x>EPA
United States
Environmental Protection
Agency
Office of
Solid Waste &
Emergency Response
EPA/530-SW-84-008
June 1984
Solid Waste
Assessing the Releases and
Costs Associated with Truck
Transport of Hazardous Wastes
Executive Summary
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This report was prepared by Dr. Mark Abkowitz and Dr. Amir Eiger, Faculty
Members, Department of Civil Engineering, Rensselaer Polytechnic Institute, Troy,
N.Y., and Mr. Suresh Srinivasan of Transportation Consultants, for the U.S.
Environmental Protection Agency and IGF Incorporated under contract.
The report has been reviewed by the U.S. Environmental Protection Agency (EPA)
and approved for publication. Its publication does not signify that the contents
necessarily reflect the views and policies of the U.S. EPA, nor does mention of
commercial products constitute endorsement or recommendation for use by the U.S.
government.
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ASSESSING THE RELEASES AND COSTS ASSOCIATED
WITH TRUCK TRANSPORT OF HAZARDOUS WASTES
EXECUTIVE SUMMARY
This report was prepared for
the Office of Solid Waste under
contract no. 68-01-6621
U.S. ENVIRONMENTAL PROTECTION AGENCY
Washington, D.C.
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Preface
This report presents an analysis which estimates the releases
from and costs of transporting hazardous wastes. These estimates will
be included in a larger, more general analysis of hazardous waste manage-
ment, namely, the Office of Solid Waste "RCRA Risk-Cost Analysis Model."
The complete report on the transportation analysis will be available
from the National Technical Information Service (NTIS), Springfield,
Virginia 22161. Single copies of the Executive Summary (including the
Table of Contents to the entire report) are available directly from EPA.
MS.
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TABLE OF CONTENTS
PAGE
ACKNOWLEDGEMENT Hi
EXECUTIVE SUMMARY 1
Fraction Release Analysis Methodology 3
Data Description 4
Estimating the Truck Accident Rate 6
Incident Modeling 7
Estimating the Expected Amount Released 9
Estimating the Cost of Transporting Waste 10
Trip Profile Analysis 10
Cost Methodology 12
Model Application 14
Release Computation 14
Cost Analysis 15
Concluding Remarks 15
CHAPTER 1 INTRODUCTION 17
CHAPTER 2 FRACTION RELEASE ANALYSIS METHODOLOGY ... 21
CHAPTER 3 DATA DESCRIPTION 25
3.1 Truck Accident and Volume Data 25
3.1.1 Texas 26
3.1.2 California 26
3.1.3 New Jersey 26
3.2 Hazardous Waste Shipment Information 28
3.2.1 California 29
3.2.2 Texas 31
3.2.3 Massachusetts 31
3.2.4 New York 34
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ACKNOWLEDGEMENT
The authors would like to acknowledge the advice, guidance and
cooperation of Curtis Haymore, Arline Sheehan and Eric Males of the
Office of Solid Waste, U.S. Environmental Protection Agency. The
assistance provided by Joseph Kirk, Leslie Kostrich, Stephen Bailey
and Jean Tilly of ICF Incorporated is also sincerely appreciated.
Finally, substantial and useful comments during the review process
were made by Russell Cappelle of American Trucking Associations,
Inc., Joseph Nalevanko of the U.S. Department of Transporation's
Materials Transportation Bureau and John Thompson of the Office of
Solid Waste, U.S. Environmental Protection Agency.
iii
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3.3 Hazardous Waste Incident Data 34
CHAPTER 4 TRIP PROFILE ANALYSIS 40
4.1 Data Refinement 40
4.2 Analysis Results 42
4.2.1 California 42
4.2.2 Texas 45
4.2.3 Massachusetts 48
4.2.4 New York 51
4.3 Implications of Pooling State Data 54
4.4 Summary 56
CHAPTER 5 INCIDENT MODELING 58
5.1 Container Classification 59
5.2 Incident Occurrence Model 61
5.3 Estimating the Mean Shipment Distance 65
5.4 Fraction Release Model 67
5.5 Fraction Release Estimators 76
5.6 Fraction Release Estimates 77
5.7 Errors of the Estimates 79
5.8 Results and Implications 81
CHAPTER 6 ESTIMATING THE TRUCK ACCIDENT RATE 83
6.1 Analysis 84
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6.2 Results and Implications 86
CHAPTER 7 ESTIMATING THE COST OF TRANSPORTING WASTE 93
7.1 Literature Review 93
7.2 Revised Procedure 104
7.2.1 Average Cost Approach - 6,000 Gallon Tanker. . . 106
7.2.2 Average Cost Approcah - 18 Ton Stake Truck . . 107
7.2.3 Deriving Cost Formulas 108
7.3 Comparison with Actual Charges 109
7.4 Summary Ill
CHAPTER 8 MODEL APPLICATION AND CONCLUDING REMARKS . 112
8.1 Scenario 1 112
8.1.1 Release Computation 112
8.1.2 Cost Analysis 114
8.2 Scenario 2 115
8.2.1 Release Computation 115
8.2.2 Cost Analysis 116
8.3 Concluding Remarks 116
REFERENCES 118
APPENDIX A LIST OF CONTAINER TYPES 121
APPENDIX B DESCRIPTION OF FAILURE MODES AND CAUSE
CODES 132
APPENDIX C INCIDENT FREQUENCY AND DAMAGE HISTOGRMS . 135
VI
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EXECUTIVE SUMMARY
In response to a growing concern over the management of
hazardous wastes and their impact on the population and environment,
the Resource Conservation and Recovery Act (RCRA) was enacted in
1976. RCRA authorized the EPA to establish a hazardous waste
control program for the nation, which includes the identification and
classification of hazardous wastes, requirements for owners and
operators of hazardous waste facilities, and guidelines for state
programs developed under the act.
In 1981, as part of the national hazards waste control program,
EPA's Office of Solid Waste began to develop its RCRA Risk/Cost
Analysis Model. The model is designed to assist in the development
of hazardous waste policies.
The RCRA Risk/Cost Analysis Model consists of an array of
possible ways to treat, transport and dispose of the hazardous wastes
generated in the United States. There are three main factors
considered in the model's formulation of possible ways to manage
hazardous waste:
(1) The type of waste (and its hazardous chemical
constituents).
(2) The types of technologies used to treat, transport and
dispose of the wastes.
(3) The environmental settings in which the wastes are
treated, transported and disposed.
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The model forms ail possible combinations of a list of wastes,
technologies and environmental settings -- or W-E-T cells. The model
then calculates the risks and costs involved in each W-E-T cell. In
this fashion, the relative merits and drawbacks of various hazardous
waste management strategies can be identified.
This report focuses on one component of the RCRA Risk/Cost
Analysis Model: the costs incurred and expected fraction released
(R ) during transport of hazardous wastes. The objectives of our
project were governed by the following criteria:
• In order to establish a tool for policy analysis, we wanted
to estimate a fraction release model that reflected, as much
as possible, actual data on hazardous waste shipments and
incidents. Compiling a comprehensive data sample
necessitated extensive data collection at both the state and
federal levels.
• In order to ascertain whether previous studies were reliable
for policy analysis, we performed a critical review of
existing truck transport cost studies. We then developed
revised cost formulas to account for deficiencies identified in
the review process and compared the revised cost procedure
with quoted rates to validate its applicability.
Because 90 percent of all current hazardous waste transport is via
truck, the transport release model and cost review were restricted to
truck transport.1
authors are presently conducting studies of the release rates
and costs of hazardous waste shipments by rail and waterborne
transport.
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Fraction Release Analysis Methodology
Hazardous waste releases during transport can result from a
number of causes (failures modes) and can occur either at shipping
terminal points or en route. We defined three incident types:
(1) Container failures due to vehicular accidents enroute.
(2) Container failures occurring enroute due to causes other
than vehicular accidents.
(3) Container failures at shipment terminal points.
We formulated a Transport Release Model to compute the expected
fraction released (Rt_) during transport. This is a function of: (1)
the expected fraction released enroute and (2) the expected fraction
released at terminal points. Deriving these release fractions requires
an understanding of the expected fraction released given an incident
for each failure mode, the probability of an incident for each failure
mode and, for enroute incidents, the distance shipped. It is
necessary to estimate these parameters for each container type used
in transport. Thus, the total number of parameters to be estimated
depends on the number of container types and failure modes.
Furthermore, the use of the model for policy analysis requires
hazardous waste shipment distances as input.
Estimating incident probabilities also requires a determination of
the total involvement. For example, total involvement for incidents
which occur enroute is a function of the total distance shipped (i.e.,
the average shipment distance multiplied by the number of
shipments). For incidents which occur at terminal points, the total
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involvement is the total number of shipments. Thus, it is necessary
to estimate the average shipping distance and the number of
shipments for each container type.
We computed these measures using: (1) shipping distances
derived from incident data, 2) data on the number of vehicular
accidents and 3) independently derived estimates of vehicular accident
rates. Subsequently, it became possible to compute incident rates for
other failure modes. It was not necessary to perform this explicitly
for each container type. Rather, we expressed all incident rates in
terms of a common vehicle accident rate. We assumed that this
accident rate does not depend 'on the container type used for
shipment.
Data Description
We identified three types of data which were necessary to
conduct the release and cost analyses:
(1) Truck accident and volume data.
(2) Hazardous waste shipment information.
(3) Hazardous waste incident data.
Wherever possible, we obtained data from 1980, 1981 and 1982,
because they represent the most recent information available on
hazardous waste incidents and shipments.
We obtained truck accident and volume data from Texas,
California and New Jersey records. Each record included average
daily counts of vehicular traffic characterized by vehicle type and the
annual number of truck accidents. The California and Texas data
included observations for interstate highways, U.S. highways and
state routes. The New Jersey data, on the other hand, included
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many highway sections containing intersections with traffic signals.
We collected data on hazardous waste shipments from California,
Texas, Massachusetts and New York manifest records. In general,
each record contained the following information: origin location,
destination location, waste type transported, quantity shipped and
unit of shipment. A significant problem with this database was its
lack of accuracy in reporting the locations of generation and disposal
sites. In some cases, the county of origin or the destination state
was the only location description. Thus, it was necessary to make
some assumptions to correct for this. problem. State data also did not
consistently include interstate shipments.
The primary data source for estimating the incident probability
and fraction release parameters was the Hazardous Material Incident
File (HAZMAT) maintained by the U.S. Department of Transportation's
Materials Transportation Bureau (MTB). HAZMAT, a compilation of
nationwide data on hazardous material spills, contains information on
the frequency and circumstances (container involvement, failure mode,
severity of resulting spills, etc.) surrounding hazardous material
incidents.
Although over 8,000 incidents of hazardous material spills
involving truck travel were reported in 1981, a closer inspection of
these data indicated that an extremely small number (84) of these
spills involved hazardous wastes. Because the sample size of
hazardous waste incidents was not large enough for statistical
analysis, we considered all of these hazardous materials incidents in
developing the incident model. Also, because we postulated that the
incident rate and fraction release models do not depend on the type
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of waste being shipped, but rather, on the container type used, and
because the HAZMAT file covers a wide range of container types, this
approach is justified.
Estimating the Truck Accident Rate
We assumed that the truck accident rate is a function of the
highway type and traffic conditions. Truck accident and volume data
were obtained from California, Texas and New Jersey; these data
represented a wide range of traffic and truck volumes and four
different highway types. To test the statistical significance of any
differences in accident rates under different highway and traffic
conditions, we conducted an analysis of variance (ANOVA), which
indicated the significance of the traffic volume, truck percentages and
highway type.
The analysis of the accident rate data yielded the following
estimate for aggregate accident involvement rates (releasing accidents
per million truck miles):
Interstates 0.13
U.S. and State Highways 0.45
Urban 0.73
Composite 0.28
These results fall within the range of previously reported
estimates and demonstrate the difference in the accident rate for
various highway types. The truck accident rate is also dependent on
both the total traffic volume and the percentage of trucks in the
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traffic stream. These results suggest that in applying the estimates
provided, cell means should be used in lieu of aggregate means if
sufficient information is available to identify the highway type and the
traffic volume.
Incident Modeling
The HAZMAT file of reported hazardous materials incidents
allows the coding of up to 334 container types and 27 failure modes.
From our analyses of these data, we identified 8 container types with
reasonably uniform physical characteristics and incident involvement
rates:
(1) Cylinders
(2) Cans
(3) Glass
(4) Plastic
(5) Fiber Boxes
(6) Tanks
(7) Metal Drums/Pails
(8) Open Metal Containers
For each of these container classes, we determined the
respective parameters in the fraction release model. Table 1
summarizes the resulting estimates of the fraction released by
container type.
The results of our analyses indicate that in terms of their
order of magnitude, the expected fractions released per mile shipped
-8 -6
range from 10 to 10 , depending on the container class. The
-6
expected fractions released at terminal points range from 10 to
10 , depending on the container class.
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Table 1 Estimates of Fraction Released by Container Class
Container
Class
Expected Fraction
Released Per
Mile Shipped**
Expected Fraction
Released at Terminal
Points
1
2
3
4
5
6
7
8*
1.3 x 10~6 + (.13 X1)
2.6 x 10~6 +(.12 A')
1.7 x 10"6 +(.27 A')
4.1 x 10"6 +(.14 A')
1.3 x 10"6 +(.12 A')
4.2 x 10"8 +(.19 A')
2.4 x 10~6 +(.10 A')
7.5 x 1(T6
1.4 x 10
-4
4.0 x 10
-4
2.6 x 10
-4
5.2 x 10
-4
6.1 x 10
-5
7.6 x 10
-6
2.9 x 10
-4
1.2 x 10
-3
*astimate associated with the release fraction during accident is not
reliable.
**A' = releasing vehicle accident rate.
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Our computed estimates indicate that:
(1) The release rates for tank trucks are much lower than
for other container types.
(2) The expected amount released at terminal points is one to
three orders of magnitude higher than the amount
released en route.
(3) The expected release fractions during transport are
potentially as high as the release fractions at disposal
sites and treatment facilities, which range from 10" to
-3 • -5 -3
10 for routine spillage and 10 to 10 for accidental
spillage.
Estimating the Expected Amount Released
Using the model parameters given in the previous sections, we
employed the following procedure to estimate the expected fraction
released during transport:
(1) Identify shipment characteristics.
- number of shipments
- volume per shipment
- trip distance
- container type
(2) Identify highway characteristics.
- highway type
- traffic volumes
(3) Select appropriate values of fraction release parameters
for the container type being considered.
(4) Compute the fraction of accidents that involve releases
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(derived as the truck accident rate multiplied by 0.2).
(5) Determine fraction released en route and at terminal
points.
(6) Multiply fraction released enroute by total trip miles and
fraction released at terminal points by the number of
shipments.
(7) Add these values to arrive at total expected fraction
released.
(8) Multiply this by the total volume to obtain the total
expected amount released.
This procedure is demonstrated in the discussion on model application.
Estimating the Cost of Transporting Waste
Trip Profile Analysis
Using the waste shipment data from Texas, California,
Massachusetts and New York, we examined the following:
(1) The mean shipping distance, segmented by waste type
(for each state).
(2) The quantity shipped, segmented by waste type (for
each state).
(3) The extent to which the above measures vary across
states.
The resulting information was used in cost applications where specific
trip lengths and the quantities shipped were not known.
In order to determine if the quantity and/or distance shipped is
related to the waste type (solid or liquid) or the particular state
under consideration, we conducted a multivariate analysis of variance.
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The results of the analysis indicated that the shipment characteristics
of liquid and solid wastes vary by state and consequently we could
not derive aggregate estimates. This resulted in our conducting
separate analyses for each state.
Our analysis results indicated that trip distance and quantity
shipped vary by waste category and also vary considerably among
states. This is likely due to differences in the manifest system,
geographic location, size and industrial activity of each state.
We did, however, conclude that the quantity transported is
independent of trip distance. Our findings do not substantiate the
argument that shipments are filled closer to capacity on longer trips
than shorter ones. We also found that in three of the four states,
the mean shipment size for liquids is larger than for solids
shipments, and that in three of the four states, the average trip
distance is longer for solids shipments than for liquids shipments.
Questions are sometimes raised regarding general waste shipment
characteristics for the United States. Although there is no basis for
assuming that our sample is typical of the entire hazardous waste
transport industry, we computed weighted averages of the shipping
distances and quantities which reflect the number of annual manifests
in each of the states. These weighted averages should not be
misinterpreted to apply to specific hazardous waste transport scenarios
in the United States.
The mean trip length for all shipments is 84.2 miles, with a
mean trip length for liquids of 77.1 miles and for solids of 109.6
miles. For liquids, the mean quantity shipped is 3,171 gallons. For
solids, it is 2,791 gallons (11.6 tons). The trip distance frequency
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distribution for all four states, for both liquids and solids, follows an
exponential distribution. This is not surprising because disposal sites
are likely to be located near points of waste generation.
Cost Methodology
We reviewed the existing literature on the cost of transporting
hazardous waste and identified seven studies which treated the issue
of estimating the cost of transporting hazardous waste by truck. All
seven studies considered this issue within the larger framework of the
total cost and risk of hazardous waste treatment at a regional level.
The studies' results varied from gross estimates of the unit cost
of transport to more sophisticated derivations of costs based on fixed
and variable components. We noted several deficiencies in these
methods, particularly in the assumptions relating to shipment
characteristics (for example, all of the studies assumed that vehicles
travel at capacity, which is not substantiated by the results of the
trip profile analysis) and their failure to compare their results to the
actual rates charged by haulers.
Using the most comprehensive of the methodologies, we
developed a revised costing procedure which was designed to
overcome these deficiencies. Our modifications included considering
trip distances and shipment sizes based on the trip profile analysis
results, using 1983 component costs, and comparing the revised
methodology to actual price quotes from waste haulers.
We then used the revised costing procedure to estimate
transport costs for 6,000 gallon tankers and 18-ton stake (flatbed)
trucks. The average costs computed using the trip profile
characteristics are:
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Tankers Stake Trucks
Average Cost Per $4.14 $4.55
Loaded Mile ($)
Average Cost Per $0.31 SO.39
Loaded Ton-Mile ($)
The average costs per loaded mile and loaded ton-mile are larger for
stake trucks than tankers. This is due to the smaller loads
associated with stake trucks.
In order to estimate the cost .of transport when details on
specific shipments are available, we derived the following formulas for
tankers and stake trucks:
88.8
elm. . ($/loaded mile) = 3.08 *
tanker
3.08 88.8
cltm. , ($/loaded ton -mile) = - *
tanker
129.38
clmstake ($/loaded mile) = 3-02
3.02 129.38
cltm , . ($/loaded ton-mile) = *
Y XY
where:
elm = cost per loaded mile
cltm = cost per loaded ton-mile
X = shipment distance (miles)
Y = shipment size (tons)
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To determine the accuracy of the revised costing procedure, we
compared its estimates with the actual rates charged by haulers. The
comparison showed that the estimates we obtained using this cost
formula appear to be quite representative of quoted rates in the
hazardous waste transport industry. The average cost figures,
however, did not compare quite as favorably. Consequently, we
recommend that the average cost figures should be used rather
carefully, and should only be employed when information js not
available on trip distance and/or shipment size.
Model Application
To illustrate the established release and cost procedures, we
posed the following problem:
Suppose 200 55-gallon drums are being shipped a distance of TOO
miles on interstate highways. The average daily traffic (ADT) and
truck percentages on the highways are unknown. What are the
expected releases and cost involved?
Release Computation
From previously reported results, we obtained the releasing
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accident rate for interstates as 0.13 x 10 releasing accidents per
truck mile. The expected amount released enroute was obtained using
the fraction released from Table 1 as:
E (release enroute) = (2.4x10~6 * 0.10x0.13x10~6) x 100 x 200 x 55
= 2.65 gallons
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E (release at terminals) = 2.9x10~4 x 200 x 55
= 3.19 gallons
Total expected release = 5.84 gallons
Cost Analysis
The average load carried by stake trucks is 2,791 gallons,
which is equivalent to 11.6 tons. The quantity being shipped is
11,000 gallons, which is equivalent to 45.83 tons. The cost per
loaded ton-mile is:
3.02 129.38
cltm . . ($/loaded ton-mile) = + = 0.37
staKe 11.6 (100M11.6)
Number of ton-miles per shipment = 11.6 x 100 = 1160
Cost per shipment = 1160 x 0.37 = $429.20
Average number of shipments = 3.94
Total Cost = 3.94 x 429.20 = $1,691.05
Concluding Remarks
This project has addressed the potential releases and costs of
transporting hazardous wastes by truck. In the course of conducting
this study, we drew several conclusions that are useful for policy
analysis. Below, we briefly discuss our conclusions.
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A trip profile analysis conducted on data from several states
indicated that, on average, wastes are shipped less than TOO miles
from their generation to their disposal sites. The average trip length
is lower for liquids than for solids. Generally speaking, the mean
quantity shipped is independent of shipping distance.
In assessing truck transport releases, it is important to
distinguish between two kinds of incidents that result in spills. For
one class of incidents, the probability of occurrence is a function of
the distance traveled; for the other, the occurrence probability for a
particular shipment is fixed. We computed expected fraction release
estimates for both kinds of incidents.
The costs of transporting hazardous wastes by truck can be
reasonably approximated using the formulas derived in this study.
These cost formulas compare well with actual industry quotes.
The individual and collective results of the entire analysis are
applicable at many levels of aggregation. Using this study's models
and cost formulas, it is possible to obtain broad estimates of expected
releases and transport costs, as well as estimates of the releases and
costs involved in individual shipments.
Perhaps the most important result of this study is that the
release rates associated with transporting hazardous wastes by truck
appear to be as large as the potential releases at treatment and
disposal sites. In fact, for some W-E-T combinations, transport may
be a potentially more dangerous activity. As a result, policymakers
should give careful consideration to the relative risks involved in the
treatment, transport and disposal of hazardous wastes.
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