Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Logistics Company Carrier Partner
2.O.15 Too I: ^^^M^
Technical Documentation^^^H^
2015 Data Year - United States Version
&EPA
United States
Environmental Protection
Agency
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Transport Partnership
U.S. ENVIRONMENTAL PROTECTION AGENCY
Logistics Company Carrier Partner
2.o.l5Tool:
Technical Documentation ^ ^
2015 Data Year - United States Version
Transportation and Climate Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
United States Office ofTransportation and Air Quality
Environmental Protection EPA-420-B-16-066
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SmartWay2.0.15
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 ton-
mile 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.
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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
Carrier 1
Carrier 2
CO2 g/mi
1,700
1,500
Mi/vr
2,000,000
1,000,000
Weighting Factor
0.667
0.333
Weighted composite g/mi
Weighted COz g/mi
1,134(0.667x1,700)
500(0.333x1,500)
1,633(1,134 + 500)
This compositing process proceeds in an identical fashion for ton-miles.
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 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
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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 C02, 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.
3
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• 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
TL
LTL
PD
Expedited
Dray
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto Carrier
Moving
Specialized
Private
TL
LTL
PD
Expedited
Dray
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto Carrier
Moving
Specialized
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
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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
TL
LTL
PD
Expedited
Dray
Dry Van
Reefer
Flatbed
Tanker
Chassis
Heavy/Bulk
Auto Carrier
Moving
Specialized
To be categorized in a particular category, a fleet must have at least 75% of its
operations by mileage in a single category, otherwise it is classified as a "Mixed" fleet.
Fleets 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.
TL
LTL
PD
Expedited
Dray
Mixed
Dry
Van
•
Reefer
Flatbed
Tanker
Chassis
Heavy
/Bulk
Auto
Carrier
Moving
Specialized
Mixed
SmartWay then looked at combining categories that exhibited similar characteristics for
simplification purposes. One prerequisite was that there needed to be a minimum
number of fleets in each category. SmartWay determined that a category needed a
minimum of 25 fleets to be created. It was also determined that dry van and chassis
(intermodal container) functioned primarily as dry van transport, so these categories
were combined. While most refrigerated carriers were truckload, a few less than
truckload refrigerated fleets exist, so these 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
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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
Heavy/
Reefer I Flatbed I Tanker I Bulk
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: C02 g/mile, C02 g/ton-
mile, 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 outpoints (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 outpoints remained as close to the originals as possible. The new
range outpoint is displayed as a number with significant digits appropriate to emission
factors in that category. The midpoint of the range is used as the emission factor for all
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 CCte), 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.
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Table 2. Example Binning Results for One Ranking Category (2010 Data)
For-H ire/Private Truckload/Ex
Rank
1
2
3
4
5
Fleets
159
241
204
139
55
Grams Per
Mile Min
602
1,601
1,700
1,800
1,900
Grams Per
Mile Max
1,600
1,699
1,799
1,899
3,701
pedited Dry Van/Container CO2 g/mile
Grams Per
Mile Avg
1,503
1,654
1,746
1,853
2,064
Grams Per Mile
Midpoint
1,550
1,650
1,750
1,850
2,801
Grams Per
Mile Std Dev
141
28
28
28
302
Similar tables 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 (m in/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 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
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.
7
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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 C02 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 C02 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 PMio were based
on the ratio of these pollutants to C02 from the EDMS 5.1.4.1 model (0.009 for NOx and
0.000059 for PMio).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-Nunez, 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. Baurn, S. Brunner, P. Eickemeier, B.
Kriemann, J. Savolainen, S. Schlomer, 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^ts/acts/customized/table?adfy=2012&adfm=l&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 Ibs) and Large (Max Takeoff Weight 41,001 to 255,000 Ibs) weight classes.
8
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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
Short-haul
Long-haul
COz/tmi
4,236
1,461
COz/mi
96,998
33,448
NOx/mi
873.2713
301.1280
NOx/tmi
38.1341
13.1497
PM/mi
5.743247
1.980430
PM/tmi
0.250797
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 C02 factor (10,084
g C02/gal diesel fuel), from publicly available data submitted in the 2010 railroad R-1
reports to the Department of Transportation. 2010 R-1 data was also used to obtain
total railcar-miles per year for 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 C02 performance data are
presented in Table 4 below.
Table 4. Rail Carrier Performance Metric Calculation Inputs and Results (2010 R-1
Data)
Rail Company
BNSF Railway
CSX Transportation
Grand Trunk
Kansas City Southern
Norfolk Southern*
Soo Line
Union Pacific
Total - Industry
Average
Gal/Yr
('OOO)Sch.
750 Line 4
1,295,147
490,050
88,290
62,354
440,159
65,530
1,063,201
3,504,731
Freight Ton-
Mi/Yr('000)
Sch .755 line
110
646,549,059
230,507,431
50,586,328
31,025,588
183,104,320
33,473,544
525,297,747
1,700,544,017
Railcar-Mi/Yr
('000) Sch.
755 sum of
lines 30, 46,
64&S2
11,230,994
4,720,293
1,206,818
609,929
4,081,893
771,033
10,336,081
32,957,041
g CO2/railcar-
mile
1,163
1,047
738
1,031
1,087
857
1,037
1,072
g CO2/short
ton-mile
20.20
21.44
17.60
20.76
24.24
19.74
20.41
20.78
: and combined subsidiaries
9 http://www.airgroup.com/standalone.php7actioiFair spec
9
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NOx and PM emission factors for rail carriers are based on industry averages. The
freight rail gNOx/ton-mile and gPIVh.s/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
201 Demission 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 PMio/gal and g NOx/gal factors from Tables 5 and 6, respectively, in EPA's 2009
Technical Highlights: Emissions Factors for Locomotives^2. To calculate g PlVh.s/gal,
we assumed 95% of PMio is PlVh.s, which we determined was a good approximation of
the share of overall PMio 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
gram/short ton-mile
gram/truck-equivalent mile
gram/TEU-mile
NOx
0.4270
13.19
4.745
PM2.5
0.0120
0.3569
0.1284
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Table 6. Underlying Emissions Inventories and Activity Data for Illustrative U.S.
Freight Rail Industry Average Factors
short ton-miles
Class l-only railcar miles (total)
50' and Larger Box Plain + Box Equipped
40' Box Plain
Flat TOFC/COFC, General, and Other
Flat Multi Level
Gondola Plain and Equipped
Refrigerated Mechanical and Non-Mechanical
Open Top Hopper General and Special Service
Covered Hopper
Tank under 22,000 gallons
Tank 22,000 gallons and over
All Other Car Types
1,819,633,000,000
34,611,843,000
2,223,402,000
22,000
5,057,466,000
1,725,998,000
7,893,684,000
495,311,000
5,913,012,000
7,210,656,000
1,295,482,000
2,394,565,000
402,245,000
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 7. Rail Carrier Average Payload
Carrier
BNSF Railway
CSX Transportation
Grand Trunk
Kansas City Southern
Norfolk Southern
Soo Line
Union Pacific
Industry Average
Avg Payload/Loaded
Railcar (tons)
108
85
80
91
76
77
91
93
Average railcar volumes were calculated for all carriers by first estimating an average
volume for each major railcar type listed in the R-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
11
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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 (IMS)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 types-
including 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.co m/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. co m/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
12
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Railcar Type
Cubic
Feet
Source/Method
Key: Norfolk Southern Railroad (IMS)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 /non-
Mechanical
6,202
Based on the average of the following refrigerated car types:
48-72ft assumed to be 6963 [based on average of 6043 (UP) and 7883
(BNSF)].
50ft assumed to be 5167(GTRC).
40-90 ft. assumed to be 6476 [based on average of 6952 (UP) and 6000
(BNSF)].
Open Top Hopper
4,220
Based on the average of the following open top hopper car types:
42ft assumed to be 3000 (UP).
54ft assumed to be 3700 (UP).
60ft assumed to be 5188 [based on average of 5125 (UP) and 5250 (GTRC)].
45ft+ assumed to be 4105 [based on average of 4500 (UP) and 3710 (BNSF).
Woodchip assumed to be 7075 [based on average of 7525 (NS), 5999 (UP),
and 7700 (CRCL)].
Small Aggregate assumed to be 2252 [based on average of 2150 (NS), 2106
(BNSF), and 2500 (CRCL)].
Covered Hopper
4,188
Based on the average of the following covered top hopper car types:
45ft assumed to be 5250 (GTRC).
Aggregate assumed to be 2575 [based on average of 2150 (NS) and 3000
(CRCL)].
Small Cube Gravel assumed to be 2939 [based on average of 2655 (NS),
3100 (CSX), and 3063 (BNSF).
Med-Large Cube Ores and Sand assumed to be 4169 [based on average of
3750 (NS) and 4589 (BNSF)].
Jumbo assumed to be 5147 [based on average of 4875 (NS), 4462 (CSX),
5175 (BNSF), and 6075 (CRCL)].
Pressure Differential (flour) assumed to be 5050 [based on average of 5124
(NS) and 4975 (CRCL)].
Tank Cars under
22,000 gallons
2,314
Assumes 1 gallon=0.1337 cubic foot (USDA).
Based on small tank car average volume of 17304 gallons, which is the
average of the following currently manufactured tank car volume design
capacities of 13470, 13710, 15100, 15960, 16410,17300,,19900, 20000,
20590, and 20610 gallons (GTRC).
Tank Cars over 22,000
gallons
3,857
Assumes 1 gallon=0.1337 (USDA).
Based on large tank car volume of 28851 gallons, which is the average of the
following currently manufactured tank car volume design capacities of 23470,
25790, 27200, 28700, 30000, 33000, and 33800 gallons (GTRC).
All Other Cars
5,014
Based on average volume presented above for each of the nine railcar types
(all flatcars are represented by the line item that includes multi-level flatcars -
7428).
13
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Table 9. Rail Carrier Average Volume Determination
Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Avg. Cu Ft.
4,555
7,177
7,177
5,190
5,190
4,188
4,220
4,220
6,202
6,202
6,395
13,625
6,395
6,395
5,772
BNSF
Railcar Miles (xlK)
1
9,338
147,226
379,762
75,894
758,442
65,077
137,449
19,272
32,910
520,521
38,624
357
71,826
20,146
Cu Ft Miles (xlK)
4,555
67,018,826
1,056,641,002
1,970,964,780
393,889,860
3,176,355,096
274,624,940
580,034,780
119,524,944
204,107,820
3,328,731,795
526,252,000
2,283,015
459,327,270
116,282,712
5,811
14
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
CSX
Railcar Miles (xlK)
6,987
144,631
137,256
64,532
153,315
78,412
35,451
17,117
11,923
125,828
29,956
162
31,913
19,861
Cu Ft Miles (xlK)
50,145,699
1,038,016,687
712,358,640
334,921,080
642,083,220
330,898,640
149,603,220
106,159,634
73,946,446
804,670,060
408,150,500
1,035,990
204,083,635
114,637,692
6,389
15
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Grand Trunk
Railcar Miles (xlK)
0
2,119
66,110
6,467
19,201
44,239
9,114
32,621
312
205
2,779
4,831
20
31,744
4,755
Cu Ft Miles (xlK)
15,208,063
474,471,470
33,563,730
99,653,190
185,272,932
38,461,080
137,660,620
1,935,024
1,271,410
17,771,705
65,822,375
127,900
203,002,880
27,445,860
6,309
16
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Kansas City Southern
Railcar Miles (xlK)
0
3,383
39,792
16,628
11,150
50,346
626
943
21
52
10,736
629
12
2,321
247
Cu Ft Miles (xlK)
24,279,791
285,587,184
86,299,320
57,868,500
210,849,048
2,641,720
3,979,460
130,242
322,504
68,656,720
8,570,125
76,740
14,842,795
1,425,684
5,938
17
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Norfolk Southern
Railcar Miles (xlK)
0
7,622
136,745
193,214
111,320
116,848
84,557
30,078
3,512
5,392
114,928
20,349
145
24,563
212,408
Cu Ft Miles (xlK)
54,703,094
981,418,865
1,002,780,660
577,750,800
489,359,424
356,830,540
126,929,160
21,781,424
33,441,184
734,964,560
277,255,125
927,275
157,080,385
1,226,018,976
6,065
18
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Soo Line
Railcar Miles (xlK)
0
725
17,972
1,203
8,856
94,146
3,077
20
159
742
11,178
2,973
12
10,068
428
Cu Ft Miles (xlK)
5,203,325
128,985,044
6,243,570
45,962,640
394,283,448
12,984,940
84,400
986,118
4,601,884
71,483,310
40,507,125
76,740
64,384,860
2,470,416
5,667
19
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Union Pacific
Railcar Miles (xlK)
0
12,311
238,241
206,370
91,775
370,929
188,027
104,969
82,874
27,009
1,026,251
46,889
350
72,371
16,769
Cu Ft Miles (xlK)
88,356,047
1,709,855,657
1,071,060,300
476,312,250
1,553,450,652
793,473,940
442,969,180
513,984,548
167,509,818
6,562,875,145
638,862,625
2,238,250
462,812,545
96,790,668
6,248
20
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Freight Car Types (Rl - Schedule 755)
Box-Plain 40-Foot
Box-Plain 50-Foot & Longer
Box-Equipped
Gondola-Plain
Gondola-Equipped
Hopper-Covered
Hopper-Open Top-General Service
Hopper-Open Top-Special Service
Refrigerator-Mechanical
Refrigerator-Non-Mechanical
Flat-TOFC/COFC
Flat-Multi-Level
Flat-General Service
Flat-All Other
All Other Car Types-Total
Average Railcar Cubic Feet
Total (for Industry Average)
Railcar Miles (xlK)
1
42,485
790,717
940,900
382,728
1,588,265
428,890
341,531
123,267
78,233
1,812,221
144,251
1,058
244,806
274,614
Cu Ft Miles (xlK)
4,555
304,914,845
5,674,975,909
4,883,271,000
1,986,358,320
6,651,653,820
1,809,915,800
1,441,260,820
764,501,934
485,201,066
11,589,153,295
1,965,419,875
6,765,910
1,565,534,370
1,585,072,008
6,091
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
21
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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 outpoints were set with the intention of identifying those payloads
that are somewhat outside typical industry values (yellow flag warnings) and those that
are far outside industry averages (red flag warnings). 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.
22
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Table 10. Truck Carrier Payload Validation Ranges
Truck Bin Category
LTL Dry Van (from Dry Van
Single - LTL-Moving-
Package)21
Package (from Dry Van
Single - LTL-Moving-
Package)22
TL Dry Van (from Dry Van
Single - other bins)
Refrigerated
Flatbed
Tanker
Moving (from Dry Van
Single - LTL-Moving-
Package)
Specialized (from Specialty -
Other bins)
Dray (from Chassis)
Auto Carrier
Heavy-Bulk
Utility (from Specialty -
Other bins)
Mixed (from Other - Heavy-
Flatbed-Mixed bins)
Expedited (from Dry Van
Single - other bins)
Range
1 Low
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Range
1 High
12 Low
0.0
0.0
10.5
14.5
14.0
19.1
6.9
20.2
11.2
5.7
2.7
20.2
14.7
10.5
Range
2 High
/3Low
0.0
0.0
14.5
17.3
18.3
22.0
11.0
22.9
16.5
11.0
16.5
22.9
21.1
14.5
Range
3 High
14 Low
13.5
13.5
22.4
22.9
26.7
27.8
19.1
28.3
27.1
21.4
44.0
28.3
33.8
22.4
Range
4 High
/5 Low
20.8
20.8
26.4
25.7
31.0
30.7
23.2
31.1
32.4
26.6
57.8
31.1
40.1
26.4
Range
5 High
(Max)
150.0
150.0
150.0
82.5
99.9
103.8
83.7
111.0
73.5
73.5
120.0
111.0
99.3
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).
23
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Figure 1. Logistics Partner Payload Distribution
Cumulative Payload Distribution - 2011 Logistics
0.9
10
20
30
40 50 60
Short Tons
70
80
90
100
As can be seen in the figure, the payload distribution is highly non-normal, so use of
validation cutoffs based on standard deviation is not appropriate. However, rough
inflection points appear at approximately 10%, 20%, 80%, and 90%. As such, these
values were used to specify the following payload validation cutoffs for logistics carriers.
• Range 1 Red: 0-12.0 tons
• Range 2 Yellow: 12.0-16.7 tons
• Range 3: 16.7-21.0 tons
• Range 4 Yellow: 21.0-27.2 tons
• Range 5 Red: 27.2 - 150 tons (150 absolute max)
Validation levels for rail and multi-modal carriers are summarized below. The upper
bound outpoints for multi-modal payloads are based on a qualitative review of 2011
multi-modal carrier tool submittals. The upper bound outpoints for rail payloads are
based on the distribution of average values estimated for Class 1 carriers (see Table 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)
24
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In addition, the absolute upper bound for rail and multi-modal carriers have both been
set at 200 tons.
Finally, any payload value less than or equal to zero will be flagged as an error and
must be changed.
Ton-Mile Validation
2011 Logistics Partner data was evaluated to establish absolute upper bounds for ton-
mile inputs. The ton-mile validation applies at the carrier (row) and total fleet
(summation of rows) level, with the same values applied to both. The maximum
allowable ton-mile value was set to twice the observed maximum value in the 2011 data
set: 209,207,446,000 ton-miles.
25
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