Logistics Company Carrier Partner 

2.0.15 Tool: 

Technical Documentation

2015 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-16-066

July 2016

Logistics Company Carrier Partner 

2.0.15 Tool: 

Technical Documentation

2015 Data Year - United States Version
1

SmartWay 2.0.15

Logistics Tool Technical Documentation

7-8-2016

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, air and 

trucking sectors1. 

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

has included in the Tool, along with publically available Class I rail 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. 

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, 

NSC, 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, package, and multi-modal / rail.) 

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

sectors, SmartWay anticipates providing performance data for ocean-going marine freight in the future as 

well. 
2

The emissions inventory for each carrier/mode combination displayed on the 

Emissions Summary, Carrier Performance, and SmartWay Category Details

screens is calculated by multiplying the appropriate unit of activity data (i.e., truck, air 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 

category.

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, aircraft, 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 
3

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, air, and rail freight transport providers. 

These data are provided in the SmartWayCarrierData2015.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, air,2 and multi-modal partners correspond to 

data submittals for the 2015 calendar year, while current Logistics partner performance 

may correspond to submittals for 2014, depending on whether the 2015 data year 

performance information for logistics companies has been released at the time of tool 

download. (Within a given data year, logistics tools are released after the multi-modal 

tool.) Performance for Rail companies are modal averages, based on publicly available 

R-1 data. 

Truck Carrier Performance

Truck carrier performance data utilized by the Logistics Tool is based on 2015 Truck 

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

carrier by SmartWay Category, with a top ranking indicating the top 20 percent 

performance level for a given pollutant/performance category. Note that g/mile and 

g/ton-mile values represent midpoints for the appropriate SmartWay Category, rather 

than exact performance levels for a given carrier. Truck SmartWay Categories include:

• TL Dry Van

• LTL Dry Van

• Refrigerated

• Flatbed

• Tanker

• Dray

• Heavy/Bulk

 2 As of 6-27-2016 no air carrier data had been approved by SmartWay.
4

• 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.

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 categories. There are relatively 

few private fleets compared to for-hire fleets. Because owners of private fleets 
5

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 

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. 

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 
6

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 five 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 

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.
7

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. 

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 

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 SmartWay Categories, the non-SmartWay performance 

metric was calculated by using the average value of these mid-points, weighted by the 

number of fleets in each category. This approach does not require the shipper to 

identify the appropriate SmartWay Category for their Non-SmartWay carrier(s), which 

they may not know, while still ensuring that the performance of their non-SmartWay 

carriers reflects the distribution of the different categories within the truck population.

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 

SmartWayCarrierData2015.xls file.3 For Non-SmartWay truck carriers, the values for 

 3 The Logistics Tool also calculates average payload and average volume for each logistics fleet defined by the user, 

weighting 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.
8

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 (2014 for logistics, and 2015

for multi-modal). Non-SmartWay carrier performance for these SmartWay Categories is 

estimated in the same way as is done for non-SmartWay Truck carriers (i.e., averaging 

the bin midpoints to calculate a modal average value).

Air and Barge Carrier Performance

Air and 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(s).

Non-SmartWay barge carrier gram per mile and gram per ton-mile performance is set to 

be 25% higher than the worst performing SmartWay barge carrier. 

Since no air carrier data submittals have been approved as of this date, performance 

levels for non-SmartWay air freight are based on publicly available data. First upper 

bound estimates for grams of CO2 per ton-mile were obtained for short and long-haul air 

freight (~4,236 g/t-mi and ~1,461 g/t-mi, respectively).4,5 Values for CO2 g/mile were 

calculated by multiplying the g/t-mi value by an average cargo payload value of 22.9 

short tons. The average payload value was estimated by dividing total air freight 

tonnage in 2012 (15M tons)6 by the total number of cargo departures in the same year 

(654,956 LTOs).7 Corresponding performance metrics for NOx and PM10 were based 

on the ratio of these pollutants to CO2 from the EDMS 5.1.4.1 model (0.009 for NOx and 

0.000059 for PM10).8 The resulting performance metrics are shown in Table 3 below. An 

average cargo volume estimate was also obtained for inclusion in the SmartWay carrier 

 4 Short haul air freight assumed to be less than 3,000 miles, covering most domestic air routes in the U.S. 5 Estimates from Figure 8.6 in Sims R., R. Schaeffer, F. Creutzig, X. Cruz-Núñez, M. D’Agosto, D. Dimitriu, M. J. 

Figueroa Meza, L. Fulton, S. Kobayashi, O. Lah, A. McKinnon, P. Newman, M. Ouyang, J. J. Schauer, D. Sperling, 

and G. Tiwari, 2014: Transport. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working 

Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. 

Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. 

Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University 

Press, Cambridge, United Kingdom and New York, NY, USA. 6 U.S. DOT Bureau of Transportaion Statistics, Fregiht Facts and Figures 2013. Accessed 20 April 2015 

http://www.ops.fhwa.dot.gov/freight/freight_analysis/nat_freight_stats/docs/13factsfigures/pdfs/fff2013_highres.pdf 7 U.S. DOT, Bureau of Transportation Statistics, U.S. Air Carrier Traffic Statistics, accessed April, 20, 2015: 

http://www.rita.dot.gov/bts/acts/customized/table?adfy=2012&adfm=1&adty=2012&adtm=12&aos=6&artd&arti&a

rts=3&asts&astns&astt=3&ascc=2&ascp 8 EDMS outputs for take-off mode, assumed to be equal to cruising mode. (Cruise emissions are not output by 

EDMS). Take-off mode emission rates were averaged across all aircraft/engine combinations in the Heavy (Max 

Takeoff Weight over 255,000 lbs) and Large (Max Takeoff Weight 41,001 to 255,000 lbs) weight classes.
9

data file based on the volume for a typical freight aircraft, the Boeing 747 200 series 

(5,123 cubic feet).9

Table 3. Assumed Performance Metrics for Non-SmartWay Air Carriers 

CO2/tmi CO2/mi NOx/mi NOx/tmi PM/mi PM/tmi

Short-haul 4,236 96,998 873.2713 38.1341 5.743247 0.250797

Long-haul 1,461 33,448 301.1280 13.1497 1.980430 0.086482

Rail Carrier Performance

All rail carriers are assumed to have the same industry modal average performance 

levels in the Logistics Tool, regardless of Partnership status. 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 R-1 data was also used to obtain 

total railcar-miles per year for all Class 1 carriers, in order to estimate gram per railcarmile 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 companyspecific data in the future. The R-1 data and corresponding CO2 performance data are 

presented in Table 4 below. 

Table 4. 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

 9 http://www.airgroup.com/standalone.php?action=air_spec
10

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 rule10. 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 Board11. 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 

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 emission estimates using the average 2010 locomotive 

g PM10/gal and g NOx/gal factors from Tables 5 and 6, respectively, in EPA's 2009 

Technical Highlights: Emissions Factors for Locomotives12. To calculate g PM2.5/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 5 presents the industry-average freight rail NOx and PM emissions factors in the 

tool and Table 6 presents the key underlying data.

Table 5. 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

 
11

Table 6. 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 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

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.

Table 7. 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 
12

weighting factor to estimate a single average railcar volume for each company. These 

values and the resulting volume estimates are presented in Table 9 below.

Table 8. Railcar Volume Assumptions and Sources

Railcar Type Cubic 

Feet 

Source/Method

Key: Norfolk Southern Railroad (NS)13, Union Pacific Railroad (UP)14, 

Burlington Northern Santa Fe Railroad (BNSF)15, CSX Transportation 

Railroad (CSX)16, World Trade Press Guide to Railcars (GTRC)17, Chicago 

Rail Car Leasing (CRCL)18, Union Tank Car Company (UTCC)19, U.S 

Department of Agriculture (USDA)20

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 

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 

7,428 Based on the average volumes of the flatcar types described above including 

multi-level as a single flat car type. 

 13 http://www.nscorp.com/nscportal/nscorp/Customers/Equipment_Guide 14 http://www.uprr.com/customers/equip-resources/cartypes/index.shtml 15http://www.bnsf.com/customers/how-can-i-ship/individual-railcar/#%23subtabs-3 16 http://www.csx.com/index.cfm/customers/equipment/railroad-equipment/#boxcar_specs 17 http://www.worldtraderef.com/WTR_site/Rail_Cars/Guide_to_rail_Cars.asp 18 http://www.crdx.com/railcar.html

19 http://www.utlx.com/bdd_tank.html 20 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
13

Railcar Type Cubic 

Feet 

Source/Method

Key: Norfolk Southern Railroad (NS)13, Union Pacific Railroad (UP)14, 

Burlington Northern Santa Fe Railroad (BNSF)15, CSX Transportation 

Railroad (CSX)16, World Trade Press Guide to Railcars (GTRC)17, Chicago 

Rail Car Leasing (CRCL)18, Union Tank Car Company (UTCC)19, U.S 

Department of Agriculture (USDA)20

volume of “All Other 

Cars”]

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 /nonMechanical 

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

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

(BNSF)].

50ft assumed to be 5167(GTRC).

40-90 ft. assumed to be 6476 [based on average of 6952 (UP) and 6000 

(BNSF)]. 

Open Top Hopper 4,220 Based on the average of the following open top hopper car types:

42ft assumed to be 3000 (UP). 

54ft assumed to be 3700 (UP).

60ft assumed to be 5188 [based on average of 5125 (UP) and 5250 (GTRC)]. 

45ft+ assumed to be 4105 [based on average of 4500 (UP) and 3710 (BNSF).

Woodchip assumed to be 7075 [based on average of 7525 (NS), 5999 (UP), 

and 7700 (CRCL)]. 

Small Aggregate assumed to be 2252 [based on average of 2150 (NS), 2106 

(BNSF), and 2500 (CRCL)].

Covered Hopper 4,188 Based on the average of the following covered top hopper car types:

45ft assumed to be 5250 (GTRC).

Aggregate assumed to be 2575 [based on average of 2150 (NS) and 3000 

(CRCL)].

Small Cube Gravel assumed to be 2939 [based on average of 2655 (NS), 

3100 (CSX), and 3063 (BNSF). 

Med-Large Cube Ores and Sand assumed to be 4169 [based on average of 

3750 (NS) and 4589 (BNSF)].

Jumbo assumed to be 5147 [based on average of 4875 (NS), 4462 (CSX), 

5175 (BNSF), and 6075 (CRCL)]. 

Pressure Differential (flour) assumed to be 5050 [based on average of 5124 

(NS) and 4975 (CRCL)]. 

Tank Cars under 

22,000 gallons

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

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

average of the following currently manufactured tank car volume design 

capacities of 13470, 13710, 15100, 15960, 16410,17300,,19900, 20000,

20590, and 20610 gallons (GTRC).

Tank Cars over 22,000 

gallons

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

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

following currently manufactured tank car volume design capacities of 23470, 

25790, 27200, 28700, 30000, 33000, and 33800 gallons (GTRC). 

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

(all flatcars are represented by the line item that includes multi-level flatcars -

7428).
14

Table 9. 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 
15

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 
16

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 
17

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 
18

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 
19

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 
20

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 
21

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 

Other Carrier Modes and Metrics

SmartWay plans to incorporate emission factors for ocean-going marine freight, and 

gram per volume-mile emission factors for all modes, in the near future. 

% SmartWay Value

The % SmartWay screen tracks the portion of goods that shippers move with
22

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. 

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). 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 SmartWay Category, which is specified for 

each carrier in 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 10. (See the Truck Tool Technical Documentation for additional 

information.) Note that Ranges 1 and 5 are colored red in the Tool, and require 

explanations before proceeding. Ranges 2 and 4 are colored yellow, and explanations 

are optional.
23

Table 10. 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)21 0.0 0.0 0.0 13.5 20.8 150.0

Package (from Dry Van 

Single - LTL-MovingPackage)22 0.0 0.0 0.0 13.5 20.8 150.0

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-MovingPackage) 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

With the exception of the LTL and package categories (which are based on 2013 data), 

all other 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.

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

and package carrier payloads. Upper bound yellow and red ranges for LTL and package (and multi-modal) carriers 

were set equal to the average payload (6.20) plus twice the standard deviation (7.33) for logistics companies using 

these carrier types (n=991 for 2013 data).
24

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 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)

• 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
25

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.