Shipper Partner 2.0.12 Tool: 

Technical Documentation

2012 Data Year - United States Version
Transportation and Climate Division

Office of Transportation and Air Quality

U.S. Environmental Protection Agency

Office of Transportation and Air Quality

EPA-420-B-13-049

October 2013

Shipper Partner 2.0.12 Tool: 

Technical Documentation

2012 Data Year - United States Version
Shipper Partner 2.0.12 Tool: Technical Documentation 1 | Page

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
Shipper Partner 2.0.12 Tool: Technical Documentation 3 | Page

CO2 g/mi Mi/yr Weighting Factor Weighted CO2 g/mi

Carrier 1 1,700 2,000,000 0.667 1,134 (0.667 x 1,700)

Carrier 2 1,500 1,000,000 0.333 500 (0.333 x 1,500)

Weighted composite g/mi 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 (T1, T2, T3) 

o T1 has a CO2 g/mile of 1,000

o T2 has a CO2 g/mile of 2,000

o T3 has a CO2 g/mile of 3,000

o T1 is Inbound

o T2 and T3 are both Outbound

o Shipper enters miles for the three carriers of 2,000, 4,000, and 2,000, respectively

o When Inbound/Outbound combo = All:

 Composite 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. 

 
Shipper Partner 2.0.12 Tool: Technical Documentation 4 | Page

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 carrierspecific 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

 Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk

Auto 

Carrier Moving Specialized

TL 

LTL

Dray 

Expedited

Package

rivate

 Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk

Auto 

Carrier Moving Specialized

TL 

LTL 

Dray 

Expedited

Package 

Note that while Specialized fleets have disparate operations/equipment types and thus do not compare 

well, they are also unlikely to compete with one another, so it was deemed 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 
Shipper Partner 2.0.12 Tool: Technical Documentation 6 | Page

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

 Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk

Auto 

Carrier Moving Specialized

TL

LTL 

Dray

Expedited

Package 

To be categorized in a particular category, a fleet must have at least 75% of its 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. 
Shipper Partner 2.0.12 Tool: Technical Documentation 7 | Page

 Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk

Auto 

Carrier Moving Specialized Mixed

TL

LTL - - - - 

Dray - - - - - 

Expedited - - - - - - - 

Package - - 2 - - - - 

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 

 

Dry Van Heavy Auto Specialized

& Chassis Reefer Flatbed Tanker & Bulk Carrier Moving Mixed

 Truckload 

Expedited

 LTL 

PD

 Dray 

Mixed

 Logistics 

Multi-modal

 

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 
Shipper Partner 2.0.12 Tool: Technical Documentation 8 | Page

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 Fleets 

Per Bin

Grams Per 

Mile Min

Grams Per 

Mile Max

Grams Per 

Mile Avg

Grams Per Mile 

Midpoint

Grams Per 

Mile Std Dev

1 132 865 1,550 1,455 1,500 115

2 254 1,550 1,649 1,603 1,600 29 

3 225 1,650 1,749 1,699 1,700 27 

4 137 1,750 1,847 1,796 1,800 30

5 111 1,850 5,121 2,011 1,900 428

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 nonSmartWay 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.
Shipper Partner 2.0.12 Tool: Technical Documentation 9 | Page

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 nonSmartWay 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-1 reports to the Department of 

Transportation. 2010 R-1 data was also used to obtain total railcar-miles per year for all Class 1 carriers, 

in order to estimate gram per railcar-mile factors. Industry average values are currently assumed for all 

rail carriers in the carrier data file. Specific rail companies may have an opportunity to provide 

company-specific data in the future. The R-1 data and corresponding CO2 performance data are 

presented in Table 3 below. 

Table 3. Rail Carrier Performance Metric Calculation Inputs and Results (2010 R-1 Data)

Rail Company

Gal/Yr 

(‘000)Sch. 750 

Line 4

Freight TonMi/Yr (‘000)

Sch .755 line 

110

Railcar-Mi/Yr 

(‘000) Sch. 755 

sum of lines 

30, 46, 64 & 82

g CO2/railcarmileg CO2/short

ton-mile

BNSF Railway 1,295,147 646,549,059 11,230,994 1,163 20.20

CSX Transportation 490,050 230,507,431 4,720,293 1,047 21.44

Grand Trunk 88,290 50,586,328 1,206,818 738 17.60

Kansas City Southern 62,354 31,025,588 609,929 1,031 20.76

Norfolk Southern* 440,159 183,104,320 4,081,893 1,087 24.24

Soo Line 65,530 33,473,544 771,033 857 19.74

Union Pacific 1,063,201 525,297,747 10,336,081 1,037 20.41 

Total – Industry 

Average

3,504,731 1,700,544,017 32,957,041 1,072 20.78

* and combined subsidiaries

 

2 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.
Shipper Partner 2.0.12 Tool: Technical Documentation 10 | Page

NOx and PM emission factors for rail carriers are also based on industry averages. Please see the 

“Background on Illustrative (Modal Average) U.S. Truck and Rail Factors” section below for details 

regarding the calculation of industry average NOx and PM performance levels for different modes.

Average payload per loaded railcar were calculated for all Class 1 carriers by dividing the value for 

annual ton-miles hauled by an estimate for loaded railcar-miles, based on 2008 R-1 data. The calculation 

uses the Total Revenue and Non-Revenue Ton-Miles as listed In the R-1 Report on line 114 of schedule 

755 divided by the Total loaded Railcar-Miles (the sum of lines 30 and 64 of schedule 755) along with the

factor for fuel gallons consumed for loaded freight that is created based on the percentage of loaded 

freight to total freight multiplied by the total diesel fuel value listed on schedule 750 Line 4. The 

following table summarizes the estimated average payload per railcar, by carrier.

Table 4. Rail Carrier Average Payload 

Carrier

Avg Payload/Loaded

Railcar (tons)

BNSF Railway 108

CSX Transportation 85

Grand Trunk 80

Kansas City Southern 91

Norfolk Southern 76

Soo Line 77

Union Pacific 91

Industry Average 93 

Average railcar volumes were calculated for all carriers by first estimating an average volume for each 

major railcar type listed in the R-1 forms (schedule 755, lines 15-81). The assumptions used to estimate 

these volumes are provided in Table 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

 BNSF

Freight Car Types (R1 - Schedule 755) Avg. Cu Ft. Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot 4,555 

 

1 

 

4,555 

Box-Plain 50-Foot & Longer 7,177 

 

9,338 

 

67,018,826 

Box-Equipped 7,177 

 

147,226 

 

1,056,641,002 

Gondola-Plain 5,190 

 

379,762 

 

1,970,964,780 

Gondola-Equipped 5,190 

 

75,894 

 

393,889,860 
Shipper Partner 2.0.12 Tool: Technical Documentation 11 | Page

 BNSF

Freight Car Types (R1 - Schedule 755) Avg. Cu Ft. Railcar Miles (x1K) Cu Ft Miles (x1K)

Hopper-Covered 4,188 

 

758,442 

 

3,176,355,096 

Hopper-Open Top-General Service 4,220 

 

65,077 

 

274,624,940 

Hopper-Open Top-Special Service 4,220 

 

137,449 

 

580,034,780 

Refrigerator-Mechanical 6,202 

 

19,272 

 

119,524,944 

Refrigerator-Non-Mechanical 6,202 

 

32,910 

 

204,107,820 

Flat-TOFC/COFC 6,395 

 

520,521 

 

3,328,731,795 

Flat-Multi-Level 13,625 

 

38,624 

 

526,252,000 

Flat-General Service 6,395 

 

357 

 

2,283,015 

Flat-All Other 6,395 

 

71,826 

 

459,327,270 

All Other Car Types-Total 5,772 

 

20,146 

 

116,282,712 

Average Railcar Cubic Feet 

 

5,811 

 CSX

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot

 

- 

 

- 

Box-Plain 50-Foot & Longer

 

6,987 

 

50,145,699 

Box-Equipped

 

144,631 

 

1,038,016,687 

Gondola-Plain

 

137,256 

 

712,358,640 

Gondola-Equipped

 

64,532 

 

334,921,080 

Hopper-Covered

 

153,315 

 

642,083,220 

Hopper-Open Top-General Service

 

78,412 

 

330,898,640 

Hopper-Open Top-Special Service

 

35,451 

 

149,603,220 

Refrigerator-Mechanical

 

17,117 

 

106,159,634 
Shipper Partner 2.0.12 Tool: Technical Documentation 12 | Page

 CSX

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Refrigerator-Non-Mechanical

 

11,923 

 

73,946,446 

Flat-TOFC/COFC

 

125,828 

 

804,670,060 

Flat-Multi-Level

 

29,956 

 

408,150,500 

Flat-General Service

 

162 

 

1,035,990 

Flat-All Other

 

31,913 

 

204,083,635 

All Other Car Types-Total

 

19,861 

 

114,637,692 

Average Railcar Cubic Feet 

 

6,389 
Shipper Partner 2.0.12 Tool: Technical Documentation 13 | Page

 Grand Trunk

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot 0 

 

- 

Box-Plain 50-Foot & Longer 2,119

 

15,208,063 

Box-Equipped 66,110

 

474,471,470 

Gondola-Plain 6,467

 

33,563,730 

Gondola-Equipped 19,201

 

99,653,190 

Hopper-Covered 44,239

 

185,272,932 

Hopper-Open Top-General Service 9,114

 

38,461,080 

Hopper-Open Top-Special Service 32,621

 

137,660,620 

Refrigerator-Mechanical 312

 

1,935,024 

Refrigerator-Non-Mechanical 205

 

1,271,410 

Flat-TOFC/COFC 2,779

 

17,771,705 

Flat-Multi-Level 4,831

 

65,822,375 

Flat-General Service 20

 

127,900 

Flat-All Other 31,744

 

203,002,880 

All Other Car Types-Total 4,755

 

27,445,860 

Average Railcar Cubic Feet 

 

6,309 
Shipper Partner 2.0.12 Tool: Technical Documentation 14 | Page

 Kansas City Southern

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot 0 

 

- 

Box-Plain 50-Foot & Longer 3,383

 

24,279,791 

Box-Equipped 39,792

 

285,587,184 

Gondola-Plain 16,628

 

86,299,320 

Gondola-Equipped 11,150

 

57,868,500 

Hopper-Covered 50,346

 

210,849,048 

Hopper-Open Top-General Service 626

 

2,641,720 

Hopper-Open Top-Special Service 943

 

3,979,460 

Refrigerator-Mechanical 21

 

130,242 

Refrigerator-Non-Mechanical 52

 

322,504 

Flat-TOFC/COFC 10,736

 

68,656,720 

Flat-Multi-Level 629

 

8,570,125 

Flat-General Service 12

 

76,740 

Flat-All Other 2,321

 

14,842,795 

All Other Car Types-Total 247

 

1,425,684 

Average Railcar Cubic Feet 

 

5,938 
Shipper Partner 2.0.12 Tool: Technical Documentation 15 | Page

 Norfolk Southern

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot 0 

 

- 

Box-Plain 50-Foot & Longer 7,622

 

54,703,094 

Box-Equipped 136,745

 

981,418,865 

Gondola-Plain 193,214

 

1,002,780,660 

Gondola-Equipped 111,320

 

577,750,800 

Hopper-Covered 116,848

 

489,359,424 

Hopper-Open Top-General Service 84,557

 

356,830,540 

Hopper-Open Top-Special Service 30,078

 

126,929,160 

Refrigerator-Mechanical 3,512

 

21,781,424 

Refrigerator-Non-Mechanical 5,392

 

33,441,184 

Flat-TOFC/COFC 114,928

 

734,964,560 

Flat-Multi-Level 20,349

 

277,255,125 

Flat-General Service 145

 

927,275 

Flat-All Other 24,563

 

157,080,385 

All Other Car Types-Total 212,408

 

1,226,018,976 

Average Railcar Cubic Feet 

 

6,065 
Shipper Partner 2.0.12 Tool: Technical Documentation 16 | Page

 Soo Line

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot 0 

 

- 

Box-Plain 50-Foot & Longer 725

 

5,203,325 

Box-Equipped 17,972

 

128,985,044 

Gondola-Plain 1,203

 

6,243,570 

Gondola-Equipped 8,856

 

45,962,640 

Hopper-Covered 94,146

 

394,283,448 

Hopper-Open Top-General Service 3,077

 

12,984,940 

Hopper-Open Top-Special Service 20

 

84,400 

Refrigerator-Mechanical 159

 

986,118 

Refrigerator-Non-Mechanical 742

 

4,601,884 

Flat-TOFC/COFC 11,178

 

71,483,310 

Flat-Multi-Level 2,973

 

40,507,125 

Flat-General Service 12

 

76,740 

Flat-All Other 10,068

 

64,384,860 

All Other Car Types-Total 428

 

2,470,416 

Average Railcar Cubic Feet 

 

5,667 
Shipper Partner 2.0.12 Tool: Technical Documentation 17 | Page

 Union Pacific

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot 0 

 

- 

Box-Plain 50-Foot & Longer 12,311

 

88,356,047 

Box-Equipped 238,241

 

1,709,855,657 

Gondola-Plain 206,370

 

1,071,060,300 

Gondola-Equipped 91,775

 

476,312,250 

Hopper-Covered 370,929

 

1,553,450,652 

Hopper-Open Top-General Service 188,027

 

793,473,940 

Hopper-Open Top-Special Service 104,969

 

442,969,180 

Refrigerator-Mechanical 82,874

 

513,984,548 

Refrigerator-Non-Mechanical 27,009

 

167,509,818 

Flat-TOFC/COFC 1,026,251

 

6,562,875,145 

Flat-Multi-Level 46,889

 

638,862,625 

Flat-General Service 350

 

2,238,250 

Flat-All Other 72,371

 

462,812,545 

All Other Car Types-Total 16,769

 

96,790,668 

Average Railcar Cubic Feet 

 

6,248 
Shipper Partner 2.0.12 Tool: Technical Documentation 18 | Page

 Total (for Industry Average)

Freight Car Types (R1 - Schedule 755) Railcar Miles (x1K) Cu Ft Miles (x1K)

Box-Plain 40-Foot

 

1 4,555 

Box-Plain 50-Foot & Longer

 

42,485 304,914,845 

Box-Equipped

 

790,717 5,674,975,909 

Gondola-Plain

 

940,900 4,883,271,000 

Gondola-Equipped

 

382,728 1,986,358,320 

Hopper-Covered

 

1,588,265 6,651,653,820 

Hopper-Open Top-General Service

 

428,890 1,809,915,800 

Hopper-Open Top-Special Service

 

341,531 1,441,260,820 

Refrigerator-Mechanical

 

123,267 764,501,934 

Refrigerator-Non-Mechanical

 

78,233 485,201,066 

Flat-TOFC/COFC

 

1,812,221 11,589,153,295 

Flat-Multi-Level

 

144,251 1,965,419,875 

Flat-General Service

 

1,058 6,765,910 

Flat-All Other

 

244,806 1,565,534,370 

All Other Car Types-Total

 

274,614 1,585,072,008 

Industry Average Railcar Cubic Feet 6,091 

% SmartWay Value

The % SmartWay screen 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); 
Shipper Partner 2.0.12 Tool: Technical Documentation 19 | Page

• 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.
Shipper Partner 2.0.12 Tool: Technical Documentation 20 | Page

S = EF x (1 / (1 – Reduction) - 1)

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). 
Shipper Partner 2.0.12 Tool: Technical Documentation 21 | Page

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 factor5

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 

 

5 1.1023 x 10-6 short tons/gram
Shipper Partner 2.0.12 Tool: Technical Documentation 22 | Page

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 PM2.56 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 

 CO2 NOx PM2.5

gram/short ton-mile 161.8 1.114 0.0480

gram/mile 1,661 11.44 0.4925

gram/TEU-mile 597.4 4.113 0.1772

Table 7: Underlying Emissions Inventories and Activity Data for Illustrative U.S. Freight Truck Industry

Average Factors in Modal Shift

CO2 (grams) 341,986,421,100,000

NOx (grams) 2,354,767,660,000

PM2.5 (grams) 101,411,195,611

short ton-miles 2,114,115,022,573 

miles 205,918,984,400

 

6 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
Shipper Partner 2.0.12 Tool: Technical Documentation 23 | Page

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 1-46b 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-1 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-1 reports (lines 15-81) by the volume-perrailcar 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 railcarmiles-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-R10-006), 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 1-46b - 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-1. Available at: http://www.stb.dot.gov/stb/industry/econ_reports.html
Shipper Partner 2.0.12 Tool: Technical Documentation 24 | Page

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-1 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 NOx and 

PM inventories in a similar fashion using the average 2010 locomotive gPM10/gal and gNOx/gal factors 

from Tables 5 and 6, respectively, in EPA's 2009 Technical Highlights: Emissions Factors for 

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 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

Boxcar 50 ft and longer 

including equipped 

boxcars

7,177 Based on the average of the following boxcar types: 

50ft assumed to be 5694 [reflecting the average of 5355 (NS), 5431 (UP), 5238 (CSX), 

6175 (BSNF), 6269 (GTRC)]. 

60ft assumed to be 6,648 [reflecting the average of 6618 (NS), 6389 (UP), 6085 (CSX), 

7500 (BNSF)].

50ft high cube assumed to be 6,304 [reflecting the average of 6339 (NS) and 6269 

(CSX)]. 

60 ft high cube assumed to be 6917 [reflecting the average of 7499 (NS) , 6646 (CSX), 

and 6607 (GTRC)].

86ft assumed to be 9999 (NS).

Autoparts assumed to be 7499 (NS).

Boxcar 40ft 4,555 Based on estimate of 50ft boxcar volume described above. Assumed 40ft length 

would result in 20% reduction in volume.

 

14 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/julqtr/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.com/bdd_tank.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
Shipper Partner 2.0.12 Tool: Technical Documentation 25 | Page

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 typesincluding 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 multilevel 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)]. 
Shipper Partner 2.0.12 Tool: Technical Documentation 26 | Page

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

Tank Cars under 22,000 

gallons

2,314 Assumes 1 gallon=0.1337 cubic foot (USDA).

Based on small tank car average volume of 17304 gallons, which is the average of the 

following currently manufactured tank car volume design capacities of 13470, 13710, 

15100, 15960, 16410,17300,19900,20000,20590, and 20610 gallons (GTRC).

Tank Cars over 22,000 

gallons

3,857 Assumes 1 gallon=0.1337 (USDA).

Based on large tank car volume of 28851 gallons, which is the average of the following 

currently manufactured tank car volume design capacities of 23470, 25790, 27200, 

28700, 30000, 33000, and 33800 gallons (GTRC). 

All Other Cars 5,014 Based on average volume presented above for each of the nine railcar types (all 

flatcars are represented by the line item that includes multi-level flatcars - 7428).

Table 9: Illustrative U.S. Freight Rail Industry Average Factors in Modal Shift 

 CO2 NOx PM2.5

gram/short ton-mile 22.94 0.4270 0.0120

gram/truck-equivalent mile 813.8 13.19 0.3569

gram/TEU-mile 292.8 4.745 0.1284

Table 10: Underlying Emissions Inventories and Activity Data for Illustrative U.S. Freight Rail Industry 

Average Factors in Modal Shift 

CO2 (grams) 41,736,353,990,153

short ton-miles 1,819,633,000,000

Class I-only diesel fuel consumption (gallons) 3,905,310,865

Class I-only railcar miles (total) 34,611,843,000

50' and Larger Box Plain + Box Equipped 2,223,402,000 

40' Box Plain 22,000 

Flat TOFC/COFC, General, and Other 5,057,466,000 

Flat Multi Level 1,725,998,000 

Gondola Plain and Equipped 7,893,684,000 

Refrigerated Mechanical and Non-Mechanical 495,311,000 

Open Top Hopper General and Special Service 5,913,012,000 

Covered Hopper 7,210,656,000 

Tank under 22,000 gallons 1,295,482,000 

Tank 22,000 gallons and over 2,394,565,000 

All Other Car Types 402,245,000

Note that NOx and PM emission factors were not available at the carrier level for the rail mode. 

Accordingly, the modal average emission factors for NOx and PM were assumed to apply equally for all 

rail carriers, 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
Shipper Partner 2.0.12 Tool: Technical Documentation 27 | Page

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) for the 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 International 13.0678

Ship_Barge International 29.1937

Ship_Feeder International 29.1937

Ship_inland_Germany Germany 41.5280

Ship_inland_China China 35.0578

Ship_Asia-Africa Asia--Africa 11.9227

Ship_Asia-South America (EC/WC) Asia--South America (EC/WC) 13.1897

Ship_Asia-Oceania Asia--Oceania 13.4028

Ship_Asia-North Europe Asia--North Europe 10.8586

Ship_Asia-Mediterranean Asia--Mediterranean 12.1358

Ship_Asia-North America EC Asia--North America EC 12.9854

Ship_Asia-North America WC Asia--North America WC 12.0818

Ship_Asia-Middle East/India Asia--Middle East/India 13.5459

Ship_North Europe-North America EC North Europe--North America EC (incl. Gulf) 14.1823

Ship_North Europe-North America WC North Europe--North America WC 13.0642

Ship_Mediterranean-North America EC Mediterranean--North America EC (incl. Gulf) 12.6788

Ship_Mediterranean-North America WC Mediterranean--North America WC 10.1433

Ship_Europe (North & Med)-Middle East/India Europe (North & Med)--Middle East/India 13.4276

 

24 Buhaug, Ø., 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
Shipper Partner 2.0.12 Tool: Technical Documentation 28 | Page

Ship_Europe (North & Med)-Africa Europe (North & Med)--Africa 15.8361

Ship_Europe (North & Med)-Oceania (via Suez / via 

Panama)

Europe (North & Med)--Oceania (via Suez / via Panama) 14.4056

Ship_Europe (North & Med)-Latin America/South America Europe (North & Med)--Latin America/South America 12.6146

Ship_North America-Africa North America--Africa 17.4549

Ship_North America EC-Middle East/India North America EC--Middle East/India 12.8788

Ship_North America-South America (EC/WC) North America--South America (EC/WC) 13.4379

Ship_North America-Oceania North America--Oceania 15.0552

Ship_South America (EC/WC)-Africa South America (EC/WC)--Africa 11.7432

Ship_Intra-Americas (Caribbean) Intra-Americas (Caribbean) 15.9222

Ship_Intra-Asia Intra-Asia 15.2012

Ship_Intra-Europe Intra-Europe 17.1790

Table 12: BSR Air Emission Factors (gCO2/short ton-mile)

Air_freight_long_>3700km International 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 SIZE AVERAGE 

CARGO 

CAPACITY 

(metric 

tonne)

Average 

yearly 

capacity 

utilization

Average 

service 

speed 

(knots)

Transport work 

per ship (tonne 

NM)

Loaded 

efficiency 

(g of CO2/ 

ton-mile)

Total 

efficiency (g 

of CO2/tonmile)

Crude oil tanker 2000,000+dwt 295,237 48% 15.4 14,197,046,742 2.34 4.23

Crude oil tanker 120,000-199,99 dwt 151,734 48% 15 7,024,437,504 3.21 6.42

Crude oil tanker 80,000-119,999 dwt 103,403 48% 14.7 4,417,734,613 4.38 8.61

Crude oil tanker 60,000-79,999 dwt 66,261 48% 14.6 2,629,911,081 6.28 10.95

Crude oil tanker 10,000-59,999 dwt 38,631 48% 14.5 1,519,025,926 7.59 13.28

Crude oil tanker 0-9,999 dwt 3668 48% 12.1 91,086,398 30.22 48.61

Products tanker 60,000+ dwt 101,000 55% 15.3 3,491,449,962 4.82 8.32

Products tanker 20,000-59,999 dwt 40,000 55% 14.8 1,333,683,350 10.51 15.03

Products tanker 10,000-19,999 dwt 15,000 50% 14.1 464,013,471 16.49 27.30

Products tanker 5,000-9,999 dwt 7,000 45% 12.8 170,712,388 21.60 42.62

Products tanker 0-49,999 dwt 1,800 45% 11 37,598,072 38.68 65.69

Chemical tanker 20,000 + dwt 32,200 64% 14.7 1,831,868,715 8.32 12.26

Chemical tanker 10,000-19,999 dwt 15,000 64% 14.5 820,375,271 10.66 15.76

Chemical tanker 5,000-9,999 dwt 7,000 64% 14.5 382,700,554 15.62 22.04

Chemical tanker 0-4,999 dwt 1,800 64% 14.5 72,147,958 27.15 32.41

LPG tanker 50,000 + m3 46,656 48% 16.6 2,411,297,106 7.59 13.14

LPG tanker 0-49,999 m3 3,120 48% 14 89,631,360 39.41 63.50

LNG tanker 200,00 + m3 97,520 48% 19.6 5,672,338,333 7.88 13.58

LNG tanker 0-199,999 m3 62,100 48% 19.6 3,797,321,655 12.26 21.17
Shipper Partner 2.0.12 Tool: Technical Documentation 29 | Page

TYPE SIZE AVERAGE 

CARGO 

CAPACITY 

(metric 

tonne)

Average 

yearly 

capacity 

utilization

Average 

service 

speed 

(knots)

Transport work 

per ship (tonne 

NM)

Loaded 

efficiency 

(g of CO2/ 

ton-mile)

Total 

efficiency (g 

of CO2/tonmile)

Bulk carrier 200,000 +dwt 227,000 50% 14.4 10,901,043,017 2.19 3.65

Bulk carrier 100,000-199,999 

dwt

163,000 50% 14.4 7,763,260,284 2.63 4.38

Bulk carrier 60,000-99,999 dwt 74,000 55% 14.4 3,821,361,703 3.94 5.98

Bulk carrier 35,000-59,999 dwt 45,000 55% 14.4 2,243,075,236 5.55 8.32

Bulk carrier 10,000-34,999 dwt 26,000 55% 14.3 1,268,561,872 7.74 11.53

Bulk carrier 0-9,999 dwt 2,400 60% 11 68,226,787 33.43 42.62

General cargo 10,000 + dwt 15,000 60% 15.4 866,510,887 11.09 17.37

General cargo 5,000-9,999 dwt 6,957 60% 13.4 365,344,150 14.74 23.06

General cargo 0-4,999 dwt 2,545 60% 11.7 76,645,792 15.91 20.29

General cargo 10,000+ dwt, 100+ 

TEU

18,000 60% 15.4 961,054,062 12.55 16.06

General cargo 5,000-9,999 dwt,

100+TEU

7,000 60% 13.4 243,599,799 20.14 25.54

General cargo 0-4,999 dwt, 

dwt+TEU

4,000 60% 11.7 120,938,043 22.63 28.90

Refrigerated 

cargo

All 6,400 50% 20 392,981,809 18.83 18.83

Container 8000+TEU 68,600 70% 25.1 6,968,284,047 16.20 18.25

Container 5,000-7,999 TEU 40,355 70% 25.3 4,233,489,679 22.19 24.23

Container 3,000-4,999 TEU 28,784 70% 23.3 2,280,323,533 22.19 24.23

Container 2,000-2,999 TEU 16,800 70% 20.9 1,480,205,694 26.71 29.19

Container 1,000-1,999 TEU 7,000 70% 19 578,339,367 42.91 46.86

Container 0-999 TEU 3,500 70% 17 179,809,363 48.61 52.99

Vehicle 4000 +ceu 7,908 70% 19.4 732,581,677 36.78 46.71

Vehicle 0-3999 ceu 2,808 70% 17.7 226,545,399 68.90 84.08

Ro-Ro 2,000 + lm 5,154 70% 19.4 368,202,021 66.12 72.25

Ro-Ro 0-1,999 lm 1432 70% 13.2 57,201,146 80.57 88.02

Note: “Loaded efficiency” is the theoretical maximum efficiency when the ship is fully loaded at service speed/85% load. Since engine 

load at the fully loaded condition is higher than the average including ballast and other voyages, the difference between the columns 

“loaded efficiency” and “total efficiency cannot be explained by differences in utilization only.

Table 14: IMO Air Emission Factors (gCO2/short ton-mile)

Boeing 747F high 691.89

Boeing 747F low 634.96

Ilyushin IL 76T high 2,627.43

Ilyushin 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 PM2.5 by 

assuming 95% of PM10 is PM2.5, which we determined was a good approximation of the share of 
Shipper Partner 2.0.12 Tool: Technical Documentation 30 | Page

overall PM10 emissions represented by particulate matter that is 2.5 micrometers in diameter or 

smaller.

Table 15: TTI Barge Emission Factors 

 CO2 NOx PM2.5

gram/short ton-mile 17.48 0.4691 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. 

Payload Validation

Payload validation cutpoints were set with the intention of identifying those payloads that are 

somewhat outside typical industry values (yellow flag warnings) and those that are far outside industry 

averages (red flag warnings).The payload check only apples to Data Availability selections 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.
Shipper Partner 2.0.12 Tool: Technical Documentation 31 | Page

Table 16. Truck Carrier Payload Validation Ranges 

Truck Bin Category

Range 1 

Low

Range 1 

High / 2 

Low

Range 2 

High / 3 

Low

Range 3 

High / 4 

Low

Range 4 

High / 5 

Low

Range 5 

High 

(Max)

LTL Dry Van (from Dry Van Single -

LTL-Moving-Package)26 0.0 0.0 11.0 19.1 23.2 83.7

Package (from Dry Van Single -

LTL-Moving-Package) 0.0 6.9 11.0 19.1 23.2 83.7

TL Dry Van (from Dry Van Single -

other bins) 0.0 10.5 14.5 22.4 26.4 150.0

Refrigerated 0.0 14.5 17.3 22.9 25.7 82.5

Flatbed 0.0 14.0 18.3 26.7 31.0 99.9

Tanker 0.0 19.1 22.0 27.8 30.7 103.8

Moving (from Dry Van Single – LTLMoving-Package) 0.0 6.9 11.0 19.1 23.2 83.7

Specialized (from Specialty - Other 

bins) 0.0 20.2 22.9 28.3 31.1 111.0

Dray (from Chassis) 0.0 11.2 16.5 27.1 32.4 73.5

Auto Carrier 0.0 5.7 11.0 21.4 26.6 73.5

Heavy-Bulk 0.0 2.7 16.5 44.0 57.8 120.0

Utility (from Specialty – Other 

bins) 0.0 20.2 22.9 28.3 31.1 111.0

Mixed (from Other - HeavyFlatbed-Mixed bins) 0.0 14.7 21.1 33.8 40.1 99.3

Expedited (from Dry Van Single -

other bins) 0.0 10.5 14.5 22.4 26.4 150.0

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.

 

26 Since LTL shipments can be very small, no lower-bound “red/yellow” ranges are designated for LTL carrier 

payloads.
Shipper Partner 2.0.12 Tool: Technical Documentation 32 | Page

Figure 1. Logistics Partner Payload Distribution 

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)

0 

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 

0 10 20 30 40 50 60 70 80 90 100

Fraction of Partner Population

Short Tons

Cumulative Payload Distribution - 2011 Logistics
Shipper Partner 2.0.12 Tool: Technical Documentation 33 | Page

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.