Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Shipper Partner 2.O.I I Tool:
Technical Documentation
2011 Data Year - United States Version
&EPA
United States
Environmental Protection
Agency
-------
Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Shipper Partner 2.O.I I Tool:
Technical Documentation
2011 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-12-058
Agency
September 2012
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SmartWay 2.0.11
Shipper Tool Technical Documentation
United States Version
8-9-12
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 publically available Class I rail C02 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 of their full freight
transportation supply chain.
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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
logo, 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 bin-level emissions
performance data for truck, logistics and multi-modal carriers as well as available Class
1 and rail-industry-wide 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 and Carrier Performance screens is calculated by multiplying
the appropriate unit of activity data (i.e., miles/railcar-miles, or ton-miles) by the
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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
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 (0.667 x 1,700)
500 (0.333 x 1,500)
1,633(1,134 + 500)
This compositing process proceeds in an identical fashion for ton-miles.
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
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For Future Tools: Addressing Empty Miles, Out-of-Route Miles, Return Miles
Ideally, total emissions should be adjusted to account for possible under-reporting of
system miles. Shippers generally only see the miles they are invoiced by the carrier
moving the freight, or use a point-to-point mileage calculation. In many cases,
shippers may be charged for all miles traveled by the carrier, including empty miles
and out-of-route miles, but shippers may only be aware of the point-to-point mileage.
Therefore a shipper will base its emissions inventory calculations only on the miles of
which they are aware, and will therefore not account for all of the emissions
associated with their freight.
EPA is investigating potential adjustment factors that can help ensure that shippers
report their full emissions inventory. These factors may be specific to each carrier
mode or possibly each carrier fleet type (e.g., distinguishing TL and LTL). While there
are many ways to calculate this factor, it will likely follow this basic form:
emissions adjustment factor = total carrier fleet odometer miles /miles invoiced to shippers
Ton-Mile Calculation
Correctly calculating Ton-Miles is critically important for the accurate determination of
your carbon foot-print. 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.
Many companies track their ton-miles and can report them directly without further
calculation. For example, logistics company systems are typically 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
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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 and rail freight transport providers. These data
are provided in the SmartWayCarrierData.xls file, which should be 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 2011 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
bin category, rather than exact performance levels for a given carrier. Truck bin
categories include:
• 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 binning processed used to
estimate the carrier-specific performance bins.
Truck Performance Binning
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In the 2011 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, utility, 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
Utility
Specialized
Private
TL
LTL
Dray
Expedited
Package
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Utility
Specialized
Note that only one Utility fleet was submitted in 2011 which was included under the
Specialized category. 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 bin.
For-hire and private fleets are combined in SmartWay categories/bins. 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 categories.
Therefore fleets can thus be categorized as shown below.
For-Hire and Private
TL
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto
Carrier
Moving
Specialized/Utility
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LTL
Dray
Expedited
Package
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.
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 bin categories illustrated below.
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SmartWay Carrier Categories: 2011 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: C02 g/mile, C02 g/ton-mile,
NOx g/mile, NOx g/ton-mile, PM10 g/mile and PM10 g/ton-mile. When bins are first
established, fleets within a category are separated into 5 groups (bins) such that an
equal number of fleets were in each bin.2 Each bin thus represents a range of emission
factors. This range, and bin outpoints (transition points from one bin to the next) were
then modified so that each bin had an equal range, and the new bin outpoints remained
as close to the originals as possible. The new range outpoint 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 bin.
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 C02), SmartWay believes it is acceptable and
appropriate to break truck fleets into 5 performance bins. 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.
2 For 2011 data, the fleets in new bin categories such as auto carriers were split into bins with equal numbers as
described above. However, the bins definitions established using 2010 fleet data were not updated for the 2011 fleet
data, for most bin categories (e.g., TL Dry Van). As such, the 2011 performance metrics for these older bin
categories were not evenly distributed across the pre-existing bins.
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Table 2. Example Binning Results for One Bin Category (2010 Data)
For-H ire/Private Truckload/Expedited Dry Van/Container CO, g/mile
Bin ID
1
2
3
4
5
Fleets
Per Bin
159
241
204
139
55
Grams Per
Mile Min
602
1,601
1,700
1,800
1,900
Grams Per
Mile Max
1,600
1,699
1,799
1,899
3,701
Grams Per
Mile Avg
1,503
1,654
1,746
1,853
2,064
Grams Per Mile
Midpoint
1,550
1,650
1,750
1,850
2,801
Grams Per
Mile Std Dev
141
28
28
28
302
Similar tables have been developed for all bin categories. The midpoint of each bin 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 bin delta (max - min) for each bin within each bin category, and using the
delta to calculate a non-SmartWay carrier midpoint for each bin category. This midpoint
was the midpoint for Bin 5 plus the standard bin delta. For example, if the Bin 5
midpoint was 10.5 and the bin categories 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 bin 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.
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 SmartWayCarrierData.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.
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Logistics and Multi-modal Carrier Performance
Logistic and multi-modal carriers have their own performance bins based on the carrier
tool submittals.3 The Shipper tool modifies the Bin 5 values for each of these bin
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
bin delta value to the Bin 5 midpoints).
Rail Carrier Performance
Rail carrier performance data are collected and displayed in the Shipper tool at the
individual company level for Class 1 rail companies. Gram per ton-mile factors were
determined by dividing total fuel use by total ton-miles and multiplied by a rail diesel C02
factor (10,084 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 each Class 1 carrier, in order to estimate gram
per railcar-mile factors. Industry average values are used for non-class 1 and non-
SmartWay rail carriers. It is anticipated that Class 2 and 3 rail companies will 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.
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
Non Class 1 and
Non-SmartWay
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 COj/railcar-
mile
1,163
1,047
738
1,031
1,087
857
1,037
1,072
g COj/short
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 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 performance
levels for different modes.
3 As of this writing 2011 performance data is included for multi-modal carriers, and 2010 data for logistics carriers.
2011 logistics carrier data should be included in the carrier file by late summer/early fall of 2012.
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Average payload per loaded railcar were calculated for each Class 1 carrier by dividing
the value for annual ton-miles hauled by an estimate for loaded railcar miles, based on
2008 R-1 data. The calculation uses the Total Revenue and Non-Revenue Ton-Miles as
listed In the R-1 Report on line 114 of schedule 755 divided by the Total loaded Railcar
Miles (the sum of lines 30 and 64 of schedule 755) along with the factor for fuel gallons
consumed for loaded freight that is created based on the percentage of loaded freight to
total freight multiplied by the total diesel fuel value listed on schedule 750 Line 4. The
following table summarizes the estimated average payload per railcar, by carrier.
Table 4. Rail Carrier Average Payload
Carrier
BNSF Railway
CSX Transportation
Grand Trunk
Kansas City Southern
Norfolk Southern
Soo Line
Union Pacific
Non Class 1 and Non-SmartWay
Avg Payload/Loaded
Railcar (tons)
108
85
80
91
76
77
91
93
Average railcar volumes were calculated for each carrier 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. 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
Avg. Cu Ft.
4,555
7,177
7,177
5,190
5,190
4,188
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-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.
4,220
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
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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
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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
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;
Shipper Partner 2.0.11 Tool: Technical Documentation 19
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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);
Total annual C02 emissions, based on the preferred calculation metric specified
for each carrier on the Activity Data screen (miles or ton-miles)
Percent Spent;
Percent Weight Shipped;
Percent Packages Shipped;
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 Strategies4
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.5 Mass emission reductions are calculated by using the appropriate emissions
4 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.
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
Shipper Partner 2.0.11 Tool: Technical Documentation 20 |
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inventory for the Emissions Summary screen (based on reported activity data and
associated carrier emissions performance data) as shown below:
S = EFx(1 /(1 - Reduction) -1)
Where:
S = Savings (tons of C02, NOx, or PM)
EF = 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 your 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.
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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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).
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 bin-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) =
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[(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, 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 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 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 C02,
NOX, and PM2.57 inventory data on short-haul single unit, short-haul combination unit,
long-haul single unit, and long-haul combination unit truck categories8 in EPA's 201 Oa
version of the Motor Vehicle Emissions Simulator (MOVES201 Oa) model9. 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
61.1023 x 10~6 short tons/gram
7 Corresponding PM10 emission factors were estimated assuming PM2.5 values were 97% of PM10 values, based
on MOVES model outputs for diesel fueled trucks.
8 These four truck categories are coded as 52, 53, 61, and 62 in the MOVES model, respectively.
9 EPA's MOVES model and accompanying resources, including technical documentation, are available at:
www.epa.gov/otaq/models/moves/index.htm.
Shipper Partner 2.0.11 Tool: Technical Documentation 23 |
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Figures10, 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 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)
PM25 (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 most recent Inventory of U.S. Greenhouse Gas Emissions and Sinks (1990-
2008)11, 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 1-46b in the Bureau
of Transportation Statistics' (BTS) National Transportation Statistics12, which is intended
to encompass all freight rail ton-miles, including Classes I, II, and III.
10U.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
11 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-l 10 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.
12 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
Shipper Partner 2.0.11 Tool: Technical Documentation 24
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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 rule13. 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 Board14. 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-1
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 mile performance metrics to the g/railcar-mile factors
displayed on the Modal Shift screen of the Shipper Tool.)
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.15 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,
13 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
14 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
15 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.
Shipper Partner 2.0.11 Tool: Technical Documentation 25 | , >: "
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respectively, in EPA's 2009 Technical Highlights: Emissions Factors for Locomotives18.
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
Flat car- all types
except for multi-level
Multi-level flat car
Cubic
Feet
7,177
4,555
6,395
13,625
Source/Method
Key: Norfolk Southern Railroad (IMS)17, Union Pacific Railroad (UP)18,
Burlington Northern Santa Fe Railroad (BNSF)19, CSX Transportation Railroad
(CSX)20, World Trade Press Guide to Railcars (GTRC)21, Chicago Rail Car
99 9"3
Leasing (CRCL) , Union Tank Car Company (UTCC) , U.S Department of
Agriculture (USDA)24
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)].
60ft high cube assumed to be 691 7 [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.
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).
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).
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.
17 http://www.nscorp.com/nscportal/nscorp/Customers/Equipment_Guide
18 http://www.uprr.com/customers/equip-resources/cartypes/index.shtml
19http://www.bnsf.com/customers/how-can-i-ship/individual-railcar/#%23subtabs-3
20 http://www.csx. co m/index.cfm/customers/equipment/railroad-equipment/#boxcar_specs
21 http://www.worldtraderef.com/WTR_site/Rail_Cars/Guide_to_rail_Cars.asp
22 http://www.crdx.com/railcar.html
23 http://www.utlx.com/bdd_tank.html
24U.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
Shipper Partner 2.0.11 Tool: Technical Documentation 26
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Railcar Type
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (IMS)17, Union Pacific Railroad (UP)
Burlington Northern Santa Fe Railroad (BNSF)
19
CSX Transportation Railroad
Chicago Rail Car
(CSX) , World Trade Press Guide to Railcars (GTRC)21
Leasing (CRCL)22, Union Tank Car Company (UTCC) , U.S Department of
Agriculture (USDA)24
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)].
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
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Railcar Type
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (IMS)17, Union Pacific Railroad (UP)18,
Burlington Northern Santa Fe Railroad (BNSF)19, CSX Transportation Railroad
(CSX) i , World Trade Press Guide to Railcars (GTRC)21, Chicago Rail Car
Leasing (CRCL)22, Union Tank Car Company (UTCC) , U.S Department of
Agriculture (USDA)24
(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, 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, even though the corresponding factors for
C02 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
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:
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• 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)25
• multi-pollutant g/ton-mile barge factors from a study prepared by the Texas
Transportation Institute (TTI) for the U.S. Maritime Administration26
Note that the factors from BSR and IMO are published in units of kgC02/metric ton-km,
so we converted this data into gC02/ton-mile by first multiplying by 1,000 (to convert
from kilograms to grams), then multiplying by 0.9072 (to convert from metric tonnes to
short tons), and then multiplying by 1.609 (to convert from kilometers to miles) to
prepare the tables below.
BSR developed average 2009 marine emission factors for various shipping corridors, as
well as global defaults that are applicable outside those corridors, based on surveys
from marine carriers. 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 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
Shi p_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
25 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
26 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_Intra-Americas (Caribbean)
Ship_Intra-Asia
Ship_Intra-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 (gCOi/short ton-mile)
Air freight long >3700km I International I 868.3227
Air freight short <3700km
International
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
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
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
Average
yearly
capacity
utilizatio
n
48%
48%
48%
48%
48%
48%
55%
55%
50%
45%
45%
64%
64%
64%
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
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
Loaded
efficiency
(g of C02/
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
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
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TYPE
Chemical
tanker
LPG tanker
LPG tanker
LNG tanker
LNG tanker
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
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
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)
1,800
46,656
3,120
97,520
62,100
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
utilizatio
n
64%
48%
48%
48%
48%
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)
14.5
16.6
14
19.6
19.6
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)
72,147,958
2,411,297,106
89,631 ,360
5,672,338,333
3,797,321,655
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 C02/
ton -mile)
27.15
7.59
39.41
7.88
12.26
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
(gof
COz/ton-
mile)
32.41
13.14
63.50
13.58
21.17
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
llyushin IL 76T
high
low
high
691.89
634.96
2,627.43
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I llyushin IL 76T | low | 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 PM2.5by 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 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. Validation messages are presented for the following
conditions:
• Average truck/logistics/multi-modal payloads are less than 9.4 tons (error - red)
• Average truck/logistics payloads are greater than 33.8 tons (error - red)
• Average multi-modal payloads are greater than 90 tons (error - red)
• Average railcar payloads are less than 9.4 tons or greater than 125 tons (error -
red)
• Average truck/logistics/multi-modal payloads are between 9.4 and 15.5 tons
(warning - yellow)
• Average truck/logistics payloads are between 27.7 and 33.7 tons (warning -
yellow)
• Average multi-modal payloads are between 60 and 90 tons (warning - yellow)
• Payload is less than or equal to zero (error)
The outpoints for Truck and Logistics carriers (and the lower bound outpoints for multi-
modal and rail carriers) are based on the payload validation ranges used in the Truck
Tool for Class 8b trucks. (See the Truck Tool Technical Documentation for additional
information.) The upper bound outpoints for multi-modal payloads are based on a
qualitative review of 2010 multi-modal carrier tool submittals. The upper bound
outpoints for rail payloads are based on the distribution of average values estimated for
Class 1 carriers (see Table 4 above). These outpoints 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).
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