"*\xSmartWay
Transport Partnership
U.S. Environmental Protection Agency
2017 SmartWay Shipper
Partner Tool:
Technical Documentation
U.S. Version 2.0.16 (Data Year 2016)
www.epa.gov/smartway
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vxSmartWay
Transport Partnership
U.S. Environmental Protection Agency
2017 SmartWay Shipper
Partner Tool:
Tecnical Documentation
U.S. Version 2.0.16 (Data Year 2016)
Transportation and Climate Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
United States
Environmental Protection
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Office ofTransportation and Air Quality
EPA-420-B-17-030
October 2017
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1.0 Overview
The SmartWay Shipper Tool is intended to help shippers estimate and assess their
carbon, PM, and NOx emissions associated with goods movement in the U.S. freight
trucking, rail, air and barge sectors1. Shippers can track their freight-related emissions
performance from year-to-year using the Tool and assess a range of strategies to
improve the emissions performance of their freight operations, including selection of
low-emissions carriers and implementation of operational strategies such as (but not
limited to) packaging improvements, load optimization and logistical improvements.
The SmartWay truck, barge, air, logistics and multimodal carrier emissions performance
data that EPA has included in the Tool, along with industry average Class I rail CO2
data, will allow shippers to generate accurate emissions inventories. The data will also
help shippers optimize their emissions performance by allowing them to better estimate
the emissions impact of individual carriers, modal shifts, and operational strategies.
2.0 Tool Inputs and Calculations
After shippers enter their company and contact information, they provide basic
information about each company they operate, including the name and NAICS code for
each of these companies. For these individual companies to show up on the SmartWay
Partner list on the EPA website, shippers should submit separate Shipper Tools, one for
each company.
For each company, shippers need to indicate whether they are entering basic or
comprehensive data for them. If they have annual mileage-related activity data by
carrier (miles or ton-miles), they may select the "Emissions Footprint and % SmartWay"
option on the Basic or Comprehensive screen, and proceed to input activity data for
each carrier. Otherwise, they must select the "% SmartWay" option, which only requires
them to report the portion of goods they move with SmartWay carrier partners based on
money spent, weight shipped, packages shipped, or another custom metric.
If shippers select the "% SmartWay Only" option, they will not be eligible for a
SmartWay Excellence Award, nor will they be able to calculate an emissions
inventory or develop emissions performance metrics (e.g. g/mile or g/ton-mile) for
their freight operations.2 All shippers - regardless of whether they select the
"Emissions Footprint" option or the "% SmartWay Only" option - will be able to see the
SmartWay Category-level emissions performance data for their truck, logistics and
multimodal carriers as well as available industry average rail emissions factors.
1 Future versions of the tool will help Shippers evaluate the emissions performance associated with ocean going
vessels.
2 Shipper partners are encouraged to select the "Emissions Footprint" reporting option for all their companies
whenever possible. When a shipper has multiple companies the reporting basis chosen for the % SmartWay Value
calculation must be the same for all companies in order for the Tool to calculate a Partner level % SmartWay Value.
However, the Shipper Tool allows users to select the "Emission Footprint" option for some companies while
selecting "% SmartWay Only" for others. In this instance a Partner level % SmartWay Value is not calculated.
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Emissions performance data for barge and air carriers are reported on a carrier-specific
basis.
After identifying and selecting all of their SmartWay and non-SmartWay carriers,
shippers can then optionally identify each carrier that they use for each company and
the service that the carrier provides (e.g., Inbound or Outbound hauls, International
and/or Domestic service, etc.). These optional parameters serve as "tags" which allows
shippers to filter their emission data as desired using the screen tools discussed in
Section 3 below.
Emission Inventory and Performance Metric Calculations
If shippers choose the "Emissions Footprint" option, the Tool will calculate their total
mass emissions (i.e., an emissions inventory) based on the mileage-related activity data
entered for each carrier, as well as various emission performance metrics (e.g.,
composite grams/mile and grams/ton-mile - see below). The Tool calculates mass
emissions based on the annual ton-mileage for each carrier.
The emissions inventory for each carrier/mode combination displayed on the
Emissions Summary, Carrier Performance and SmartWay Category Details
screens is calculated by multiplying the appropriate unit of activity data (i.e., truck,
railcar or barge-miles, or ton-miles) by the corresponding carrier emissions performance
data. To calculate composite, company-wide emissions performance metrics on the
Carrier Performance screen (i.e., overall g/mile and g/ton-mile performance), the Tool
weights the emissions performance of each of the shipper company's carriers by the
percentage of the company's overall freight activity that the carrier moves. An example
composite performance calculation is provided below.
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Table 1. Example Gram per Mile Compositing Calculation
CO2 g/mi
Mi/yr
Weighting Factor
Weighted C02g/mi
Carrier 1
1,700
2,000,000
0.667
1,134 (0.667x1,700)
Carrier 2
1,500
1,000,000
0.333
500 (0.333 x 1,500)
Weighted composite g/mi
1,634 (1,134 + 500)
This compositing process proceeds in an identical fashion for gram per ton-mile metrics,
using ton-miles instead of miles as the basis for weighting. Weighted-average payloads
are also calculated in this way, using the relative ton-miles for each carrier as the
weighting factor. Weighted average payload for each shipper company is displayed at
the bottom of the Activity Data screen in the Tool.
Likewise, if a shipper selects one or more filters (e.g., inbound domestic carriers-only),
the Tool adjusts the weighting factors to ensure that they sum to 100% for the selected
subset of carriers. The following provides a simplified example calculation.
o Shipper selects three Truck carriers (T1, T2, T3)
o T1 has a CO2 g/mile of 1,000
o T2 has a CO2 g/mile of 2,000
o T3 has a CO2 g/mile of 3,000
o T1 is Inbound
o T2 and T3 are both Outbound
o Shipper enters miles for the three carriers of 2,000, 4,000, and 2,000,
respectively
o When Inbound/Outbound combo = All:
¦ Composite C02 g/mile = [(1,000*2,000 + 2,000*4,000 + 3,000*2,000) /
8,000] = 2,000
o When Inbound/Outbound combo = Inbound:
¦ Composite C02 g/mile = [1,000*2,000 / 2,000] = 1,000
o When Inbound/Outbound combo = Outbound:
¦ Composite C02 g/mile = [(2,000*4,000 + 3,000*2,000) / 8,000] = 2,300
Ton-Mile Calculation
Correctly calculating Ton-Miles is critically important for the accurate determination of
your carbon footprint You can calculate your company's ton-miles as follows.
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Determine the ton-miles hauled per year attributable to each carrier. A ton-mile is one
ton moving one mile. DO NOT ESTIMATE TON-MILES BY SIMPLY MULTIPLYING
TOTAL MILES BY TOTAL TONS - this calculation effectively assumes your entire
tonnage is transported on EACH AND EVERY shipment, and will clearly overstate your
ton-miles.
Many companies track their ton-miles and can report them directly without further
calculation. For example, shipper company systems are often set up to associate a
payload with the mileage traveled on each trip by carrier, and are then summed at the
end of the year. If such information is not available, there are two ways to calculate ton-
miles:
1) Companies can determine their average payload per carrier, multiply the average
payload by the total miles per carrier, and sum the results for all carriers for the
reporting year; or
(total miles per carrier x total tons per carrier)
2) Set Ton-miles per carrier =
total # of trips per carrier
NOTE: In both ton-mile calculations, empty miles are not factored in while the fuel used
to drive those empty miles is factored in.
To check your estimate, divide ton-miles by miles. The result is your fleet-average
payload. If this number is not reasonable, (e.g., typically between 15 and 25 tons for
Class 8b trucks), please check your calculations.
Carrier Emissions Performance Data
The current SmartWay program provides CO2, NOx and PM gram per mile, and gram
per ton-mile emission factors for truck, rail, air and barge freight transport providers.
These data are provided in the SmartWayCarrierData2016ST.xls file, which is
downloaded to the user's computer using the button on the Tool's Home screen.
It is envisioned that SmartWay will incorporate emission factors ocean-going vessel
transport providers, and gram per volume-mile emission factors for all modes, in the
future.
Truck Carrier Performance
Truck carrier performance data utilized by the current Shipper Tool is based on 2016
Truck Partner Tool submittals. Performance data includes g/mile and g/ton-mile for
each truck carrier. Note that g/mile and g/ton-mile values represent midpoints for the
appropriate SmartWay Category, rather than exact performance levels for a given
carrier. Truck SmartWay Categories include:
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• TL Dry Van • Auto Carrier
• LTL Dry Van • Expedited
• Refrigerated • Heavy/Bulk
• Flatbed • Moving
• Tanker • Specialized
• Dray • Mixed
• Package
The following provides an overview of the process used to estimate the carrier-specific
performance ranges.
Truck Performance Categories
In the 2015 SmartWay Truck Tool, data is collected at the individual company fleet
level. Fleets are characterized by a) business type: for-hire or private, b) operational
type: truckload/expedited, less than truckload, dray, expedited, or package delivery, and
c) equipment type: dry van, refrigerated van, flatbed, tanker, chassis (container),
heavy/bulk, auto carrier, moving, or specialized (e.g., hopper, livestock, others.)
The possible categories are shown below.
For-Hire
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
TL
LTL
Dray
Expedited
Package
Private
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
TL
LTL
Dray
Expedited
Package
Note that while Specialized fleets have disparate operations/equipment types and thus
do not compare well, they are also unlikely to compete with one another, so it was
deemed acceptable to aggregate these disparate fleets into one category.
For-hire and private fleets are combined in the SmartWay Categories. There are
relatively few private fleets compared to for-hire fleets. Because owners of private fleets
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generally hire their own fleets exclusively, it was determined that grouping for-hire and
private fleets together would not be detrimental to for-hire fleets, and the simplicity of
one for-hire and private category outweighed the benefits of listing fleets separately.
Grouping for-hire and private separately would have doubled the number of SmartWay
Categories. Therefore, fleets can thus be categorized as shown below.
For-Hire and Private
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
TL
LTL
Dray
Expedited
Package
To be categorized in a particular category, a fleet must have at least 75% of its mileage
in a single category, otherwise it is classified as a "Mixed" fleet. Fleets may be mixed
via their operational or equipment type. Fleets are generally segregated by their
operational type, but some mixing does occur via equipment type, especially with
smaller carriers that do not differentiate their fleet. Fleets that do not have 75% of their
operations in a specific SmartWay Category are placed in the Mixed category.
Individual fleets were then placed into SmartWay Categories. The following shows the
relative number of fleets for the various category intersections, with darker shadings
indicating more fleets.
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
Mixed
LTL
-
-
-
-
Dray
-
-
-
-
-
Expedited
-
-
-
-
-
-
-
Package
-
-
-
-
-
-
-
Mixed
-
-
-
-
-
SmartWay then considered combining categories with similar characteristics for
simplification purposes. One prerequisite was that there needed to be a minimum
number of fleets in each category. SmartWay determined that a category needed a
minimum of 25 fleets to be created. It was also determined that dry van and chassis
(i.e. intermodal container) groups functioned primarily as dry van transport, so these
categories were combined. While most refrigerated carriers were truckload, a few less
than truckload refrigerated fleets exist, so these categories were combined. Although
no expedited or package refrigerated fleets were identified, these categories were also
combined into one overall refrigerated category so that no operation and equipment
type intersections would be left undefined. A similar situation was identified with flatbed,
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tanker, heavy/bulk, auto carrier, moving, and specialized fleets. All dray fleets were
collapsed into one category. Any fleet that had mixed operation and/or mixed
equipment was placed into a single mixed category. Finally, logistics and multimodal
fleets were also included and retained as unique categories.
The final performance categories for 2017 are illustrated below. The solid colors
indicate how operation and equipment type assignments vary by performance category.
For example, if 75% or more of a fleet's mileage is associated with reefer trucks, the
fleet is assigned to the Reefer category regardless of the operation percentage across
truckload, expedited, LTL, and package categories. However, the Reefer category
assignment is overridden if the operation category is greater than or equal to 75% dray,
logistics, or multimodal. Similar assignment rules apply to flatbed, tanker, heavy/bulk,
auto carrier, moving, and specialized equipment types. Only the Dry Van/Chassis
equipment category is subdivided by the truckload, expedited, LTL, and package
operation categories, meaning that the 75% threshold must be met for both equipment
and operation type in these cases. All other equipment/operation type percentage
distributions are assigned to the Mixed category.
Figure 1. SmartWay Carrier Categories and Data Specificity - 2017 Calendar Year
TRUCK
Dry Van
Heavy
Auto
Specialized
& Chassis
Reefer
Flatbed
Tanker
& Bulk
Carrier
Moving
& Utility
Mixed
Dray
Dray
5 Performance Levels
Truckload
Truckload DryVan
5 Performance Levels
Reefer
Flatbed
Tanker
Heavy
Auto
Moving
Specialized
Mixed
Expedited
Expedited
& Bulk
Carrier
& Utility
5 Performance Levels
5
5
5
5
5
5
5
5
LTL
LTL
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
5 Performance Levels
Levels
Levels
Levels
Levels
Levels
Levels
Levels
Levels
Package
Package Delivery
5 Performance Levels
Less than 75%
Mixed
in any category
Rail
Single Modal Average for All Rail
(No company differentiation allowed per Association of American Railroads)
Barge
Company Specific Data
Air
Company Specific Data
Logistics
5 Performance Levels
Emission Factor Data Only
(No 5 Performance Level Ranking)
Multimodal
Marine
To Be Determined
(Proposed availability in 2016 calendar year)
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It is possible that SmartWay will expand these categories in the future based on in-use
experience or as a result of further data analysis, and/or requests from industry.
Fleets within a SmartWay Category have been ranked from lowest emission factor
(best) to highest emission factor (worst) for each of the following metrics: CO2 g/mile,
CO2 g/ton-mile, NOx g/mile, NOx g/ton-mile, PM10 g/mile and PM10 g/ton-mile. When
SmartWay Categories are first established, fleets within a category are separated into 5
ranges such that an equal number of fleets were in each range. Each range thus
represents a group of emission factors. These ranges, and associated ranking
"cutpoints" (transition points from one rank to the next) were then modified so that each
range had an equal difference between upper and lower bounds, and the new cutpoints
remained as close to the originals as possible. The new range cutpoints are displayed
as numbers with significant digits appropriate to emission factors in that range. The
midpoint of the range is used as the emission factor for all fleets in that range.
It would be simpler and more straightforward to use fleet-specific emission factors,
however the trucking industry expressed concern that revealing exact data could be
used to back-calculate mile per gallon numbers. The above described methodology
prevents a determination of an exact mpg figure, while at the same time attributing an
emission factor much more precisely than a modal default number. Given the large
number of trucking fleets, and thus opportunity for fleets to be very close to each other
in performance (for example 0.001 g/mile of CO2), SmartWay believes it is acceptable
and appropriate to break truck fleets into 5 performance ranges for each SmartWay
Category.
The table below illustrates the ranges in the For Hire/Private Truckload/Expedited Dry
Van SmartWay Category, using 2013 truck Partner data as an example.
Table 2. Emission Factor Ranges for One Performance Category (2013 Data)
For-Hire/Private Truckload/ Dry Van CO2 g
/mile
Group
ED
Fleets
Per Bin
Grams Per
MileMin
Grams Per
Mile Max
Grams Per
Mile Avg
Grams Per Mile
Midpoint
Grams Per
Mile Std Dev
1
186
944
1,549
1,452
1,500
118
2
227
1,551
1,650
1,601
1,600
28
3
194
1,651
1,749
1,692
1,700
29
4
140
1,751
1,848
1,798
1,800
29
5
115
1,851
5,090
2,010
1,900
359
Similar tables have been developed for all performance SmartWay Categories. The
midpoint of each performance range is the data that a shipper downloads into their
SmartWay Shipper Tool to represent the emission performance of a specific fleet that is
in the associated range. Once the categories and ranges have been established, the
fleets of any new companies joining SmartWay will fall into one of the predefined
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categories/ranges. SmartWay expects to update the category/range structure
periodically.
Performance estimates for non-SmartWay truck carriers were calculated based on the
lowest performing truck partners. Since no data exists to define non-SmartWay fleets,
SmartWay believes the prudent approach is to assign conservative emission factors to
non-SmartWay companies. Also, this policy makes it likely that any company joining
SmartWay will see better emission factors displayed than the non-SmartWay default
emission factors.
The non-SmartWay performance metrics were calculated by taking a standard
performance range delta (max - min) for each range within each SmartWay Category,
and using the delta to calculate a non-SmartWay carrier midpoint for each
category. This midpoint was the midpoint for Range 5 plus the standard range
delta. For example, if the Range 5 midpoint was 10.5 and the category's standard delta
was 1, then the non-SmartWay midpoint was calculated to be 11.5. Once the non-
SmartWay midpoints for each pollutant were calculated for all SmartWay Categories,
the non-SmartWay performance metric was calculated by using the average value of
these mid-points, weighted by the number of fleets in each category. This approach
does not require the shipper to identify the appropriate SmartWay Category for their
non-SmartWay carrier(s), which they may not know, while still ensuring that the
performance of their non-SmartWay carriers reflects the distribution of the different
categories within the truck population.
As discussed in the Shipper Tool Quick Start Guide, depending upon the type of data
available for a given carrier, the user may input ton-miles or miles, and rely on carrier
data to back-calculate the other value. For example, providing ton-miles and average
payload allows the Tool to estimate total miles, by dividing the former by the latter. For
non-SmartWay truck carriers, the values for average payload (18.7 tons) were derived
from the average values for all truck partners (2011 data), weighted by miles.
Logistics and Multimodal Carrier Performance
Logistic and multimodal carriers have their own performance categories based on the
carrier Tool submittals for the most recent available calendar year. Multimodal carrier
categories are also differentiated by mode combinations, including Surface,3 Surface-
Air, Surface-Marine, and Surface-Air/Marine. Multimodal composite fleets designated
as having an Air "element" include SmartWay or Non-SmartWay air carriers that
comprise at least 10% of the composite fleet's ton-miles or include one or more air
component fleets. Similarly, composite fleets with a Marine "element" have barge
carriers responsible for 10% or more of the composite fleet ton-miles or include one or
more barge component fleets. Multimodal composite fleets can have both an Air
3 Surface multimodal carriers utilize road (truck and logistics carriers) and rail modes.
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designation and a Marine designation by meeting the above requirements. When this is
the case these fleets are designated Surface-Air-Marine.4
Non-SmartWay carrier performance for SmartWay Categories is estimated in the same
way as is done for non-SmartWay Truck carriers (i.e., averaging the bin midpoints to
calculate a fleet average value).
Air and Barge Carrier Performance
Air and barge carriers have agreed to have their actual emissions results made public,
and, barge performance values used in the Shipper Tool are carrier-specific. The gram
per mile performance values for barge carriers correspond to individual barge (nautical)
miles travelled, rather than miles travelled by a string of barges or the associated tug(s).
Non-SmartWay barge carrier gram per mile and gram per ton-mile performance is set to
be 25% higher than the worst performing SmartWay barge carrier.
Since no air carrier data submittals have been approved as of this date, performance
levels for non-SmartWay air freight are based on publicly available data. First upper
bound estimates for grams of CO2 per ton-mile were obtained for short and long-haul air
freight (-4,236 g/t-mi and -1,461 g/t-mi, respectively).5-6 Values for CO2 g/mile were
calculated by multiplying the g/t-mi value by an average cargo payload value of 22.9
short tons. The average payload value was estimated by dividing total air freight
tonnage in 2012 (15M tons)7 by the total number of cargo departures in the same year
(654,956 LTOs).8 Corresponding performance metrics for NOx and PM10 were based
on the ratio of these pollutants to CO2 from the EDMS 5.1.4.1 model (0.009 for NOx and
0.000059 for PM10).9 The resulting performance metrics are shown in Table 3. An
average cargo volume estimate was also obtained for inclusion in the SmartWay carrier
data file based on the volume for a typical freight aircraft, the Boeing 747 200 series
(5,123 cubic feet).10
4 Air and/or marine carriers may be utilized directly by the multimodal carrier, or may be utilized indirectly by
logistics business units hired by the multimodal carrier.
5 Short haul air freight assumed to be less than 3,000 miles, covering most domestic air routes in the U.S.
6 Estimates from Figure 8.6 in Sims R, R. Schaeffer, F. Creutzig, X. Cruz-Nunez, M. D'Agosto, D. Dimitriu, M. J.
Figueroa Meza, L. Fulton, S. Kobayashi, O. Lah, A. McKinnon, P. Newman, M. Ouyang, J. J. Schauer, D. Sperling,
and G. Tiwari, 2014: Transport. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working
Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R.
Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B.
Kriemann, J. Savolainen, S. Schlomer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University
Press, Cambridge, United Kingdom and New York, NY, USA.
7 U.S. DOT Bureau of Transportaion Statistics, Fregiht Facts and Figures 2013. Accessed 20 April 2015
http://www.ops.fhwa.dot.gov/freight/freight_analysis/nat_freight_stats/docs/13factsfigures/pdfs/fff2013_highres.pdf
8 U.S. DOT, Bureau of Transportation Statistics, U.S. Air Carrier Traffic Statistics, accessed April, 20, 2015:
http://www.rita.dot.gov/bts/acts/customized/table?adfy=2012&adfm=l&adty=2012&adtm=12&aos=6&artd&arti&a
rts=3&asts&astns&astt=3&ascc=2&ascp
9 EDMS outputs for take-off mode, assumed to be equal to cruising mode. (Cruise emissions are not output by
EDMS). Take-off mode emission rates were averaged across all aircraft/engine combinations in the Heavy (Max
Takeoff Weight over 255,000 lbs) and Large (Max Takeoff Weight 41,001 to 255,000 lbs) weight classes.
10 http://www. airgroup. com/standalone.php?action=air spec
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Table 3. Assumed Performance Metrics for Non-SmartWay Air Carriers
C02/tmi
CO^mi
NOx/mi
NOx/tmi
PM/mi
PM/tmi
Short-haul
4,236
96,998
873.2713
38.1341
5.743247
0.250797
Long-haul
1,461
33,448
301.1280
13.1497
1.980430
0.086482
Rail Carrier Performance
Rail carrier performance data are collected and displayed in the Shipper Tool at the
industry average level derived from Class 1 rail company data. Gram per ton-mile
factors were determined by dividing total fuel use by total ton-miles and multiplied by a
rail diesel CO2 factor (10,180 g CCh/gal diesel fuel), from publicly available data
submitted in the 2010 railroad R-1 reports to the Department of Transportation. 2010 R-
1 data was also used to obtain total railcar-miles per year for all Class 1 carriers, in
order to estimate gram per railcar-mile factors. Industry average values are currently
assumed for all rail carriers in the carrier data file, regardless of SmartWay Partnership
status. Specific rail companies may have the opportunity to provide company-specific
data in the future. The R-1 data and corresponding CO2 performance data are
presented in Table 4 below.
Table 4. Rail Carrier Performance Metric Calculation Inputs & Results (2010 R-1
Data)
Rail Company
Gal/Yr
('OOO)Sch.
750 Line 4
Freight Ton-
Mi/Yr ('000)
Sch .755 line
110
Railcar-Mi/Yr
('000) Sch.
755 sum of
lines 30, 46,
64 & 82
g C02/railcar-
mile
g C02/short
ton-mile
BNSF Railway
1,295,147
646,549,059
11,230,994
1,163
20.20
CSX Transportation
490,050
230,507,431
4,720,293
1,047
21.44
Grand Trunk
88,290
50,586,328
1,206,818
738
17.60
Kansas City Southern
62,354
31,025,588
609,929
1,031
20.76
Norfolk Southern*
440,159
183,104,320
4,081,893
1,087
24.24
Soo Line
65,530
33,473,544
771,033
857
19.74
Union Pacific
1,063,201
525,297,747
10,336,081
1,037
20.41
Total - Industry
Average
3,504,731
1,700,544,017
32,957,041
1,072
20.78
* and combined subsidiaries
NOx and PM emission factors for rail carriers are also based on industry averages.
Please see the "Background on Illustrative (Modal Average) U.S. Truck and Rail
Factors" section below for details regarding the calculation of industry average NOx and
PM performance levels for different freight modes.
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Average payloads per loaded railcar were calculated for all Class 1 carriers by dividing
the value for annual ton-miles hauled by an estimate for loaded railcar-miles, based on
2008 R-1 data. The calculation uses the Total Revenue and Non-Revenue Ton-Miles as
listed In the R-1 Report on line 114 of schedule 755 divided by the Total loaded Railcar-
Miles (the sum of lines 30 and 64 of schedule 755) along with the factor for fuel gallons
consumed for loaded freight that is created based on the percentage of loaded freight to
total freight multiplied by the total diesel fuel value listed on schedule 750 Line 4. The
following table summarizes the estimated average payload per railcar, by carrier.
Table 5. Rail Carrier Average Payload
Carrier
Avg Payload/Loaded
Railcar (tons)
BNSF Railway
108
CSX Transportation
85
Grand Trunk
80
Kansas City Southern
91
Norfolk Southern
76
Soo Line
77
Union Pacific
91
Industry Average
93
Average railcar volumes were calculated for all carriers by first estimating an average
volume for each major railcar type listed in the R-1 forms (schedule 755, lines 15-81).
The assumptions used to estimate these volumes are provided in Table 10 below. The
railcar-miles reported for each railcar type were multiplied by these average volumes to
estimate annual cubic foot-miles travelled by car type for each company and for the
industry average. The distribution of cubic foot-miles across car types was used as the
weighting factor to estimate a single average railcar volume for each company. These
values and the resulting volume estimates are presented in Table 6 below.
Table 6. Rail Carrier Average Volume Determination
BNSF
Freight Car Types (R1 - Schedule 755)
Avg. Cu Ft.
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
4,555
1
4,555
Box-Plain 50-Foot & Longer
1,111
9,338
67,018,826
Box-Equipped
1,111
147,226
1,056,641,002
Gondola-Plain
5,190
379,762
1,970,964,780
Gondola-Equipped
5,190
75,894
393,889,860
Hopper-Covered
4,188
758,442
3,176,355,096
12
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BNSF
Freight Car Types (R1 - Schedule 755)
Avg. Cu Ft.
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Hopper-Open Top-General Service
4,220
65,077
274,624,940
Hopper-Open Top-Special Service
4,220
137,449
580,034,780
Refrigerator-Mechanical
6,202
19,272
119,524,944
Refrigerator-Non-Mechanical
6,202
32,910
204,107,820
Flat-TOFC/COFC
6,395
520,521
3,328,731,795
Flat-Multi-Level
13,625
38,624
526,252,000
Flat-General Service
6,395
357
2,283,015
Flat-All Other
6,395
71,826
459,327,270
All Other Car Types-Total
5,772
20,146
116,282,712
Average Railcar Cubic Feet
5,811
13
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CSX
Freight Car Types (R1 - Schedule 755)
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
6,987
50,145,699
Box-Equipped
144,631
1,038,016,687
Gondola-Plain
137,256
712,358,640
Gondola-Equipped
64,532
334,921,080
Hopper-Covered
153,315
642,083,220
Hopper-Open Top-General Service
78,412
330,898,640
Hopper-Open Top-Special Service
35,451
149,603,220
Refrigerator-Mechanical
17,117
106,159,634
Refrigerator-Non-Mechanical
11,923
73,946,446
Flat-TOFC/COFC
125,828
804,670,060
Flat-Multi-Level
29,956
408,150,500
Flat-General Service
162
1,035,990
Flat-All Other
31,913
204,083,635
All Other Car Types-Total
19,861
114,637,692
Average Railcar Cubic Feet
6,389
14
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Grand Trunk
Freight Car Types (R1 - Schedule 755)
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
0
Box-Plain 50-Foot & Longer
2,119
15,208,063
Box-Equipped
66,110
474,471,470
Gondola-Plain
6,467
33,563,730
Gondola-Equipped
19,201
99,653,190
Hopper-Covered
44,239
185,272,932
Hopper-Open Top-General Service
9,114
38,461,080
Hopper-Open Top-Special Service
32,621
137,660,620
Refrigerator-Mechanical
312
1,935,024
Refrigerator-Non-Mechanical
205
1,271,410
Flat-TOFC/COFC
2,779
17,771,705
Flat-Multi-Level
4,831
65,822,375
Flat-General Service
20
127,900
Flat-All Other
31,744
203,002,880
All Other Car Types-Total
4,755
27,445,860
Average Railcar Cubic Feet
6,309
15
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Kansas City Southern
Freight Car Types (R1 - Schedule 755)
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
0
Box-Plain 50-Foot & Longer
3,383
24,279,791
Box-Equipped
39,792
285,587,184
Gondola-Plain
16,628
86,299,320
Gondola-Equipped
11,150
57,868,500
Hopper-Covered
50,346
210,849,048
Hopper-Open Top-General Service
626
2,641,720
Hopper-Open Top-Special Service
943
3,979,460
Refrigerator-Mechanical
21
130,242
Refrigerator-Non-Mechanical
52
322,504
Flat-TOFC/COFC
10,736
68,656,720
Flat-Multi-Level
629
8,570,125
Flat-General Service
12
76,740
Flat-All Other
2,321
14,842,795
All Other Car Types-Total
247
1,425,684
Average Railcar Cubic Feet
5,938
16
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Norfolk Southern
Freight Car Types (R1 - Schedule 755)
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
0
Box-Plain 50-Foot & Longer
1,622
54,703,094
Box-Equipped
136,745
981,418,865
Gondola-Plain
193,214
1,002,780,660
Gondola-Equipped
111,320
577,750,800
Hopper-Covered
116,848
489,359,424
Hopper-Open Top-General Service
84,557
356,830,540
Hopper-Open Top-Special Service
30,078
126,929,160
Refrigerator-Mechanical
3,512
21,781,424
Refrigerator-Non-Mechanical
5,392
33,441,184
Flat-TOFC/COFC
114,928
734,964,560
Flat-Multi-Level
20,349
277,255,125
Flat-General Service
145
927,275
Flat-All Other
24,563
157,080,385
All Other Car Types-Total
212,408
1,226,018,976
Average Railcar Cubic Feet
6,065
17
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Soo Line
Freight Car Types (R1 - Schedule 755)
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
0
Box-Plain 50-Foot & Longer
725
5,203,325
Box-Equipped
17,972
128,985,044
Gondola-Plain
1,203
6,243,570
Gondola-Equipped
8,856
45,962,640
Hopper-Covered
94,146
394,283,448
Hopper-Open Top-General Service
3,077
12,984,940
Hopper-Open Top-Special Service
20
84,400
Refrigerator-Mechanical
159
986,118
Refrigerator-Non-Mechanical
742
4,601,884
Flat-TOFC/COFC
11,178
71,483,310
Flat-Multi-Level
2,973
40,507,125
Flat-General Service
12
76,740
Flat-All Other
10,068
64,384,860
All Other Car Types-Total
428
2,470,416
Average Railcar Cubic Feet
5,667
18
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Union Pacific
Freight Car Types (R1 - Schedule 755)
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
0
Box-Plain 50-Foot & Longer
12,311
88,356,047
Box-Equipped
238,241
1,709,855,657
Gondola-Plain
206,370
1,071,060,300
Gondola-Equipped
91,775
476,312,250
Hopper-Covered
370,929
1,553,450,652
Hopper-Open Top-General Service
188,027
793,473,940
Hopper-Open Top-Special Service
104,969
442,969,180
Refrigerator-Mechanical
82,874
513,984,548
Refrigerator-Non-Mechanical
27,009
167,509,818
Flat-TOFC/COFC
1,026,251
6,562,875,145
Flat-Multi-Level
46,889
638,862,625
Flat-General Service
350
2,238,250
Flat-All Other
72,371
462,812,545
All Other Car Types-Total
16,769
96,790,668
Average Railcar Cubic Feet
6,248
19
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Total (for Industry Average)
Freight Car Types (R1 - Schedule 755)
Railcar Miles (xlK)
Cu Ft Miles (xlK)
Box-Plain 40-Foot
1
4,555
Box-Plain 50-Foot & Longer
42,485
304,914,845
Box-Equipped
790,717
5,674,975,909
Gondola-Plain
940,900
4,883,271,000
Gondola-Equipped
382,728
1,986,358,320
Hopper-Covered
1,588,265
6,651,653,820
Hopper-Open Top-General Service
428,890
1,809,915,800
Hopper-Open Top-Special Service
341,531
1,441,260,820
Refrigerator-Mechanical
123,267
764,501,934
Refrigerator-Non-Mechanical
78,233
485,201,066
Flat-TOFC/COFC
1,812,221
11,589,153,295
Flat-Multi-Level
144,251
1,965,419,875
Flat-General Service
1,058
6,765,910
Flat-All Other
244,806
1,565,534,370
All Other Car Types-Total
274,614
1,585,072,008
Industry Average Railcar Cubic Feet
6,091
% SmartWay Value
The % SmartWay screen presents the portion of goods that shippers move with
SmartWay Partners (expressed as a percentage between 0 and 100). Shippers select
the basis for calculating the percentage shipped with SmartWay Partners, including the
following options:
• Total annual miles (the Tool will automatically populate the % SmartWay screen
with any carrier activity data that shippers entered in the freight Activity Data
20
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screen). Miles correspond to truck-miles for trucks, aircraft-miles for air, barge-
miles for barge, and railcar-miles for rail;
• Total annual ton-miles (the Tool will automatically populate the % SmartWay
screen with any carrier activity data that shippers entered on the freight Activity
Data screen);
• Custom Factors including -
o Percent Spent;
o Percent Weight Shipped;
o Percent Packages Shipped;
o Other Custom Metric (as defined by Shipper).
3.0 Calculator Tools
In addition to estimating a shipper's emissions inventory and performance metrics, the
Shipper Tool also allows shippers to estimate the emissions impact of system activity
strategies as well as modal shifts, if the user provides mileage-related activity data
under the "Emissions Footprint" option.
Shipper System Activity Strategies11
The System Activities screen is optional and is intended for reference purposes only.
On the System Activities screen, shippers may estimate emission reduction benefits
for the following options:
• Miles Removed from the System
o Distribution center relocation
o Retail sales relocation
o Routing optimization
o Cube optimization
o Larger vehicles and/or multiple trailers
• Weight Removed from System
o Product weight reduction
o Package weight reduction
o Vehicle weight reduction
For each system activity selected, shippers must provide an estimate of the percentage
reduction in freight activity (in miles or weight), for each mode of interest, along with a
11 The "System Activities" calculation sheet cannot be used if shippers do not provide mileage-related activity data,
since the Tool will be unable to determine the shippers' baseline mass emissions.
21
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detailed text description of the strategy. The Tool assumes that total mass emissions
are reduced in direct proportion with the specified mileage or weight reduction.12
Mass emission reductions are calculated by using the appropriate emissions inventory
from the Emissions Summary screen (based on reported activity data and associated
carrier emissions performance data) as shown below:
S = EM x (1 / (1 - Reduction) -1)
Where:
S = Savings (tons of CO2, NOx, or PM)
EM = Emissions inventory value (tons of CO2, NOx, or PM from Emissions
Summary screen)
Reduction = the reduction in total miles or weight as a result of the
strategy (expressed as fraction)
Fractional reduction estimates must be documented in the Shipper Tool. An example
calculation is provided below:
A shipper changes the shape of its milk cartons from round to square. As a result, the
shipper can pack 20% more milk cartons per truck trailer than the rounded milk
cartons. This reduces 20% of the loads associated with that product line
(corresponding to the "Cube Optimization" activity selection for the "Miles removed from
system" category). However, the company sells many products, and the total
truckloads associated with milk shipments is 1,000 out of 50,000 overall
truckloads. The efficiency gain is thus 20% x (1,000/50,000), or a 0.4% system
improvement. Therefore, the shipper would enter "0.4" in the Percent Improvement
column. This assumes that all loads on average travel an equivalent distance. If milk
loads were significantly shorter than other loads, then a mileage-based weighting per
trip would need to be applied to arrive at a percent improvement. The burden of proof
on demonstrating an accurate percent reduction and modal allocation is the
shipper's. The data sources and methodology should be briefly described in the Tool
under Data Source/Methodology. The shipper should, at a minimum, keep detailed
records electronically within the company to document the estimate upon EPA
request. The shipper can also submit any documentation in electronic text format along
with the Tool to its Partner Account Manager.
12 This assumption should be accurate for weight reduction strategies when applied to truckload shipments that
weigh out. Additional uncertainty arises in the case of LTL and package delivery shipments, where weight
reductions may not result in one-to-one reductions in miles hauled. Uncertainties are even greater for non-truck
modes, where the shipper commonly does not control the entire content of the container. Likewise, this assumption
may not hold if shippers reduce freight by loading more products (i.e., more weight) on trucks that were previously
cubing out, since the increase in payload will negatively impact the truck's fuel economy and g/mile emissions
performance.
22
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Modal Shift
Overview
The Modal Shift screen in the Tool is optional and is intended for reference purposes
only. Shippers should develop their carrier emissions inventories (and associated
emissions factors for their companies) by inputting activity data in the Activity Data
screen.
Shippers wishing to conduct scenario analyses can use the Modal Shift screen to
estimate the emissions impacts associated with modal shifts by specifying the mode
from which they are considering shifting their freight ("From Mode"), as well as the
target mode ("To Mode"). Shippers have several options for selecting an emissions
factor for both the "From Mode" and "To Mode". First, the Tool automatically calculates
and displays the average emission factors for truck, barge, air and rail modes
corresponding to the carrier data file values used on the Activity Data screen
(corresponding to the "Shipper's Carrier Average" Emission Factor Source selection).
In this case partners can also adjust their estimates of emission impacts from modal
shifts by applying different filters for the "From" Mode (e.g., just considering inbound
international freight). Second, partners may select illustrative industry average emission
factors (discussed in the section below) from the drop-down menu (corresponding to the
"Modal Average" selection). Third, the shipper can input a set of alternative emissions
factors of their choice (corresponding to the "User Input" selection). In this instance the
user must also provide a description of the source of the information used to develop
the alternate factors (by selecting the "User Input Data Source" button).
Note: the emissions factors that automatically appear on the Modal Shift screen do not
include all potential emissions impacts; for example, the factors do not include
emissions associated with drayage (i.e., short-distance trips often required to move
freight from one mode to another), or operations at intermodal facilities.
While EPA has populated the Tool with illustrative modal average freight emission
factors, we recommend that partners use more representative emission factors to
analyze scenarios whenever possible. For example, partners may wish to evaluate the
emissions impact from moving freight from rail to a specific truck fleet by consulting the
SmartWay Category average emissions factors associated with the fleet (available on
the SmartWay website), or by inputting data that partners receive directly from a carrier.
For better estimates of emission impacts from modal shifts, partners are encouraged to
use a factor that reflects the full emissions impact (e.g., including anticipated drayage
emissions) and that best represents the fleet equipment and operational type that they
are most likely to work with for their unique freight movement.
While we have not provided modal average ocean-going vessel factors in the Tool,
there are several external resources that partners can consult. We have included some
selected sources of ocean-going vessel factors in the following section.
23
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In order to calculate the emissions impact associated with a modal shift, shippers input
the activity data corresponding with their modal shift scenario expressed in a given unit
(miles or ton-miles) and the Tool combines that data with a corresponding emission
factor (described above) in the same unit. The Tool then displays the change in
emissions (as calculated below) in tons per year.
Total Emission Impact (tons/yr) =
[(Efficiency Before x "From Mode" Amount) -
(Efficiency After x "To Mode" Amount)] x grams to short tons conversion factor13
If the shipper is evaluating a mode shift between truck and rail or barge, and if the
available activity units are in miles rather than ton-miles, then the activity data entered
must be expressed in terms of railcar-miles or barge-miles, as appropriate in order to be
consistent with the g/mile factors included in the carrier data file. Determination of
railcar and barge-miles for any particular container/commodity type and route should be
made in consultation with carriers or logistics service providers in order to account for
volume differences compared to truck carriers.
If you need to convert truck-miles to railcar and/or barge-mile equivalents for your
assessment, a railcar-to-truck equivalency factor can be calculated by first identifying
the average cargo volume for a given rail carrier (see Table 5 above). These volumes
estimates should be weighted by the miles associated with each rail carrier in order to
estimate a single weighted-average railcar volume for the carrier company in question.
Similarly, weighted average volumes can also be calculated for the different truck
carriers associated with the given shipping company. (Company-specific volume data is
contained within the carrier data file for SmartWay truck carriers.) The weighting
calculations should involve all carriers used by the company if no filters are selected on
the Modal Shift screen (only relevant for the "From" mode). Otherwise the weighted
average calculation should only be performed for the filtered subset (e.g., inbound
domestic truck carriers).
Once the weighted average volumes are determined for both rail and truck modes, you
can calculate the ratio of the average railcar volume to the average truck volume (R).
Using industry average volume estimates as described in Appendix A, we estimate R to
equal approximately 1.41, meaning that the average railcar has 1.41 times the volume
of an average truck trailer/container. Next, you can convert your truck-equivalent mile
estimates to railcar equivalent miles by dividing truck miles by the ratio R.14 Enter the
corresponding railcar-mile activity estimate in the "Amounts" column.
The same process is used to convert truck-miles to barge-mile equivalents, although
national average barge volume information was not identified for this analysis. In this
case volume estimates may be used for specific barge carriers from the carrier data file.
13 1.1023 x 10'6 short tons/gram
14 Any route mileage differences must be adjusted for separately.
24
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In addition, the value for truck miles should also be divided by 1.15 to convert from
statute to nautical miles.15
Background on Illustrative U.S. Modal Average Factors
Modal Average performance metrics have been estimated for rail, truck and multimodal
modes (both gram per mile and gram per ton-mile), as well as for barge and air modes
(gram per ton-mile only) in order to estimate emission impacts using the Modal Shift
screen. We developed the freight truck g/ton-mile factors with 2014 CO2, NOx, and
PM2.516 inventory data on short-haul single unit, short-haul combination unit, long-haul
single unit, and long-haul combination unit truck categories17 in EPA's 2014a version of
the Motor Vehicle Emissions Simulator (MOVES2014a) model.18 MOVES does not
contain ton-mile data, so we then divided the MOVES-based inventories by 2014 ton-
mile data from the Bureau of Transportation Statistics,19 which we determined was the
most recent, comprehensive national freight truck ton-mile dataset available. For the
freight truck g/mile factors, we used the same emissions inventory data as the g/ton-
mile factors described above and divided them by the corresponding 2014 VMT data in
MOVES2014a.
Table 7 presents the illustrative freight truck emissions factors in the tool and Table 8
presents the key underlying data. (Note that the modal average factors calculated for
truck carriers were assumed valid for logistics carriers as well.)
Table 7: Illustrative U.S. Freight Truck Industry Average Factors in Modal Shift
C02
N0X
PM2.5
gram/short ton-mile
210
1.145
0.0454
gram/mile
1,546
8.45
0.335
Table 8: Underlying Emissions Inventories and Activity Data for Illustrative U.S.
CO2 (grams)
418,275,000,000,000
NOx (grams)
2,286,630,000,000
PM2.5 (grams)
90,672,929,280
short ton-miles
1,996,165,000,000
miles
270,592,000,000
15 Barge performance values are expressed in grams per nautical mile, to be consistent with barge carrier reporting
practices.
16 Corresponding PM10 emission factors were estimated assuming PM2.5 values were 97% of PM10 values, based
on MOVES model outputs for diesel fueled trucks.
17 These four truck categories are coded as 52, 53, 61, and 62 in the MOVES model, respectively.
18 EPA's MOVES model and accompanying resources, including technical documentation, are available at:
www.epa.gov/otaq/models/moves/index.htm.
19
https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national transportation statistics/html/table 01
50.html
25
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We developed the freight rail gC02/ton-mile factors with 2008 inventory data from
EPA's Inventory of U.S. Greenhouse Gas Emissions and Sinks (1990-2008),20 which is
based on Class I rail fuel consumption data from the Association of American Railroads
and estimates of Class II and III rail fuel consumption by the American Short Line and
Regional Railroad Association. We divided this emissions inventory by the rail ton-mile
data (2007) presented in Table 1-46b in the Bureau of Transportation Statistics' (BTS)
National Transportation Statistics,21 which is intended to encompass all freight rail ton-
miles, including Classes I, II, and III.
We developed the freight rail gNOx/ton-mile and gPM2.5/ton-mile factors with 2010
inventory data from Tables 3-82 and 3-83, respectively, in EPA's 2008 Regulatory
Impact Analysis for a locomotive diesel engine rule.22 This inventory data represents
2010 emission projections for all U.S. rail except for passenger and commuter rail (i.e.,
large line-haul, large switch, and small railroads), which we determined would very
closely align with the freight rail sector. We divided this emissions inventory data by the
2007 BTS ton-mile data described above.
We developed the freight rail g/mile factors by using 2008 railcar mileage data from
lines 15 through 81 of R-1 forms that Class I railroad companies submitted to the
Surface Transportation Board.23 We developed the CO2 inventory for the rail g/mile
factors by using 2008 Class I rail fuel consumption reported in the R-1 reports and an
emissions factor of 10,180 gCC^/gallon, which corresponds to the diesel emissions
factor in the current version of the SmartWay Truck Tool.24 We developed the NOx and
PM inventories in a similar fashion using the average 2010 locomotive gPM10/gal and
gNOx/gal factors from Tables 5 and 6, respectively, in EPA's 2009 Technical Highlights:
Emissions Factors for Locomotives,25 To calculate gPM2.5/gal, we assumed 95% of
PM10 is PM2.5, which we determined was a good approximation of the share of overall
PM10 emissions represented by particulate matter that is 2.5 micrometers in diameter
or smaller.
20 U.S. EPA, 2010. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2008, Washington DC (EPA
430-R-10-006), available at: http://www.epa.gov/climatecliange/emissions/usgginv_archive.html. Total freight rail
GHG emissions are presented in Table A-l 10 of the inventory. Table 10 in this document presents C02-only data.
In order to isolate the CCVonly emissions data, we accessed spreadsheets that are not publically available.
21 U.S. DOT, Research and Innovative Technology Administration, Bureau of Transportation Statistics, 2009.
National Transportation Statistics, Table l-46b - U.S. Ton-Miles of Freight (BTS Special Tabulation) (Updated
September 2009). Available at:
www.bts.gov/publications/national transportation statistics/html/table 01 46b.html
22 U.S. EPA, Office of Transportation and Air Quality, 2008. Regulatory Impact Analysis: Control of Emissions of
Air Pollution from Locomotive Engines and Marine Compression Ignition Engines Less than 30 Liters Per Cylinder,
EPA420-R-08-001a, WashingtonDC. Available at: www.epa.gov/otaq/regs/nonroad/420r08001a.pdf
23 Surface Transportation Board (STB), Industry Data, Economic Data, Financial and Statistical Reports, Class 1
Annual Report, Form R-1. Available at: http://www.stb.dot.gov/stb/industry/econ_reports.html
24 The source of the diesel factor is the fuel economy calculations in 40 C.F.R 600.113 available at
http://edocket.access.gpo.gov/cfr 2004/iulqtr/pdf/40cfr600.113-93.pdf.
25 U.S. EPA, Office of Transportation and Air Quality, 2009. Technical Highlights: Emission Factors for
Locomotives, EPA-420-F-09-025, Washington DC. Available at:
http://www.epa.gov/oms/regs/nonroad/locomotv/420f09025.pdf.
26
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Table 9 presents the illustrative freight rail emissions factors in the Tool and Table 10
presents the key underlying data.
Table 9: Illustrative U.S. Freight Rai
C02
NOx
PM2.5
gram/short ton-mile
22.94
0.4270
0.0120
gram/railcar mile
1,072
18.6
0.503
gram/TEU-mile
292.8
4.745
0.1284
Industry Average
:actors in Modal Shift
Table 10: Underlying Emissions Inventories and Activity Data for Illustrative U.S.
Freight Rail Industry Average Factors in Modal Shift
C02 (grams)
41,736,353,990,153
short ton-miles
1,819,633,000,000
Class l-only diesel fuel consumption (gallons)
3,905,310,865
Class l-only railcar miles (total)
34,611,843,000
50' and Larger Box Plain + Box Equipped
2,223,402,000
40' Box Plain
22,000
Flat TOFC/COFC, General, and Other
Flat Multi Level
5,057,466,000
1,725,998,000
Gondola Plain and Equipped
7,893,684,000
Refrigerated Mechanical and Non-Mechanical
495,311,000
Open Top Hopper General and Special Sen/ice
5,913,012,000
Covered Hopper
7,210,656,000
Tank under 22,000 gallons
1,295,482,000
Tank 22,000 gallons and over
2,394,565,000
All Other Car Types
402,245,000
Note that NOx and PM emission factors were not available at the carrier level for the rail
mode. Accordingly, the modal average emission factors for NOx and PM were
assumed to apply equally for all rail carriers.
Modal average estimates for multimodal carriers were calculated for intermodal
truck/rail freight movements by estimating the average length of haul for rail freight (990
miles)26 and truck drayage carriers (398 miles).27 Based on these estimates we
assume a "typical" intermodal container shipment will travel 71 % by rail, and 29% by
truck. These percentages are applied as weights to the modal average rail and truck
mode values calculated above in order to estimate modal average performance metrics
for intermodal shipments (see Table 11).
26 BTS Table 1-38, Class I Rail average length of haul for 2013 -
http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national transportation statistics/html/
tablet) 138. html.
27 Harrison, R. et al, Characteristics of Drayage Operations at the Port of Houston, University of Texas Center for
Transportation Research, Table 4, September 2008.
27
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Table 11: Modal Average Performance Metric Estimates for Rail, Truck, and
ntermodal
Mode
g'mi
g/ton-mi
CO2
NOx
PM10
PM2.5
CO2
NOx
PM10
PM2.5
Rail
1,072
18.6
0.519
0.503
22.94
0.427
0.012
0.012
Truck
1,546
8.54
0.345
0.335
210
1.145
0.047
0.045
Intermodal
1,209
15.68
0.469
0.454
77.19
0.635
0.022
0.022
NOTE: if you wish to estimate the emission impacts for other modal combinations (e.g.,
truck/barge) select the "User Input" option to provide the appropriate performance
metric estimates.
The modal average barge emissions factors presented in Table 12 are from a study
prepared by the Texas Transportation Institute (TTI) for the U.S. Maritime
Administration28 and reflect inland waterway towing operations in the U.S. We
converted the PM10 factor in the TTI study into PM2.5 by assuming 95% of PM10 is
PM2.5, which we determined was a good approximation of the share of overall PM10
emissions represented by particulate matter that is 2.5 micrometers in diameter or
smaller.
Table 12: Modal Average Barge Emission Fac
C02
NOx
PM2.5
gram/short ton-mile
17.48
0.4691
0.0111
ors
Estimates of average g/mi performance metrics were not identified for barge carriers.
Modal average estimates for air freight are based on EDMS outputs, presented in Table
3, provided again below.
Table 3: Modal Average Air Emission Factors
CC>2/tnii
C02/mi
N Ox/mi
NOx/tmi
PM/mi
PM/tmi
Short-haul
4,236
96,998
873.2713
38.1341
5.743247
0.250797
Long-haul
1,461
33,448
301.1280
13.1497
1.980430
0.086482
Outside Sources of Ocean-Goinq Marine Emission Factors
There are many sources of marine emission factors available in research literature and
other GHG estimation tools. For reference, we have included below:
28 U.S. Maritime Administration and the National Waterways Foundation (U.S. MARAD), amended March 2009. A
Modal Comparison of Domestic Freight Transportation Effects on the General Public. Prepared by Center for Ports
& Waterways, Texas Transportation Institute, Table 10. Available at:
www.waterwayscouncil.org/study/public%20study.pdf
28
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¦ gC02/ton-mile marine factors from the Business for Social Responsibility's (BSR)
Clean Cargo Tool gCCh/ton-mile marine factors from a study prepared for the
International Maritime Organization (IMO)29
Note that the factors from BSR and IMO are published in units of kgC02/metric ton-km,
so we converted this data into gC02/ton-mile by first multiplying by 1,000 (to convert
from kilograms to grams), then multiplying by 0.9072 (to convert from metric tonnes to
short tons), and then multiplying by 1.609 (to convert from kilometers to miles) to
prepare the tables below.
BSR developed average 2009 marine emission factors for various shipping corridors, as
well as global defaults that are applicable outside those corridors, based on surveys
from marine carriers. The BSR marine factors in Table 14 below are from the "Emission
Factors & Distances" tab in their tool.
Table 14: BSR Marine Emission Factors (gC02/short ton-mile)
Ship_general
International
13.0678
Ship_Barge
International
29.1937
Ship_Feeder
International
29.1937
Ship_inland_Germany
Germany
41.5280
Ship_inland_China
China
35.0578
Ship_Asia-Africa
Asia—Africa
11.9227
Ship_Asia-South America (EC/WC)
Asia—South America (EC/WC)
13.1897
Ship_Asia -Oceania
Asia—Oceania
13.4028
Ship_Asia-North Europe
Asia—North Europe
10.8586
Ship_Asia-Mediterranean
Asia—Mediterranean
12.1358
Ship_Asia-North America EC
Asia—North America EC
12.9854
Ship_Asia-North America WC
Asia—North America WC
12.0818
Ship_Asia-Middle East/India
Asia—Middle East/India
13.5459
Ship_North Europe-North America EC
North Europe—North America EC (incl. Gulf)
14.1823
Ship_North Europe-North America WC
North Europe—North America WC
13.0642
Ship_Mediterranean-North America EC
Mediterranean—North America EC (incl. Gulf)
12.6788
Ship_Mediterranean-North America WC
Mediterranean—North America WC
10.1433
Ship_Europe (North & Med)-Middle East/India
Europe (North & Med)—Middle East/India
13.4276
Ship_Europe (North & Med)-Africa
Europe (North & Med)—Africa
15.8361
Ship_Europe (North & Med)-Oceania (via Suez
/ via Panama)
Europe (North & Med)—Oceania (via Suez / via
Panama)
14.4056
Ship_Europe (North & Med)-Latin
America/South America
Europe (North & Med)—Latin America/South
America
12.6146
Ship_North America-Africa
North America—Africa
17.4549
Ship_North America EC-Middle East/India
North America EC—Middle East/India
12.8788
Ship_North America-South America (EC/WC)
North America—South America (EC/WC)
13.4379
Ship_North America-Oceania
North America—Oceania
15.0552
Ship_South America (EC/WC)-Africa
South America (EC/WC)—Africa
11.7432
29 Buhaug, et al. for the International Maritime Organization (IMO), 2009. Second IMO GHG Study 2009,
International Maritime Organization (IMO), London, UK, April 2009. Available at:
http://www.imo.org/OurWork/Environment/PollutionPrevention/AirPollution/Documents/GHGStudyFINAL.pdf
29
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Ship_Intra-Americas (Caribbean)
Intra-Americas (Caribbean)
15.9222
Ship_Intra-Asia
Intra-Asia
15.2012
Ship_Intra-Europe
Intra-Europe
17.1790
The marine factors in the IMO study reflect commonly-used equipment sizes and types.
The factors in Tables 15 below come from Table 9.1 4 in the IMO study.
Table 15: IMO Marine Emission Factors
TYPE
SIZE
AVERAGE
CARGO
CAPACITY
(metric
tonne)
Average
yearly
capacity
utilization
Average
service
speed
(knots)
Transport
work per ship
(tonne NM)
Loaded
efficiency
(g of CO J
ton-mile)
Total
efficiency
(g of
C02/ton-
mile)
Crude oil
tanker
2000,000+dwt
295,237
48%
15.4
14,197,046,74
2
2.34
4.23
Crude oil
tanker
120,000-199,99
dwt
151,734
48%
15
7,024,437,504
3.21
6.42
Crude oil
tanker
80,000-119,999
dwt
103,403
48%
14.7
4,417,734,613
4.38
8.61
Crude oil
tanker
60,000-79,999 dwt
66,261
48%
14.6
2,629,911,081
6.28
10.95
Crude oil
tanker
10,000-59,999 dwt
38,631
48%
14.5
1,519,025,926
7.59
13.28
Crude oil
tanker
0-9,999 dwt
3668
48%
12.1
91,086,398
30.22
48.61
Products
tanker
60,000+ dwt
101,000
55%
15.3
3,491,449,962
4.82
8.32
Products
tanker
20,000-59,999 dwt
40,000
55%
14.8
1,333,683,350
10.51
15.03
Products
tanker
10,000-19,999 dwt
15,000
50%
14.1
464,013,471
16.49
27.30
Products
tanker
5,000-9,999 dwt
7,000
45%
12.8
170,712,388
21.60
42.62
Products
tanker
0-49,999 dwt
1,800
45%
11
37,598,072
38.68
65.69
Chemical
tanker
20,000 + dwt
32,200
64%
14.7
1,831,868,715
8.32
12.26
Chemical
tanker
10,000-19,999 dwt
15,000
64%
14.5
820,375,271
10.66
15.76
Chemical
tanker
5,000-9,999 dwt
7,000
64%
14.5
382,700,554
15.62
22.04
Chemical
tanker
0-4,999 dwt
1,800
64%
14.5
72,147,958
27.15
32.41
LPG tanker
50,000 + m3
46,656
48%
16.6
2,411,297,106
7.59
13.14
LPG tanker
0-49,999 m3
3,120
48%
14
89,631,360
39.41
63.50
LNG tanker
200,00 + m3
97,520
48%
19.6
5,672,338,333
7.88
13.58
LNG tanker
0-199,999 m3
62,100
48%
19.6
3,797,321,655
12.26
21.17
Bulk carrier
200,000 +dwt
227,000
50%
14.4
10,901,043,01
7
2.19
3.65
Bulk carrier
100,000-199,999
dwt
163,000
50%
14.4
7,763,260,284
2.63
4.38
Bulk carrier
60,000-99,999 dwt
74,000
55%
14.4
3,821,361,703
3.94
5.98
Bulk carrier
35,000-59,999 dwt
45,000
55%
14.4
2,243,075,236
5.55
8.32
Bulk carrier
10,000-34,999 dwt
26,000
55%
14.3
1,268,561,872
7.74
11.53
Bulk carrier
0-9,999 dwt
2,400
60%
11
68,226,787
33.43
42.62
30
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TYPE
SIZE
AVERAGE
CARGO
CAPACITY
(metric
tonne)
Average
yearly
capacity
utilization
Average
service
speed
(knots)
Transport
work per ship
(tonne NM)
Loaded
efficiency
(g of CO2I
ton-mile)
Total
efficiency
(g of
C02/ton-
mile)
General cargo
10,000 + dwt
15,000
60%
15.4
866,510,887
11.09
17.37
General cargo
5,000-9,999 dwt
6,957
60%
13.4
365,344,150
14.74
23.06
General cargo
0-4,999 dwt
2,545
60%
11.7
76,645,792
15.91
20.29
General cargo
10,000+ dwt, 100+
TEU
18,000
60%
15.4
961,054,062
12.55
16.06
General cargo
5,000-9,999 dwt,
100+TEU
7,000
60%
13.4
243,599,799
20.14
25.54
General cargo
0-4,999 dwt,
dwt+TEU
4,000
60%
11.7
120,938,043
22.63
28.90
Refrigerated
cargo
All
6,400
50%
20
392,981,809
18.83
18.83
Container
8000+TEU
68,600
70%
25.1
6,968,284,047
16.20
18.25
Container
5,000-7,999 TEU
40,355
70%
25.3
4,233,489,679
22.19
24.23
Container
3,000-4,999 TEU
28,784
70%
23.3
2,280,323,533
22.19
24.23
Container
2,000-2,999 TEU
16,800
70%
20.9
1,480,205,694
26.71
29.19
Container
1,000-1,999 TEU
7,000
70%
19
578,339,367
42.91
46.86
Container
0-999 TEU
3,500
70%
17
179,809,363
48.61
52.99
Vehicle
4000 +ceu
7,908
70%
19.4
732,581,677
36.78
46.71
Vehicle
0-3999 ceu
2,808
70%
17.7
226,545,399
68.90
84.08
Ro-Ro
2,000+ Im
5,154
70%
19.4
368,202,021
66.12
72.25
Ro-Ro
0-1,999 Im
1432
70%
13.2
57,201,146
80.57
88.02
Note: "Loaded efficiency" is the theoretical maximum efficiency when the ship is fully loaded at service speed/85% load.
Since engine load at the fully loaded condition is higher than the average including ballast and other voyages, the difference
between the columns loaded efficiency" and "total efficiency cannot be explained by differences in utilization only.
4.0 Data Validation
The Shipper Tool also contains data validation checks designed to identify missing and
potentially erroneous data. At this time the only validation involves payload checks and
total ton-mile checks, on the Activity Data screen.
Payload Validation
Payload validation cutpoints were set with the intention of identifying those payloads
that are somewhat outside typical industry values (yellow flag warnings) and those that
are far outside industry averages (red flag warnings). The payload check only apples to
Data Availability selections a, b, and c where payloads are either entered by the user, or
calculated based on other inputs. Checks are applied at the carrier (row) level.
Payload checks are specific to the truck SmartWay Category, which is available for
each carrier from the Carrier Data File. For Truck carriers, the payload checks are
consistent with the Class 8b payload checks currently in the Truck Tool, and are shown
below in Table 16. (See the Truck Tool Technical Documentation for additional
31
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information.) Note that Ranges 1 and 5 are colored red, and require explanations
before proceeding. Ranges 2 and 4 are colored yellow, and explanations are optional.
Table 16. Truck Carrier Payload Validation Ranges
Truck Bin Category
Range
1 Low
Range
1 High
/ 2 Low
Range
2 High
/ 3 Low
Range
3 High
/ 4 Low
Range
4 High
/ 5 Low
Range
5 High
(Max)
LTL Dry Van (from Dry Van
Single - LTL-Moving-
Package)30
0.0
0.0
0.0
9.9
15.7
150.0
Package (from Dry Van
Single - LTL-Moving-
Package)22
0.0
0.0
0.0
9.9
15.7
150.0
TL Dry Van (from Dry Van
Single - other bins)
0.0
10.5
14.5
22.4
26.4
150.0
Refrigerated
0.0
14.5
17.3
22.9
25.7
82.5
Flatbed
0.0
14.0
18.3
26.7
31.0
99.9
Tanker
0.0
19.1
22.0
27.8
30.7
103.8
Moving (from Dry Van
Single - LTL-Moving-
Package)
0.0
6.9
11.0
19.1
23.2
83.7
Specialized (from Specialty -
Other bins)
0.0
20.2
22.9
28.3
31.1
111.0
Dray (from Chassis)
0.0
11.2
16.5
27.1
32.4
73.5
Auto Carrier
0.0
5.7
11.0
21.4
26.6
73.5
Heavy-Bulk
0.0
2.7
16.5
44.0
57.8
120.0
Utility (from Specialty -
Other bins)
0.0
20.2
22.9
28.3
31.1
111.0
Mixed (from Other - Heavy-
Flatbed-Mixed bins)
0.0
14.7
21.1
33.8
40.1
99.3
Expedited (from Dry Van
Single - other bins)
0.0
10.5
14.5
22.4
26.4
150.0
30 Since LTL and package shipments can be very small, no lower-bound "red/yellow" ranges are designated for LTL
and package carrier payloads. Upper bound yellow and red ranges for LTL and package (and multi-modal) carriers
were set equal to the average payload (6.20) plus twice the standard deviation (7.33) for logistics companies using
these carrier types (n=991 for 2013 data).
32
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With the exception of LTL and package carrier selection (see footnote 30), Logistic
carrier payload validations are based on 2011 Logistics Partner data, and use simple
cutoffs from the cumulative payload distribution shown in Figure 2 below.
Figure 2. Logistics Partner Payload Distribution
Cumulative Payload Distribution - 2011 Logistics
1
0.9
c
_o
0.8
JS
3
0.7
a
o
a.
0.6
a
c
E
0.5
(O
a.
M-
0.4
o
c
o
0.3
t!
(O
LL.
0.2
0.1
0
J
f
1
j\
j\
10
20
30
40 50 60
Short Tons
70
80
90
100
As can be seen in the figure, the payload distribution is highly non-normal, so use of
validation cutoffs based on standard deviation is not appropriate. However, rough
inflection points appear at approximately 10%, 20%, 80%, and 90%. As such, these
values were used to specify the following payload validation cutoffs for logistics carriers.
• Range 1 Red: 0 - 12.0 tons
• Range 2 Yellow: 12.0 - 16.7 tons
• Range 3: 16.7 - 21.0 tons
• Range 4 Yellow: 21.0 - 27.2 tons
• Range 5 Red: 27.2 - 150 tons (150 absolute max)
Validation cutoffs for rail and surface multimodal carriers are summarized below. The
upper bound outpoints for surface multimodal payloads are based on a qualitative
review of 2011 multimodal carrier Tool submittals. The upper bound outpoints for rail
payloads are based on the distribution of average values estimated for all Class 1
carriers (see Table 5 above).
33
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• Average surface multimodal payloads less than 9.4 tons (error - red)
• Average surface multimodal payloads greater than 95 tons (error - red)
• Average railcar payloads less than 9.4 tons or greater than 125 tons (error - red)
• Average surface multimodal payloads between 9.4 and 15.5 tons (warning -
yellow)
• Average surface multimodal payloads between 60 and 95 tons (warning - yellow)
In addition, the absolute upper bound for rail and surface multimodal carriers have both
been set at 200 tons. Multimodal carriers with an air component have their maximum
allowable average payload set to 58 tons, corresponding to the maximum payload
capacity for the largest aircraft make/model specified by SmartWay partners in 2017.
Payloads above this amount will trigger a "red" out of range error that must be explained
by the partner in order to proceed, although no value has been set for a maximum
allowable payload at this time. Payloads between 29 and 58 tons will receive a "yellow"
warning which may be explained if the partner chooses. Payloads greater than zero and
less than 29 tons will receive a "red" out of range error requiring an explanation.
Any payload value less than or equal to zero will be flagged as an error and must be
changed.
Finally, barge carrier payloads are flagged for verification if their density is greater than
0.6 tons per cubic foot or less than 0.003 tons per cubic foot, consistent with the
payload validation used in the Barge Tool.
Ton-Mile Validation
2011 Logistics Partner data was evaluated to establish absolute upper bounds for ton-
mile inputs. The ton-mile validation applies at the carrier (row) and total fleet
(summation of rows) level, with the same values applied to both. The maximum
allowable ton-mile value was set to twice the observed maximum value in the 2011 data
set: 209,207,446,000 ton-miles.
34
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Appendix A
Calculation of Truck-Equivalent Mileage Factors for Rail
Truck-equivalent can be converted into railcar-miles, so that partners can more readily
estimate emissions impacts from shifting freight between truck and rail modes, by
estimating the average volume capacity of Class I railcars and dividing it by an average
freight truck volume capacity. This results in a rough estimate that does not take into
consideration the utilized volume of railcars or the comparative freight truck, but we
determined that this was the best available data and method to estimate modal average
railcar-equivalent miles.
To estimate the average volume capacity of railcars, we multiplied the railcar miles
reported by each company for each railcar type in their respective 2008 R-1 reports
(lines 15-81) by the volume-per-railcar assumptions in Table A-1 to obtain total Class I
TEU-miles. We then divided the total railcar TEU-miles by the total railcar-miles to
estimate the average railcar volume capacity. We then divided this average railcar
volume capacity (3.92 TEUs) by the average freight truck volume capacity that we
developed for the truck g/TEU-mile factor discussed above (2.78 TEUs) to develop the
conversion factor -1.41 railcar-miles-to-truck-miles. In the absence of more specific
data, this factor can be used to convert truck miles to railcar miles for use on the Modal
Shift screen of the Shipper Tool. Note that no equivalent information was identified for
the estimation of industry-average barge volumes.
Table A-1: Railcar Volume Assumptions and Sources
Railcar Type
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (NS)31, Union Pacific Railroad (UP)32,
Burlington Northern Santa Fe Railroad (BNSF)33, CSX Transportation
Railroad (CSX)34, World Trade Press Guide to Railcars (GTRC)35, Chicago
Rail Car Leasing (CRCL)36, Union Tank Car Company (UTCC)37, U.S
Department of Aqriculture (USDA)38
Boxcar 50 ft and
longer including
equipped boxcars
7,177
Based on the average of the following boxcar types:
50ft assumed to be 5694 [reflecting the average of 5355 (NS), 5431 (UP),
5238 (CSX), 6175 (BSNF), 6269 (GTRC)].
60ft assumed to be 6,648 [reflecting the average of 6618 (NS), 6389 (UP),
6085 (CSX), 7500 (BNSF)].
50ft hiah cube assumed to be 6.304 lYeflectina the averaae of 6339 CNS^ and
6269 (CSX)].
60 ft hiah cube assumed to be 6917 lYeflectina the averaae of 7499 CNS^ .
6646 (CSX), and 6607 (GTRC)l.
31 http://www.nscorp.com/nscportal/nscorp/Customers/Equipment_Guide
32 http://www.uprr.com/customers/equip-resources/cartypes/index.shtml
33http://www.bnsf.com/customers/how-can-i-ship/individual-railcar/#%23subtabs-3
34 http://www.csx.eom/index.cfm/customers/equipment/railroad-equipment/#boxcar_specs
35 http://www.worldtraderef.com/WTR_site/Rail_Cars/Guide_to_rail_Cars.asp
36 http://www.crdx.com/railcar.html
37 http://www.utlx.com/bdd_tank.html
38U.S. Department of Agriculture (USDA), 1992, Weights, Measures, and Conversion Factors for Agricultural
Commodities and Their Products, Agricultural Handbook Number 697, Economic Research Service, Washington,
DC. Available at: http://www.ers.usda.gov/publications/ah697/ah697.pdf
35
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RailcarType
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (NS)31, Union Pacific Railroad (UP)32,
Burlington Northern Santa Fe Railroad (BNSF)33, CSX Transportation
Railroad (CSX)34, World Trade Press Guide to Railcars (GTRC)35, Chicago
Rail Car Leasing (CRCL)36, Union Tank Car Company (UTCC)37, U.S
Department of Agriculture (USDA)38
86ft assumed to be 9999 (NS).
Autoparts assumed to be 7499 (NS).
Boxcar 40ft
4,555
Based on estimate of 50ft boxcar volume described above. Assumed 40ft
length would result in 20% reduction in volume.
Flat car - all types
except for multi-level
6,395
Based on the average of the following flat car types:
60ft assumed to be 6739 (BNSF).
89ft assumed to be 9372(BNSF).
Coil assumed to be 3387(NS).
Covered coil assumed to be 5294 lYeflectina the averaae of 8328 (NS) and
2260 (BNSF)].
Centerbeam assumed to be 6546 lYeflectina the averaae of 5857 CUP") and
7236 (BNSF)].
Bulkhead assumed to be 7030 (BNSF).
Multi-level flat car
13,625
Based on the average of the following multi-level flat car types:
Unilevel (that carrv verv larae carao. such as vehicles/tractors) assumed to be
12183 (NS).
Bi-level assumed to be 1438KNS).
Tri-level assumed to be 14313 (based on averaae of 15287 (NS") and 13339
(BNSF).
Flat Car - all types-
including multi-level
[not used in analysis,
except for estimating
volume of "All Other
Cars"]
7,428
Based on the average volumes of the flatcar types described above including
multi-level as a single flat car type.
Gondola - all types
Including equipped
5,190
Based on the average of the following gondala car types:
52-53ft assumed to be 2626 Ibased on averaae of 2665 (NS). 2743 (CSX).
2400 (BNSF), and 2697(CRLC)].
60-66ft assumed to be 3372 Ibased on averaae of 3281 (NS). 3242 (CSX).
3350 (BNSF), CRCL-3670,and 3366 (GTRC)].
Municipal Waste assumed to be 7999 (NS).
Woodchip assumed to be 7781 Ibased on averaae of 7862 (NS") and 7700
(CRCL)].
Coal assumed to be 4170 [based on averaae of 3785 (NS) and 4556 (BNSF)l.
Refrigerated -
Mechanical /non-
Mechanical
6,202
Based on the average of the following refrigerated car types:
48-72ft assumed to be 6963 Ibased on averaae of 6043 (UP) and 7883
(BNSF)].
50ft assumed to be 5167(GTRC).
40-90 ft assumed to be 6476 Ibased on averaae of 6952 (UP) and 6000
(BNSF)l.
Open Top Hopper
4,220
Based on the average of the following open top hopper car types:
42ft assumed to be 3000 (UP).
54ft assumed to be 3700 (UP).
60ft assumed to be 5188 [based on average of 5125 (UP) and 5250 (GTRC)].
45ft+ assumed to be 4105 Ibased on averaae of 4500 (UP) and 3710 (BNSF).
Woodchip assumed to be 7075 Ibased on averaae of 7525 (NS). 5999 (UP),
and 7700 (CRCL)].
Small Aaareaate assumed to be 2252 Ibased on averaae of 2150 (NS). 2106
(BNSF), and 2500 (CRCL)l.
Covered Hopper
4,188
Based on the average of the following covered top hopper car types:
45ft assumed to be 5250 (GTRC).
Aaareaate assumed to be 2575 Ibased on averaae of 2150 (NS) and 3000
(CRCL)].
Small Cube Gravel assumed to be 2939 Ibased on averaae of 2655 (NS).
3100 (CSX), and 3063 (BNSF).
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RailcarType
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (NS)31, Union Pacific Railroad (UP)32,
Burlington Northern Santa Fe Railroad (BNSF)33, CSX Transportation
Railroad (CSX)34, World Trade Press Guide to Railcars (GTRC)35, Chicago
Rail Car Leasing (CRCL)36, Union Tank Car Company (UTCC)37, U.S
Department of Agriculture (USDA)38
Med-Larae Cube Ores and Sand assumed to be 4169 Ibased on averaae of
3750 (NS) and 4589 (BNSF)].
Jumbo assumed to be 5147 Tbased on averaae of 4875 (NSV 4462 (CSX).
5175 (BNSF), and 6075 (CRCL)].
Pressure Differential (flour) assumed to be 5050 Tbased on averaae of 5124
(NS) and 4975 (CRCL)l.
Tank Cars under
22,000 gallons
2,314
Assumes 1 gallon=0.1337 cubic foot (USDA).
Based on small tank car average volume of 17304 gallons, which is the
average of the following currently manufactured tank car volume design
capacities of 13470, 13710, 15100, 15960, 16410,17300,19900,20000,20590,
and 20610 gallons (GTRC).
Tank Cars over 22,000
gallons
3,857
Assumes 1 gallon=0.1337 (USDA).
Based on large tank car volume of 28851 gallons, which is the average of the
following currently manufactured tank car volume design capacities of 23470,
25790, 27200, 28700, 30000, 33000, and 33800 gallons (GTRC).
All Other Cars
5,014
Based on average volume presented above for each of the nine railcar types
(all flatcars are represented by the line item that includes multi-level flatcars -
7428).
37
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