescribed number of blasting tests at each mine.
Since blasting was not a continuous operation, there was no
continuous plume to provide assistance in locating the samplers. For
coal blasts in particular, the portion of the plume below the high
wasll usually was channeled parallel to the pit but any portion rising
above the high wall was subject to ambient winds and often separated
from the plume in the pit.
Finally, representative soil samples could not be obtained for this
source because of the abrupt change in the characteristics of the soil
caused by the blast. The moisture contents reported in Table 9-1 were
for samples of coal in place and overburden from drilling tests (both
prior ot blasting).
177
-------
SECTION 10
RESULTS FOR SOURCES TESTED BY WIND TUNNEL METHOD
SUMMARY OF TESTS PERFORMED
As discussed previously, the wind tunnel method was used to test
particulate emissions generated by wind erosion of coal storage piles
and exposed ground areas. These sources were tested at three mine
sites during the period October 1979 through August 1980.
A total of 37 successful wind tunnel tests were conducted at the
three mines. Tests at Mine 1 took place in late autumn, with below normal
temperatures and snowfall being encountered. Emissions tests were
distributed by source and by mine as follows:
Number of tests
Source Mine 1 Mine 2 Mine 3
Coal storage piles 4' 7 16
Exposed ground areas 1 5 4
The decision of when to sample emissions from a given test surface was
based on the first observation of visible emissions as the tunnel flow
rate wis incrased. At Min:s 1 and 2, if visible emissions in the blow
exhaust were not observed at a particular tunnel flow "ate, no air
sampling was performed, but a velocity profi'e was obtained. Then the
tunnel flow rate was increased to the next level and the process repeated.
When visible emissions were observed, emission sampling was performed and
then repeated at the smae wind speed (but for a longer sampling time) to
measure the decay in the erosion rate. At Mine 3, particle movement cn
the test surface was used as the indicator that the threshold velocity
had been reached and that emission sampling should be performed. Five
tests on coal piles and seven tests on exposed ground areas were conducted
on surfaces where no erosion was visually observed, and 1n these cases
no emissions sampling was performed.
Tale 10-1 lists the test site parameters for the wind ••unnel tests
conducted on coal pile surfaces. The ambient temperature and relative
humidity measurements were obtained just above the coal surface external
to the tunnel.
178
-------
TABLE 10-1. WIND EROSION TEST SITE PARAMETERS - COAL STORAGE PILES
Mine/Sitea
Run
Date
Start
time
(hr;sec)
Sampling
duration
(min:sec)
Ambient
meteoroloov
T emp R.ri
(°C) (%)
Mine 1/Site A
J-22
11/9/79
-
-
-2.8
-
Mine 1/Site B
J-23
11/9/79
-
-
-2.8
-
J-24
11/9/79
1330:00
5.30
-1.1
79
J-25
11/9/79
1413:00
30.00
-1 1
79
Mine 1/Site C
J-26
11/9/79
1606 30
1:00
-1.1
79
J-27
11/9/79
1620:15
8-15
-1.1
79
Mine 2/Site A
K-30
1C/31/79
-
-
3. 3
75
Mine 2/Site E
K-38
11/3/79
-
-
-1.1
100
K-39
11/3/79
1417-25
6:00
2.8
61
Mine 2/Site F
K-40
11/3/79
1550.05
6:49
4.4
60
K-41
11/3/79
1635:25
30.00
2.8
65
Mine 2/Site G
K-42
11/4/79
1120:00
5:50
2.8
64
K-43
11/4/79
1156:20
30:00
3.9
70
Mine 2/Site H
K-44
11/4/79
-
-
2.2
-
K-45
11/4/79
1652:40
3:35
2.8
51
K-46
11/4/79
1717:;0
30:00
2.8
51
Mine 3/Sfte A
P-2Q
8/12/80
0848:00
30:00
24
39
P-21
8/12/30
0946:00
10:00
29
26
P-22
8/12/80
1014:00
.40:00
29
26
(continued)
179
-------
TABLE 1C-1 (continued).
Mine/Sitea
Run
Date
Start
tine
(hr:lec)
Sampling
duration
(mm: sec)
Amoient
meteorology
Temp. R H
(°C) (%)
P-23
8/12/80
1114:00
10:00
33
21
P-24
8/12/80
1222:00
40.00
33
21
P-25
8/12/80
1538.00
10-00
37
12
P-26
8/12/80
1617-00
10:00
37
12
Mine 3/Site B
P-27
8/12/80
1813.00
2.00
37
12
P-28
8/13/80
1017-00
8:00
28
35
P-29
8/13/80
1134:00
2 00
34
24
P-30
8/13/80
1145-00
8.00
34
24
Mine 3/Site C
P-31
6/13/80
1546:00
2:0 0
34
19
P-32
8/13/80
1601:00
8:00
34
19
P-33
8/13/80
1649.00
2.00
34
19
P-34
8/13/80
1704:00
8.00
34
19
P-35
8/13/80
1738:00
26:00
34
19
a Mine 1/Site A - Base of pile.
Mine 1/Site B - Traveled area (dozer track) surrounding pile.
Mine 1/Site C - Traveled area (light duty vehicle track) surrounding pile.
Mine 2/Site A - Raw coal surge pile.
Mine 2/Site E - Raw coal surge pile.
Mine 2/Site F - Raw coal surge pile.
Mine 2/Site G - Raw coal surge pile.
Mine 2/Site H - Along dozer track or raw coal surge pile.
Mine 3/Siie A - Approximately 1 kilometer east of power plant on crusted vehicle
track.
Mine 3/Site B - Twenty-five meters south of Site A on furrow in coal pile.
Mine 3/Site C - Seventy-five meters west of Site B on uncrusted haul truck track.
180
-------
Table 10-2 gives the tunnel test conditions for the wind erosion
emission tects on coal surfaces. The equivalent speed at 10 m was
determined by extrapolation of the logarithmic ve^city profile measured
in the wind tunnel test section above the eroding surtace. The first
friction velocity, which is a measure of the wind shear at the eroding
surface, was determined from the velocity profile.
Table 10-3 gives the erosion-related properties of the coal surfaces
from which wind-generated emissions were measuied. The silt and moisture
values were determined from representative undisturbed sections of the
erodible su-face ("before" erosion) and from the actual test surface
after erosion; therefore, only one "before" condition and one "after"
condition existed for each test site. The roughness height was
determined from the velocity profile measured above the test surface
at a tunnel wind speed just below the threshold value.
Table 10-2 lists the test site parameters for the wind tunnel tests
conducted on exposed ground areas. The surfaces tested included top-
soil, subsoil (with and without snow cover), overburden and scoria.
For Runs J-28, K-31 through K-34, K-47 and K-48, no air sampling was
performed, but velocity profiles were obtained.
Table 10-5 gives the tunnel test conditions for the wind erosion
emission tests on exposed ground are<*s. Table 10-6 gives the erosion-
related properties of the exposed ground surfaces from which wind-
generated emissions were measured.
RESULTS
Table 10-7 and 10-8 present the wind erosion emission rates measured
for coal piie surfaces and exposed ground areas, respectively. Emission
rates are given for suspended particulate matter (particles smaller than
30>um 1n aerodynamic diameter) and inhalable particulate matter (parti-
cles smaller than 15 Jim in aerodynamic diameter).
For certain emission samp.ing runs, emission rates could not be
calculated. No parWle size data were available for run J-30. For
exposed ground area runs P-37 and P-41, neasured emissions consisted
entirely of particles larger than 11.6jum aerodynamic diameter (the
cyclone cut point).
The means, standard deviations, and ranges of SP emission rates for
each source category are shown below:
181
-------
TABLE 10-2. WIND TUNNEL TEST CONDITIONS - COAL STORAGE PILES
Run
Wind speed at
tunnel centerline
Friction velocity
Equivalent speed
at 10 m
(ra/s)
(mph)
(m/s)
(mph)
(m/s)
(mph)
J-24
14.3
32.1
0.97
2.17
25.0
56.0
J-25
14.2
31.8
0.96
2.15
25.0
56.0
J-26
11.7
26.2
0.63
1.41
18.8
42.0
J-27
15.6
35.0
0.94
2.10
25.9
58.0
K-39
16.7
37.3
1.46
3.27
32.2
72.0
K-40
15.0
33.5
1.46
3.27
29.1
65.0
K-41
14.8
33.2
1.44
3.22
29.1
65.0
K-42
16.9
37.9
1.73
3.87
33.5
75.0
K-43
16.9
37.9
1.73
3.87
33.5
75.0
K-45
13.6
30.4
1.32
2.95
27.3
61.0
K-46
13.6
30.4
1.32
2.95
27.3
61.0
P-20
11.6
25.9
0.44
0.984
16.8
37.5
P-21
13.1
29.2
0.60
1.34
19.2
43.0
P-22
13.1
29.2
0.60
1.34
19.2
43.0
P-23
14.2
31.8
0.64
1.43
21.9
49.0
P-24
14.8
33.2
0.61
1.36
20.3
45.5
P-25
16.0
35.8
0.66
1.48
22.4
50.0
P-26
16.2
36.3
0.71
1.59
23.7
53.0
P-27
16.0
35.7
1.00
2.24
26.4
59.0
P-28
15.8
35.4
1.20
2.68
30.6"
68.5
(continue
182
-------
TABLE 10-2 (continued).
Run
Wind speed at
tunnel centeriine
Friction velocity
Equivalent speed
at ?0 it
(m/s)
(mph)
(m/s)
(mph)
(m/s)
(niph)
P-29
17.3
38.6
1.31
2.93
>31.3
>70.0
P-30
16.9
37.7
1.08
2.42
26.4
59.0
P-31
11.8
26.3
0.91
2.04
21.5
48.0
P-32
12.0
26.8
0.95
2.12
24.6
55.0
P-33
14.5
32.4
1.15
2.57
26.6
59.5
P-34
14.4
^ n a
1.25
2.80
31.3
70.0
P-35
14.5
32.4
1.25
2.80
>31.3
>70.0
143
-------
TABLE 10-3. WIND EROSION SURFACE CONDITIONS - COAL STORAGE PILES
Run
Si It
Moisture
Roughness
Height
(cm)
Threshold speed
at tunnel
center! me
(m/s) (mpr.)
Berore
(%)
After
(%)
Before
(%)
After
(%>
J-24
16.4
-
2.5
-
0 04
9.52
21.3
J-25
16.4
6. S
2.5
3.3
0.04
9.52a
21. 3a
J-26
16.4
-
2.5
-
0.008
5. 52a
21.3*
J-27
16.4
-
2.5
-
0.02
9. 52a
21.3a
K-39
5.1
4 2
20.2
19.9
0.16
14.1
31.6
<-40
5.1
-
20.2
-
0.25
14.1
31.6
K-41
5.1
6.8
20 2
10.5
0.25
14.1
31.6
K-42
3.4
-
6.8
-
C. 30
14.1
31.6
K-43
3.4
2.3
6.8
6.4
0.30
14 1
31.6
K-45
11.6
-
2.8
-
0.25
11.1
24 8
K-46
11.6
10.0
2.8
2.1
0.25
11.1
24 6
P-20
3.8
4.1
4.6
3.4
0.0005
8.76
19.5
P-21
3.8
4.1
4.6
3.4
0.0024
8.76
19 6
P-22
3.8
4.1
4.6
3.4
0.0024
8.76
19.6
P-23
3.8
4.1
4.6
3.4
0.0022
8.76
19.6
P-24
3.8
4.1
4.6
3.4
0 0009
3.76
19.6
P-25
3.8
4.1
4.6
3.4
0.0009
8.76
19.6
P-26
3.8
4.1
4.6
3.4
0.0017
8.76
19.6
P-27
4.0
3.8
7.8
5.1
0.025
14.6
32.6
(continued)
18'-
-------
TABLE 10-3 (continued).
Run
Silt
Mot sture
Roughness
Height
(cm)
Threshold speed
at tu.-nel
center!ine
(m/s) (mph)
Before
(%)
After
{%)
Before
(%)
After
(X)
P-28
4.0
3.8
7.8
5.1
0.078
14.6
32.6
P-29
4.0
3.8
7.8
5.1
0.078
14 6
32.6
P-30
4.0
3.8
7.8
5.1
0.030
14.6
32.6
P-31
4.4
-
3.4
-
0.085
8.32
18.6
P-32
4.4
-
3.4
-
0.10
8.32
18.6
P-33
4.4
-
3.4
-
0.10
8.32
18.6
P-34
4.4
-
3 4
-
0.15
8 32
18.6
P-35
4.4
•
3.4
~
0.15
8.32
18.6
a Assumed the sairc as J-24.
185
-------
TABLE 10-4. WIND EROSION TEST SITE PARAMETERS - EXPOSED GROUND AREAS
Mine/Site3
Run
Date
Start
time
(hr-sec)
Samp!ing
duration
(mm: sec)
Ambient
meteo'olocv
Temp R H.
(°C) (%)
Mine 1/Site D
J-28
11/10/79
-
-
0.6
-
J-29
11/10/79
1141:00
30:00
0.6
91
J-30
11/10/79
1342:20
30-10
2.8
87
Mine 2/Site B
K-31
11/1/79
-
-
2.2
60
K-32
11/1/79
-
-
2 2
oO
K-33
11/1/79
-
-
2.2
60
M-.ne 2/Site C
K-34
11/2/79
-
.
-1.7
eo
K-35
11/2/79
1454:00
3:21
-1.7
80
K-36
11/2/79
1536.00
30- 36
-1.7
30
Mine 2/Site 0
K-37
11/2/79
1704.17
11.43
-1.7
oO
Mine 2/Site I
K-47
11/5/79
-
-
-1.1
-
Mine 2/Site J
K-48
11/5/79
-
-
-1.1
-
K-49
11/5/79
1515:CO
5.00
0 6
63
Mine 2/Site J
K-50
11/5/79
1555:30
28: 00
0.0
75
Mine 3/Site D
P-36
8/14/80
1012:00
2:00
-
-
P-37
8/14/80
1026:00
4:00
-
-
P-38
8/14/80
1042:00
4:00
-
-
Mine 3/Site I
P-39
0/14/80
1212:00
4:00
-
-
Mine 3/S1te E
P-40
8/14/80
1225.00
4.00
-
-
P-41
8/14/80
1240.00
4.00
-
-
186
-------
Footnotes for Table 10-4.
Mine 1/Site D - Subsoil covered with one-half inch of snow, which melted
prior to Run J-30.
Mine 2/Site 9 - Exposed soil near pit.
Mine 2/Site C - Oragline access road recentiy cut down; road surface represented
disturbed overburden.
Mine 2/Site D - Adjacent to Site C and in same natenal.
Mine 2/5ite I - Snail bank maae of overburden and left by grader on side of uniavea
road.
Mine 2/Site J - Scoria fiauT road.
Mine 3/Site D - Exposed topsoil. Two hundred meters south of p*;t.
Mine 3/S">te £ - Five meters west of Site D.
187
-------
TABLE 10-5- WIND TUNNEL TEST CONDITIONS - EXPOSED GROUND AREAS
Run
Wind speed at
tunnel center!ine
Friction
velocity
Equivalent speed
at 10 m
(m/s)
(mph)
(m/s)
(mph)
(m/s)
(mph)
J-29
18.1
40.5
1.96
4.38
38.0
85.0
J-30
16.6
37.1
1.62
3.62
32.6
73.0
K-35
15.1
33.7
1.54
3.44
30.9
69.0
K-36
14.8
33.1
1.51
3.38
30.0
67.0
K-37
15.1
33.7
1.54
3.44
30.9
69.0
K-49
15.8
35.4
1.56
3.49
30.4
68.0
K-50
15.8
35.4
1.56
3.49
30.4
68.0
P-36
10.3
19.6
0.87
1.95
15.7
35.0
P-37
10.3
19.6
0.87
1.95
15.7
35.0
P-38
10.3
19.6
0.87
1.95
15.7
35.0
f-39
6.3
14.0
0.33
0.738
10.3
23.0
P-40
8.1
18.0
0.44
0.984
13.0
29.0
P-41
10.7
23.9
1.00
2.24
20.1
45.0
188
-------
TABLE 10-WIND EROSION SURFACE CONDITIONS - EXPOSED GROUND AREAS
Run
Silt
Moisture
Roughness
Height
(cm)
— SS ¦ . . T7 • '.t'S
Threshold speed
at tunnel
center!i ne
(m/s) (mpn)
Before
(«
After
(X)
Before
1%)
After
w
J-29
-
-
-
-
0.38
>18.3
>41
J-30
-
-
-
-
0.25
>18.3
>41
K-35
21.1
18.8
6.4
5.6
0.30
10.5
23.4
K-36
21.1
18.8
6.4
5.6
0.30
10.5
23.4
K-37
21.1
22.7
6.4
5.6
0.30
10.5
23.4
K-49
IB. 8
-
4.1
-
0.26
13.5
30 1
K-50
18.8
15.1
4.1
2.7
0.26
13.5
30.1
P-36
5.1
-
0.8
0.13
4.65
10.4
P-37
5.1
-
0.8
0.13
4.65
10.4
P-38
5.1
-
0.8
0.13
4.65
10.4
P- 39
5.1
-
-
0.0075
5.14
11.5
P-40
5.1
-
-
0.01
5.14
11. S
P-41
5.1
~
•
0.21
5.14
11.5
— ¦ ¦— T
189
-------
TABLE 10-7. WIND EROSION TEST RESULTS - COAL STORAGE PILES
Run
Emission rate
Surcended
oerticulate
Inha1aDle
particulate
(g/m2-s)
(lb/acre-s)
(g/m'-s)
(lb/acre-s;
J-24
0.00340
0.0303
0.00226
0.0202
J-25
0.00520
0.0464
0.00344
0.0307
J-26
0.254
2.27
0.157
1.40
J-27
0.0746
0.668
0.0472
0.421
K-39
0.170
1.52
0.119
1.06
K-40
0.111
0.991
0.0722
0.644
K-41
0.00454
0.040b
0.00296
0.0254
K-42
0.0961
0.831
0.0626
0.55?
K-43
0.00436
0.0389
0.00279
0.0249
K-45
0.0598
0.53*
0.0436
0.389
K-46
0.00741
0.0661
0.00543
o
o
CD
u;
P-20
0.0127
0.113
0.00811
0.0724
P-21
0.00966
0.0662
0.00414
0.0369
P-22
0.00108
0.00964
0.000597
0.00533
P-23
0.00232
0.0207
0.00139
C.0124
P-24
0.00176
0.0157
0.00107
0.00955
P-25
0.00392
0.0350
O.C0231
0.0206
P-26
0.00946
0.0846
0.C0533
0.0476
P-27
0.0386
0.344
0.0202
0.180
P-28
0.00578
0.0513
0.00343 -
0.030c
(continued)
190
-------
TABLE 10-7 (continued).
Emission rate
Suspended particulate
Inhalable
particulate
Run
(g/m2-s)
(lo/acre-s)
(g'm2-s)
(lb/acre-s)
P-29
0.0161
0.144
0.0112
0.100
P-30
0.00168
0.0150
0.000970
0.00866
P- 31
0.0191
0.170
0.0101
0.0901
P-32
0.00231
0.0206
0.000343
0.00842
P- 33
0.0274
0.245
0.0157
0 140
P-34
0.00605
0.05^0
0.00303
0.0270
e-35
0.00278
0.0248
0.00185
0.0155
191
-------
TASLE 10-8. WIND EROSION TEST RESULTS - EXPOSED GROUND AREAS
Run
Emi ssion
rate
Suspended
particulate
InnalaHe
Darticulate
(g/m2-s)
(lb/acre-s)
(g/m*-w
(lb/acre-s)
J-29
0.00160
0.0143
0.00108
0.00964
J-30a
•
•
•
-
K-35
0.0368
0.329
0.0245
0.219
K-36
0.00120
0.0107
0.000822
0.00734
K-37
0.00693
0.0618
0.00458
0 0409
K-49
0.0337
0.301
0.0222
0.198
K- 50
0.000782
0 00698
0.000652
0.0C582
P-36
0.0161
0.144
0.0101
0.0901
P-37
0.0305
0.272 ,
0.0130
0.170
P-33
0.0602
0.537
0.0377
0 336
P-39b
-
-
-
-
P-40
0.116
0.104
0.00755
0 0674
P-41b
-
-
-
-
a No particle size data available.
b Emissions consisted entirely of particles larger than 11.6 m" aerodynamic
diameter.
192
-------
SP emission rate (lbs/acre-s)
Source
No. tes*.s Mean Std. dev. Range
Coal piles
On pile, uncrusted
On pile, crusted
Surrounding pile
16
7
4
0.318 0.439
0.0521 0.0415
0.754 1.054
0.0150-1.52
0.00964-0.113
0.0303-2.27
Exposed ground areas
0.264 0.195
0.0143
0.142 0.160
0.104-0.537
0.0143
0.00698-0.329
Soil, dry
Soil, wet
Overburden
4
1
5
It can be seen that natural surface crusts on coal piles are effective,
in mitigating wind-generated dust emissions. In addition, emissions from
areas surrounding piles appear to exceed emissions from uncrusted pile
surfaces but are highly variable.
With reference to the rates measured for exposred ground areas,
emissions from more finely textured soil exceed emissions from overburden.
As expected, the presence of substantial moisture in the soil is effective
1n reducing emissions.
Examinations of the conditions under which tests were conducted
indicates (1) an Increase in emission rate with wind speed and (2) a
decrease in emission rate with time after onset of erosion. This must
be considered in comparing emission rates for different source conditions.
PROBLEMS ENCOUNTERED
The only significant problem in this phase of the study was the
unforeseen resistance of selected test surfaces to wind erosion. Thres-
hold velocities were unexpectedly high and occasionally above the maximum
tunnel wind speed. This occurred primarily because of the presence of
natural surface crusts which protected against erosion. As a result,
the testing of many surfaces was limited to determination of surface
roughness heights.
Although testing of emissions was Intended to be restricted only to
dry surfaces, the occurrence of snowfall at Mine 1 provided an interesting
test condition for the effect of surface moisture. This helps to better
quantify the seasonal variation 1n wind-generated emissions.
193
-------
SECTION 11
RESULTS fOR SOURCE TESTED BY QUASI-STACK SAMPLING
SUMMARY OF TESTS PERFORMED
Overburden drilling was the only source tested by the quasi-stack
method. A total of 30 tests were conducted—11 at the first mine, 12
at the winter visit to the first mine, and 7 at the third mine. No
drilling samples were taken a' t". second mine because the overburden
was not shot, and hence not dnI ed, at that mine. No testing was done
for coal drilling because it was not judged to be a significant source.
Sampling was done on the downwind side of the drill platform; the
enclosure was to contain all the plume coming from beneath the platform.
Four isokinetic samp1iriy heads were located across the far side of the
enclosure. Each collected particulate matter in a settling chamber and
on a filter. Because of the proximity of the sampling inlets to the
source (2 to 3 m), the assumption was made that the filter catch was
the suspended material and the settling chamber was the settleable
material.
Test conditions for the drill tests are summarized in Table 11-1.
Testing took place over a wide range of drilling depths (30 to 110 fit)
and soil silt contents (5.? to 26.8 percent), so these can be evaluated
as correction factors. However, there was very little variation in the
moisture contents of the samples. No determination was made whether
this was due to the undisturbed overburden material having a fairly
narrow range of moisture contents or whether it woS coincidence that all
moisture contents were in the range of 7 to 9 percent. In either case,
moisture content is not a candidate for a correction factor because of
the narrow range of observed values.
The wind speeds reported in Table 11-1 are not ambient speeds; they
are the average speeds measured by a hot-wire anemometer at the far end
of the enclosure. In general, they were much lower than ambient because
the wind was blocked by the drilling rig and platform. The speeds shown
In the tab!e are the averages for each sampling period of speeds *nd the
sampling heads were set at to sample Isokinetically. The four heads were
adjusted individually based on wind speed measurements taken at that point
1n the enclosure. Wind speed profiles were observed to be fairly uniform
across the enclosure, especially in comparison with traverses across a
stack.
194
-------
TABLE 11-1. TEST CONDITIONS FOR DRILLS
Test
Date
Start
tine
Sampli ng
duration,
minutes
Source
characteristics
Soil
proDerties
Meteorological
conditions
Depth,
feet
Drill
dia.r'/)
Silt,
%
Moisture,
%
Temp,
°F
Wind
speed,
m/s
Mine 1
1
7/31/79
11:00
12
45
12.5
26.8
7.7
85
1.5
2
7/31/79
12:30
17
45
12.5
2 6.8
7.7
90
1.1
3
7/31/79
12:58
10
45
12.5
26.8
7.7
91
1.5
4
7/31/79
13:15
7
45
12.5
26.8
7.7
91
J.5
5
7/31/79
13:40
8
45
12.5
26.8
7.7
93
1.0
6
8/16/79
9:00
29
75
12.5
23.3
7.2
67
0.5
7
8/16/79
9:45
35
75
12.5
23.3
7.2
73
0.5
8
8/16/79
10:15
34
75
12.5
23.3
7.2
74
1.3
9
8/16/79
11:00
37
75
12.5
23.3
7.2
75
1.5
10
8/16/79
12:00
34
75
12.5
23.3
7.2
73
1.8
11
8/16/79
13:30
39
75
12.5
23.3
7.2
70
1.5
Mine 1W
1
12/05/79
10:40
41
90
12.2
5.2
7.4
59
1.4
2
12/05/79
11:21
37
50
12.2
5.2
7.4
63
1.4
3
12/05/79
13:02
58
90
12.2
5.2
7.4
64
2.8
4
12/06/79
9:48
26
50
12.2
5.2
7.4
45
1.0
5
12/06/79
10:35
46
90
12.2
5.2
7.4
51
1.6
6
12/06/79
11:25
33
90
12.2
5.2
7.4
51
1.3
7
12/07/79
7:30
47
100
12.2
9.3
7.4
33
0.9
8
12/07/79
8:35
49
100
12.2
9.3
7.4
33
0.8
9
12/07/79
9:40
68
100
12.2
9.3
7.4
33
0.7
10
12/07/79
11:00
25
50
12.2
9.3
7.4
33
0.4
11
12/07/79
12:45
18
50
12.2
9.3
7.4
34
0.5
12
12/07/79
13:30
60
100
12.2
9.3
7.4
34
0.4
Mine 3
1
7/23/80
12:37
39
110
12.0
6.9
9.0
88
7.5
2
7/23/80
13:25
72
110
12.0
6.9
9.0
89
2.5
3
7/24/80
9:57
6
30
9.9
11.1
6.9
78
1.3
4
7/24/80
11:38
26
60
9.9
11.1
6.9
81
1.3
5
7/24/80
12:10
8
30
9.9
11.1
6.9
89
1.5
6
7/24/80
12:39
7
30
9.9
11.1
6.9
90
1.0
7
7/24/80
13:02
9
30
9.9
11.1
6.9
90
1.0
-------
RESULTS
The results of the drill tests are shown in Table 11-2. The values
labeled "filter" are suspended particulate, comparable to TSP emission
rates by other sampling methods. No smaller size fractions than suspended
particulate were obtained for this source. The filter catch averaged
only 14.2 percent of the total catch (filter plus settling chamber),
indicatino that most of the material emitted from the drill holes was of
large particle size, and therefore readily settleable. This appears to
be a reasonable finding, since a large portion of the emissions were
produced by an air blast as the drill first entered the ground.
The total emissions per test had much wider variation than the
suspended portion (filter catch). However, the total emission values
were not used for development of any emission factor, so this variation
was of little consequence.
The units for the TSP emission rates are lb/hole. The overall range
of emission rates was wide—0.04 to 7.29 lb/hole—but ranges for subsets
from the individual mine visits were considerably narrower. The
statistics for the three subsets by mine visit are:
Mine No. samples Mean, lb/hole Std dev Rangp
1 11 0.84 0.84 0.04-2.43
1W 12 1.98 1.21 0.06-3.38
3 7 4.73 1.95 1.79-7.29
None of the samples were outliers (more than two standard deviations
away) from the mean value of their subsets. The mean TSP emission rate
for the 30 samples was 2.20 lb/hole and the standard deviation was 1.97.
Only one value, 7.29, was more than two standard deviations away from
this mean. This distribution is prior to inclusion of correction factors,
which are expected to explain part ofi the observed variation In emission
rates.
PROBLEMS ENCOUNTERED
The quasi-stack sampling method had not been used previously on any
open fugitive dust sources similar toj those at surface mines. However,
the method worked well for sampling drilling emissions and only a few
problems were encountered. The most important problem was that part of
the plume sometimes drifted outside the enclosure when a change 1n wind
direction occurred. No method could be found to account for this 1n
estimating source strength, so it wasj Ignored In the calculations. The
effect of emissions escaping the enclosure was to underestimate actual
"emission rate,1 possibly by as much as' 20 percent (based on the maximum
-volume of-visible plume outsidethe enclosure).
196
-------
TABLE 11-2. APPARENT EMISSION RATES FOR DRILLING
(lb/hole)
Mine 1
Filter
Total
Mine 1W
Fi1ter
Total
Mine 3
FiIter
Total
1
1.18
6.75
1
0.76
5.80
1
3.06
21.07
2
0.20
0.75
2
3.38
43.46
2
7.29
35.23
3
0.24
0.81
3
2.57
144.93
3
4.65
12.72
4
0.04
0.28
4
1.95
23.52
4
6.48
22.18
5
0.17
0.47
5
2.54
111.72
5
4.04
15.92
6
0.11
1.92
6
2.91
44.34
6
1.79
9.96
7
0.33
7.61
7
3.35
66.50
7
5.84
26.47
8
1.56
24.31
8
3.05
40.71
9
1.98
50.31
9
2.23
34.86
10
2.43
41.01
10
0.53
2.09
11
0.95
12.69
11
0.06
1.04
12
0.45
3.88
-------
Another problem with the sampling method was that no particle size
data were obtained. Collection of millipore samples for microscopic
analysis was originally planned, but the oarticle size d.ita obtained
by microscopy in the comparability study oid nt agr^e well with that
from aerodynamic sizing devices.
A third problem was securing representative soil samples. As the
drilling progressed, soil brought to the surface sometimes changed in
appearance as different soil strata were encountered. Usually, a compo-
site of the different soils was collected to be sub-nit^d as t.ie soil
sample. However, the soil type discharged for *he longest period o'
time or multiple samples could have been taken. Also, there was no
assurance that soil sppearance was a good indicator of charges in its
moisture or :»ilt "ontent.
198
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SECTION 12
EVALUATION OF RESULTS
EMISSION RATES
A total of 2C5 tests were conducted during the four sampling periods
at three mines. The tests for each sou-ce were distributed fairly
uniformly across the three mines, as previously shown in Table 3-8,
despite difficulties in obtaining tests of particular sources at each
mine. The total number of tests for each source was based on sample
variance of data from the first two mines; required sample sizes were
calculated by the two-stage method described in Section 5.
As in any fugitive dust sampling effort, several problems were
encountered during the study:
Large average differences 1n concentrations were obtained for
collocated samples, indicating iriprecision of the sampling
techniques.
Inability to control the mining operations led to some tests in
which data hsd to be approximated or some operation cycles
excluded.
Handling problems with the dlchotomous filters may have contributed
to an underestimate of emission rates in some cases.
Representative soil samples could not be obtained for some tests
because of accessibility problems, etc., so moisture and silt
values from prior or later tests had to be substituted.
However, the errors Introduced by these problems appeared to be small
1n relation to the natural variance in emission rates of the sources as
a result of meteorology, mining equipment, operation, etc. In other
s-ords, selection of time and place for sampling probably had far more
Impact on the resulting emission rates than oroblems associated with
measurement of the rates.
The selection of mines may also have Influenced final emission
factors. Emission rates measured at Mines 1 and 2 were generally 1n
the same range. However, the emission rates measured at Mine 3 were
»n general outside the range of values frcm Mines 1 and 2. Correction
factors were used to explain the range In values so that the average
rates employed in determining the final emission factors would not be
blasec by the Hgh values from Mine 3.
199
-------
for all three mines, the relative standard deviations, a measure of
variation in the sample data, ranged from 0.7 to 1.5 for different sources.
Emission rates for most sources varied over two orders of magnitude in
sample size of 12 to 39. Similar variation was observed in some of the
independent variables thought to have an effect on emission rates.
The remainder of this section is devoted primarily to three aspects
of the test data—particle size distribution, deposition, and effectiveness
of control measures. The evaluation of the independent variables and
their effect on emission rates in discussed in Section 13.
PARTICLE SIZE DISTRIBUTIONS
Considerable effort was expended in the comparability study evaluating
three particle sizing methods—cascade impactors, dlchotomous samplers,
and microscopy. The comparison of methods, presented in Section 6, showed
that the cascade impactors and dichotomies samplers gave approximately
the same particle size distributions. In contrast, the microscopy data
varied widely. It was concluded that microscopy is a useful tool for
semiquantitative estimates uf various particle types but is inadequate
for primary particle sizing of fugitive dust emissions.
Cascade Impactor Dota
As mentioned in Section 3, greased substrates were used in cascade
Impactors operated at the third mine to minimize particle bounce-through.
The effectiveness of this preventive measure was checked by comparing
the relative amounts of particulate catcb on the back-up filter and on
teh impactor substrates of cyclone/lmpactor sample with and without
greased substrates.
In Table 12-1, cyclone/lnpactor samples of uncontrolled emissions
from each source category at Mines 1 and 2 (where ungreased substrates
were used) are compared with samples of the same sources from Mine 3.
Sampling heights for the Impactor varied slightly by mine, which
Introduces another variaole into the comparison. It is evident from
Table 12-1 that greasing produces little change in the proportion of
material caught on the back-up filter. Only in the case of haul trucks
does a positive effect of greasing appear. On the other hand, the
single scraper emission sample collected at the third mine shows a
larger portion of partlcuSlte on the back-up filter. Although comparisons
of this type should ideally be based on collocated samplers, no readily
Identifiable pattern for the effect of greasing emerges from this
comparison.
200
-------
TABLE 12-1. COMPARISON OF SAMPLE CATCHES ON GREASED AND
UNGREASED IMPACTOR SUBSTRATES
Source
Mine
Sampling
height, a
No. of
runs
Mean ratio of
back-up filter catch
to substrate catch
Scrapers
1
2.0
3
0.245
2
2.5
4.
0.254
3
1.5
la
0.419
Graders
2
2.5
5
0.367
3
1.5
2
0.361
Light- and
1
2.0
3
0.315
medi urn-duty
2
2.5
4
0.350
vehicles
3
1.5
3
0.380
Haul trucks
1
2.0
4
0.339
2
2.5
5
0.314
3
1.5
3
0.245
a It may be significant that this run had the lowest emission rate of the
scraper tests.
Note: Samples at Mines 1 and 2 were collected on ungressed substrates; samples
at Mine 3 were collected on greased substrates.
201
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Dichotomous Sampler Data
At the outset of the study, it was hypothesized that, as the larger
particles fell out of the plume downwind of a mining source, the fraction -
of the remaining suspended particulate less than 15>um and less than
2.5jum would increase. Further, it was expected that only a small per-
centage of the particulate generated by a source would be in the less
than 2.5 ,um range. The test data obtained from the dichotomous samples
supported both of these hypotheses.
While the data produced the expected results, there were several
inherent limitations in the sampling technique that were discovered
during the study. These were: the small sample weights collected for
the fine particle samples; the low ratio of net weight to tare weight
of the filter media; and the variable particle size cut point of the
inlet.
The small sample weights on the fine filters were attributed to
two causes: the low volume of air collected and the small amount of
particulate less than 2.5 jm present in the plumes. Since the flow rate
of the sampler was so low, 1.0 m^/h, only a small amount of mass was
collected when the concentrations were low. The net weight of the
particulate collected on the fine quality assurance in weighing. These
net weights were only a small fraction of the tare weight of the filter.
Consequently, the potential weighing error was much higher for the
dichotomous filters than for hi-vol filters, which collect a much greater
mass. However, the number of filters checked that exceeded the 100/jg
tolerance in weighing was almost the same for dichotomous filters (5 of
281) as it was for hi-vol filters (7 of 774), which had an allowable
tolerance of 3.0 mg.
An associated problem was the filter media itself. The dust particles
did not adhere well to the Teflon surface. Rather, the particulate
remained on the surface of the filter where it was easily dislodged.
Extensive quality assurance procedures were implemented for the handling
of the filters to minimize particle losses. These procedures were
discussed in Section 4.
The light loadings on the fine filter stages presented additional
problems during the calculation procedures. A negligible mass on the
fine filters resulted 1n a negligible concentration. For the upwind-
downwind sampling, 25 percent of all the fine filters had calculated
concentrations of zero. There was little variation 1n this number
between sources. The individual percentages ranged from 18 to 30
percent. The problem was further complicated when upwind concentrations
were substracted from downwind concentrations. An additional 10 to
20 percent of the fine concentrations:became negligible after accounting
for upwind concentrations.
202
-------
These negligible values, by themselves, were not a problem. The
data sinply indicated that there were no measureabls emissions in the less
than 2.5 ;um size range. However, the particle size cut point of the
inlet is dependent on wind speed (Wedding 1980). Consequently, measured
coarse concentrations had to be corrected to a 15 ;um cut point. This
adjustment was based on an assumed lognormal distribution of particles
in the 2.5 to 30 pm range. In order to determine the 15 jum value, a con-
centration different from zero was needed for the less than 2.5 jjm size.
As discussed in Section 5, the concentration resulting from the minimum
detectable mass was substituted for anv negligible downwind concentrations.
This substitution had the effect of artificially raising the fine
particulate concentration for each source. This change resulted in an
increase in average FP concentrations of about 10 percent.
Even though there were problems with the dichotomous sampler data,
this sappier was chosen for generating the final particle size data for
several reasons:
1. During the study design, the dichotomous sampler was the
EPA method of choice for selective particle size sampling.
As such, it is considered state-of-the-art for ambient
particle size measurements.'
2. The cascade lmpactor could not be conveniently used. Data
from the comparability studies showed tnat comparison of
dichotomoi'S sampler and cascade impactor results was
reasonable. However, no upwind impactor data were generated.
Also, PEDCo did not use any impactors.
3 Both contractors used the same type of dichotomous sampler.
As shown in Section 6, the dichotomous sampler produced
internally consistent results. Therefore, it was expected
that particle size data generated by both contractors would
be consistent.
4. Based on the results of the comparability studies, the
dichotomous sampler gave the most consistent results of
the three method evaluated.; Extensive project resources
were expended to fine the most valid particle sizing
method. Special quality assurance procedures were
developed and Implemented to control problems in the
data.i The precision of collocated dichotomous samplers
and the number of filters that exceeded the quality
assurance tolerance 1n weighing {5 out of 281) were about
the same as that for h1-vols (7 out of 774).
203
-------
Particle Size Distribution Data
The average fraction of particles less than 15 jum and less than
2.5 yum are shown in Table 12-2. The data for each source are expressed
as fractions of TSP for upwind-downwind tests and as fractions of SP
(less than 30 jum diameter particles) for profiling and wind tunnel tests.
These fractions were calculated from the raw test results presented in
in Sections 6 through 11.
As shown in the table, IP fractions are reasonably consistent. They
vary from 0.30 to 0.67. The FP/TSP ratios have a much wider variation,
from 0.026 to 0.196. The 0.196 value for overburden dozers appears to
be an anomaly. Excluding this value, the range is from 0.026 to C.074.
The high overburden dozer ratios are due to the assumption of minimum
detectable concentrations on the fine filters combined with low TSP
concentrations for most of ~"'¦lese tests.
Also evident from the table is that tne standard deviation values
are generally higher for sources measured with the upwind/downwind
technique as opposed to the profiler technique. This difference is
inherent in the sampling configurations. Upwind/downwind data are
generated from multiple downwind distances and are the average of several
points. In contrast, profiler data are gathered at a single point 5 m
from the source.
DEPOSITION
Data for quantifying deposition were generated in three ways:
1. For 48 profiling tests, deposition was measured by collocated
dustfall buckets at 5, 20, and 50 m downwind of the source.
2. For 77 upwind-downwind sampling tests, deposition was deter-
mined by apparent source depletion with distance. Measure-
ments were made at four downwind distances at a maximum distance
of 200 m downwind of the source.
3. For 10 comparability tests, exposure profiling and upwind-
downwind samplers were run on a common source so that
simultaneous measurements by these methods could be compared.
Downwind distances were 5, 20, and 50 m.
Dustfall
A consistent reduction in dustfall rates with distance from the
source was found In 38 of 48 successful exposure profiling tests. The
average difference between collocated dustfall buckets was 42.6 percent.
204
-------
TABLE 12-2. PARTICLE SIZE DISTRIBUTIONS BASHD ON NET CONCENTRATIONS
Source
n
Average
IP/TSP
Std. dev.
of IP/TSP
Average
FP/TSP
Std. dev.
of FP/TSP
Blasting
18
0.44
0.28
0.051
0.039
Coal loading
24
0.30
0.15
0.030
0.035
Dozer, coal
12
0.49
0.24
0.031
0.033
«v»ertvrJe>i
Dozer,
14
0.54
0.54
0.196
0.218
Dragline
19
0.32
0.22
0.032
0.040
Light- and
medium-duty
vehicles
11
0.65
0.16
0.074
0.078
Scrapers0
14
0.49
0.07
0.026
0.021
Graders3
7
0.48
0.10
0.055
0.041
Haul trucks3
28
0.52
0.08
0.033
0.037
Coal storage piles3
27
0.61
0.08
Expused areas3
10
0.67
0.06
a Expressed as ratios of SP (suspended particulate, <30 pm) rather than TSP.
205
-------
The dustfall rates for each test were converted to equivalent depletion
factors (ratio between the apparent emission rate, Qx, at a distance x
downwind and the initial emission rate, Q0) by a four step procedure:
!. Total dustfall from 5 m to 20 m and from 20 m to 50 m was
calculated by multiplying the average dustfall rate over
each distance times the distance. The resulting total dustfall
values were in units of mg/m-min.
2. The initial emission rate for each test corresponding to the
dustfall rates was total particualte (TP). The TP emission
rate was converted from lb/VMT to mg/tf-min, using the number
of vehicle passes and the sampling duration of the test.
3. The total dustfall values for each distance were divided by
the initial emission rate to determine the fraction of TP
emissions deposited over that distance.
4. The depletion factor, or fraction of initial emissions
remaining airborne, for TP to any distance (20 to 50 m in
thic case) was 1.0 minus the total fraction deposited
by that distancp.
The calculated depletion factors for each profiling test in which
dustfall measurements were taken (excluding the comparabi1ity tests)
are shown in Table 13-3. Deposition, measured as dustfall and expressed
as a fraction of initial emissions, appeared to be very uniform from
test to test and from source to source. This was evident from the low
standard deviations compared to mean values.
The deposition rates by test were correlated with several potential
variables such as wind speed and particle size distribution. These
analyses did not reveal any significant relationships that could form
the basis for an empirical deposition function.
Apparent Source Depletion
Consistent source depletion oven the three or four downwind sampling
distances was evident in only 13 of 77 upwind-downwind tests. The average
depletion factors at all downwind distances were substantially greater
than 1.0 (indicating plume enhancement rather than depletion).
The average TSP depletion factors for each source sampled by the
upwind-downwind method are presented 1n Table 12-4. Every one of the
sources except haul roads displayed an increase 1n apparent emission
rates with distance.
.206
-------
TABLE 12-3. DEPLETION FACTORS CALCULATED FROM DUSTFALL MEASUREMENTS
Depletion factor
Depletion factor
Source/
(Q„/Qn)
Source/
(QVQn)
test No.
At 20 m
At 50 m
test No.
At 20 m
At 50 m
Haul trucks
Light-duty veh.
Jll
0.84
0.76
J13
0.95
0.92
K1
0.91
0.79
J18
0.97
0.97
K6
0.91
0.84
J19
0.96
0.91
K7
0.87
0.68
K2
0.96
0.91
K8
0.94
0.93
K3
0 97
0.93
K9
0.95
0.93
K4
0.92
0.81
KIO
0.88
0. 7a
K5
0.92
0.80
Kll
0.89
0.78
Pll
0.92
0.87
K12
0.90
0.77
P12
0.89
0.84
K13
0.92
0.88
Average
0.940
0.887
K26
0.94
0.92
Std. dev.
0.028
0.060
LI
0.95
C. 92
L2, L3, L4
0.98
0.97
Scrapers
PI
0.94
0.89
K15
0.92
0.86
P2*
0.82
0.50
K16
0.98
0.93
P4
0.99
0.98
K17
0.78
0.72
P5
0.98
0.96
K18
0.82
0.76
P6
0.93
0.80
K22
0.85
0.69
P7
0.98
0.96
K23
0.93
0.85
P8
0.99
0.99
L5, L6
0.99
0.98
P9
0.99
0.99
Average
0.896
0.827
Average
0.929
0.856
Std. dev.
0.081
0.109
Std. dev.
0.050
0.124
Graders
K19
0.88
0.73
K20
0.92
0.75
K21
0.84
0.62
K24
0.78
0.51
K25
0.84
0.65
P16
0.80
0.66
P17
0.95
0.90
Average
0.859
0.689
Std. dev.
0.062
0.122
Avg. of 44 tests
0.914
0.831
* Test had 2 bad passes.
-------
The standard deviations of the depletion factors displayed two
characteristics: relative standard deviations (RSD) consistently in-
creased with distance from the source; and the RSD values were fairly
high, indicating much variation in results from the individual tests.
Interestingly, the haul road tests had similar depletion rates to
the comparability tests (which were conducted on haul roads arid scrapers)
when differences in wind speed were considered. This observation led to
another comparison—between tests in which the source was sampled as a
line source and those in which it was sampled as a point source. The
15 line source tests had average depletion fetors less than 1.0, but
did not demonstrate continuing deposition with increasing distance. In
contracts, the point source tests had average depletion factors of i.36,
1.35, and 1.52 at three successive distances from the source. The IP
data could not be effectively analyzed for source depletion because
dichotomous samplers were plered at only the first two distances in all
upwind-downwind tests after the comparability tests.
Comparability Study
A discussion of deposition data from the comparability studies is
contained in Section 6. Data are summarized in Figure 6-7. Dustfall
data were not meaningful because of data scatter. For exposure profiling,
the 30 um depletion factors at 20 m and 50 m were found to be 103 percent
(source enhancement) and 55 percent. Corresponding TSP data for upwind-
downwind sampling was found to be 87 perce .t and 56 percent. The data
for 50 m from both measurement techniques indicated considerably greater
source depletion than was found in 44 exposure profiling tests with
dustfall measurements (Table 12-3).
Comparison of Sources of Deposition Data
Data analyzed with respect to deposition were dustfall buckets from
profiling tests; sou~ce depletion from upwind-downwind tests; and pro-
filing data from the comparability study. These analyses did not reveal
any significant relationships that could form the basis for an empiri-
cally derived deposition function. Because these analyses were ncn-
prodictive and the primary method of measuring deposition (apparent source
depletion in upwind-downwind sampling) gave unstable results, a deposition
function cannot be presented at this time. However, several conclusions
can be drawn.
Based on experience gained from this study, 1t 1s recommended that
future dustfall measurement be performed with the following considerations:
1. Dustfall measurements at various distances downwind of the
source should be accompanied by a coincident upwind measurement
that is subtracted as a background value. Dustfall data for a
208
-------
TABLE 12-4. DEPLETION FACTORS FOR UPWIND-DOWNWIND TESTS
Tests
Pt or
line
No.
tests
TSP depletion factor
Average
stability
class
Average
wind
speed,
m/s
20-
40 m
50-
70 m
80-
100 m
Coal loading
P
25
1.63
1.40
1.63
B-C
2.3
Dozer, avb.
P
11
1.04
1.20
1.28
B-C
3.3
L
4
0.90
0.99
1.40
B-C
2.3
Dozer, coal
P
7
0.96
1.60
1.46
W
3.5
L
5
1.19
1.22
1.33
c-o
4.7
Dragline
P
19
n. d.
1.32
1.61
c
3.6
Haul trucks
L
6
0.78
0.79
0.64
D
5.0
All uw.-dw.
P
62
1.36
1.35
1.52
C
3.5
(except compar.}
L
15
0.81
0.98
0.98
C
4.2
209
-------
test should be invalidated if the upwind sample is impacted by
the source as a result of wind reversal.
2. The measurements should be done in duplicate to reduce error
and so that the precision of the measurement can oe assessed.
3. Measurements should be taken at distances greater than 50 m
to quantify the continuing fallout of particles. However,
at greater distances, collection of a detectable mass of
dustfall during a short sampling period may be a problem.
The principal shortcoming of the technique is that the data presented
are for total particulate, which in general are of less interest than
TSP or IP data.
The upwind-downwind source depletion data which indicated source
enhancement in the majority of tests was misleading. Poor results
have been attributed to three main causes.
First, many of the sources tested by upwind-downwind required
placement of the first row of sarrpiers at relatively large distances
from the source (30-60 m compared to 5-10 profiling). A large part
of the deposition may already have occurred prior to this first
distance, resulting in apparent emission rates of about the same
magnitude at the four downwind distances, rather than decreasing with
distance from an emission rate measured immediately downwind of the
source.
The second suspected cause was that reentrainment may actrally be
Increasing downwind concentrations. Mos\. of the source listed in
Table 12-4 were, by necessity, tested with the samplers placed on
recently-disturbed surfaces adjacent to the sources. Haul roads were
an exception, 1n that stable vegetated areas adjacent to the roads
could be selected as sampling locations.
The third suspected cause of an upward bias in emission rates
with distance was the point source dispersion equation. If equivalent
data are input to the point and line source dispersion equations, the
line source version will usually indicate a greater reduction in
apparent emission rates with distance. The sensitivity of calculated
emission rates to several parameters in the point source equation but
not in the line source equation were evaluated, but no single parameter
was Isolated that could be masking the reduction in apparent emission
rates with Increase in distance.
Because of these three identified problems, 1t is recommended that
additional deposition measurements be made on line sources where reentrain-
'ment nea.* downwind samplers 1s minimized.
210
-------
ESTIMATED EFFECTIVENESS OF CONTROL MEASURES
Two control measures for unpaved roails and mine areas were tested
as part of this study. The controls were calcium chloride/watering and
watering only. Table 12-5 summarizes the results obtained. No control
cost data were obtained.
At Mine 1, two tests of an unpaved access road treated with calcium
chloride were performed. According to plant personnel, calcium chlorite
(Dow Peladow) had been applied at a density of 0.6 gallon of 30 percent
solution per square yard of road surface, approximately three months
prior to testing. This road was watered four times each day to main-
tain the effectiveness of the calcium chloride. Watering occur-
-------
TABLE 12-5. CALCULATED EFFICIENCIES OF CCNTROL MEASURES
Source
Control
measure
SPa/IP/FP
Measured emission rates, lb/MT^
Mean control
efficiency, X
Uncontrolled
Controlled
Access road
Calciur.i
SP
5.5, 8.2, 6.7
0.35
95
(Mine 1)
chloride
IP
4.5, 6.6, 5.2
0.34
95
FP
0.50, 1.5, 0.22
0.09
88
Haul road
Watering
SP
6.4, 4.4, 4.5, 6.0
2.2, 2.5, 0.60, 3.4
59
(Mine 2)
IP
3.3, 2.3, 2.3, 3.2
1.1, 1.3, 0.40, 1.8
61
FP
0.15, 0.18, 0.19, 0.23
0.07, 0.10, 0.10, 0.06
58
Haul road
Watering
SP
20.6, 6.3, 24.1, 14.1
5.1, 1.8, 8.4, 4.3, 5.G
69
(Mine 3)
IP
14.7, 3.2, 11.5, 6.3
2.2, 1.0, 4.1, 2.1, 2.5
73
FP
0.29, 0.20, 0.14
0.05, 0.11, 0.15, 0.10,
0.07
54
Coal loading
Watering
TSP
0.120, 0.082, 0.193,
0.051, 0.010, 0.009,
78
(Mine 3)
0.358, 0.188
0.014, 0.035, 0.062,
0.058, 0.095, 0.042
IP
0.044, 0.008, 0.038
0.016, 0.002, 0.001,
81
0.121
0.006, 0.008, 0.012,
0.014, 0.020, 0.011
FP
0.0038, 0.0005, 0.0033
0.0022, 0.0002, 0.0001,
68
0.0035
0.0001, 0.0012, 0.0012,
0.0005, 0.0005, 0.0021
? SP 1s the <3C yin fraction, approximately equal to TSP.
Emission factors for coal loading are expressed in units of lb/ton.
-------
The 3fficiency values for watering of haul roads obtained 1n this
study (Table 12-5) were higher than the previously reported values and
the original estimate of 50 percent. The efficiency values for calcium
chloride are consistent with reported values of initial control effi-
ciency exceeding 90 percent for other chemical treatment measures:
lignin sulfonate applied to haul roads in a tacomte mine and petroleum
resin applied to a steel plant road (Cowherd, et al. 1979).
213
-------
SECTION 13
DEVELOPMENT OF CORRECTION FACTORS AND EMISSION FACTOR EQUATIONS
The method for developing correction factors was based on multiple
linear regression (MLR), as described in Section 5. To summarize the
method briefly, values for all variables being considered as possible
correction factors were tablulated by source with the corresponding
TSP eir.isison rates for each test, then the data were transformed to
their natural logarithms. The transformed da^a were in^i,t to the MLR
program, specifiying the stepwise option and permitting entry of all
variables that incr:?ased the multiple regression coefficient (initially
allowing the program to determine the order of entry of the variables).
The W.R output of greatest interest with the significance of each
variable. In nontechnical terms, significance is the probability that
the observed relationship between the Independent and dependent vari-
ables Is due to chance. If the significance was less than 0.05, the
variable was Included as a correction factor; if it was between 0.05
and 0.20 , its inclusion was discretionary; and if above 0.20, the
variable was not Included. The correction factors were irultlplicati ve
because of the In transformation; the power for each significant
correction factor was specified in the MLR output. as the coefficient
(B value) for that variable in the linear regression equation.
This MLR analysis could not be employed with data from the wind
erosion sources because sequential tests were found to be related and
were grouped, thus reducing the number of Independent data points.
Mith the large number of potential correction parameters in relation
to data points, regression analysis was not feasible.
MULTIPLE LIMEAR REGRESSION ANALYSIS
The stepwise multiple linear regression program that is the nucleus
of the correction factor deveopment procedure Is explained In moderate
detail In Appendix A. Further Information on It can be found 1n the
following three references; Statistical Methods, Dcurth Edition
(Snedecor 1946); Applied Regression Analysis (Draper and Snrtth 1965);
and SPSS, Second Edition (N1e 1975).
214
-------
The independent variables that were evaluated as possible correction
factors are listed in Table 13-1. An assessment was made during the MLR
analysis to determine the portion of the total variation in the emission
factors explained by the correction factors (multiple regression coefficient
squared) and whether additional variables should have been considered. The
data for each of these variables were presented in tables thi oughout
Sections 7 through 11, and have not been repeated here.
The dsta were all transformed to their natural logarithms prior to
running MLR. The presumption that the In transformation would provide
better final emission factor equations was based on three considerations:
the data sets all had high relative standard deviations indicating that
the distributions of the emission factor were skewed to the right
(i.e., a long upper tail); the homogeneity of variances (a condition
for any least squares analysis) was increased; and multiplicative cor-
rection factors were preferable to additive ones.
More than one MLR was usually required to obtain the final MLR
equations with its associated significance and regression coefficients
(B values). Second and third runs were neeeded to eliminate a data
point shown to be an outlier, to remove a variable highly correlated
with another, to remove a variable with significance of 0.05 to 0.20
that entered the stepwise regression ahead of another variable still
being evaluated, or to eliminate a dummy variable (such as a source
subcategory or control/no control) after Its significant had been
determined. The sequence of MLR runs with the TSP data for each
source 1s documented by presenting in Table 13-2 the results of the first
run for each source (with all the variables included), a description in
Table 13-3 of all changes made to get to the final run, and in Table
13-4 the results of the final run.
The multiple regression (correlation) coefficient, R, is a measure
of how well the variables In the equation explain variations in emission
rate. (Actually, R^ Is the portion of the total variation explained
by the use of the specified variables). Significance, the seco.id re-
ported statistic, estimates the change that the observed correlation
for a particular variable is due to random variation. Finally, the
residual relative standard deviation measures the amount of variability
left In the transformed data set after adjustment as Indicated by the
regression equation. In the transformed data set, the mean logarithmic
values can be quite small. Consequently, the relative standard devia-
tions are larger than normally encountered in regression analysis.
Several Independent variables were fairly significant (less than
0.20) when they entered the regression equations, but were not included
as correction factors In the final emission factors. The reasons for
omitting these potential correction factors are explained below, by
source:
215
-------
TABLE 13-1. VARIABLES EVALUATED AS CORRECTION FACTORS
Source
SdtTlpl 6
size
Variables evaluated
Units
Drill, overburden
30
Silt
Moisture
Depth of drilling
%
%
ft
Blasting
IB
Material blasted (coal
or overburden)
No. of holes
Area blasted
Depth of holes
Moisture
Distance to samplers
Wind speed
Stability class
f?b
ft
%
m
m/s
Coal loading
25
Equipment type
Bucket size
Moisture
yd3
%
Dozer
27
Material worked
Dozer speed
Silt
Moisture
Wind speed
fliph
%
%
m/s
Dragline
19
Orop distance
Bucket size
Silt
Moisture
ft
yds
%
%
Scrapers
15
Silt
Weight
Vehicle speed
Wheels
Silt loading
Moisture
Wind speed
%
tons
mph
g/m2
%
m/s
Graders
7
c
c
Light- and medium-
duty vehicles
10
c
c
Haul trucks
27
c
c
a Uncontrolled runs only.
0 Originally reported 1n metric units the variable values were
converted to engllsh units.
c Same as for scrapers.
216
-------
TABLE 13-2. RESULTS OF FIRST MULTIPLE LINEAR REGRESSION RUNS (TSP)
Source
Variable (in order
of MLR output)
Multiple
R
Signif-
icance
Rel.
std.
dev.
9.54
Drill
Silt
0.51
0.004
8.35
Moisture
0.53
0.421
8.40
Depth
0.53
0.719
8.54
0.515
Blasting, all
Area blasted
0.73
0.001
0.363
Moisture
0.79
0.077
0.337
Depth of holes
0.90
0.002
0.246
Wind speed
0.91
0.248
0.242
No. of holes
0.93
0.163
0.232
Material blasted
0.93
0.300
0.230
Dist. to samplers
0.94
0.589
0.238
Stability class
0.94
0.910
0.250
0.596
Blasting, coal3
Moisture
0.82
0.000
0.353
Areas blasted
0.90
0.022
0.287
Wind speed
0.92
0.143
0.269
No. of holes
0.94
0-123
0.247
Depth of holes
0.94
0.608
0.257
Stability class
0.94
0.523
0.267
Dist. to samplers
0.95
0.662
0.2e3
0.414
Coal leading, all
Equipment type
0.74
0.000
0.287
Moisture
0.77
0.097
0.275
Bucket size
0.89
0.000
0.203
0.492
Coal loading.
Moisture
0.80
0.000
0.306
front-eno loader
Watering
0.90
0.001
0.230
0.762
Dozer, all
Material worked
0.66
0.000
0.582
Moisture
0.91
0.000
0.331
Silt
0.92
0.040
0.308
Dozer speed
0.95
0.004
0.260
Wind speed
0.95
0.477
0.263
0.458
Oozer, coala
Silt
0.97
0.000
0.112
Moisture
0.98
0.139
0.103
Dozer speed
0.98
0.625
0.108
(continued)
217
-------
TABLE 13-2 (continued)
Rel.
Variable (in order
Multiple
Signif-
std.
Source
of MLR output)
P.
icance
dev.
0.8£7
Dozer, overburden3
Moisture
0.78
0.001
0.566
Silt
0.87
0.029
0.471
Dozer speed
0.91
0.072
0.417
0.416
Drag!ine
Drop distance
0.74
0.000
0.208
Moisture
0.85
0.004
0.229
Silt
0.86
0.365
0.230
Bucket size
0.87
0.147
0.236
0.526
Scrapers (all
Weight
0.68
0.022
0.407
uncontrolled)
Moisture
0.80
0.076
0.350
Wheels
0.85
0.232
0.336
Silt
0.94
0.028
0.235
Vehicle speed
0.96
0.187
0.212
Silt loading
0.97
0.318
0.206
Wind speed
0.97
0.734
0.235
16.933
Graders (all .
Silt loading
0.40
0.500
17.909
uncontrolled)
Vehicle speed
0.63
0.471
18.614
Wheels
0.96
0.226
9.144
6.562
Light- and medium-
Moisture
0.97
o.oco
1.741
duty vehicles (all
Weight
0.99
0.005
3.019
uncontrolled)
Wheels
0.99
0.349
1.017
Silt
0.99
0.681
1.093
Silt loading
1.00
0.133
0.890
Wind speed
1.00
0.202
0.749
0.788
Haul trucks
Vehicle speed
0.51
o.ou
0.693
(includes uw.-dw.
Wind speed
0.72
0.003
0.573
tests, all
Moisture
0.89
0.000
0.390
uncontrolled)
Silt loading
0.91
0.039
0.357
Wheels
0.91
0.701
0.365
Weight
0.92
0.318
0.364
Silt
0.92
0.886
0.375
A
This source was evaluated initially as a subset of the entire data set and
^ was not carried through the subsequent data analyses.
Weight, moisture, silt, and wind speed were rejected in the first MLR
because of an insufficient tolerance level.
Vehicle speed was rejected because of an insufficient tolerance level.
218
-------
TABLE 13-3. CHANGES MADE IN MULTIPLE LINEAR REGRESSION RUNS (TSP)
Source
Change made
Run
No.
Reason
Drill
Remove two data points
2
Outliers
Blasting, all
Specify moisture as first
variable
2
Moisture had R = 0.72 vs.
area with R = 0. 73
Coal loading, all
Eliminate bucket size, add
control
Remove one data point
2
3
Bucket size was to the 12.3
power
Outlier
Dozer, all
Remove one data point
2
Outlier
Dragline
Remove one data point
2
Outlier
Scraper
Drop wheels, moisture, and
silt loading
Add moisture; remove aniso-
kinetic runs; drop wind
2
3
Wheels did not vary appre-
ciably, moisture and silt
loading difficult to
quantify
Moisture needs to explain
low emissions at mine.
Four anisokinetic runs
(low winds) eliminated
Graders
Drop wheels, weight, mois-
ture, and silt loading
2
Wheels and weight did not
vary appreciably, moisture
and silt loading difficult
to quantify
Light- and medium
duty vehicles
Haul trucks
Drop wind speed, vehicle
speed, anisokinetic
runs
Remove K-7 and L-l
2
3
Three anisokinetic runs (low
winds) eliminated, vehicle
speed correlation incon-
sistent with previous
studies
Outlier and run unrepre-
sented by vehicle mix
219
-------
TABLE 13-4. RESULTS OF FINAL MULTIPLE LINEAR
DEGRESSION RUNS (TSP)
Rel. std.
Source
Variable
Multiple R
Significance
dev.
5.30
Drill
Silt
0.59
0.001
4.36
0.515
Blasting, all
Moisture
0.72
0.001
0.367
Depth
0.84
0.009
0.300
Area
0.90
0.012
0.246
0.341
Coal loading, all
Moisture
0.67
0.000
0.258
Control
0.77
0.012
0.227
0.774
Dozer, all
Material worked
0.67
0.000
0.587
Moisture
0.93
0.000
0.298
Silt
0.95
0.005
0.253
Dozer speed
0.97
0.003
0.210
0.389
Dragline
Drop distance
0.80
0.000
0.241
Moisture
0.91
0.001
0.172
Silt
0.93
0.043
0.153
0.647
Scrapers
Silt
0.70
0.036
0.494
Weight
0.93
0.006
0.271
Vehicle speed
0.96
0.111
0.225
Moisture
0.96
0.634
0.243
2.013
Graders
Vehicle speed
0.83
0.022
1.237
Wind speed
0.87
0.333
1.212
Silt
0.90
0.451
1.252
6.562
Light- and
Moisture
0.97
0.000
1.741
medium-duty
Height
0.99
0.005
1.019
vehicles
Wheels
0.99
0.349
1.017
Silt
0.99
0.681
1.093
Silt loading
1.00
0.133
0.890
Wind speed
1.00
0.202
0.749
0.540
Haul trucks
Wheels
0.66
0.002
0.416
Silt loading
0.72
0.146
0.400
Weight
0.80
0.036
0.355
Silt
0.82
0.324
0.355
Moisture
0.82
0.458
0.360
220
-------
Drills/Silt - This variable was hiqhly significant but was inversely rather
than directly related to emission rate. Therefore, the last potential
correction factor for this source *s eliminated; the reported emission
factor is simply the geometric mean of the observed values.
Blasts/ No. of holes - This variable was highly correlated with another
independent variable, area blasted, which entered the regression
equation before number of holes.
Coal loading/Bucket size - Bucket size was related to emission rate by a
power of -12.3 in the regression equation, primarily because of the
very narrow range of bucket sizes tested—14 to 17 yd^. Also, bucket
size only had a correlation of 0.05 with emission rate.
Dozer, all/Dozer speed - Although equipment speed was significant in the
combined data set, it was not significant in either of the subsets
(coal dozers or overburden dozers).
Dragline/Silt - In the first run, silt was not a significant variable.
However, when an outlier was removed, it became highly significant
but was inversely rather than directly related to emission rate
Scrapers/Vehicle speed - This parameter was significant at the 0.111
level, in the discretionary range. It was omitted because of its
high correlation with silt which entered the equation earlier.
Light- and medium-duty vehicles/Weight This was omitted to preserve
the simplicity of the resulting equation in light of the high
correlation between emission factor and moisture, the first para-
meter entered.
Haul trucks/Vehicle speed - Inverse relationship with emission rate was
Inconsistent with all previous studies.
Haul trucks/Weight - This parameter was! omitted because it coefficient
was negative, which is difficult to justify from the physics of the
problem.
These relationships conflicted with previous experience in fugitive
dust testing . While the actual relationship may be similar to that
Indicated by the MLR equation, some confirmation 1n the form of additional
data was thought to be needed before including these dubious parameters
as correction factors.
The transformations, initial MLR runs, adjustments, and additional
MLR runs were done by the same procedures with the IP emission data as
with the TSP data, using the same values of the independent variables.
221
-------
The results are summarized in an analogous series of three tables—
Tables 13-5, 13-6 and 13-7. As indicated in Table 13-6, very few changes
were required from the initial runs of the IP data, with the benefit
of the prior TSP runs. For every source, the same independent variables
were highly significant for IP as for TSP.
EMISSION FACTOR PREDICTION EQUATIONS
The prediction equations obtained from the MLR analyses are summarized
in Table 13-8. These equations were taken directly fro mthe MLR runs
described in Tables 13-4 and 13-7, with the coefficients in the Table
13-8 equation:, being the exponentials of the MLR equation constant terms
and the exponents for each term being the B values. These equations give
estimates of the median value of the emission factors for given value(s)
of the correction factor(s). (The coefficients and exponents are from
the intermediate MLR step that includes only the significant variables
that appear in the final equatijn.) All but four of the independent
variables in the equations in Table 13-8 are significant at the 0.05
level or better. The four variables in the discretionary range (0.05
to 0.20) that were included are: L in haul truck TSP equation, a =
0.146; A in the coal basting IP equation, a = 0.051; M in the overbjrden
IP equation, a = 0.71; and S 1n the grader IP equation, a = 0.078. The
geometric mean values and ranges of the correction factors are summarized
in Table 13-9.
CONFIDENCE AND PREDICTION INVERVALS
A computational procedure for obtaining confidence and prediction
Intervals for emission factors is described in Appendix B at the end of
this volume of the report. An example of this computation is given here
for coal loading emission data versus the moisture content correction
factor.
I
Figure 13-1 summarizes the results of this example and also Includes
the observed emission factors. The line in the center of the graph is
the predicted median emission rate estimated by the goemetric mean. The -
inside set of curves give the confidence interval for the "true median"
as a function of moisture content (M), and the outside set of curves
give the prediction Interval for an individual emission factor. The
Intervals vary 1n lenqth as a function of M. The widths of the intervals
are measures of the precision of the estimated factors. These precisions
are comparable to those of existing emission factors as illustrated in
Section 14.
222
-------
TABLE 13-5. RESULTS OF FIRST MULTIPLE LINEAR REGRESSION RUNS (IP)
Variable (in order
Multiple
Signif-
Rel. std.
Source
of MLR output)
R
icance
dev.
Drill
N/A
9.54
0.753
Blasting, all
Moisture
0.81
0.015
0.367
Depth of holes
0.88
0.040
0.330
Area blasted
0.92
0.000
0.451
Wind speed
0.93
0.210
0.321
No. of holes
0.94
0.225
0.312
Material blasted
0.95
0.272
0.307
Dist. to samplers
0.95
0.313
0.305
Stability class
0.95
0.841
0.323
0.933
Blasting, coal3
Moisture
0.86
0.000
0.490
Areas blasted
0.91
0.050
0.421
No. of holes
0.93
0.146
0.392
Wind speed
0.94
0.202
0.373
Dist. to samplers
0.96
0.248
0.360
Stability class
0.96
0.489
0.373
0.235
Coal loading, all
Moisture
0.49
0.017
0.210
Control
0.66
0.017
0.185
Equipment type
0.67
0.576
0.189
1.569
Dozer, all
Material worked
0.71
0.000
1.132
Moisture
0.91
0.000
0.683
Silt
0.94
0.006
0.579
Dozer speed
0.97
0.001
0.449
0.682
Dozer, coala
Moisture
0.91
0.000
0.291
Silt
0.96
0.012
0.213
Dozer speed
0.96
0.420
0.216
8.262
Dozer, overburden3
Silt
0.77
0.004
5.550
Moisture
0.85
0.071
4.830
Dozer speed
0.87
0.290
4.756
0.259
Dragli ne
Moisture
0.49
0.032
0.232
Drop distance
0.69
0.015
0.197
Silt
0.72
0.281
0.196
Bucket size
0.73
0.582
0.200
(continued)
223
-------
TABLE 13-5 (continued)
Source
Variable (in order
of MLR output)
Multiple
R
Signif-
icance
Rel. std.
dev.
0.987'
Scrapers (all
Weight
0.71
0.015
0.735
uncontrolled)
Moisture
0.81
0.094
0.647
Wheels
0.86
0.173
0.600
Silt
0.93
0.058
0.469
Vehicle speed
0.96
0.086
0.371
Silt loading
0.98
0.238
0.341
Wind speed
0.98
0.737
0.386
0.906
Graders (all
Silt
0.30
0.626
0.998
uncontrolled)
Wheels
0.65
0.397
0.975
Silt loading
0.87
0.442
0.883
1.977
Light- and medium-
Silt loading
0.97
0.000
0.526
duty vehicles
Silt
0.98
0.043
0.410
(all uncontrolled)
Vehicle speed
0.99
0.010
0.243
Wind speed
1.00
0.044
0.170
1.991
Haul trucks
Vehicle speed
0.40
0.046
1.861
(includes uw.-dw.
Wind speed
0.64
0.006
1.600
tests, all
Moisture
0.84
0.000
1.153
uncontrolled)
Silt loading
0.84
0.695
1.177
Wheels
0.84
0.754
1.235
Weight
0.85
0.609
1.228
Silt
0.85
0.724
1.259
a This source was evaluated initially as a subset of the entire data set and
was not carried through the subsequent data analyses.
224
-------
TABLE 13-6. CHANGES MADE IN MULTIPLE LINEAR REGRESSION RUNS (IP)
Source
Change made
Run No.
Reason
Blasting, all
None
Coal loading, all
None
Dozer, all
Remove one data point
2
Outlier
Dragline
None
Scrapers
Drop wheels, silt
loading, wind speed;
remove anisokinetic
runs
2
Wheels did not vary
appreciably, silt
loading difficult to
quantify; fcur aniso-
kinetic runs (low
winds) eliminated
Graders
Drop wheels, weight,
moisture, and silt
loading
2
Wheels and weight did
not vary appreciably;
moisture and silt
loading difficult to
quantify
Light- and medium-
duty vehicles
None
Haul trucks
Drop wind speed,
vehicle speed; remove
anisokinetic runs plus
K-7 and L-l
2
Three anisokinetic
runs (low winds)
eliminated. Vehicle
speed correlation
inconsistent with
previous studies.
L-i is outlier and
K-7 had unrepresenta-
tive vehicle mix
225
-------
TABLE 13-7. RESULTS OF FINAL MULTIPLE LINEAR REGRESSION RUNS (IP)
Source
Variable
Multiple R
Significance
Rel. std.
dev.
0.753
Blasting, all
Moisture
0.81
0.000
0.451
Depth of holes
0.88
O.Olo
0.376
Area blasted
0.92
0.040
0.330
0.235
Coal loading, all
Moisture
0.49
0.017
0.210
Control
0.66
0.017
0.185
1.676
Dozer, all
Material worked
0.70
0.000
1.230
Moisture
0.92
0.000
0.696
Silt
0.95
0.006
0.583
Dozer speed
0.98
0.000
0.405
0.259
Dragline
Moisture
0.49
0.032
0.232
Drop distance
0.69
0.015
0.197
1.706
Scrapers
Silt
0.67
0.046
1.346
Weight
0.90
G. 015
0.856
Vehicle spaed
0.96
0.036
0.580
3.439
Graders
Vehicle speed
0.70
0.078
2.680
Wind speed
0.81
0.246
2.478
Silt
0.89
0.254
2.220
1.977
Light- and
Moisture
0.95
0.000
0.667
medium-duty
Weight
0.99
0.005
0.382
vehicles
Silt
0.99
0.084
0.321
Vehicle speed
0.99
0.217
0.298
Silt loading
1 00
0.161
0.253
Wind speed
1.00
3.216
0.216
1.043
Haul trucks
Wheels
0.65
0.003
0.816
Weight
0.68
0.272
0.809
Silt loading
0.72
0.198
0.790
Silt
0.73
0.617
0.81U
Moisture
0.74
0.473
0.823
226
-------
TABLE 13-8. PREDICTION EQUATIONS FOR MEOIAN EMISSION RATES
Prediction equations
FP/TSP
ratios
Source
TSP
IP
mediae
value
Units
Drill
1.3
None3
Nonea
lb/hole
.lasting, all
951 A08
2550 A0,6
D1.8H1.9
d15h2-3
0.030
lb/blast
Coil loading
1.16/M1'2
0.119/M0'9
0.019
lb/ten
Dozer, all
Coal
78.4 s1-2/^'3
18.6 s1-5/^-4
0.022
lb/h
Overburden
5.V s1,2/M1,3
1.0 s^W-4
0.105
lb/h
Dragline
0.0021 d1-1/M°'3
0.0021 d°*7/M0'3
0.017
lb/yd3
Scrapers
(2.7x10'5)s13H2-4
(6.2xl0"^)s1'4W2'5
0.026
lb/VMT
Graders
0.040 S2,5
0.051 S20
0.031
Ib/VHT
Light- and medium-
duty vehicles
5.79/M40
3.72/M4-3
0.040
lb/VMT
Haul trucks
0.0067 w3-\0-2
0.0051 w3-5
0.017
lb/VMT
Test method allowed for measurement of TSP only.
s = silt content, % 2
A = area blasted, ft
0 = depth of holes, ft
M = moisture content, X
d = drop distance, ft
W - vehicle weight, tons
S 3 vehicle speed, mph
w 3 number of wheels -
L = silt loading, g/ta
227
-------
TABLE 13-9. TYPICAL VALUES FOR CORRECTION FACTORS
Source
Correction
factor
GMa
Range'*
Hin. Max.
Units
Blasting
Moisture
Depth
Area
17.2
25.9
18.BBS
7.2
20
1076
38
135
103,334
Percent
Ft2
Ft
Coal loading
Moisture
17.8
6.6
38
Percent
Dozers, coal
Moisture
Silt
10.4
8.6
4.0
S.O
22.0
11.3
Percent
Percent
ovb.
Moisture
Silt
7.9
6.9
2.2
3.8
16.8
15.1
Percent
Percent
Draglines
Drop distance
Moisture
28.1
3.2
5
0.2
100
16.3
Ft
Percent
Scrapers
Silt
Weight
16.A
53.8
7.2
36
25.2
70
Percent
Tons
Graders
Speed
7.1
5.0
11.6
e?ph
Light- and
medium-duty
vehicles
Moisture
1.2
0.9
1.7
Percent
Haul trucks
Wheels
Silt loading
8.1
40.8
6.1
3.8
10 0
2S4.0
Number
g/m*
GM = antilog {In ^correction factor)}, that is, the antilog of the average
k of the In of the correction factors.
Range is defined by alninum (Hin.) and oaxisium (Max.) values of observed
correction factors.
228
-------
0.35
951 CONFIDENCE LIMITS FOR MEDIAN E
95* PREDICTION LIMITS FOR E
ESTIMATED MEDIAN EMISSION RATE (EL-
MEASURED EMISSION RATES
0.30
0.25
> 0.20
0.15
0.10
0.05
MOISTURE, %
Figure 13-1. Confidence and prediction Intervals for etnl'sslon
factors for coal loading.
229
-------
To summarize the information contained in these curves for confidence
intervals, the following information is presented:
1. Prediction equation for the median emission factor from
Table 13-8: TSP, lb/ton = 1.16M1*?.
2. Geometric mean end range (maximum and minimum values) of
moisture content correction factor from Table 13-9: GM =
17.8 percent, 6.5 to 38 percent.
3. Estimated median emission factor at the geometric mean (GM)
of the correction factor from Table 13-10: 0.034 lb/ton.
4. Ninety-five percert confidence intervals for the median emission
factor (the medlar, value for a large number of tests over one
year) at the GM of each correction factor from Table 13-10:
0.023 lb/ton to 0.049 lb/ton.
5. Ninety-five percent prediction intervals for an individual
emission factor Approximately one hour) at »-he GM of the
correction factor from Table 13-10: 0.005 lb/ton to 0.215
lb/ton.
The confidence and prediction interval data are given on»y tor one
value of the correction factor(s) in order to simplify the presentation.
The widths of the intervals of the GM are Indicative of the widths at
other values provided one uses a percentage of the median value in deriving
the confidence and prediction limits. For example, for the coal loading
lata the lower confidence limits are approximately 50 to 70 percent of
the median value, the upper limits are 140 to 170 percent of the median
value; the lower prediction limits are 15 percent of the median value
and the upper limits are 630 percent (or 6.3 times) of the median value.
The coal loading data are slightly more variable than data for other
sources and hence the limits are proportionately wider than for the other
sources.
Fine particulate (FP) emission factors were not developed by the
same series of steps as were the TSP and IP factors, because of the larger
variances expected In these data sets and the many tests with negligible
readings. However, the relative standard deviations calculated from data
in Table 12-2 Indicate variability approximately the same as for TSP and
IP data. The geometric mean ratios of FP to TSP presented 1n Table 13-8
are proposed for use with the TSP emission factor equations to derive
FP emission factors. The FP emission factor 1s obtained by multiplying
the median FP/TSP ratio times the calcualted TSP emission factor for
each source.
230
-------
TABLE 13-10. EMISSION FACTORS, CONFIDENCE AND PREDICTION INTERVALS
Source
TSP/IP
Emission
factor,
tnedian
value
Units
95%
confidence
interval
for median .
LCLd UCLd
95% prediction
interval
for
emission
factor
LPL UPL
Drills
TSP
1.3
lb/hole
0.8 2.0
0.1 12.7
Blasting,
TSP
35.4
lb/blast
22.7 55.3
5.1 245.8
all
IP
13.2
8.5 20.7
2.0 87.9
Coal
TSP
0.034
lb/ton
0.023 0.049
0.005 0.215
loading,
IP
0.008
0.005 0.013
0.001 0.071
all
Dozers, all
TSP
46.0
Ib/h
35.5 59.6
18.1 117.0
coal
IP
20.0
13.2 30.4
4.5 90.2
ovb.
TSP
3.7
lti/h
2.6 5.3
0.91 15.1
If
0.88
0.59 1.3
0.21 3.7
Draglines
TSP
0.059
lb/yd3
0.046 0.075
0.020 0.170
IP
0.013
0.009 0.020
0.002 0.085
Lt.- and
TSP
2.9
lb/VHT
2.3 3.9
1.35 6.4
med.-duty
IP
1.8
1.6 2.0
0.64 5.0
vehicles
Graders
TSP
5.7
lb/VHT
3.2 9.9
1.14 28.0
IP
2.7
1.4 5.3
0.39 18.5
Scrapers
TSP
13.2
lb/VHT
10.0 17.7
5.2 33.1
IP
6.0
4.3 8.9
1.8 20.2
Haul trucks
TSP
17.4
lb/VHT
12.8 23.4
4.3 68.2
IP
8.2
5.7 11.0
1.8 33.7
These exact values from the MLR output are slightly different than can be
obtained from the equations In Table 13-8 and the correction factor values
^ 1n Table 13-9 due to the rounding of the exponents to one decimal place.
LCL denotes lower confidence Unit. UCL denotes upper confidence Halt.
231
-------
EMISSION FACTORS FOR WIND EROSION SOURCES
In nearly all of the tests of of wind erosion emissions from the surface
of coal piles and exposed ground area;, the SP and IP emission rates were
lOund to decay sharply with time. An exception was the sandy topsoil tested
at Mine 3; in that case, an increase in emission rate was observed, probably
because of the entrainnent effect cu' infiltration air as the loose soil
surface receded below the sides of the wind tunnel. The concept of erosion
potential was introduced in Section 5 to treat the case of an exponentially
decreasing quantity of erodible material on the test supface. The erosion
potential is tne total quantity o.' particles, in any specified particle
size range, present on the surface (per unit area) that can be removed by
erosion at a particular wind speed.
The calculation of erosion potential necessitated grouping of
sequential tests on th*» same surface. In effect, this reduced the number
of Independent data points for coal and overburden emissions from 32 to
16. As a result, the decision was made not to subject these data to
regression analysis because of the large number of potentially significant
correction parameters in relation to the number of emission measurements
for any given surface type and condition.
Table 13-11 lists the calculated values of erosion potential classified
by erodible surface type and by wind speed at the tunnel centerline. For
the most part, the test wlna speeds fit 1ntc 3-mph increments; values of
erosion potential for the few runs performed at other wind speeds are
listed under the nearest wind speed category. Whenever erosion potential
Is given as a range, the extremes represent two data points obtained at
nominally the same conditions.
Erosion potential was calculated using Equation 22 (Chapter 5), which
Is repeated here:
where
Mo » erosion potential, I.e., quantity of erodible material present
on the surface before the onset of erosion, g/m2.
232
-------
TABLE 13-11. CALCULATED EROSION POTENTIAL VERSUS WIND SPEED
Surface
Mine
T-sst series
1_ # :
fcrosion potential,
lb/acre
26 mph*
29 mph a
32 mph*
35 mph *
38 mph *
frnl
Area surrounding pile
1
J-26
> 140b
h
J-26 and 27
470
On pile, uncrusted
2
K-45 and 46
230
K-40 and 41
480
K- 39
550b
K-42 and 43
370
On pile, lightly
3
P-20
68b
crusted tracks
P-31 and 32
30
P-20 to 22
140
P-20 to 24
260.
P-31 to 35
130
On pile furrow
3
P-27 and 28
7.1
P-27 to 30
90
Overburden
2
K-35 and 3S
90b
K-37
40
Scoria (roadbed caterial)
2
K-49 and 50
100
? Wipd speed measured at a height of 15 cm above the eroding surface.
Estimated value.
Erosion l^ss may have occurred prior to testing.
-------
t = cumulative erosion time, s
= measured loss during time period 0 to t^, g/m2
Lg = measured loss during time period 0 to tg, g/m2
Alternatively, Equation 22 can be rewritten as follows:
(Eq. 22a)
An iterative calculation procedure was required to calculate erosion
potential from Equation 22 or 22a. Further, two cumulative loss values
and erosion times obtained from back-to-back testing of the same surface
were required. Each loss value was calculated as the product of the
emission rate and the erosion time.
For example, Runs P-27 and P-28 took place on a coal pile furrcw at
a tunnel centerline wind speed of 36 mph. The incremental losses were
calculated as follows:
P-27: 0.0386 g/m2-s x 120 s = 4.63 g/m2
P-28: 0.00578 g/m?-s x 480 s = 2.77 g/m2
Thus the values substituted into Equation 22 for this test series were:
Lj a 4.63 g/m2
tj « ICO s
L2 = 4.63 + 2.77 = 7.40 g/m2
t2 = 120 ~ 480 -= 600 s
A value of Mq = 10 was selected and substituted into the rlght-hana
side of equation 22a and the left-hand side was solved for Mq. The
resulting value of 7.75 was then substituted back Into the right-hand
side to obtain a new solut1on--7.48. Additional substitutions were made
and the iteration procedure converged quickly to 7.46 for erosion potential
(M0), indicating that only a s.nall additional loss (0.06 g/m2) would have
occurred if the tunnel had been operated beyond the 600-s time period at
the same wind speed. The corresponding nonmerlc value for the erosion
potential Is 67 lb/acre, which rounds to 70 lb/acre.
234
-------
Data from unpaired runs (J-26, J-27, K-39, P-20, and K-37) were used
to derive estimated values of erosion potential. Except for J-26, the
erosion times were long enough so that the measured losses approximated
the corresponding erosion potentials.
Note that whenever a surface was tested at sequentially increasing
wind speeds, the measured losses from the lower speeds were added to the
losses at tne next higher speeds and so on. This-reflects the hypothesis
tnat, if the lower speeds had not been tested beforenand, correspondingly
greater losses would have occurred at the higher speeds.
The emissions from the coal pile at Kine 3 appear to be significantly
lower than the coal pile emislsons measured at Mines I and 2. the coal
pile at Mine 3, which had been inactive for a period of days, was
noticeably crusted; but attempts were made to test areas where reiativ;ey
fresh vehicle tracks were present. It is not known what percentage of
the erosion potential of these test areas may have been lost because of
brief periods of high winds which typically occurred with the evening
wind shift. The coal pile furrow tested at Mine 3 had a much greater
portion of large chunks of coal (exceeding 1 inch in size) on the surface,
1n comparison with the scraper and truck tracks.
The uncrusted overburden and scoria surfaces tested at Mine 2 exhibited
emission rates that were much lower than the coal surfaces tested, expect
for the coal pile furrow. This reflects the larger portion of noneroaiDie
coarse aggregates present on these non-coal surfaces.
The wind speeds that were used in the testing (Table 13-11), which
exceeded the threshold for the onset of visually observable emissions,
corresponded to the upper extremes of the frequency distributions of hourly
mean wind speeds observed (at a height of 5-10 m) for most areas of the
country. For flat surfaces, the wind speed at the center!ine of the wind
tunnel, 15 cm above the surface, is about half the value of the wind
speed at the 10 m reference height. However, for elevated pile surfaces,
particularly on the windward faces, the ratio (ui5+uref) may approach
and even exceed unity. It should be noted that small but measureable
erosion may have occurred at the threshold velocity.
In estimating the magnitude of wind generated emislsons, wind gusts
must e'so be taken Into account. For th«? surfaces tested, typically
about three-fou.*ths of the erosion potential was emitted within 5 min of
cumulative erosion time. Therefore, although the mean wind speeds at
surface coal mines will usually not be high enough to produce continuous
wind erosion, gusts may quickly deplete the erosion potential over a
period of a few hours. Because erosion potential Increases rapidly with
Increasing wind speed, estimated emissions should be related to tne yuats
of highest magnitude.
235
-------
The routinely measured meteorological variable which best reflects
the magnitude of wind gusts is the fastest mile. This quantity represents
the wind speed corresponding to the whole mile of wind movement which has
passed by the 1-mile contact anemometer in the least amount of time. Daily
measurements of the fastest mile are presented in the monthly Local CI Histo-
logical Data (LCD) summaries. The duration of the fastest mile, typically
about 2 min (for a fastest mile of 30 mph), matches well with the half
lift of the erosion process, which ranges between 1 and 4 min^
Emissions generated by wind erosion are also dependent on the frequency
of disturbance of the erodible surface because each time that a surface is
disturbed, its erosion potential is restored. A disturbance is defined
as an action which results in the exposure of fresh surface material.
On a storage pile, this would occur whenever aggregate material is either
added to or removed from the old surface. A disturbance of an exposed
ground area may also result from the turning of surface material to a
depth exceeding the size of the largest pieces of material present.
Although vehicular traffic alters the surface by pulverizing surface
material, this effect probably does not restore the full erosion potential,
except for surfaces that crust before substantial wind erosion occurs.
In tnat case, creaking or tne crust over the area ut tne uiie/surrace
contact once again exposes the eroaiDie material Deneath.
T s emission factor for wind generated emissions of a specified
particle size range may be expressed in units of Ib/acre-month as follows:
Emission Factor = f'P(u+i5) (Eq. 29}
where f = frequency of disturbance, per month
P(u+j5) = erosion potential corresponding to the observed
(or probable) fastest mile of wind for the
period between disturbances, after correcting
the fastest mile to a height of 15 cm (as
described below), lb/acre.
P(u+ic) Is taken directly from Table 13-11 for the type of surface being
considered. Interpolation or limited extrapolation of erosion potential
data may be required.
When applying Equation 29 to an erodible surface, a modified form of
Equation 18 (page 84) 1s used to correct the fastest mile of wind from
the reference anemometer height at the reporting weather station to a
height of 15 cm. The correction equation 1s as follows:
236
-------
+
u,r = u.
K)
*15 " ref
+ ' 2_1 (Eq. 30)
lnfref '
zo
where u+i^ = corrected value of the fastest mile, mph
uref = value of the fastest mile measured at the reference
height, mph
^ref = height of the reference anemometer above ground, cm
hsurf = height of the eroding surface aoove yrounu, cm
z0 = roughness neignt or tne erouiny surTace, cm
An estimated value of the roughness height for the surface being considered
may be obtained from Table 13-12.
Equation 30 is restricted to cases for which href - hsurf 15 cm.
Because the standard reference height for meteorological measurement is
10 m, this restriction generally allows for piles as flat upper surfaces
as high as about 9.85 m and conical piles as hign as 19.7 m. However,
there may be situations which do not conform to the above restriction; for
example, when ths meteorological measurement height is as low as 5 m. As
a default value for these cases, u^5 is set equal to uref, I.e., no height
correction is made for the measured fastest mile.
Values of hsurr- In Equation 30 reflect the extent to which the eroding
surface contour penetrates the surface wind layer. Clearly for flat ground
surfaces, hsurf = 0. For an elevated storage pile with a relatively
flat upper surface, hsurf represents the height of the upper surface above
grouna. For conical shaped piles, one-half the pile height is used as a
first approximation for hsurf. In the case of elevated storage pile
surfaces, the emission factor equation (Equation 29) is expressed per
unit area of contact between the pile and the ground surface.
To illustrate the application of Equation 29, the following hypothetical
example 1s offered. A coal surge pile planned for a new mine development
will have a relatively flat roper surface with an average height of 6 m.
The pile will be disturbed at nearly regular intervals every 3 months by
adding coal to or removing coal from the surface using trucks ana Truni-
end loaders. During periods between disturbance, it 1s antlclpatea that
light crusting will occur. The fastest mile data for the nearest weather
station 1s shown 1n Table 13-13, representing a 5-year length of record.
237
-------
TABLE 13-12. SURFACE AND EMISSION CHARACTERISTICS
Surface
Mine
Roughness
height, cm
Threshold
speed, mph
IP/SP
ratio
Coal
Area surrounding pile
1
0.01
21
0.62
On pile, uncrusted
2
0.3
25
0.68
On pile, lightly
crusted tracks
3
0.06
20
0.55
On pile furrow
3
0.05
33
0.60
Overburden
2
0.3
23
0.68
Scoria
2
0.3
30
0.75
238
-------
TABLE 13-13. HYPOTHETICAL MONTHLY WIND DATA PRESENTED
IN LCD FORMAT
Wind
Resultant
Fastest mile
Month
Direction
Speed,
mph
Avg. speed,
mph
Speed,
mph
Direction
Date
January
21
0.5
7.8
32
NW
17
February
27
2.2
9.2
34
NW
23
March
27
1.9
10.9
47
N
11
April
04
0.3
8.7
38
S
10
May
17
3.9
10.8
37
sw
18
June
16
2.3
8.9
35
N
26
July
16
1.0
7.9
35
SW
9
August
13
1.4
7.5
31
w
30
September
20
1,9
9.0
45
NW
23
October
17
1.1
7.5
37
NW
7
November
22
0.7
9.2
34
W
26
December
28
2.4
9.1
41
W
24
239
-------
The height ot the reference meteorological instrument is 8.0 m above the
ground.
To derive the annual average emisison factor, the year is divided into
quarterly periods. The fastest mile for each period is determined, and the
average value is calculated. From Table 13-13, the 3-month fastest mile
values of 47, 38, 45, and 41 mph yield an a-'erage of 43 mph. Next, Equation
30 is used to correct the average fastest mile from the reference heignt
of 8 m to 15 cm above the 6-m height of the upper pile surface. A value
of 0.06 cm is used as the roughness height for a lightly crusted coal
pile surface, as taken from Table 13-12. Substitution ot these aata into
Equation 30 yields:
In
In
15
+ . _ 0.06 A _ «
U15 = 4 800-600~ ~ mp
0.06
From Table 13-11. tne SP erosion potential for 29 mph on a lightly crusted
coal pile is 140 lb/acre. Substitution into Equation 29 yields:
SP emission factor - 5^25. x ^40 - 45 —
mo acre acre-mo
Using the appropriate IP/SP ratio from Table 13-12, the corresponainy IP
emission factor is 46 x 0.55 = 25 lb/acre-mo.
One notable limitation in the use of Equation 29 is its application
to active piles. Because the fastest mile is recorded only once a day,
use of the daily fastest mile to represent a surface disturbed more thar.
once per day will result in an over-estimate of emissions.
The approach outlined above for calculation of emission factors appears
to be fundamentaly sound, but data limitations produce a large amount of
uncertainty in the calculated factors. Even though the erosion potential
values are judged to be accurate to within a factor or two or oetter for
the surface tested, it is not known how wen these sunaces represent the
range of erodible surface conditions found at Western surface coal mines.
Additional uncertainty results from the use of Equation 30 to correct the
fastest mile values to a height of 15 cm above the erodible surface.
Taking all the sources of uncertainty into account, it is tnougnt that the
wind erosion emission factors derived for surfaces similar tc those testea
are accurate to within a factor of aboL.c three.
The levels of uncertainty 1r. SP and IP emission factors derived by
the technique outlined in this section could be reduced substantially by
gathering more data to better define:
240
-------
1. Relationship of erosion potential to wind speed.
2. Relationship between approach wind speed and the distribution
of surface wind speed around basic pile shapes of varying size.
3. Relationship of erosion potential to surface texture.
4. Effect of crusting.
Previous research on wind erosion cf natural surfaces could provide
some insight into the nature of these effects. Soil loss resulting from
wind erosion cf agricultural land has been the subject of field and
laboratory investigation for a number ot years. This research has
focused on the movement of total soil mass, primarily sand-sized aggre-
gates, as a ^unction of wind and soil conditions (Bagncld 1941; C^epi'l
and Woodruff 1963). Only relat1vel> recently, howe»"vr, have field
measurements been performed in an effort to quantify fine particle emissions
produced during wind erosion of farm fields (Gillette and BUfford 1972;
Gillette 1978).
Until further research is accomplished, 1t is recomrended tnat wind
erosion factors be used with full consideration of their uncertainty and
preliminary nature. It is recommended that their use be restricted to
estimates of emissions relative to other mine sources and that they not
be used for estimating the ambient air impact of wind erosion at surface
coal mines.
241
-------
SECTION 14
EVALUATION OF EMISSION FACTORS
COMPARISON WITH PREVIOUSLY AVAILABLE EMISSION FACTORS
As noted in Section of this report, a number of TSP emission factors
for surface coal mining operations were available in the published litera-
ture prior to this study. However, only those factors reported by the
U.S. Environmental Protection Agency (1978a) were based on actual testing
in surface coal mines. Other investigators (Cowherd et al. 1979, McCalden
and Heidel 1978, and Uyck and Stukel 1976) have reported emission factors
for vehicular traffic on unpaved roads expressed in the form of predictive
equations. Their factors were not developed with any data from surface
ccal mines, but were based on field data from unpaved roads of similar
characteristics.
Cowherd et al. (1979) used the exposure profiling method to develop a
predictive emission factor equation for vehicular traffic on unpaved roaus.
Their equation was developed from measurement of emissions from a wide
range of vehicle types (weighing from ?. to 1 b7 tons) traveling on rural
roads, roads at steel plants, and haul roads at a taconite mine.
The emission factor equation developed by McCalden and Heidel (1978)
was developed from upwind-downwind tests of light-duty vehicles traveling
on five unpaved roads In the Tucson, Arizona area. The downwind samplers
were located 50 feet from the test roads.
Dyck and Stukel (1976) used the upwind-downwind sampling method to
measure emissions from a single 4-1/2 ton flat-bed truck traveliny over
access roads at construction site in Illinois. Vehicle weight was varied
by placing sand bags on the truck bed. Downwind samplers were located at
SO to 150 feet from the test road.
Table 14-1 compares emission factors from the present study with
emission factors reported by tPA and those reported by the other Investigators
cited above. The factors listed for the present study are medians of the
TSP emission factors measured for each source category. The factors listed
by EPA (1978a) are averages of those reported for each of the five mines
tested.
242
-------
TABLE 14-1. TSP EMISSION FACTOR COKPARISOh
Emission
TSP emission factor
Source
factor,
units
This study3
U.S. EPA, 1978a
Other Studies
Drills, ovb.
lb/hole
1.3
1.5
-
Blasting
lb/blast
35.4
55
-
Loading, coal
lb/ton
0.037
0.036
-
Dozers, coal
lb'h
46.0
-
-
Dozers, ovb.
lb/h
3.7
-
-
Dragline
1 b
0.059
0.027
-
Scrapers
lb''MT
13.2
-
35.4 (Cowherd et a 1.1974)
Graders
lb '"NT
5.7
-
6.1 (Cowherd et al.1979)
Light- and
medium-duty
vehicles
lb VMT
2.9
•
2.2 (Cowherd et a..1979)
2.9 (McCalden and
Heider 1978)
Haul trucks
lb7 MT
17.4
14.1
42.8 (Cowherd et ai.1979)
38.0 (Dyck and Stukel
1976)
* Geometric mean (GM) emission factor for correction factors at their GM
values, Table 13-9.
243
-------
The other factors listed for unpaved roads were calculated from the
respective emission factor equations, using the necessary average cor-
rection parameter values obtained in the present study.
In three of five cases, the average emission factor obtained 1n
this study is essentially the same as that reported by EPA in 1978. The
factors obtained for access roads are about the same as those calculated
from the predictive equations of other investigations. However, the
factors obtained in the present study for haul trucks, scrapers, and
graders are smaller than those calculated from the predictive equations
of other investigators.
STATISTICAL CONFIDENCE IN EMISSION FACTORS
Confidence intervals associated with the emission factors were pre-
sented In Table 13-10. They are shown again, expressed as fractions of
the corresponding emission factors, 1n Table 14-2. Also shown 1n this
table are the relative errors predicted in Table 4 of the Second Draft
Statistical Plan (June 1980). (For purposes of calculation, the half-
width of the confidence Interval divided by the median is equal to the
relative error.) Comparison of the 80 percent confidence Intervals and
20 percent risk level relative errors reveals that the actual confidence
intervals were smaller, and therefore better, than the estimated or
predicted error levels 1n 7 out uf 10 cases. These results were achieved
because correction factors were able to explain a large portion of the
sample variance for almost every source.
The confidence intervals as a fraction of the emission factor averaged
about -0.20 to +0.24 at the 80 percent confidence level and about -0.30
to +0.43 at the 95 percent confidence level. In comparison, 12 of the
most widely used particulate emission factors in EPA's Compilation of Air
Pollutant Emission Factors, AP-42 (1975), had an average 80 percent con-
fidence interval of j^O.28 and an average 95 percent confidence Interval
of +0.45, according to a published analysis of AP-42 factors (PEOCo
Environmental 1974). Information extracted from Table 2-12 of the
published analysis Is presented In Table 14-3. Considering the greater
variability Inherent In emission rates for fugitive dust sources than for
most industrial process or combustion sources, the mining emission factors
reported herein appear to be on a par with factors In AP-42 that have been
given a ranking of A.
With the confidence intervals achieved for all sources, additional
sampling using the same techniques to Improve precision of one or more
factors does not seem to be warranted. However, it should be noted that
these emission factors are still limited In their applicability to Western
mines and to the ranges of correction parameter conditions over which the
present tests were conducted. Also, the number of mines represented Is
small (only three), hence, the mine to mine differences are not yet fully
documented.
244
-------
TABLE 14-2. HALF-WIDTH OF CONFIDENCC INTERVALS COMPARED
TO MEDIAN TSP EMISSION FACTOR
Half-width confidence interval/
median emission factor
Source
80%
95%
Relative er-or pre-
dicted in statistical
plan (20% risk level)
Drills
-0.25, +0.29
-0.35, +0.50
0.20
Blasting
-0.24, +0.30
-0.36, +0.56
0.36
Coal loading
-0.22, *0.30
-0.32, +0.51
0.32
Dozers, coal
-0.15, +0.17
-0.23, +0.30
0.31
Dozers, ovb.
-0.20, *0.25
-0.30, +0.44
0.31
Oraglinc
-0.15, +0.15
-0.22, +0.27
0.21
Haul truck
-0.18, +0.21
-0.27, +0.36
0.19
Light- and
medium-duty veh.
-0.13, +0.16
-0.22, +0.27
0.45
Scraper
-0.16, +0.19
-0.25, +0.34
0.24
Grader
-0.28, +0.33
-0.43, +0.76
•
0.27
Average
-0.20, +0.24
-0.30, +0.43
0.29
8 Due to the logarithmic transformation used In the analysis, the Intervals
ore not symmetrical when presented in base^.
245
-------
TABLE 14-3. EVALUATION OF WIDELY-USED PARTICULATE EMISSION FACTORS
FROM AP-42
Half-width of
confidence
interval
Source
Emission
factor, EF
Accuracy
ranking
No. of
tests, n
Precision,
s/EFv^"
80%
95%
Pulv. coal wet
boiler
13A
A
89
0.029
0.04
0.06
Pulv. coal dry
boiler
17A
A
34
0.049
0.06
0.10
Spreader stoker
13A
A
17
0.132
0.18
0.28
Asphaltic concrete
dryer
45
A
5
0.123
0.19
0.34
Brick curing, gas
0.07
C
3
0.230
0.43
0.99
Brick curing, oil
0.07
C
6
0.204
0.30
0.52
Brick curing, coal
1.30
C
14
0.255
0.34
0.55
Cement kiln, dry
46
B
10
0.206
0.28
0.47
Cement kiln, wet
42.8
B
12
0.236
0.32
0.52
Clay drying
70
A
2
0.018
0.06
0.23
Lime rotary kiln
200
B
4
0.263
0.43
0.84
Refinery FCC
242
A
2
0.785
2.42
9.98
Average
16
0.211
0.28
0.45
Source: Columns 2, 4, and 5, PEDCo Environmental,1974
Columns 1 and 3, AP-42
246
-------
PARTICLE SIZE RELATIONSHIPS
Emission factors were developed specifically for the IP and TSP size
ranges, with full data analyses being devoted to each. Because of data
analysis problems associated with the very low concentrations of FP, the
emission factors for this size fraction were not calculated by profiling,
upwind-downwind dispersion equations, etc. Instead, net concentrations for
all tests were expressed as a fraction of TPS; the geometric mean fraction
for tests of each source was applied to the TSP emission factor for that
source to calculate the FP emission factor.
The suspended particulate (SP) emission factors from profiling tests
are not actually TSP, but the fraction of total emissions less than 30 Ajm
in aerodynamic diameter. Several references in the literature cite 30 /im
as the approximate particle size for 50 percent collection efficiency by
the hi-vol sampler. Since TSP is not a clearly defined size distribution,
this was the best approximation that could be made from the profiling
samples, which collect all particle sizes in the plume nondiscnminately.
From the median emission factors for IP and TSP (Table 13-10), size
distributions of emissions appeared to be fairly uniform from source to
source. IP and TSP ratios varied from 0.22 to 0.62. The IP to TSP
emission factor ratios were similar to those of the IP to TSP net concen-
trations (shown in Table 12-2), but were not the same because of the
independent MLR analyses employed to develop the emission factors for
TSP and IP. Also, the emission factor ratios *re based on geometric
rather than arithmetic means. The IP to TSP ratios were lower than
typical in ambient air. However, these ratios were measured at the
sources. As the {missions proceed downwind, greater deposition of the
TSP fraction should increase the ratio.
The FP and TSP emission factor ratios »*re derived directly from
the geometric mean ratios of their net concentrations, and are the same
as were shown in Table 13-8. One of the sources had a ratio that was an
'apparent anomally--overburn dozers, with an FP to TSP ratio of 0.105.
Overburden dozer tests were usually conducted with no visible plume and
low downwind concentrations, with accompanying potential for particle
size distributions skewed toward smaller particles. With the exception
of this source, the range of median FP to TSP ratios by scarce was 0.017
to 0.040.
For the two sources that constitute the majority of emissions at
most mines, haul trucks and scrapers, the average FP to TSP ratios were
0.017 and 0.026, respectively. Because mining emissions are mechanically
generated dust, a low percentage of fine particualte would be expected
In the TSP emissions. It is not possible to compare the size distri-
bution data from this study with that from previous fugitive dust sampling
studies because particle size sampling problems make previous data suspect.
247
-------
Recognizing that there are still several unresolved problems with generating
fine particle data for fugitive dust sources, it is concluded that data from
the present study are reasonable based on their consistency arid the observed
agreement between dichotomous and cascade impactor data.
HANDLING OF DEPOSITION
The emission factors in Table 13-10 were all developed from sampling
right at the source. The present test data and information from numerous
other studies indicate fairly rapid deposition of these emissions as they
n.ove away from th3 source. Therefore, any ambient air quality analysis
using these emission factors should have some provision for considering
deposition or fallout.
Different subsets of tests and alternative measurement techniques
(dustfall and apparent source depletion as discussed in Section 12)
produced greatly varying deposition rates with distance, from no
deposition to an average of 79 percent reduction in TSP in the first
100 m. Only a small part of the differences :ould be explained by
parameters such as wind speed and stability class. The net result
of the large discrepancies was that test data from the study could
not be used to develop a deposition function for application with the
emission factors. An empirically-derived function would have been
limited to about the first 200 m anyway.
Stlectlon from among available theoretical deposition models is
outside the scope of this study, especially since none of the three
that were cowpared with test data matched well in the majority of the
tests. Of the three theoretical deposition functions, the tilted plume
model is the most simplistic and shows the most rapid deposition over
the firft several km. The other two models, source depletion and
surface depletion, display similar rates and represent supposed options
between computational ease and greater accuracy. According to a
published review of the two modesl, source depletion overestimates
deposition at all distances 1n comparison with the more accurate
surface depletion functions (Horst 1977). However, for the distances
and emission heights of interest in mining analyses, the reported
differences were minimal (less than 10 percent).
248
-------
All *hree deposition modesl require an estimate of settling velocity,
a value usually not available. From the brief analysis of observed
deposition rates shown in the table on Page 6-28, possible values are
2 cm/s for Lhe IP fraction and 10 cnt/s for TSP.
249
-------
SECTION 15
CONCLUSIONS AND RECOMMENDATIONS
SUMMARY OF EMISSION FACTORS
Emission facators for 12 significant sources of particulate emissions
at surface coal mines were developed from extensive sampling at three
different Western mines. Five sampling techmques--exposure profiling,
upwind-downwind, balloon sampling, wind tunnel testing, and quasi-stack--
were used on the 12 different source types, to best match the advantages
of a particular sampling technique to the characteristics of a source.
Sampling was conducted throughout the year so that measured emission rates
would be representative of annual emission rates. The resulting emission
factors are summarized in Table 15-1.
The factors for TSP and IP are in the form of equations with corrections
factors for independent variables that were found to have a significant
effect (at the 0.146 or better risk level) on each source's emission rates.
The ranges of independent variables (correction factors) over which sampling
was conducted, and for which the equations is valid, are shown in Table 15-1.
The units for the emission factors and correction factors were selected
for ease in obtaining annual activity rates and average parameter values,
respectlvely. The equations are also appropriate for estimating short-
term emission rates. For any correction factor that cannot be accurately
quantified, a default value equal to its geometric mean (GM) value can be
used, see Table 13-9. For each source, the FP emission factor is obtained
by multiplying the calculated TSP emission factor by the FP fraction shown
in Table 15-1.
The 80 and 95 percent confidence intervals for each of the TPS and IP
emission factors, based on sample sire and standard deviation, were
previously presented in Table 13-10. The average 80 percent confidence
Interval for TSP was -20 to +24 percent of the median value. By comparing
confidence intervals for the present emission factors with those for
factors published by EPA in their Compilation of <*.ir Pollutant Emission
Factors, AP-42 (1975), 1t was determined that the present factors should
receive an A ranklng.
250
-------
TABLE 15-1. SUMMARY OF WESTERN SURFACE COAL MINING EMISSION FACTORS
Source
TSP/IP
Prediction equation
for emission factor
FP fraction
of TSP
Units
Range of correction
parameters
Drills
TSP
1.3
None
lb/hole
None
Blasting
TSP
IP
961 A0,8
d1.8 h1-9
2550 A06
01.5 m2.3
0.030
lb/blast
A
M
0
=
2
area blasted, ft
1076 to 103,334
moisture, %
7.2 to 38
depth of holes, ft
20 to 135
Coal loading
TSP
IP
1.16/M12
0.119/M0,9
0.019
lb/ton
M
-
6.6 to 38
Dozers, coal
TSP
IP
78.4 sL2/M1,3
18.6 s15^1-4
0.022
lb/h
s
M
=
silt content, %
6.0 to 11.3
4.0 to 22.0
Dozers, ovb.
TSP
IP
5.7 s1,2/M13
1.0 s15/^4
0.105
lb/h
s
M
=
3.8 to 15.1
2.2 to 16.8
dragline
TSP
IP
0.0021 d^/M0-3
0.0021 d0,7/M0'3
0.017
lb/yd3
d
M
=
drop distance, ft
5 to 100
0.2 to 16.3
(continued)
-------
TABLE 15*1 (continued)
Source
TSP/IP
Prediction equation
for emission factor
FP fraction
of TSP
Units
Range of correction
parameters
Scrapers
TSP
IP
(2.7xl0~5) s^V'4
(6.2xl0~6) ,1-V-5
0.026
lb/VMT
s
W
=
7.2 to 25.2
vehicle weight, tons
36 to 64
Graders
TSP
IP
0.040 S2,5
0.051 S20
0.031
lb/VMT
5
=
vehicle speed, mph
5 0 to 11.8
Light- and
tnediusrdut/
vehicles
TSP
IP
5.79/M4-0
3.22/M4,3
0.040
lb/VMT
M
'
0.9 to 1.7
Haul trucks
TSP
IP3
0.0067 w3'4L0 2
0.0051 w3*5
0.017
lb/VMT
w
L
=
average number of wheels
6.1 to 10.0 -
silt loading, g/m
3.8 to 254.0
3 Silt loading was not a significant correction parameter for the IP fraction.
-------
Emission factors were reported for three size ranges--firie particulate
(<2.5/um), mhalable particulate (<15 jjm), and total suspended particulate
(no well-defined upper cut point, but approximated az 40jjm). The fairly
consistent ratios of FP and IP to TSP for di.ferent sources indicate that
fugitive dust sources at mines all have similar size distributions. Most
of th.j oa^ticle sizing data were obtained with dichotomous samplers.
The emission factors 1n Table 15-1 are all for uncontrolled emission
rates. Control efficiencies of a few control measures were estimated by
testing, as reported in Table 12-5. These control efficiencies should be
applied to the calculated emission factors :n cases where such controls
have been applied or are anticipated. However, many of the dust-producing
operations are not normally controlled.
The design and field work for this study have received far more review
and quality assurance checks than any similar projects in air pollution
control. However, because of the large variations in emission rates over
time for mining sources and the imprecision of key sampling instruments
while sampling in dense dust pluses, the added care in conducting the
study did not result in appreciable better sampling data with which to
develop the emission factors.
LIMITATIONS TO APPLICATION OF EMISSION FACTORS
The emission factors are designed to be widely applicable through
the use of correction factors, but they still have some limitations
which should be noted:
1. The factors should be used only fo" estimating emissions
from Western coal mines. There is no basis for assuming
they would be appropriate for other types of surface mining
operations or for coal mines located in other geographic
areas without further evaluation.
2. Correction factors used in the equations should be limited
to values within the ranges tested (see fable 15-1). This
1s particularly important for correction fictors with a
large exponent, because of the large change in the resulting
emlsison factor associated with a change In the correction
factor.
3. These factors should be combined with a deposition function
for use 1n ambient air quality analyses. After evaluation
of the deposition daca from this study, no empirical
deposition function could be developed. Any function sub-
sequently developed from these date should have provision
for further deposition beyond the distance of sampling
1n this study (100-200 m).
253
-------
4. The factors were obtained by sampling at the point of emission
and do not address possible reductions in emissions in order
to account for dust being contained within the mine pit.
5. As with all emission factors, these mining faccors do not
assume the calculation of an accurate emission value from
an individual operation. The emission estimates are more
reliable when applied to a large number of operations, as in
the preparation of an emission inventory for an entire mine.
The emission factors are also more reliable when estimating
emissions over the long term because of short-term source
variation.
6. Appropriate adjustments shoud be made in estimating annual
emissions with these factors to account for days with ram,
snow cover, temperatures below freezirg, and intermittent
control measures.
7. The selection of mines and their small number may have biased
final emission factors, but the analysis did not indicate
that a bias exists.
8. The confidence intervals cited in Table 13-10 estimate how
well the equations predict the measured emission rates at
the geometric mean of each correction factor. For predicting
emission rates from a mine not involved in the testing or
for predicting rates under extreme values of the stated range
of applicubility of the correction factors, confidence in-
tervals would be wider.
9. Error analyses for exposure profiling and upwind-downwind
sampling indicated potential errors of 30 to 35 percent and
30 to 50 percent, respectively, inaependent of the statistical
errors due to source variation and limited sample size.
10. Geometric means were used to describe average emission ratps
becajse the data sets were distributed lognormally ratiier than
normally. The procedure makes conpanson with previous
emission factors difficult, because previous factors were
all arlthmetric mean values.
11. Wind erosion emission estimates should be restricted to
calculation of emissions relative to other mining sources;
they should not be included 1n estimates of ambient air
impact.
254
-------
REMAINING RESEARCH
A comprehensive study such as the present one that has evaluated
alternative sampling and analytical techniques is bound to identify
areas whe^e additional research would be valuable. Also, sotne
inconsistencies surface during the data analysis phase, when it is too
late to repeat any of the field studies. Therefore, a brief list of
u..resolved problems has been compiled and is presented here.
1. Sampling *t Midwestern and Eastern coal mines is definitely
needed so that emission factor applicable to all surface coal
mines are available.
2. A resolution of which deposition function is most accurate
in describing fallout of mining emissions is still needed.
Closely related to this is the need for a good measurement
method for deposition for several hundred meter:, downwind
of the source (dustfall Is recommended for measurements jp
to 100 or 200 m). In thp present study, both the source
depletion and dustfall measurement methods -ere found to
have deficiencies.
3. A method for obtaining a valid size distribution of particles
over the range of approximately 1 to 50 jjrn under near-
isokinetic conditions is needed for exposure profiling. The
method should utilize a single scrapie for sizing rather than
building a size distribution from fractions collected in
different samplers.
4. The emission factors presented herein should be validated by
sampling at one or more additional Western mines and comparing
calculated values with the measured ones.
5. Standardized procedures for handling dlchotomous filters should
be developed. These should address such areas as numbering of
the filters rather than thalr petri dishes, proper exposure
for filters used as blanks, transporting exposed filters to
the laboratory, eaullibrating filters pMor to weighing, and
evaluation of filter media other than Teflon for studies where
only gravimetric data are required.
6. One operation determined In the study design to be a signifi-
cant dust-producing source, shovel/truck loading of overburden,
was not sampled because it was not perfarmed at any of the
mines tested. Sampling of this operation at a mine 1n Wyoming
and development of an emission factor would complete the 11st
of emission factors for significant sources at Western coal
mines (See Table 2-1).
255
-------
Further study of emission rate decay o^er time frpn eroding
surfaces Is needed. In particular, more information should
be obtained on the effect of wind gusts in removing the
potentially e^odible material from the surface during periods
when the average wind speed 1s not high enough to erode the
surface.
More testing of controlled sources should be done so that
confidence in the control efficiencies is comparable to that
for the uncontrolled emission rates.
-------
SECTION 16
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Oenver, Colorado. January 1979.
Wedding, James B. Ambient Aerosol Sampling: History, Present
Thinking and a Proposed Inlet fo* Inhalable P*-t1culate Matter.
Paper presented at the A1r Pollution Control .'.sociation Specialty
Conference, Seattle, Washington. April 23, 1980.
Wyoming Depe"tment of Environmental Quality. Wyoming Air Quality
Maintenance Area Analysis. Appendix B: Development of a Particu-
late Emission Factor for Surface Mining 1n the Poader River Basin
of Wyoming. Cheyenne, Wyoming. May 1976,
Wyoming Department o* Environmental Quality. Memorandum on
—^ Fugitlva Dust Emission Factors. Cfievenre, Wyoming. January 24,
1979.
260
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Zimmerman, J. R., and R. S. Thompson. User's Guide for HIWAY, A
Highway Air Pollution Model. U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina. EPA-650/4-74-0P8.
February 1975.
261
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APPENDIX A
STEPWISE MULTIPLE LINEAR REGRESSION
Multiple linear regression (MLR) 1s a statistical technique for
estlmacing expected values of a dependent variable, in this case
particulate emission rates, in tervs of corresponding values of two
or more other (independent) variables. MLR uses the method of least
squares to determine a linear prediction equation from a set of
simultaneously-obtained data points for all the variables. The
equation 1«. of the form:
Emission rate = + B2X2 +...+ Bnxn + constant
where x^ to xn = concurrent quantitative values for each of
the Independent variables
Bj to Bn = corresponding coefficients
The coefficients are estimates of'the rate of change in emission
rates produced by each variab'e. They can be determined easily by
use of an MLR computer program or with a programmed calculator. Other
outputs of the MLR program are:
1. A correlation matrix. It gives the simple correlation coefficients
of all of the variables (dependent and independent) with one another.
It is useful for identifying two interdependent (highly correlated--
either positive or negative) variables (two variables that produce
tne same effect on emission rates), one of which should be eliminated
from the analysis.
2. The multiple correlation coefficient (after addition of each independent
variable to the equation). The square of the multiple correlation
coefficient Is the fraction of total variance in emission rates that
Is accounted for by the variables In the equation at the point.
1
3. Residual coefficient of variability. This Is the standard deviation
of the emission rates predicted by the equation (with the sample
data set) divided by the mean of the predicted emlslson rates,
expressed as a percent. If a variable eliminates some sample
variance, it will reduce the standard deviation and hence the
relative coefficient of variability.
A-l
-------
4. Significance of regression as a whole. This value is calculated
from an F test by comparing the variance accounted for by the
regression equation to the residual variance. A 0.05 significance
level Is a 1 in 20 change of the correlation being due to random
occurrence.
5. Significance of each variable. This is a measure of whether the
coefficient (B) is different than 0, or that the relationship
with the dependent variable is due to random occurrence. Variables
that do not meet a prespecified significance level may ue
eliminated from the equation.
6. Constant in the equation.
The multiple correlation coefficient, unlike the simple correlation
coefficient, is always positive and varies from 0 to 1.0. A value of
zero indicates no correlation and 1.0 means that all sample points lie
precisely on the regression plane. Because of random fluctuations
In field data and inability to identify all the factors affecting
emission rates, the multiple coefficient is almost never zero even when
there is no real correlation and never 1.0 even when concentrations
track known variables very closely. Therefore, it is important to test
for statistical significance.
The form of MLR in the program used In this study was scepwise
MLR. Variables were added to the equation in order of greatest
Increase in the multiple correlation coefficient, with concentrations
then adjusted for that variable and regressed against the remaining
variables again. The procedure can be ended by specifying a maximum
number of variables or a minimum F value In the significance test.
In subsequent runs, the order of entry of variables was sometimes
altered by specifying that a certain variable be entered first or
last.
In order to satisfy the requirement that the variables be quanti-
tative, some were input as dummy variables with only two possible values.
For example, in an MLR run of all blasts, one variable had a value of
0 for all coal blasts and 1 for all overburden blasts. The significance
of this variable determined whether there was a significant difference
between coal and overburden blast emission rates, and the B value was
a direct mwasure of the difference between the two average emission
rates after adjustment for other variables in the MLR equation.
A statistically significant regression relationship between
independent variables end particulate emission rates is no indication
that the Independent variables cause the observed changes In emission
rate, as both may be caused by a neglected third variable.
A-2
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APPENDIX B
CALCULATIONS FOR CONFIDENCE AND PREDICTION INTERVALS
The computational procedures for confidence and prediction Intervals
for emission rates are illustrated in this appendix using TSP emission rates
for coal loading as a function of moisture content (M). The data are
tabulated in Table B-l for convenience, that is, the moisture, %, and
the observed emission rate, lb/ton, for each of the 24 t^sts. The
arithmetic average (X), standard deviation (s), and geometric mean (GM)
are given at the bottom of the table.
Confidence Interval
The computational procedure for confidence intervals is as follows:
1. The first step in the analysis Is to perform a linear regression
analysis. In this example, the dependent variable is the
logarithm of the emission rate (In E) and the independent
variable is the logarithm of moisture (In M). (Natural
logarithms, i.e., to base e are used throughout this
discussion).
2. The prediction equation for the :nean In E is given by:
1 is the predicted mean for In E as a function of M
b0, bj ere the regression coefficients estimated from
the data
In M 1s the In of moisture content
In H 1s the arithmetic average of In M
(In M « 2.882 for this example)
In E e bD + bj (In H - Tnli)
(B-l)
where
B-l
-------
TABLE B-l. TSP EMISSION RATES FOR COAL LOADING, LB/TON
Observed
Test
Moisture,
emission.
number
%
lb 'ton
1
22
0.0069
2
22
0.0100
3
38
0.0440
4
38
0.0680
5
38
0.0147
6
38
0.0134
7
38
0.0099
8
38
0.0228
9
38
0.0206
10
38
0.0065
11
11.9
0.1200
12
11.9
0 %jBZO
13
11.9
0.0510
14
18
0.010b
15
18
0.0087
16
18
0.0140
17
12.2
0.0350
18
11.1
0.0620
19
11.1
0.0580
20
li.l
0.1930
21
11.1
0.0950
22
6.6
0.0420
23
6.6
0.3580
24
6.6
0.1880
X
21.42
0.0639
s
12.64
0.0819
GH
17.85
0.0337
8-2
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3.
The fallowing results are obtained from the MLR (multiple lineer
regression) computer printout for subsequent i.se in computation.
The prediction equation is:
A
In E = -3.385 - 1.227 (In M - 2.882)
Note: Almost all computer printouts give the prediction equation
TnThe form:
1^ - 0.
152 - 1.227 In M (B-2)
that 1s, the constants are combined into one term (0.152 = -3.385 +
1.227 x 2.882). The form provided above in Equation B-l Is simpler
for the computation of the confidence and prediction intervals. In
.the above form b0 1s the average of the In t (In E), which is avail-
able in the printout.
In addition, one obtains:
r2 = 0.451 (the square of the correlation coefficient)
, i
s2 ^ 0.764, s = 0.874 (the standard deviation of the
logarithm of the observed emission rates about the
corresponding predicted In values).
I
The variance of the estimated regressions coefficients are read
or computed from data listed 1n the computer printout:
s02 3 estimated variance of bQ = s}
n
s02 = 0.764 = 0.0318
2T~
Sj2 =» estimated variance of bj
= (0.2523)2 = 0.0637
The value of Sj2 can be computed by formulas given 1n Hald.1 In
this case = 0.2523 1s given in the computer printout for the
purpose of testing the significance of the estimated coefficient bj.
4. The standard deviation of In E is
s(1tTe> » [s02 + Sj2 (In M - in H)2]1/2 (B-4)
¦-[0.0318 + 0.0637 (In.M -2.882)2]1/2 re-Si
S-3
-------
5. The geometric mean of the emission factor E ifi given by:
exp {ln^E} (B-6)
and this estimates the median value of E as a function
of M. It should be noted that the mean value of E is
•estimated by:
exp {lrf^E + S s2} (E-7)
Throughout the remainder of this discussion the GM
values are used as estimates of the corresponding
median emission value.
6. The confidence interval for the median value of E as a
function of M is obtained by:
exp {ln^k ± t s(ln^E)} (B-8)
/n /\
where In E and s(ln E) are obtained from Equations B-2
and B-4, respectively, and t is read for the desired
confidence level from a standard t table available in
almost any statistical test (e.g., Hald's tables2).
Substituting values of M in Equation
-------
0.35
95J CONFIDENCE LIMITS FOR MEDIAN E
95% PREDICTION LIMITS FOR E
ESTIMATED MEDIAN EMISSION RATE (EL-
MEASUkED EMISSION RATES
0.30
0.25
^ 0.20
0.15
0.10
0.05
MOISTURE, *
Figure 8-1. Confidence and prediction Intervals for emission
factors for coal loading.
B-5
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80°/ Limits fUCL = 0'043 Wton
Limits {LCL = 0 02? lb/ton
The median value is:
exp {lrTk} = 0.0339
The above confidence limits are also expressed belov as percent-
ages of the predicted median, 0.0339.
qi®/ r initc cUCL = 1.45 x predicted median
* 'LCL = 0.68 x predicted median
fln«y rimite jUCL = 1.27 x predicted median
s LCL = 0.80 * predicted median
These limits are a measure of the quality of the prediction
of the median emission E for given M on the basis of the data
from the three mines. The widths of these confidence intervals
are consistent with data typically reported by EPA as stated in
Section 15.
One application of these limits would be to estimate the
median annual emissions based on a large number of tons of coal
loaded at the none with GM moisture content of 17.85 percent. If
the moisture content deviates from this value (17.85%), it is
necessary to calculate the interval at the appropriate value of M
using Equation (B-8).
Because of the complication in presenting the complete
results for all sources and pollutants ae in Figure B-l, the
confidence intervals are presented only for the correction fac-
tors (M in this example) at their GM value. Table 13-10 contains
these data for all sources and pollutants.
Prediction Interval
The confidence interval previously described gives a measure
of the quality of the data and of the predicted median which is
applicable only for a large number of operations relative to the
emission factor of interest. In the example in this appendix,
this would imply a large number of coal loading operations (or
tonnage of coal loaded). There will be applications in which the
number of operations is not lar^e and a prediction interval is
desired which is expressed as a function of the number of opera-
tions. The calculation of this interval follows the first three
steps of that for the confidence interval; the subsequent steps,
starting with Step 4, are as follows:
4. The standard deviation of an individual predicted In
emission factor is:
8-6
-------
6 (In E) = [s2 (ln^E) + s2]**
= Ijp + Bj2 (In M - In M)2 + a2]** (B-9)
For the coal loading data,
B(ln E) = [0.0318 + 0.0637 (In M - 2.882)2 + 0.764)** (B-10)
5. The prediction interval for an emission factor E is:
y'S.
exp {In E ± t s(ln E)}
For the coal loading data, this interval is given by:
exp {In E ± t[0.0318 + 0.0637 (In M - 2.882)2 ~ 0.764]'5} (B-ll)
The results are plotted in Figure B-l as a function of
M. For the CM of M (i.e.. In M = 2.832), the predic-
tion limits are:
qvy t -Jini t-cf »L = 0.215 lb/ton
95% Limits{ ^ s 0>005 lb/ton
any rimit-sJ = 0.110 lb/ton
804 Limits{ lrL _ 0>0i0 lb/ton
6. The prediction interval for an individual value is
obviously much wider than the corresponding confidence
interval for a median value. If it is desired to pre-
dict the emissions based on a number of operations, say
N (e.g., N tons of coal), the confidence interval is
given by
expUrTk ± t [s3 (In E) + ip)*1} (B-12)
that is, the last term in Equation B-9 is divided by N
instead of 1. Note that as N becomes large thiB result
simplifies to that of Eguation (B-6).
Test for Normality
One of the major assumptions in the calculations of the con-
fidence and prediction intervals is that the In residuals (de-
viations of the In E from In E) Are normally distributed, hence
the lognorraality assumption for the original (and transformed
data). A check for normality was performed on the In residuals
for six data sets with the largest number of date values. In two
of the six cases the data deviated from normality (these two
cases were TSP and 1? emissions for Blasting). Based on these
results, the lognormal assumption was made because of both com-
putational convenience and adequate approximation for oost of the
data.
B-7
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REFERENCES
1. Hald, A. Statistical Theory with Engineering Applications.
John Wiley and Sons, Inc. New York. 1952
2. Hald, A. Statistical Tables and formulas. John Wiley and
Sons, Inc. New York. 1952.
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