Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Shipper Partner 2.O.14 Tool:
Technical Documentation 8^^
2014 Data Year - United States Version
United States
Environmental Protection
Agency
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Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Shipper Partner 2.O.14 Tool:
Technical Documentation
2014 Data Year - United States Version
Transportation and Climate Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
United States Office ofTransportation and Air Quality
Environmental Protection EPA-420-B-15-089
A9ency October 2015
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SmartWay 2.0.14
Shipper Tool Technical Documentation
United States Version
10-3-15
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 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, logistics and multi-modal carrier emissions performance
data that EPA has included in the Tool, along with industry average Class I rail C02
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.
1 While this Tool is primarily focused on freight movements in the rail, barge and trucking sectors, future
tools will help Shippers evaluate the emissions performance associated with other transport modes
including self-propelled marine and air.
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If shippers select the "% SmartWay Only", 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 ranking category-level
emissions performance data for their truck, logistics and multi-modal carriers as well as
available industry average rail emissions factors. Emissions performance data for
barge 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
they 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 Ranking 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.
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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Table 1. Example Gram per Mile Compositing Calculation
Carrier 1
Carrier 2
CO2 g/mi
1,700
1,500
Mi/yr
2,000,000
1,000,000
Weighting Factor
0.667
0.333
Weighted composite g/mi
Weighted COz g/mi
1,134(0.667x1,700)
500(0.333x1,500)
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 C02 g/mile of 1,000
o T2 has a C02 g/mile of 2,000
o T3 has a C02 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 CO2 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 CO2 g/mile = [1,000*2,000 / 2,000] = 1,000
o When Inbound/Outbound combo = Outbound:
• Composite CO2 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 C02, NOx and PM gram per mile, and gram
per ton-mile emission factors for truck rail and barge freight transport providers. These
data are provided in the SmartWayCarrierData2014.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 from self-propelled
marine and air transport providers, and gram per volume-mile emission factors for all
modes, in the near future.
Truck Carrier Performance
Truck carrier performance data utilized by the current Shipper Tool is based on 2013
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 ranking category, rather than exact performance levels for a given carrier.
Truck ranking categories include:
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• TL Dry Van
• LTL Dry Van
• Refrigerated
• Flatbed
• Tanker
• Dray
• Package
• Auto Carrier
• Expedited
• Heavy/Bulk
• Moving
• Specialized
• Mixed
The following provides an overview of the truck carrier ranking process used to estimate
the carrier-specific performance ranges.
Truck Performance Ranking
In the 2014 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
TL
LTL
Dray
Expedited
Package
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
Private
TL
LTL
Dray
Expedited
Package
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
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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 ranking categories. There
are relatively few private fleets compared to for-hire fleets. Because owners of private
fleets generally hire their own fleets exclusively, it was determined that ranking 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.
Ranking for-hire and private separately would have doubled the number of ranking
categories. Therefore fleets can thus be categorized as shown below.
For-Hire and Private
TL
LTL
Dray
Expedited
Package
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
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 ranking category are placed in the Mixed category.
Individual fleets were then placed into ranking categories. The following shows the
relative number of fleets for the various category intersections, with darker shadings
indicating more fleets.
TL
LTL
Dray
Expedited
Package
Mixed
Dry Van
^m
Reefer
-
-
Flatbed
-
-
-
Tanker
-
-
-
-
-
Chassis
-
-
-
Heavy/Bulk
-
-
-
-
Auto
Carrier
-
-
-
Moving
-
-
-
Specialized
-
-
-
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
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(intermodal container) 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,
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 multi-modal
fleets were also included and retained as unique categories.
The final performance categories for 2015 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 PD categories. However, the Reefer category
assignment is over-ridden if the operation category is greater than or equal to 75% dray,
logistics, or multi-modal. 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 PD 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.
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Barge
SmartWay Carrier Categories and Data Specificity
2015 Calendar Year
Rail
Single Modal Average for All Rail
[No company differentiation allowed per Association of American Railroads)
Air
Company Specific Data
Logistics
5 Performance Levels
Multimodal
Emission Factor Data Ontv
[No 5 Performance Level Ranking)
Marine
To Be Determined
(Proposed availability in 2016 calendar year)
It is possible that SmartWay will expand these categories based on in-use experience or
as a result of further data analysis, and/or requests from industry.
Fleets within a category have been ranked from lowest emission factor (best) to highest
emission factor (worst) for each of the following metrics: C02 g/mile, C02 g/ton-mile,
NOx g/mile, NOx g/ton-mile, PM10 g/mile and PM10 g/ton-mile. When performance
ranking 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
"outpoints" (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 outpoints
remained as close to the originals as possible. The new range outpoints 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.
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It would be simpler and more straightforward to use fleet-specific emission factors,
however the trucking industry expressed concern with revealing exact data that 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 CCte), SmartWay believes it is acceptable
and appropriate to break truck fleets into 5 performance ranges for each ranking
category. The table below illustrates the ranges in the For Hire/Private
Truckload/Expedited Dry Van ranking category, using 2013 truck Partner data as an
example.
Table 2. Example Emission Factor Ranges for One Performance Category (2013
Data)
For-H ire/Private Truckload/ Dry Van CO2 g
Group
ID
1
2
3
4
5
Fleets
Per Bin
186
227
194
140
115
Grams Per
Mile Min
944
1,551
1,651
1,751
1,851
Grams Per
Mile Max
1,549
1,650
1,749
1,848
5,090
Grams Per
Mile Avg
1,452
1,601
1,692
1,798
2,010
/mile
Grams Per Mile
Midpoint
1,500
1,600
1,700
1,800
1,900
Grams Per
MileStd Dev
118
28
29
29
359
Similar tables have been developed for all performance ranking 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
categories/ranges. SmartWay expects to update the category/range structure
approximately every three years.
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 the standard
performance range delta (max - min) for each range within each ranking 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 ranking categories, the worst performance value
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was selected to be the midpoint for all non-SmartWay Truck carriers. This approach
does not require the shipper to identify the appropriate ranking category for their non-
SmartWay carrier(s), which they may not know.
As discussed in the Shipper Tool User 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 Multi-modal Carrier Performance
Logistic and multi-modal carriers have their own performance categories based on the
carrier Tool submittals.3 The Shipper Tool modifies the Range 5 values for each of
these categories (logistics and multi-modal) to estimate non-SmartWay carrier
performance in the same way as was done for non-SmartWay Truck carriers (i.e.,
adding the standard range delta value to the Range 5 midpoints).
Barge Carrier Performance
Barge carrier performance data are collected and displayed in the Shipper Tool for each
individual carrier, without performance range grouping/midpoint determination. Non-
SmartWay barge carrier performance is assumed to be 25% lower (worse) than the
worst performing SmartWay barge partner. Payloads for non-SmartWay partners are
set equal to the average of SmartWay partners.
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 C02 factor (10,180 g C02/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 an opportunity to provide company-specific
data in the future. The R-1 data and corresponding C02 performance data are
presented in Table 3 below.
3 As of this writing 2014 performance data is included for multi-modal carriers, and 2013 data for logistics carriers.
2014 logistics carrier data should be included in the carrier file by fall of 2015.
10
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Table 3. Rail Carrier Performance Metric Calculation Inputs and Results (2010 R-1
Data)
Rail Company
BNSF Railway
CSX Transportation
Grand Trunk
Kansas City Southern
Norfolk Southern*
Soo Line
Union Pacific
Total - Industry
Average
Gal/Yr
('OOO)Sch.
750 Line 4
1,295,147
490,050
88,290
62,354
440,159
65,530
1,063,201
3,504,731
Freight Ton-
Mi/Yr('000)
Sch .755 line
110
646,549,059
230,507,431
50,586,328
31,025,588
183,104,320
33,473,544
525,297,747
1,700,544,017
Railcar-Mi/Yr
('000) Sch.
755 sum of
lines 30, 46,
64&S2
11,230,994
4,720,293
1,206,818
609,929
4,081,893
771,033
10,336,081
32,957,041
g CO2/railcar-
mile
1,163
1,047
738
1,031
1,087
857
1,037
1,072
g CCVshort
ton-mile
20.20
21.44
17.60
20.76
24.24
19.74
20.41
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 modes.
Average payload 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.
11
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Table 4. Rail Carrier Average Payload
Carrier
BNSF Railway
CSX Transportation
Grand Trunk
Kansas City Southern
Norfolk Southern
Soo Line
Union Pacific
Industry Average
Avg Payload/Loaded
Railcar(tons)
108
85
80
91
76
77
91
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 8 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 5 below.
Table 5. Rail Carrier Average Volume Determination
Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Avg. Cu Ft.
4,555
7,177
7,177
5,190
5,190
4,188
4,220
4,220
6,202
6,202
BNSF
Railcar Miles (xlK)
1
9,338
147,226
379,762
75,894
758,442
65,077
137,449
19,272
32,910
Cu Ft Miles (xlK)
4,555
67,018,826
1,056,641,002
1,970,964,780
393,889,860
3,176,355,096
274,624,940
580,034,780
119,524,944
204,107,820
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Freight Car Types (Rl - Schedule 755)
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Avg. Cu Ft.
6,395
13,625
6,395
6,395
5,772
BNSF
Railcar Miles (xlK)
520,521
38,624
357
71,826
20,146
Cu Ft Miles (xlK)
3,328,731,795
526,252,000
2,283,015
459,327,270
116,282,712
5,811
13
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
CSX
Railcar Miles (xlK)
6,987
144,631
137,256
64,532
153,315
78,412
35,451
17,117
11,923
125,828
29,956
162
31,913
19,861
Cu Ft Miles (xlK)
50,145,699
1,038,016,687
712,358,640
334,921,080
642,083,220
330,898,640
149,603,220
106,159,634
73,946,446
804,670,060
408,150,500
1,035,990
204,083,635
114,637,692
6,389
14
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Grand Trunk (Canadian National)
Railcar Miles (xlK)
0
2,119
66,110
6,467
19,201
44,239
9,114
32,621
312
205
2,779
4,831
20
31,744
4,755
Cu Ft Miles (xlK)
15,208,063
474,471,470
33,563,730
99,653,190
185,272,932
38,461,080
137,660,620
1,935,024
1,271,410
17,771,705
65,822,375
127,900
203,002,880
27,445,860
6,309
15
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Kansas City Southern
Railcar Miles (xlK)
0
3,383
39,792
16,628
11,150
50,346
626
943
21
52
10,736
629
12
2,321
247
Cu Ft Miles (xlK)
24,279,791
285,587,184
86,299,320
57,868,500
210,849,048
2,641,720
3,979,460
130,242
322,504
68,656,720
8,570,125
76,740
14,842,795
1,425,684
5,938
16
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Norfolk Southern
Railcar Miles (xlK)
0
7,622
136,745
193,214
111,320
116,848
84,557
30,078
3,512
5,392
114,928
20,349
145
24,563
212,408
Cu Ft Miles (xlK)
54,703,094
981,418,865
1,002,780,660
577,750,800
489,359,424
356,830,540
126,929,160
21,781,424
33,441,184
734,964,560
277,255,125
927,275
157,080,385
1,226,018,976
6,065
17
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Soo Line (Canadian Pacific)
Railcar Miles (xlK)
0
725
17,972
1,203
8,856
94,146
3,077
20
159
742
11,178
2,973
12
10,068
428
Cu Ft Miles (xlK)
5,203,325
128,985,044
6,243,570
45,962,640
394,283,448
12,984,940
84,400
986,118
4,601,884
71,483,310
40,507,125
76,740
64,384,860
2,470,416
5,667
18
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Union Pacific
Railcar Miles (xlK)
0
12,311
238,241
206,370
91,775
370,929
188,027
104,969
82,874
27,009
1,026,251
46,889
350
72,371
16,769
Cu Ft Miles (xlK)
88,356,047
1,709,855,657
1,071,060,300
476,312,250
1,553,450,652
793,473,940
442,969,180
513,984,548
167,509,818
6,562,875,145
638,862,625
2,238,250
462,812,545
96,790,668
6,248
19
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Industry Average Railcar Cubic Feet
Total (for Industry Average)
Railcar Miles (xlK)
1
42,485
790,717
940,900
382,728
1,588,265
428,890
341,531
123,267
78,233
1,812,221
144,251
1,058
244,806
274,614
Cu Ft Miles (xlK)
4,555
304,914,845
5,674,975,909
4,883,271,000
1,986,358,320
6,651,653,820
1,809,915,800
1,441,260,820
764,501,934
485,201,066
11,589,153,295
1,965,419,875
6,765,910
1,565,534,370
1,585,072,008
6,091
% SmartWay Value
The % SmartWay screen tracks 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, 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 Strategies4
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
text description of the strategy. The Tool assumes that total mass emissions are
reduced in direct proportion with the specified mileage or weight reduction.5
4 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.
5 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.
21
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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 C02, NOx, or PM)
EM = Emissions inventory value (tons of C02, NOx, or PM)
Reduction = the reduction in total miles or weight as a result of the
strategy (expressed as fraction)
Fractional reduction estimates must be documented with 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 added 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 their Partner Account Manager.
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
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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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 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 rail and/or trucking
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 an
alternative emissions factor of their choice (corresponding to the "User Input" selection).
Note that 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 the operation of intermodal facilities.
While EPA has populated the Tool with illustrative modal average freight rail and truck
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 ranking 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 likely
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.
Partners may also evaluate modal shifts to and from the self-propelled marine and
aviation sectors by inputting an emissions factor of their choice ("User Input" option
only). While we have not provided illustrative self-propelled marine and aviation freight
factors in the Tool, there are several external resources that partners can consult. We
have included some selected sources of self-propelled marine and aviation factors in
the following section.
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.
23
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Total Emission Impact (tons/yr) =
[(Efficiency Before x "From Mode" Amount) -
(Efficiency After x "To Mode" Amount)] x grams to short tons conversion factor6
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 carrier (see Table 5 above). These volumes
estimates are contained in the Carrier Data File, and should be weighted by the miles
associated with each rail carrier entered on the Activity Data screen in order to
estimate a single weighted-average railcar volume for the shipper company in question.
Similarly, weighted average volumes can also be calculated for the different truck
carriers associated with the given shipping company. 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. Next, you can convert your truck-equivalent mile estimates
to railcar equivalent miles by dividing truck miles by the ratio R7 Enter the
corresponding railcar mile activity estimate in the "Amounts" column of the Modal Shift
screen.
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.
In addition the value of truck miles to R should also be divided by 1.15 to convert from
statute to nautical miles.8
61.1023 x 10'6 short tons/gram
7 Any route mileage differences must be adjusted for separately.
8 Barge performance values are expressed in grams per nautical mile, to be consistent with barge carrier reporting
practices.
24
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Background on Illustrative (Modal Average) U.S. Truck and Rail Factors
Modal Average performance metrics have been developed for rail and truck modes
(both gram per mile and gram per ton-mile), for estimating emission impacts using the
Modal Shift screen. We developed the freight truck g/ton-mile factors with 2010 C02,
NOx, and PM2.59 inventory data on short-haul single unit, short-haul combination unit,
long-haul single unit, and long-haul combination unit truck categories10 in EPA's 201 Oa
version of the Motor Vehicle Emissions Simulator (MOVES2010a) model11. MOVES
does not contain ton-mile data, so we then divided the MOVES-based inventories by
2002 ton-mile data from the Federal Highway Administration's 2009 Freight Facts and
Figures^2, 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 2010 VMT
datainMOVES2010a.
Table 6 presents the illustrative freight truck emissions factors in the tool and Table 7
presents the key underlying data. (Note that the modal average factors calculated for
truck carriers were assumed valid for logistics and multi-modal carriers as well.)
Table 6: Illustrative U.S. Freight Truck Industry Average Factors in Modal Shift
gram/short ton-mile
gram/mile
gram/TEU-mile
C02
161.8
1,661
597.4
NOx
1.114
11.44
4.113
PM2.5
0.0480
0.4925
0.1772
Table 7: Underlying Emissions Inventories and Activity Data for Illustrative U.S.
Freight Truck Industry Average Factors in Modal Shift
CO2 (grams)
NOx (grams)
PIVh .5 (grams)
short ton-miles
miles
341,986,421,100,000
2,354,767,660,000
101,411,195,611
2,114,115,022,573
205,918,984,400
We developed the freight rail gCO2/ton-mile factors with 2008 inventory data from
EPA's Inventory of U.S. Greenhouse Gas Emissions and Sinks (1990-2008)™, which is
9 Corresponding PM10 emission factors were estimated assuming PM2.5 values were 97% of PM10 values, based
on MOVES model outputs for diesel fueled trucks.
10 These four truck categories are coded as 52, 53, 61, and 62 in the MOVES model, respectively.
11 EPA's MOVES model and accompanying resources, including technical documentation, are available at:
http://www3.epa.gov/otaq/models/moves/index.htm.
12U.S. DOT, Federal Highway Administration, 2009. Freight Facts and Figures 2009, FHWA-HOP-10-007, Ton
Miles of Truck Shipments by State: 2002 (Table 3-10). Available at:
http://ops.fhwa.dot.gov/freight/freight_analysis/nat_freight_stats/docs/09factsfigures/table3_10.htm
13 U.S. EPA, 2010. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-200%, WashingtonDC (EPA
430-R-10-006), available at: http://www.epa.gov/climatechange/emissions/usgginv_archive.html. Total freight rail
25
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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™, 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 rule15. 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 Board16. We developed the C02 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 gC02/gallon, which corresponds to the diesel emissions
factor in the current version of the SmartWay Truck Tool.17 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™. 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.
Table 8 presents the illustrative freight rail emissions factors in the Tool and Table 9
presents the key underlying data.
GHG emissions are presented in Table A-l 10 of the inventory. Table 10 in this document presents CCh-only data.
In order to isolate the CCh-only emissions data, we accessed spreadsheets that are not publically available.
14 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
15 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, Washington DC. Available at: www.epa.gov/otaq/regs/nonroad/420r08001a.pdf
16 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
17 The source of the diesel factor is the fuel economy calculations in 40 C.F.R600.113 available at
http://edocket.access.gpo.gov/cfr 2004/iulqtr/pdf/40cfr600.113-93.pdf.
18 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://www3.epa.gov/otaq/regs/nonroad/locomotv/420f09025.pdf.
26
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Table 8: Illustrative U.S. Freight Rail Industry Average Factors in Modal Shift
gram/short ton-mile
gram/railcar mile
gram/TEU-mile
C02
22.94
1,072
292.8
NOX
0.4270
18.6
4.745
PM2.5
0.0120
0.503
0.1284
Table 9: Underlying Emissions Inventories and Activity Data for Illustrative U.S.
Freight Rail Industry Average Factors in Modal Shift
CO2 (grams)
short ton-miles
Class l-only diesel fuel consumption (gallons)
Class l-only railcar miles (total)
50' and Larger Box Plain + Box Equipped
40' Box Plain
Flat TOFC/COFC, General, and Other
Flat Multi Level
Gondola Plain and Equipped
Refrigerated Mechanical and Non-Mechanical
Open Top Hopper General and Special Service
Covered Hopper
Tank under 22,000 gallons
Tank 22,000 gallons and over
All Other Car Types
41,736,353,990,153
1,819,633,000,000
3,905,310,865
34,611,843,000
2,223,402,000
22,000
5,057,466,000
1, 725, 998, 000
7,893,684,000
495,311,000
5,913,012,000
7,210,656,000
1,295,482,000
2,394,565,000
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.
Outside Sources of Marine and Air Emission Factors
There are many sources of marine and aviation emission factors available in research
literature and other GHG estimation tools. For reference, we have included below:
• gC02/ton-mile marine and aviation factors from the Business for Social
Responsibility's (BSR) Clean Cargo Tool gC02/ton-mile marine and aviation factors
from a study prepared for the International Maritime Organization (IMO)19
• multi-pollutant g/ton-mile barge factors from a study prepared by the Texas
Transportation Institute (TTI)forthe U.S. Maritime Administration20
19 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
20 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. Available at: www.waterwayscouncil.org/study/public%20study.pdf
27
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Note that the factors from BSR and IMO are published in units of kgCCte/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. BSR also included two aviation factors in their tool from DEFRA
for short and long international trips, which reflect higher C02 emissions rates from
shorter trips because landing and take-off operations consume more fuel than cruising
at altitude. The BSR aviation and marine factors in Tables 10 and 11 below are from
the "Emission Factors & Distances" tab in their tool.
Table 101: BSR Marine Emission Factors (gCO2/short ton-mile)
Ship_general
Ship_Barge
Ship_Feeder
Ship_inland_Germany
Ship_inland_China
Ship_Asia-Africa
Ship_Asia-South America (EC/WC)
Ship_Asia-Oceania
Ship_Asia-North Europe
Ship_Asia-Mediterranean
Ship_Asia-North America EC
Ship_Asia-North America WC
Ship_Asia-Middle East/India
Ship_North Europe-North America EC
Ship_North Europe-North America WC
Ship_Mediterranean-North America EC
Ship_Mediterranean-North America WC
Ship_Europe (North & Med)-Middle East/India
Ship_Europe (North & Med)-Africa
Ship_Europe (North & Med)-Oceania (via Suez
/ via Panama)
Ship_Europe (North & Med)-Latin
America/South America
Ship_North America-Africa
Ship_North America EC-Middle East/India
Ship_North America-South America (EC/WC)
Ship_North America-Oceania
Ship_South America (EC/WC) -Africa
Ship_Intra-Americas (Caribbean)
Ship_Intra-Asia
Ship_Intra-Europe
International
International
International
Germany
China
Asia --Africa
Asia-South America (EC/WC)
Asia—Oceania
Asia—North Europe
Asia-Mediterranean
Asia-North America EC
Asia-North America WC
Asia-Middle East/India
North Europe— North America EC (incl. Gulf)
North Europe— North America WC
Mediterranean— North America EC (incl. Gulf)
Mediterranean— North America WC
Europe (North & Med)-Middle East/India
Europe (North & Med)-Africa
Europe (North & Med)-Oceania (via Suez/ via
Panama)
Europe (North & Med)-Latin America/South
America
North America-Africa
North America EC— Middle East/India
North America-South America (EC/WC)
North America— Oceania
South America (EC/WC) -Africa
Intra-Americas (Caribbean)
Intra-Asia
Intra-Europe
13.0678
29.1937
29.1937
41.5280
35.0578
11.9227
13.1897
13.4028
10.8586
12.1358
12.9854
12.0818
13.5459
14.1823
13.0642
12.6788
10.1433
13.4276
15.8361
14.4056
12.6146
17.4549
12.8788
13.4379
15.0552
11.7432
15.9222
15.2012
17.1790
28
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'able 11: BSR Air Emission Factors (gCO2/short ton-mile)
Air freight long >3700km
Air freight short <3700km
International
International
868.3227
2049.9959
The marine and aviation factors in the IMO study reflect commonly-used equipment
sizes and types. The factors in Tables 12 and 13 below come from Table 9.1 and 9.4 in
the IMO study, respectively.
Table 12: IMO Marine Emission Factors
TYPE
Crude oil
tanker
Crude oil
tanker
Crude oil
tanker
Crude oil
tanker
Crude oil
tanker
Crude oil
tanker
Products
tanker
Products
tanker
Products
tanker
Products
tanker
Products
tanker
Chemical
tanker
Chemical
tanker
Chemical
tanker
Chemical
tanker
LPG tanker
LPG tanker
LNG tanker
LNG tanker
Bulk carrier
Bulk carrier
Bulk carrier
Bulk carrier
Bulk carrier
Bulk carrier
SIZE
2000,000+dwt
120,000-199,99
dwt
80,000-119,999
dwt
60,000-79,999 dwt
10, 000-59, 999 dwt
0-9,999 dwt
60,000+ dwt
20,000-59,999 dwt
10,000-1 9,999 dwt
5,000-9,999 dwt
0-49,999 dwt
20,000 + dwt
10,000-1 9,999 dwt
5,000-9,999 dwt
0-4,999 dwt
50,000 + m3
0-49,999 m3
200,00 + m3
0-1 99,999m3
200,000 +dwt
100,000-199,999
dwt
60,000-99,999 dwt
35,000-59,999 dwt
10, 000-34, 999 dwt
0-9,999 dwt
AVERAGE
CARGO
CAPACITY
(metric
tonne)
295,237
151,734
103,403
66,261
38,631
3668
101,000
40,000
15,000
7,000
1,800
32,200
15,000
7,000
1,800
46,656
3,120
97,520
62,100
227,000
163,000
74,000
45,000
26,000
2,400
Average
yearly
capacity
utilization
48%
48%
48%
48%
48%
48%
55%
55%
50%
45%
45%
64%
64%
64%
64%
48%
48%
48%
48%
50%
50%
55%
55%
55%
60%
Average
service
speed
(knots)
15.4
15
14.7
14.6
14.5
12.1
15.3
14.8
14.1
12.8
11
14.7
14.5
14.5
14.5
16.6
14
19.6
19.6
14.4
14.4
14.4
14.4
14.3
11
Transport
work per ship
(tonne NM)
14,197,046,74
2
7,024,437,504
4,417,734,613
2,629,911,081
1,519,025,926
91,086,398
3,491 ,449,962
1 ,333,683,350
464,013,471
170,712,388
37,598,072
1,831,868,715
820,375,271
382,700,554
72,147,958
2,411,297,106
89,631,360
5,672,338,333
3,797,321 ,655
10,901,043,01
7
7,763,260,284
3,821 ,361 ,703
2,243,075,236
1 ,268,561 ,872
68,226,787
Loaded
efficiency
(gofCCV
ton -mile)
2.34
3.21
4.38
6.28
7.59
30.22
4.82
10.51
16.49
21.60
38.68
8.32
10.66
15.62
27.15
7.59
39.41
7.88
12.26
2.19
2.63
3.94
5.55
7.74
33.43
Total
efficiency
(gof
COz/ton-
mile)
4.23
6.42
8.61
10.95
13.28
48.61
8.32
15.03
27.30
42.62
65.69
12.26
15.76
22.04
32.41
13.14
63.50
13.58
21.17
3.65
4.38
5.98
8.32
11.53
42.62
29
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TYPE
General cargo
General cargo
General cargo
General cargo
General cargo
General cargo
Refrigerated
cargo
Container
Container
Container
Container
Container
Container
Vehicle
Vehicle
Ro-Ro
Ro-Ro
SIZE
10,000 + dwt
5,000-9,999 dwt
0-4,999 dwt
10,000+dwt, 100+
TEU
5,000-9,999 dwt,
100+TEU
0-4,999 dwt,
dwt+TEU
All
8000+TEU
5,000-7,999 TEU
3,000-4,999 TEU
2,000-2,999 TEU
1,000-1, 999 TEU
0-999 TEU
4000 +ceu
0-3999 ceu
2,000 + Im
0-1, 999 Im
AVERAGE
CARGO
CAPACITY
(metric
tonne)
15,000
6,957
2,545
18,000
7,000
4,000
6,400
68,600
40,355
28,784
16,800
7,000
3,500
7,908
2,808
5,154
1432
Average
yearly
capacity
utilization
60%
60%
60%
60%
60%
60%
50%
70%
70%
70%
70%
70%
70%
70%
70%
70%
70%
Average
service
speed
(knots)
15.4
13.4
11.7
15.4
13.4
11.7
20
25.1
25.3
23.3
20.9
19
17
19.4
17.7
19.4
13.2
Transport
work per ship
(tonne NM)
866,510,887
365,344,150
76,645,792
961,054,062
243,599,799
120,938,043
392,981,809
6,968,284,047
4,233,489,679
2,280,323,533
1 ,480,205,694
578,339,367
179,809,363
732,581,677
226,545,399
368,202,021
57,201,146
Loaded
efficiency
(gofCCV
ton -mile)
11.09
14.74
15.91
12.55
20.14
22.63
18.83
16.20
22.19
22.19
26.71
42.91
48.61
36.78
68.90
66.12
80.57
Total
efficiency
(gof
CO2/ton-
mile)
17.37
23.06
20.29
16.06
25.54
28.90
18.83
18.25
24.23
24.23
29.19
46.86
52.99
46.71
84.08
72.25
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.
Table 13: IMP Air Emission Factors (gCO2/short ton-mile)
Boeing 747F
Boeing 747F
llyushin IL 76T
llyushin IL 76T
high
low
high
low
691.89
634.96
2,627.43
1,605.65
The barge emissions factors presented in Table 14 are from Table 10 in the TTI study
and reflect inland waterway towing operations in the U.S. We converted the PM10 factor
in the TTI study into PM2.5by 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 14: TTI Barge Emission Factors
gram/short ton-mile
CO2
17.48
NOX
0.4691
PM2.5
0.0111
Estimates of average g/mi performance metrics were not identified for barge carriers.
30
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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 performance ranking 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 15. (See the Truck Tool Technical Documentation for
additional 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 15. Truck Carrier Payload Validation Ranges
Truck Bin Category
LTL Dry Van (from Dry Van
Single - LTL-Moving-
Package)21
Package (from Dry Van
Single - LTL-Moving-
Package)
TL Dry Van (from Dry Van
Single - other bins)
Refrigerated
Flatbed
Tanker
Range
1 Low
0.0
0.0
0.0
0.0
0.0
0.0
Range
1 High
/2Low
0.001
0.001
10.5
14.5
14.0
19.1
Range
2 High
/3Low
__22
__28
14.5
17.3
18.3
22.0
Range
3 High
14 Low
9.9
9.9
22.4
22.9
26.7
27.8
Range
4 High
/5 Low
15.7
15.7
26.4
25.7
31.0
30.7
Range
5 High
(Max)
83.7
83.7
150.0
82.5
99.9
103.8
21 Since LTL and package shipments can be very small, no lower-bound "red" ranges are designated for LTL and
package carrier payloads. Lower bound "yellow" ranges are set at 2 pounds. The upper bound "yellow" range was
defined as 1 to 2 standard deviations from the average shipper payload designated for LTL carriers (2013 data year).
22 LTL and package carriers have only one lower bound warning range.
31
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Truck Bin Category
Moving (from Dry Van
Single - LTL-Moving-
Package)
Specialized (from Specialty -
Other bins)
Dray (from Chassis)
Auto Carrier
Heavy-Bulk
Utility (from Specialty -
Other bins)
Mixed (from Other - Heavy-
Flatbed-Mixed bins)
Expedited (from Dry Van
Single - other bins)
Range
1 Low
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Range
1 High
/2Low
6.9
20.2
11.2
5.7
2.7
20.2
14.7
10.5
Range
2 High
/3Low
11.0
22.9
16.5
11.0
16.5
22.9
21.1
14.5
Range
3 High
14 Low
19.1
28.3
27.1
21.4
44.0
28.3
33.8
22.4
Range
4 High
/5Low
23.2
31.1
32.4
26.6
57.8
31.1
40.1
26.4
Range
5 High
(Max)
83.7
111.0
73.5
73.5
120.0
111.0
99.3
150.0
With the exception of LTL and package carrier selection (see footnote 26), Logistic
carrier payload validations are based on 2011 Logistics Partner data, and use simple
cutoffs from the cumulative payload distribution shown in Figure 1 below.
32
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Figure 1. Logistics Partner Payload Distribution
Cumulative Payload Distribution - 2011 Logistics
0.9
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 multi-modal carriers are summarized below. The upper
bound outpoints for multi-modal payloads are based on a qualitative review of 2011
multi-modal 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
4 above).
• Average multi-modal payloads less than 9.4 tons (error - red)
• Average multi-modal payloads greater than 95 tons (error - red)
• Average railcar payloads less than 9.4 tons or greater than 125 tons (error - red)
• Average multi-modal payloads between 9.4 and 15.5 tons (warning - yellow)
• Average multi-modal payloads between 60 and 95 tons (warning - yellow)
33
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In addition, the absolute upper bound for rail and multi-modal carriers have both been
set at 200 tons.
Finally, any payload value less than or equal to zero will be flagged as an error and
must be changed.
NOTE: Barge carrier payloads are not subject to validation at this time. SmartWay will
develop validation ranges for these carriers in the future as data becomes available.
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)23, Union Pacific Railroad (UP)24,
Burlington Northern Santa Fe Railroad (BNSF)25, CSX Transportation
Railroad (CSX)26, World Trade Press Guide to Railcars (GTRC)27, Chicago
Rail Car Leasing (CRCL)28, Union Tank Car Company (UTCC)29, U.S
Department of Agriculture (USDA)30
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 high cube assumed to be 6,304 [reflecting the average of 6339 (NS) and
6269 (CSX)].
60 ft high cube assumed to be 6917 [reflecting the average of 7499 (NS),
6646 (CSX), and 6607 (GTRC)].
23 http://www.nscorp.co m/nscportal/nscorp/Customers/Equipment_Guide
24 http://www.uprr.com/customers/equip-resources/cartypes/index.shtml
25http://www.bnsf.com/customers/how-can-i-ship/individual-railcar/#%23subtabs-3
26 http://www.csx. co m/index.cfm/customers/equipment/railroad-equipment/#boxcar_specs
27 http://www.worldtraderef.com/WTR_site/Rail_Cars/Guide_to_rail_Cars.asp
28 http://www.crdx.com/railcar.html
29 http://www.utlx.com/bdd_tank.html
30 U.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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Railcar Type
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (NS)23, Union Pacific Railroad (UP)24,
Burlington Northern Santa Fe Railroad (BNSF)25, CSX Transportation
Railroad (CSX)26, World Trade Press Guide to Railcars (GTRC)27, Chicago
Rail Car Leasing (CRCL)28, Union Tank Car Company (UTCC)29, U.S
Department of Agriculture (USDA)30
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 [reflecting the average of 8328 (NS) and
2260 (BNSF)].
Centerbeam assumed to be 6546 [reflecting the average of 5857 (UP) 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 carry very large cargo, such as vehicles/tractors) assumed to be
12183 (NS).
Bi-level assumed to be 14381(NS).
Tri-level assumed to be 14313 (based on average 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 [based on average of 2665 (NS), 2743 (CSX),
2400 (BNSF), and 2697(CRLC)].
60-66ft assumed to be 3372 [based on average of 3281 (NS), 3242 (CSX),
3350 (BNSF), CRCL-3670,and 3366 (GTRC)].
Municipal Waste assumed to be 7999 (NS).
Woodchip assumed to be 7781 [based on average of 7862 (NS) and 7700
(CRCL)].
Coal assumed to be 4170 [based on average of 3785 (NS) and 4556 (BNSF)].
Refrigerated -
Mechanical /non-
Mechanical
6,202
Based on the average of the following refrigerated car types:
48-72ft assumed to be 6963 [based on average of 6043 (UP) and 7883
(BNSF)].
50ft assumed to be 5167(GTRC).
40-90 ft assumed to be 6476 [based on average of 6952 (UP) and 6000
(BNSF)].
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 [based on average of 4500 (UP) and 3710 (BNSF).
Woodchip assumed to be 7075 [based on average of 7525 (NS), 5999 (UP),
and 7700 (CRCL)].
Small Aggregate assumed to be 2252 [based on average of 2150 (NS), 2106
(BNSF), and 2500 (CRCL)].
Covered Hopper
4,188
Based on the average of the following covered top hopper car types:
45ft assumed to be 5250 (GTRC).
Aggregate assumed to be 2575 [based on average of 2150 (NS) and 3000
(CRCL)].
Small Cube Gravel assumed to be 2939 [based on average of 2655 (NS),
3100 (CSX), and 3063 (BNSF).
36
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Railcar Type
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (NS)23, Union Pacific Railroad (UP)24,
Burlington Northern Santa Fe Railroad (BNSF)25, CSX Transportation
Railroad (CSX)26, World Trade Press Guide to Railcars (GTRC)27, Chicago
Rail Car Leasing (CRCL)28, Union Tank Car Company (UTCC)29, U.S
Department of Agriculture (USDA)30
Med-Larqe Cube Ores and Sand assumed to be 4169 [based on average of
3750 (NS) and 4589 (BNSF)].
Jumbo assumed to be 5147 [based on average of 4875 (NS), 4462 (CSX),
5175 (BNSF), and 6075 (CRCL)].
Pressure Differential (flour) assumed to be 5050 [based on average of 5124
(NS) and 4975 (CRCL)].
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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