Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Shipper Partner 2.O.I2 Tool:
Technical Documentation
2OI2 Data Year - United States Version
&EPA
United States
Environmental Protection
Agency
-------
Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Shipper Partner 2.O.I2 Tool:
Technical Documentation
2OI2 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 pp/\ /ion R 17 flAQ
Agency tm-^U-b-13-U4a
October 2013
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SmartWay 2.0.12
Shipper Tool Technical Documentation
United States Version
10-1-13
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 rail and trucking sectors1 with a greater
degree of sophistication than was possible with previous SmartWay tools. 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 new SmartWay truck, logistics and multi-modal 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
more accurate emissions inventories. The new 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.
1 While this Tool is primarily focused on freight movements in the rail and trucking sectors, our long-term
vision is to provide shippers with tools to help them evaluate the emissions performance associated with
other transport modes including marine and air.
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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", 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. 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 truck, logistics and multi-modal carriers as well as
available industry average Class 1 rail emissions factors.
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 offers two options for calculating mass emissions, based on either the annual mileage
or ton-mileage data that shippers enter for each carrier. We encourage shippers to select the unit of
activity data that is most appropriate for characterizing each truck carrier operation (e.g., use grams per
mile for TL and grams per ton-mile for LTL and rail.)
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., miles/railcar-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.
Table 1. Example Compositing Calculation
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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 CO2 g/mi
1,134(0.667x1,700)
500(0.333x1,500)
1,633(1,134 + 500)
This compositing process proceeds in an identical fashion for ton-miles. Weighted-average payloads are
also calculated in this way, using the relative ton-miles for each carrier as the weighting factor. This
value 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 (Tl, T2, T3)
o Tl has a CO2g/mileof 1,000
o T2 has a CO2g/mileof 2,000
o T3 has a CO2g/mileof 3,000
o Tl 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.
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 truck, and will
clearly overstate your ton-miles.
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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 and rail freight transport providers. These data are provided in the
SmartWayCarrierData2012.xls file, which are 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 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 Shipper Tool is based on 2012 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:
• TL Dry Van
• LTL Dry Van
• Refrigerated
• Flatbed
• Tanker
• Dray
• Package
• Auto Carrier
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• Expedited
• Heavy/Bulk
• Moving
• Specialized
• Mixed
The following provides an overview of the truck carrier ranking process used to estimate the carrier-
specific performance bins.
Truck Performance Ranking
In the 2012 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
rivate
TL
LTL
Dray
Expedited
Package
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized
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 possible to aggregate these
disparate fleets into one category.
For-hire and private fleets are combined in SmartWay 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
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separately. Ranking for-hire and private separately would have doubled the number of 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 operations by 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 category are placed in the Mixed category.
Individual fleets were then placed into categories. The following shows the relative number of fleets for
the various category intersections, with darker shadings indicating more fleets.
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TL
LTL
Dray
Expedited
Package
Mixed
Dry Van
^m
Reefer
-
-
Flatbed
-
-
-
Tanker
-
-
-
2
-
Chassis
-
-
-
Heavy/Bulk
-
-
-
-
Auto
Carrier
-
-
-
Moving
-
-
-
Specialized
-
-
-
Mixed
-
-
SmartWay then looked at combining categories that exhibited 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 (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 intersections would be left undefined. A similar situation was identified
with flatbed, tanker, heavy/bulk, auto carrier, moving, and specialized fleets. All dray was 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. This produces the final performance categories illustrated below.
SmartWay Carrier Categories: 2012 Data 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: CO2 g/mile, CO2 g/ton-mile, NOx g/mile, NOx g/ton-mile,
PM10 g/mile and PM10 g/ton-mile. When performance categories are first established, fleets within a
category are separated into 5 groups such that an equal number of fleets were in each category. Each
bin thus represents a range of emission factors. This range, and ranking cutpoints (transition points
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from one rank to the next) were then modified so that each category had an equal range, and the new
cutpoints remained as close to the originals as possible. The new range cutpoint is displayed as a
number with significant digits appropriate to emission factors in that category. The midpoint of the
range is used as the emission factor for all fleets in a category.
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 exact 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 categories. The table below illustrates the bins in
the For Hire/Private Truckload/Expedited Dry Van/Container category, using 2010 truck Partner data as
an example.
Table 2. Example Binning Results for One Performance Category (2012 Data)
For-Hire/Private Truckload/Expedited Dry Van/Container CO2 g/mile
Bin ID
1
2
3
4
5
Fleets
Per Bin
132
254
225
137
111
Grams Per
Mile Min
865
1,550
1,650
1,750
1,850
Grams Per
Mile Max
1,550
1,649
1,749
1,847
5,121
Grams Per
Mile Avg
1,455
1,603
1,699
1,796
2,011
Grams Per Mile
Midpoint
1,500
1,600
1,700
1,800
1,900
Grams Per
Mile Std Dev
115
29
27
30
428
Similar tables have been developed for all performance 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 bin. Once the categories and bins have been
established, the fleets of any new companies joining SmartWay will fall into one of the predefined
categories/bins. SmartWay expects to update the category/bin 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 was selected
to be the midpoint for all non-SmartWay Truck carriers. This approach does not require the shipper to
identify the appropriate bin category for their non-SmartWay carrier(s), which they may not know.
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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. Alternatively, freight density and cargo volume utilization information
can also be used to estimate average payloads. For this reason, average payload and volume
information are provided for each carrier in the SmartWayCarrierData2012.xls file. For non-SmartWay
truck carriers, the values for average payload (18.7 tons) and average volume (3,260 cubic feet) 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.2 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).
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 (10,084 g CO2/gal diesel fuel),
from publicly available data submitted in the 2010 railroad R-l reports to the Department of
Transportation. 2010 R-l 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. Specific rail companies may have an opportunity to provide
company-specific data in the future. The R-l data and corresponding CO2 performance data are
presented in Table 3 below.
Table 3. Rail Carrier Performance Metric Calculation Inputs and Results (2010 R-l 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 & 82
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 CO2/short
ton-mile
20.20
21.44
17.60
20.76
24.24
19.74
20.41
20.78
* and combined subsidiaries
As of this writing 2012 performance data is included for multi-modal carriers, and 2011 data for logistics carriers.
20121 logistics carrier data should be included in the carrier file by late summer/early fall of 2013.
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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-l data. The calculation
uses the Total Revenue and Non-Revenue Ton-Miles as listed In the R-l 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 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-l 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
Avg. Cu Ft.
4,555
7,177
7,177
5,190
5,190
BNSF
Railcar Miles (xlK)
1
9,338
147,226
379,762
75,894
Cu Ft Miles (xlK)
4,555
67,018,826
1,056,641,002
1,970,964,780
393,889,860
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Freight Car Types (Rl - Schedule 755)
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
Avg. Cu Ft.
4,188
4,220
4,220
6,202
6,202
6,395
13,625
6,395
6,395
5,772
BNSF
Railcar Miles (xlK)
758,442
65,077
137,449
19,272
32,910
520,521
38,624
357
71,826
20,146
Cu Ft Miles (xlK)
3,176,355,096
274,624,940
580,034,780
119,524,944
204,107,820
3,328,731,795
526,252,000
2,283,015
459,327,270
116,282,712
5,811
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
CSX
Railcar Miles (xlK)
6,987
144,631
137,256
64,532
153,315
78,412
35,451
17,117
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
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Freight Car Types (Rl - Schedule 755)
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)
11,923
125,828
29,956
162
31,913
19,861
Cu Ft Miles (xlK)
73,946,446
804,670,060
408,150,500
1,035,990
204,083,635
114,637,692
6,389
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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
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
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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
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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
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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
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
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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
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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 screen). Miles correspond to
truck miles for trucks, and railcar-miles for rail;
• Total annual ton-miles (the Tool will automatically populate the % SmartWay screen with any
truck or rail carrier activity data that shippers entered on the freight Activity Data screen);
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• Total annual CO2 emissions, based on the preferred calculation metric specified for each carrier
on the Activity Data screen (miles or ton-miles)
• 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 current Shipper
Tool also allows shippers to estimate the emissions impact of operational strategies as well as modal
shifts, if the user provides mileage-related activity data under the "Emissions Footprint" option.
Shipper Operational Strategies3
The Shipper Strategies screen is optional and is intended for reference purposes only. On the Shipper
Strategies 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 shipper strategy 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.4 Mass emission reductions are calculated by using the appropriate
emissions inventory for the Emissions Summary screen (based on reported activity data and associated
carrier emissions performance data) as shown below:
3 This "Shipper Strategies" 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.
4 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.
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S=EFx(l/(I-Reduction)-!)
Where:
S = Savings (tons of CO2, NOx, or PM)
EF = Emissions inventory value (tons of CO2, 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 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 and rail modes corresponding to the
company-specific data from 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).
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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 we have 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 marine and aviation sectors by inputting an
emissions factor of their choice ("User Input" option only). While we have not provided illustrative
marine and aviation freight factors in the Tool, there are several external resources that partners can
consult. We have included some selected sources of 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.
Total Emission Impact (tons/yr) =
[(Efficiency Before x "From Mode" Amount) -
(Efficiency After x 'To Mode" Amount)] x grams to short tons conversion factor
5
If the shipper is evaluating a mode shift between truck and rail, and if the available activity units are in
miles rather than ton-miles, then an adjustment factor must be applied to the above equation
converting railcar-miles (the activity unit for the rail mode) to equivalent truck miles (the unit for the
truck mode).
The railcar-to-truck equivalency factor is 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
are weighted by the miles associated with each rail carrier 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 are also calculated for the different truck carriers associated with the given
shipping company. The weighting calculations 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 is only performed for the filtered subset (e.g., inbound domestic truck carriers).
Once the weighted average volumes are determined for both rail and truck modes, the Tool calculates
51.1023 x 10"6 short tons/gram
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the ratio of the average railcar volume to the average truck volume (R). Next, the Tool converts the
g/railcar-mile values (g/RC-mi) to g/truck-equivalent mile values by dividing g/RC-mi by the ratio R. The
Tool then shows these values in the appropriate efficiency column, and uses these values to calculate
emission changes as shown in the equation above. This approach does not require the shipper to
develop and apply equivalency factors, relying on simple railcar-mile activity estimates.
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 CO2, NOX, and PM2. 5s inventory data on short-haul single
unit, short-haul combination unit, long-haul single unit, and long-haul combination unit truck categories7
in EPA's 2010a version of the Motor Vehicle Emissions Simulator (MOVES2010a) model8. 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 Figures9, 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 data in MOVES2010a.
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 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
CO2
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)
PM2.5 (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
Corresponding PM10 emission factors were estimated assuming PM2.5 values were 97% of PM10 values, based
on MOVES model outputs for diesel fueled trucks.
7 These four truck categories are coded as 52, 53, 61, and 62 in the MOVES model, respectively.
8 EPA's MOVES model and accompanying resources, including technical documentation, are available at:
www.epa.gov/otaq/models/moves/index.htm.
9 U.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
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We developed the freight rail gCO2/ton-mile factors with 2008 inventory data from EPA's most recent
Inventory of U.S. Greenhouse Gas Emissions and Sinks (1990-2008)10, 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 latest rail ton-mile data (2007) presented in Table l-46b in the Bureau of
Transportation Statistics' (BTS) National Transportation Statistics11, 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 rule12. 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-l forms that Class I railroad companies submitted to the Surface Transportation Board13. We then
converted the railcar-miles into "truck-equivalent" 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 very crude 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 truck-equivalent railcar miles. (As discussed above, carrier-specific volumes and
truck-equivalent conversion factors can be applied by selecting the "Select Carriers" data source option
on the Modal Shift screen, if available.)
To estimate the average volume capacity of Class I railcars, we multiplied the railcar miles reported by
each company for each railcar type in their respective 2008 R-l reports (lines 15-81) by the volume-per-
railcar assumptions in Table 8 to get 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) 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. (Note the 1.41 factor was also used to convert modal average g/truck-equivalent
10 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/climatechange/emissions/usgginv_archive.html. Total freight rail GHG
emissions are presented in Table A-110 of the inventory. Table 10 in this document presents CO2-only data. In
order to isolate the CO2-only emissions data, we accessed spreadsheets that are not publically available.
11 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
12 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
13 Surface Transportation Board (STB), Industry Data, Economic Data, Financial and Statistical Reports, Class 1
Annual Report, Form R-l. Available at: http://www.stb.dot.gov/stb/industry/econ_reports.html
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mile performance metrics to the g/railcar-mile factors displayed on the Modal Shift screen of the
Shipper Tool.)
We developed the CO2 inventory for the rail g/mile factors by using 2008 Class I rail fuel consumption
reported in the R-l reports and an emissions factor of 10,180 gCO2/gallon, which corresponds to the
diesel emissions factor in the current version of the SmartWay Truck Tool.14 We developed the NOxand
PM inventories in a similar fashion using the average 2010 locomotive gPMlO/gal and gNOx/gal factors
from Tables 5 and 6, respectively, in EPA's 2009 Technical Highlights: Emissions Factors for
Locomotives15. 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 9 presents the illustrative freight rail emissions factors in the Tool and Table 10 presents the key
underlying data.
Table 8: Railcar Volume Assumptions and Sources
Railcar Type
Boxcar 50 ft and longer
including equipped
boxcars
Boxcar 40ft
Cubic
Feet
7,177
4,555
Source/Method
Key: Norfolk Southern Railroad (NS)16, Union Pacific Railroad (UP)17, Burlington
Northern Santa Fe Railroad (BNSF)18, CSX Transportation Railroad (CSX)19, World Trade
Press Guide to Railcars (GTRC)20, Chicago Rail Car Leasing (CRCL)21, Union Tank Car
Company (UTCC)22, U.S Department of Agriculture (USDA)23
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)].
86ft assumed to be 9999 (NS).
Autoparts assumed to be 7499 (NS).
Based on estimate of 50ft boxcar volume described above. Assumed 40ft length
would result in 20% reduction in volume.
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.
15 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.
16 http://www.nscorp.com/nscportal/nscorp/Customers/Equipment_Guide
17 http://www.uprr.com/customers/equip-resources/cartypes/index.shtml
18http://www.bnsf.com/customers/how-can-i-ship/individual-railcar/#%23subtabs-3
19 http://www.csx.com/index.cfm/customers/equipment/railroad-equipment/#boxcar_specs
20 http://www.worldtraderef.com/WTR_site/Rail_Cars/Guide_to_rail_Cars.asp
21 http://www.crdx.com/railcar.html
22 http://www.utlx.eom/bddj:ank.html
23U.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
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Railcar Type
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (NS)16, Union Pacific Railroad (UP)17, Burlington
Northern Santa Fe Railroad (BNSF)18, CSX Transportation Railroad (CSX)19, World Trade
Press Guide to Railcars (GTRC)20, Chicago Rail Car Leasing (CRCL)21, Union Tank Car
Company (UTCC)22, U.S Department of Agriculture (USDA)23
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).
Med-Large 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)].
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Railcar Type
Tank Cars under 22,000
gallons
Tank Cars over 22,000
gallons
All Other Cars
Cubic
Feet
2,314
3,857
5,014
Source/Method
Key: Norfolk Southern Railroad (NS)16, Union Pacific Railroad (UP)17, Burlington
Northern Santa Fe Railroad (BNSF)18, CSX Transportation Railroad (CSX)19, World Trade
Press Guide to Railcars (GTRC)20, Chicago Rail Car Leasing (CRCL)21, Union Tank Car
Company (UTCC)22, U.S Department of Agriculture (USDA)23
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).
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).
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).
Table 9: Illustrative U.S. Freight Rail Industry Average Factors in Modal Shift
gram/short ton-mile
gram/truck-equivalent mile
gram/TEU-mile
CO2
22.94
813.8
292.8
NOX
0.4270
13.19
4.745
PM2.5
0.0120
0.3569
0.1284
Table 10: 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
1,725,995,000
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, even though the corresponding factors for CO2 emissions are company-specific. Also, note
that the g/truck-equivalent mile factors for NOx and PM were converted back to a g/railcar mile basis
for inclusion in the carrier file, to be consistent with the Modal Shift calculation methodology described
above.
Outside Sources of Marine and Air Emission Factors
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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:
• gCO2/ton-mile marine and aviation factors from the Business for Social Responsibility's (BSR) Clean
Cargo Tool gCO2/ton-mile marine and aviation factors from a study prepared for the International
Maritime Organization (IMO)24
• multi-pollutant g/ton-mile barge factors from a study prepared by the Texas Transportation Institute
(TTI)forthe U.S. Maritime Administration25
Note that the factors from BSR and IMO are published in units of kgCO2/metric ton-km, so we converted
this data into gCO2/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 CO2 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 11 and 12 below are
from the "Emission Factors & Distances" tab in their tool.
Table 11: 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
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
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
24 Buhaug, 0., 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
25 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
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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_lntra-Americas (Caribbean)
Ship_lntra-Asia
Ship_lntra-Europe
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
15.8361
14.4056
12.6146
17.4549
12.8788
13.4379
15.0552
11.7432
15.9222
15.2012
17.1790
Table 12: 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 13 and 14 below come from Table 9.1 and 9.4 in the IMO study, respectively.
Table 13: 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
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
10,000-19,999 dwt
5,000-9,999 dwt
0-49,999 dwt
20,000 + dwt
10,000-19,999 dwt
5,000-9,999 dwt
0-4,999 dwt
50,000 + m3
0-49,999 m3
200,00 + m3
0-199,999 m3
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
Average
yearly
capacity
utilization
48%
48%
48%
48%
48%
48%
55%
55%
50%
45%
45%
64%
64%
64%
64%
48%
48%
48%
48%
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
Transport work
per ship (tonne
NM)
14,197,046,742
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
Loaded
efficiency
(g of CO2/
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
Total
efficiency (g
of CO2/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
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TYPE
Bulk carrier
Bulk carrier
Bulk carrier
Bulk carrier
Bulk carrier
Bulk carrier
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
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
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)
227,000
163,000
74,000
45,000
26,000
2,400
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
50%
50%
55%
55%
55%
60%
60%
60%
60%
60%
60%
60%
50%
70%
70%
70%
70%
70%
70%
70%
70%
70%
70%
Average
service
speed
(knots)
14.4
14.4
14.4
14.4
14.3
11
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)
10,901,043,017
7,763,260,284
3,821,361,703
2,243,075,236
1,268,561,872
68,226,787
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
(g of CO2/
ton-mile)
2.19
2.63
3.94
5.55
7.74
33.43
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 (g
of CO2/ton-
mile)
3.65
4.38
5.98
8.32
11.53
42.62
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 14: IMP Air Emission Factors (gCO2/short ton-mile)
Boeing 747F
Boeing 747F
MyushinlL76T
MyushinlL76T
high
low
high
low
691.89
634.96
2,627.43
1,605.65
The barge emissions factors presented in Table 15 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 PM2.5 by
assuming 95% of PM10 is PM2.5, which we determined was a good approximation of the share of
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overall PM10 emissions represented by particulate matter that is 2.5 micrometers in diameter or
smaller.
Table 15: TTI Barge Emission Factors
gram/short ton-mile
C02
17.48
NOX
0.4691
PM2.5
0.0111
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.
Pavload 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 warningsj.The payload check only apples to Data Availability selections 2, 3, 5, and 6,
where payloads are either entered by the user, or calculated based on other inputs. Checks are applied
at the carrier (row) level. Both direct payload inputs and indirect payload (derived from density and
load % calculators) are checked, using the same criteria for each. If Data Availability Options 3 or 6 are
used, the following equation is used to calculate inferred payload:
Payload (tons) = (density/2000) x carrier average volume x (average load percent/100)
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 16. (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.
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Table 16. Truck Carrier Payload Validation Ranges
Truck Bin Category
LTL Dry Van (from Dry Van Single -
LTL-Moving-Package)26
Package (from Dry Van Single -
LTL-Moving-Package)
TL Dry Van (from Dry Van Single -
other bins)
Refrigerated
Flatbed
Tanker
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
0.0
0.0
0.0
0.0
0.0
0.0
Range 1
High / 2
Low
0.0
6.9
10.5
14.5
14.0
19.1
6.9
20.2
11.2
5.7
2.7
20.2
14.7
10.5
Range 2
High/ 3
Low
11.0
11.0
14.5
17.3
18.3
22.0
11.0
22.9
16.5
11.0
16.5
22.9
21.1
14.5
Range 3
High/ 4
Low
19.1
19.1
22.4
22.9
26.7
27.8
19.1
28.3
27.1
21.4
44.0
28.3
33.8
22.4
Range 4
High/ 5
Low
23.2
23.2
26.4
25.7
31.0
30.7
23.2
31.1
32.4
26.6
57.8
31.1
40.1
26.4
Range 5
High
(Max)
83.7
83.7
150.0
82.5
99.9
103.8
83.7
111.0
73.5
73.5
120.0
111.0
99.3
150.0
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.
Since LTL shipments can be very small, no lower-bound "red/yellow" ranges are designated for LTL carrier
payloads.
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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 levels for rail and multi-modal carriers are summarized below. The upper bound cutpoints for
multi-modal payloads are based on a qualitative review of 2011 multi-modal carrier Tool submittals.
The upper bound cutpoints 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)
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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.
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.
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