Logistics Partner 2.0.13 Tool: 

Technical Documentation 

2013 Data Year - United States Version 
Transportation and Climate Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency

Logistics Partner 2.0.13 Tool: 

Technical Documentation 

2013 Data Year - United States Version 

Office of Transportation and Air Quality 

EPA-420-B-14-052 

July 2014 
 

 

 

 

 

 

 

 

SmartWay 2.0.13

Logistics Tool Technical Documentation 

7-8-2014 

1.0 Overview 

The SmartWay Logistics Tool is intended to help logistics companies estimate and 

assess their carbon, PM, and NOx emission performance levels as well as their total 

emissions associated with goods movement in the U.S. freight rail, barge and trucking 

sectors1 

. 

The new SmartWay truck and barge carrier emissions performance data that EPA has 

included in the tool, along with publically available Class I rail CO2 data, will allow 

logistics companies to generate more accurate emissions performance estimates and 

mass emissions inventories. The tool will allow logistics companies to track their 

freight-related emissions performance from year to year, and also help optimize their 

emissions performance by allowing them to better estimate the emissions impact of 

individual carriers. 

1 While this tool is primarily focused on freight movements in the U.S. rail, barge and trucking freight 

sectors, our long-term vision is to provide users with tools to help them evaluate the emissions 

performance associated with other transport modes including ocean-going marine and air. 

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2.0 Tool Inputs and Calculations 

After logistics companies enter their company and contact information, they provide 

basic information about each company they operate, including name, SCAC, MCN, and 

US DOT Number. Logistics companies then identify each carrier that they use for each 

logistics business unit. Next, users proceed to input activity data for each carrier 

specified. 

Emission Inventory and Performance Metric Calculations 

After inputting the required mileage and/or ton-mile information for each carrier used, 

the tool will calculate the associated total mass emissions (i.e., an emissions inventory) 

based on the mileage-related activity data entered, 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 logistics companies enter for each carrier. We 

encourage logistics companies to select the unit of activity data that is most appropriate 

for characterizing each carrier type (e.g., use grams per mile for TL and grams per tonmile 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., truck or barge miles, 

railcar-miles, or ton-miles) by the corresponding carrier emissions performance data. 

To calculate composite, business unit-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 logistics business unit’s carriers by 

the percentage of the business unit’s overall freight activity that the carrier moves. An 

example composite performance calculation is provided below. 

Table 1. Example Compositing Calculation 

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. 

Note that the composite emissions performance values are the numbers that will 

be used to place logistics partners into performance bins within the logistics 

ranking category. 

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Ton-Mile Calculation 

Correctly calculating Ton-Miles is critically important for the accurate determination of 

your carbon foot-print. You can calculate your business unit’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, railcar, or barge, 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 tonmiles: 

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: Empty miles are not included in the ton-mile calculation, but the fuel used to 

move those empty miles are included in the overall g/ton-mile calculations. 

To check your estimate, divide ton-miles by miles. The result is your fleet-average 

payload. If this number is not reasonable, 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, barge and rail freight transport providers. These 

data are provided in the SmartWayCarrierData2013.xls file, which should be 

downloaded to the user’s computer using the appropriate button on the tool’s Home 

page. Performance data for Truck, barge and Multi-modal partners correspond to data 

submittals for the 2013 calendar year, while current Logistics partner performance 

corresponds to submittals for 2012. Performance for Rail companies are modal 

averages, based on publicly available R-1 data. Performance values for non-SmartWay 

truck, multi-modal and logistics partners are based on the lowest performing SmartWay 

partner fleets, with the exception of non-SmartWay barge carriers – SmartWay does not 

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have performance estimates for non-SmartWay barge carriers at this time.2 For this 

reason the Logistics Tool cannot calculate carbon footprints for this portion of 

your carrier fleet at this time. . SmartWay plans to incorporate emission factors for 

non-SmartWay barge carriers, as well as for ocean-going marine and air transport 

providers as a whole, and gram per volume-mile emission factors for all modes, in the 

near future. 

Truck Carrier Performance 

Truck carrier performance data utilized by the Logistics Tool is based on 2013 Truck 

Partner Tool submittals. Performance data includes g/mile and g/ton-mile for each truck 

carrier by ranking category, with a top ranking indicating top 20 percent performance for 

a given pollutant/bin category. 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 

• Heavy/Bulk 

• Package 

• Auto Carrier 

• Moving 

• Specialized 

• Mixed 

• Expedited 

The following provides an overview of the truck carrier ranking process used to estimate 

the carrier-specific performance bins. 

Truck Performance Ranking 

In the 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, package delivery, or expedited, and C.) 

equipment type: dry van, refrigerated van, flatbed, tanker, heavy/bulk, chassis 

(container), auto carrier, moving, utility, or specialized (e.g., hopper, livestock, other). 

The possible categories are shown below. 

2 All rail carriers are assumed to have the same industry modal average performance levels in the Logistics Tool, 

regardless of the partnership status. 

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For-Hire 

Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk Auto Carrier Moving Specialized 

TL 

LTL 

PD 

Expedited 

Dray 

Private 

Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk Auto Carrier Moving Specialized 

TL 

LTL 

PD 

Expedited 

Dray 

For-hire and private fleets are combined in SmartWay ranking categories. There are 

relatively few private fleets compared to for-hire fleets. Because owners of private fleets 

generally hire their own fleets exclusively, it was determined that ranking for-hire and 

private fleets together would not be detrimental to for-hire fleets, and the simplicity of 

one for-hire and private category outweighed the benefits of listing fleets separately. 

Ranking for-hire and private separately would have doubled the number of categories. 

Fleets can thus be categorized as shown below. 

For Hire / Private 

Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk Auto Carrier Moving Specialized 

TL 

LTL 

PD 

Expedited 

Dray 

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 could be mixed via their operational or equipment type. Fleets are generally 

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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 graphic illustrates the 

population of the various categories. The darker the shade of the intersection, the 

higher the number of fleets in that category. 

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Dry 

Van 

Reefer Flatbed Tanker Chassis Heavy/ 

Bulk 

Auto 

Carrier 

Moving Specialized Mixed 

TL 

LTL 

PD 

Expedited 

Dray 

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 two categories were combined. A similar 

situation was identified with flatbed, and flatbed truckload and less than truckload were 

combined. Although no less than truckload tanker fleets were identified, tanker 

truckload and less than truckload were combined into one category so that no 

intersections would be left undefined. Similar aggregations were made for the 

remaining, less common body types including heavy/bulk, auto carrier, moving and 

specialized. All dray was collapsed into one category, and package delivery was 

restricted to dry van body types. Any fleet that had mixed operation and/or mixed 

equipment was placed into a single mixed category. This produces the final bin 

categories illustrated below. 

For-Hire and Private 

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. 

Companies 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/tonmile, NOx g/mile, NOx g/ton-mile, PM10 g/mile and PM10 g/ton-mile. Companies within 

a category were then separated into 5 groups (rankings) such that an equal number of 

companies were in each. Each ranking category thus represents a range of emission 

factors. This range, and associated cutpoints (transition points from one ranking 

category to the next) were then modified so that each bin had an equal range, and the 

new ranking category cutpoints remained as close to the originals as possible. The new 

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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 

companies in a ranking category. 

It would be simpler and more straightforward to use company-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 companies, and thus opportunity for companies 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 rankings. The table 

below illustrates the ranking results for the For Hire/Private Truckload/Expedited Dry 

Van/Container category, using 2010 truck partner data. 

Table 2. Example Binning Results for One Ranking Category (2010 Data) 

For-Hire/Private Truckload/Expedited Dry Van/Container CO2 g/mile 

Rank Fleets Grams Per 

Mile Min 

Grams Per 

Mile Max 

Grams Per 

Mile Avg 

Grams Per Mile 

Midpoint 

Grams Per 

Mile Std Dev 

1 159 602 1,600 1,503 1,550 141 

2 241 1,601 1,699 1,654 1,650 28 

3 204 1,700 1,799 1,746 1,750 28 

4 139 1,800 1,899 1,853 1,850 28 

5 55 1,900 3,701 2,064 2,801 302 

Similar tables were developed for all categories. The midpoint of each ranking category 

is the data that a logistics company will download into their SmartWay Logistics Tool to 

represent the emission performance of a specific carrier fleet that is in the associated 

rank category. Once the categories and ranks have been established, the carrier fleets 

of any new companies joining SmartWay will fall into one of the predefined 

categories/ranks. SmartWay expects to update the category/ranks 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 specifically for 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 rank range delta (min/max) for each ranking category, and using the delta 

to calculate a non-SmartWay carrier midpoint for each category. This midpoint was the 

midpoint for Rank 5 plus the standard range delta. For example, if the Rank 5 midpoint 

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was 10.5 and the Ranking 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 Ranking Categories, the worst performance value was 

selected to be the midpoint for the non-SmartWay Truck carriers. This approach does 

not require the shipper to identify the appropriate ranking category for their NonSmartWay carrier(s), which they may not know. 

As discussed in the Logistics Tool Data Entry and Troubleshooting Guide, 

depending upon the type of data available for a given carrier, the user may input tonmiles 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 

SmartWayCarrierData2013.xls file.3 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 bins based on the carrier 

tool submittals for the most recent available calendar year (2012 for logistics, and 2013 

for multi-modal). The Logistics Tool modifies the Bin 5 values for each of these ranking 

categories (logistics and multi-modal) to estimate non-SmartWay carrier performance in 

the same way as was done for non-SmartWay Truck carriers (i.e., adding the standard 

range delta value to the Rank 5 midpoints). 

Barge Carrier Performance 

Barge carriers have agreed to have their actual emissions results made public, hence, 

barge performance values used in the Logistics are carrier-specific. , The gram per mile 

performance values for barge carriers correspond to individual barge miles travelled, 

rather than miles travelled by a string of barges or the associated tug. 

Rail Carrier Performance 

Rail carrier performance data are collected and displayed in the Logistics 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 R3 The Logistics Tool also calculates average payload and average volume for each logistics fleet defined by the user, 

weighting truck and rail carrier payloads and volumes by the miles assigned on the Tool Activity screen. The 

resulting average payload and volume figures will be included in subsequent updates to the SmartWay Carrier file 

for use by Shippers and Logistics companies. 

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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/railcarmile g 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 

NOx and PM emission factors for rail carriers are based on industry averages. The 

freight rail gNOx

/ton-mile and gPM2.5/ton-mile factors were developed with 2010 

inventory data from Tables 3-82 and 3-83, respectively, in EPA’s 2008 Regulatory 

Impact Analysis for a locomotive diesel engine rule. 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 EPA determined would very 

closely align with the freight rail sector. This emissions inventory data was divided by 

the 2007 R-1 ton-mile data. 

EPA developed the industry average freight rail g/mile factors by using 2008 railcar 

mileage data from lines 15 through 81 of R-1 forms that Class I railroad companies 

submitted to the Surface Transportation Board. The railcar miles were then converted 

into “truck-equivalent” railcar miles by estimating the average volume capacity of Class I 

railcars and dividing that 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 EPA determined that this was the best available 

data and method to estimate modal average truck-equivalent railcar miles. 

To estimate the industry average volume capacity of Class I railcars, the railcar miles 

reported by each company for each railcar type in their respective 2008 R-1 reports 

(lines 15-81) were multiplied by the volume-per-railcar assumptions in Table 7 below to 

obtain total Class I TEU-miles. EPA then divided the total railcar TEU-miles by the total 

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railcar miles to estimate the industry average railcar volume capacity. EPA then divided 

this average railcar volume capacity (3.92) by the average freight truck volume capacity 

(2.78 TEUs) to develop the conversion factor - 1.41 railcar-miles-to-truck-miles. 

EPA developed the NOx and PM inventories using the average 2010 locomotive 

gPM10/gal and gNOx/gal factors from Tables 5 and 6, respectively, in EPA's 2009 

Technical Highlights: Emissions Factors for Locomotives. To calculate gPM2.5/gal, we 

assumed 95% of PM10 is PM2.5, which we determined was a good approximation of 

the share of overall PM10 emissions represented by particulate matter that is 2.5 

micrometers in diameter or smaller. 

Table 4 presents the industry-average freight rail NOx and PM emissions factors in the 

tool and Table 5 presents the key underlying data. 

Table 4. Illustrative U.S. Freight Rail Industry Average Factors 

NOx PM2.5 

gram/short ton-mile 0.4270 0.0120 

gram/truck-equivalent mile 13.19 0.3569 

gram/TEU-mile 4.745 0.1284 

Table 5. Underlying Emissions Inventories and Activity Data for Illustrative U.S.
 

Freight Rail Industry Average Factors
 

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

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 

Flat Multi Level 

5,057,466,000 

1,725,998,000 

Gondola Plain and Equipped 7,893,684,000 

Refrigerated Mechanical and Non-Mechanical 495,311,000 

Open Top Hopper General and Special 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 

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 RailcarMiles (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. 

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Table 6. 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 7 below. 

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 7 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 rail 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 8 below. 

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Table 7. Railcar Volume Assumptions and Sources 

Railcar Type Cubic 

Feet 

Source/Method 

Key: Norfolk Southern Railroad (NS)4, Union Pacific Railroad (UP)5, Burlington 

Northern Santa Fe Railroad (BNSF)6

, CSX Transportation Railroad (CSX)7 , 

World Trade Press Guide to Railcars (GTRC)8

, Chicago Rail Car Leasing 

(CRCL)9

, Union Tank Car Company (UTCC) 10, U.S Department of Agriculture 

(USDA) 11 

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. 

Flat car – all types 6,395 Based on the average of the following flat car types: 

except for multi-level 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 

multi-level as a single flat car type. 

Gondola – all types 5,190 Based on the average of the following gondala car types: 

Including equipped 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), 

4 http://www.nscorp.com/nscportal/nscorp/Customers/Equipment_Guide 

5 http://www.uprr.com/customers/equip-resources/cartypes/index.shtml 6

http://www.bnsf.com/customers/how-can-i-ship/individual-railcar/#%23subtabs-3 7 http://www.csx.com/index.cfm/customers/equipment/railroad-equipment/#boxcar_specs 8 http://www.worldtraderef.com/WTR_site/Rail_Cars/Guide_to_rail_Cars.asp 

9 http://www.crdx.com/railcar.html

10 http://www.utlx.com/bdd_tank.html 11 U.S. Department of Agriculture (USDA), 1992, Weights, Measures, and Conversion Factors for Agricultural 

Commodities and Their Products, Agricultural Handbook Number 697, Economic Research Service, Washington, 

DC. Available at: http://www.ers.usda.gov/publications/ah697/ah697.pdf 

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Railcar Type Cubic 

Feet 

Source/Method 

Key: Norfolk Southern Railroad (NS)4, Union Pacific Railroad (UP)5, Burlington 

Northern Santa Fe Railroad (BNSF)6

, CSX Transportation Railroad (CSX)7 , 

World Trade Press Guide to Railcars (GTRC)8

, Chicago Rail Car Leasing 

(CRCL)9

, Union Tank Car Company (UTCC) 10, U.S Department of Agriculture 

(USDA) 11 

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 - 6,202 Based on the average of the following refrigerated car types: 

Mechanical /non- 48-72ft assumed to be 6963 [based on average of 6043 (UP) and 7883 

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

22,000 gallons 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 3,857 Assumes 1 gallon=0.1337 (USDA). 

gallons 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). 

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Table 8. 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 

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 

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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 

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 

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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 

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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 

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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 

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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 

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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 

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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 

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). You may select 

either ton-miles or total miles as the basis for determining your % SmartWay Value. 

Note that the tool will automatically populate the % SmartWay screen with any carrier 

activity data entered in the Activity Data screen. In addition, the metric selected for the 

first business unit (miles or ton-miles) will be chosen as the basis for your other 

business units as well, so that a company-level % SmartWay Value can be calculated. 

22 
 

 

 

 

 

 

 

 

 

 

To see your company-level % SmartWay Value, calculated across all business units, go 

to the % SmartWay Report in the Reports Menu via the Home page. 

3.0 Data Validation 

The Logistics 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) must be 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 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 9. (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. 

23 
 

 

Table 9. 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-MovingPackage)12 0.0 0.0 11.0 19.113 23.2 83.7 

Package (from Dry Van 

Single - LTL-MovingPackage) 0.0 0.0 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 

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

Specialized (from Specialty -

Other bins) 0.0 20.2 22.9 28.3 31.1 111.0 

Dray (from Chassis) 0.0 11.2 16.5 27.1 32.4 73.5 

Auto Carrier 0.0 5.7 11.0 21.4 26.6 73.5 

Heavy-Bulk 0.0 2.7 16.5 44.0 57.8 120.0 

Utility (from Specialty – Other 

bins) 0.0 20.2 22.9 28.3 31.1 111.0 

Mixed (from Other - 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. 

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

and package carrier payloads.

13 A further assessment of reasonable upper bound LTL payloads is planned for 2015.
 

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Fraction of Partner Population 

Figure 1. Logistics Partner Payload Distribution 

Cumulative Payload Distribution - 2011 Logistics 

1 

0.9 

0.8 

0.7 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

0 

0 10 20 30 40 50 60 70 80 90 100 

Short Tons 

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 Class 1 carriers (see Table 6 

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) 

25 
 

 

 

• Average multi-modal payloads between 60 and 95 tons (warning – yellow) 

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 tonmile 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. 

26