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# DRAFT
ERTAC Rail Emissions Inventory Part 2: Class I Railyard Switcher Locomotives

Michelle Bergin, GA Environmental Protection Divisi on Matthew Harrell, IL Environmental Protection Agency Mark Janssen, Lake Michigan Air Directors Consortiu m

Acknowledments: Robert Fronczak, Association of Ame rican Railroads Laurel Driver, US EPA, Office of Air Quality Plann ing and Support Byeong Kim, GA Environmental Protection Division

Introduction

Air protection agencies from twenty-seven states, c oordinated through the Eastern Regional Technical Advisory Committee (ERTAC) and headed by the Lake M ichigan Air Directors Consortium (LADCO), identified a need to better quantify and characteri ze rail-related emissions inventories. Traditional locomotives largely utilize diesel engines, resulti ng in emissions of NO

x , diesel PM, hydrocarbons, greenhouse gases, and other pollutants. These emis sions are sometimes concentrated in areas exceeding National Ambient Air Quality Standards. No cohesiv e nationwide railroad emission estimates are known to have been made previously. Inventory deve lopment methods for locomotive emissions estimates vary from state to state and, in general, lack the spatial or temporal resolution needed to support air quality modeling and planning 1-5

.

The ERTAC Rail Subcommittee (ERTAC Rail) was establ ished with active representatives from twelve member states, three regional planning offices, and the US EPA. The subcommittee’s goals are to (1 ) standardize agencies’ inventory development methods through a collaborative effort, (2) improve the quality of data received and the resulting emission inventories, and (3) reduce the administrative bur den on railroad companies of providing data. With supp ort from the Rail industry and assistance from the ERTAC Rail Data Workgroup (Appendix A), ERTAC Rail has developed 3 inventories of locomotive emissions for Class I line-haul, Shortline and Regi onal Railroads, and Class I railyard switchers (Tab le 1). Because of the difficulty in obtaining data an d differences in states’ needs for inventory years, sources from both 2007 and 2008 were utilized (Appe ndix B.)

The Surface Transportation Board (STB) defines Clas s I Railroads as having had minimum carrier operating revenues of $401.4 million (USD) in 2008. There are 8 Class I Railroads operating in the United States (Table 2), about 33 Regional Railroad s (Class II), and approximately 540 Class III Railroads (Shortlines). While categorized as a Clas s I Railroad, Amtrak was excluded from these inventories because of significant differences in e quipment and operational characteristics. Line-hau l locomotives travel long distances (e.g. between cit ies) while switcher locomotives largely operate in railyards, splitting and joining rail cars with var ying destinations. Passenger and Commuter Rail (including Amtrak), industrial locomotives, and ass ociated non-locomotive equipment are not included

in these inventories.2

Table 1. Summary of ERTAC Rail Inventories: U.S. Lo comotive Emissions and Fuel Use for
either 2007 or 2008*. Fuel Use** (gal/yr) Emissions (tons/yr)

NO

x PM 2.5 HC SO 2 CO NH 3 CO 2 Class I***

line-haul 3,770,914,002 754,443 23,439 37,941 7,836 110,969 347 42,305k

Class I

switcher 301,046,290 74,431 2,042 4,867 624 9,230 28 3,367k

Class II

and III 157,800,000 47,035 1,065 1,737 327 4,631 14 1,765k

*See Appendix B for a description of the year and s ource of data utilized for each inventory. **Locomotive grade diesel ***Excluding Amtrak and including work train fuel u se

Table 2. Class I Railroads and Reported Locomotive Fuel Use 6

.

Class I Railroads* R-1 Reported Locomotive Fuel Use (gal/yr)

Line-Haul (2007)** Switcher

(2008) BNSF 1,393,874,954 52,497,057 Canadian National 93,830,751 12,290,022 Canadian Pacific ***50,320,233 4,937,067 CSX 514,687,186 53,717,674 Kansas City Southern 69,787,071 1,816,759 Norfolk Southern 463,267,278 32,317,375 Union Pacific 1,185,146,529 143,470,336 Total 3,770,914,002 301,046,290 * Excluding Amtrak

** Includes work trains

*** CP’s line-haul fuel use values include 2008 dat a (rather than 2007) for their Delaware and Hudson subsidiary.

This paper documents the data sources and methodolo gies used for calculating the Class I switcher (“Railyard”) inventory. Information on ERTAC Rail, Railroad participation, the Rail industry, and effects of rail on air quality are available elsewh ere 7

.

Method

Switcher locomotives are expected to be the single largest source of air emissions in railyards. Therefore, as a starting point for a comprehensive railyard inventory, a Class I switcher emission inventory was developed. It is assumed that estima tes for yards of interest, associated equipment and activity, and smaller railroads could be refined la ter.

While ERTAC Rail represents states east of the Miss issippi River, the railroad companies specified the y wanted this effort to result in a consistent nation wide inventory. ERTAC Rail agreed to calculate

emissions for all states when the data was availabl e and when additional significant effort was not3

required. Because both the dataset of railyards an d switcher fuel use was nationwide in scope, the resulting initial railyard inventory is a nationwid e, ‘top-down’ derivation. However, railroad compan ies may have different levels and quality of data avail able, and may have interpreted some data requests differently. Also, states are requested to update yards they have detailed information on when possib le, and a few states (i.e. California) have unique rail road operations and equipment. Therefore, data for some areas will be more accurate than for others, a nd locally-derived inventories may be more accurate

.

This documentation describes development of the ini tial top-down inventory, which consisted of three

main activities: 1. Locate Class I Railyards

2. Select/Calculate Emission Factors 3. Estimate Locomotive Activity 4. Improve Estimates

1. Locate Class I Railyards.

Identification and correct placement of railyards w as an important first step, requiring a comprehensi ve electronic dataset. A confidential database was obt ained from the Federal Railroad Administration (FRA) with permission from the Class I Railroads (F RA database) 8 . A comparable public database compiled by the Bureau of Transportation Statistics is also available 8 . Data from the public source will

not match the confidential data used for this inven tory exactly but will be very similar. The FRA database has rail links (track lengths) individuall y identified as parts of specific railyards. While there may be discrepancies in how each railroad defined r ailyard links, this dataset appears to identify mos t Class I railyards in the U.S., and shows a high den sity of yards in the eastern states (Figure 1). T he database gives length, up to 3 owners and 3 operato rs, and a Federal Density Code (explained below) fo r each railyard link.

Figure 1. Class I Railyards in the United States a nd estimates of Annual NOx emissions from switcher locomotives (tons/yr in 2008).4

2. Select/Calculate Emission Factors.

The EPA provides annual default emission factors ba sed on characteristic operating cycles (‘duty cycles’) and an annual estimated nationwide fleet m ix for both switcher and line-haul locomotives (i.e

. percent of locomotives in each Tier level category) . However, switcher fleet mix is not uniform from company to company and, as can be seen in Figure 2, Class I railroad activity is highly regional.

As an alternative approach, ERTAC Rail requested ea ch Class I rail company to provide a description of their switcher fleet mix based on Tier rating, whic h each company provided under a confidentiality agreement. An engine’s Tier level determines allow able emission limits based on the year the engine was built and/or re-manufactured (Table 3). While engine emissions are variable within Tier categorie s, this estimate likely provides a better regional est imate than the nationwide average. The companyspecific systemwide fleet mix was used to calculate weighted average emissions factors for switchers operated by each Class I railroad, resulting in ran ges between fleet emission factors such as from 6.1 0 to 6.69 g/gal PM 10 and 212.98 to 264.48 g/gal NO

x .

Figure 2. Class I Railroad Territories in the Unit ed States 9

.

Table 3. EPA switcher locomotive emission factors by Tier, 1997 standards (grams/gal).

PM 10 HC NO

x CO Uncontrolled (pre-1973) 6.688 15.352 264.48 27.816 Tier 0 (1973-2001) 6.688 15.352 191.52 27.8165

Tier 1 (2002-2004) 6.536 15.352 150.48 27.816 Tier 2 (2005 + ) 2.888 7.752 110.96 27.816
Listed years apply to the year the engine was built . Table based on values from 8 . Note that the new standards released in 2008 did not apply to existing fleets in the year 2 008.

For locomotives, PM 2.5 is assumed to be 97% of PM 10 10 , and emission factors for SO 2 and NH 3 are 1.88 g/gal 10 and 83.3 mg/gal 11 respectively. VOC emissions are calculated as 1.0 53 times the HC emissions

for locomotives 12

. Note that non-road engine and fuel specific informa tion is sparse for these conversions. Greenhouse gases are also estimated u sing emission factors shown in Table 4.

Table 4. EPA greenhouse gas emission factors for l ocomotive diesel fuel (grams/gal). 13

CO 2 N 2 O CH 4 Locomotive diesel 1.015E4 0.26 0.80

These emission factors are based on a characteristi c duty cycle for switchers which assumes operation over 24-hour per day 365 days per year. An evaluat ion of the effect of variability in railyards and switching duties on emissions would be very useful for future emission estimates.

3. Estimate Locomotive Activity.

Class I railroads report total annual switcher loco motive fuel use to the STB, which is reported in publicly available ‘R-1’ reports (Table 2). There may be inconsistencies between railroads in how fue l use is estimated to be apportioned between line-hau l and switcher locomotive use, and possibly even in the total locomotive fuel use, so these values shou ld be evaluated and may be adjusted in the future. However, the use of these values provides a startin g point for estimating total U.S. Class I locomotiv erelated emissions segregated and spatially allocate d by Class I carrier. The R-1 reports were used by

ERTAC for both the line-haul and switcher locomotiv e emissions inventories to provide consistency.

The next step for inventory development is to alloc ate switcher fuel use to each railyard. Two methods were first applied, one that relies on publicly ava ilable line-haul activity (the ‘Dencode’ method), a nd the other using confidential line-haul activity (th e ‘MGT’ method.) At this time, Norfolk Southern an d Kansas City Southern have provided input for use of the MGT method, and the Dencode method is applied for the other five railroads.

The Dencode Method – Publicly available data

Each link in both the publicly available BTS databa se and the confidential FRA database has a ‘Federal Density Code’ (Dencode) ranging from 1 to 7 assigne d based on the cumulative annual freight tonnage hauled on the link (track). Total Switcher Fuel Us e in each railyard Y (SFU Y ) is estimated as follows:

First a Switcher Activity Indicator per yard (SAI Y ) is calculated by multiplying the average dencode of the links within a railyard by the sum of the lengt h of the links for that railyard (Eqn 1).

SAI Y = )

* ( nY nY FDC l 

## ∑ Equation 1

SAI Y = Switcher Activity Indicator in Railyard Y6

n Y = number of links identified as part of railyard Y

l nY = length of link n in miles

FDC
n = Federal Density Code (1 to 7) of link n

Next, this value is then weighted (SAI Y ’) based on an ownership factor (OF) set between 0 and 1. The OF depends on the number of owners listed for each railyard: if there is one owner the OF is set to 1 , if there are two owners the primary owner is set to 0. 8 and the secondary is 0.2, and if there are 3 owne rs the primary is 0.7, the secondary is 0.2, and the t ertiary is 0.1.

SAI Y ’ = OF Y * SAI Y Equation 2

Next, the SAI Y ’ of all railyards belonging to a Class I railroad (RR) were summed, and the fraction of the railroads total SAI associated with each railya rd was multiplied by the railroads total annual swi tcher fuel use reported in the R-1 (TFU RR ), resulting in the total Switcher Fuel Use for eac h railyard Y (Eqn 2).

SFU Y = RR

RR Y Y TFU SAI SAI
*

' ' 

# ∑ Equation 3

SFU Y = Switcher Fuel Use at railyard Y

Finally, the SFU Y is multiplied by the emission factors described in the previous section to obtain annual switcher emissions at each railyard.

The MGT Method – Confidential data

Two railroads, Norfolk Southern and Kansas City Sou thern (KCS), provided confidential link-level tonnage information and weighting factors to correc t skewed estimates to improve estimated switcher activity at important yards. Other railroads may a lso allow the use of this technique for their inven tories in the future. In addition, KCS provided yard-spec ific activity information.

The MGT Method also uses the FRA database for raily ard identification and link lengths. However, rather than using the average dencode per link, con fidential annual gross tonnage (MGT) hauled per lin k in the railyard was used to calculate the railyard switcher activity (SAI Y ). This is calculated by replacing FDC

n in Equation 2 with link-specific tonnage MGT

n (Equation 4).

SAI Y = )

* ( nY nY MGT l 

# ∑ Equation 4

SAI Y = Switcher Activity Indicator in Railyard Y

n Y = number of links identified as part of railyard Y

l nY = length of link n in miles

MGT nY = million gross tons on link n7

This method provides a more refined comparison betw een railyards than the use of the 7-category dencodes; however, is more susceptible to errors fo r yards where tonnage is not correlated to switchin g activity. For example, a yard with large coal trai ns pulling through used for crews to change over wo uld be assigned an overly high level of emissions for s witching activity. To account for this, a discreti onary Switching Activity Factor (SAF) was introduced to a llow railroads to roughly weight yards with clearly higher or lower levels of switching activity than w hat results from the mathematical allocation. Therefore, SAI Y is weighted based on both the ownership factor (OF ) as well as the SAF (Equation 5). For example, a yard used for crew changes and not s witching may have an SAF of 0, while a yard at a major interchange between cities may have an SAF of 3.

SAI Y ’ = OF Y *SAF Y * SAI Y Equation 5

Again, the SAI Y ’ of all railyards belonging to a Class I railroad (RR) are summed, and the fraction of the railroads total SAI associated with each railyard w as multiplied by the railroads total annual switche r fuel use reported in the R-1 (TFU RR ), resulting in the total Switcher Fuel Use for eac h railyard Y (Equation 6).

SFU Y = RR

RR Y Y TFU SAI SAI
*

' ' 

# ∑ Equation 6

While the SAF allows estimates of yard-specific emi ssions to be adjusted, the total level of emissions for each railroad, which is based on systemwide fue l use and systemwide emission factors, remains unchanged. The MGT method SFU Y is also later multiplied by the emission factors d escribed in the previous section to obtain annual switcher emission s at each railyard.

4. Improve estimates.

In addition to the Switching Activity Factor descri bed above, direct input was also used to improve emission estimates for important railyards. Each C lass I railroad provided an estimate of annual aver age switcher fuel use (generally much lower than the EP A default of 82,490 gal/yr) as well as the name, location, and number of operating switchers for rai lyards with 8 or more switchers operating in ozone or PM 2.5 nonattainment areas. Some railroads, Kansas City S outhern in particular, then provided additional railyard specific data. This directly reported dat a was used to overwrite the dencode or MGT derived emissions estimates for those railyards.

The difference in estimated fuel use for those rail yards was re-allocated (added or removed) between t he remaining railyards belonging to that Class I railr oad. It is important to note that there are some discrepancies in how this data was reported for the large railyards by each railroad. For example, so me railroads reported all switchers located at a raily ard while others reported ‘full time equivalent’ switchers, meaning the number of switchers normaliz ed to a full working cycle (24-hours per day yearround.) This process should be standardized for fu ture inventory versions. Variability is also introd uced

because ‘switcher’ locomotives can also be used for ‘road work’, meaning they occasionally work between yards more like a line-haul.

States also have the option of updating specific ra ilyard emissions estimates. Because this inventory is derived ‘top-down’, local studies and familiarity w ith specific railyards is expected to provide bette r8

estimates, which can be used to adjust this invento ry. Care must be taken to ensure the other railyar d estimates are adjusted to account for increases or decreases in estimated fuel use per yard.

Limitations, Conclusions, and Future Work

What this ERTAC Rail railyard inventory does well i s provide a comprehensive overview of where railyards are, who owns them, and gives a geographi cal allocation of switcher emissions bounded by what is reported as nationwide switcher fuel usage by the Class I railroads. These sources can be important for air quality management in nonattainme nt areas, as well as in regional analysis and for future transportation and freight planning. This i nventory will be useful for regional and some local modeling, helps identify where railyards need to be better characterized, and provides a strong foundation for future development of a meaningful n ationwide Class I switcher emissions inventory.

There are important uncertainties associated with e stimates from this method, including, but not limit ed to, the use of tonnage hauled as an indicator of th e amount of switching activity, and, for a few of t he railroads, how the amount of switcher fuel use was determined to be reported in the R-1. The R-1 reported values are currently under examination.

There is also likely significant variability in act ual switching duty-cycles and, potentially, in the number of switchers operating at some railyards at differe nt times of the year. ‘Road-switching’, or the use of what are considered switching locomotives to move b etween nearby yards, should be addressed in either this or the ERTAC line-haul inventory.

It must be noted that freight-related rail activity is not always routine and no annual emissions inve ntory will ever be able to capture the innate variability of the source. However, as other large emission sources are reduced, and if rail activity increases as expected, it is important to include our best estimates of these sources in air quality and epide miological analysis. In the future, on-line data l oggers and other tracking technologies, combined with ambi ent studies and detailed modeling, will hopefully provide more insight to the emissions of locomotive s and other railyard sources.

References

1. E.H. Pechan & Associates, Inc., “Documentation for Aircraft, Commercial Marine Vessel, Locomotive, and Other Nonroad Components of the Nat ional Emissions Inventory, Volume I – Methodology”; EPA Contract No.: 68-D-02-063. Prepar ed for the US EPA Emissions, Monitoring and Analysis Division, Sept. 30, 2005. ftp://ftp.epa.gov/EmisInventory/2002finalnei/docume ntation/mobile/2002nei_mobile_nonroad_ methods.pdf . Related documents at ftp://ftp.epa.gov/EmisInventory/2002finalnei/docume ntation/mobile/2002nei_mobile_nonroad_tr ain.pdf

2. Sierra Research, Inc., “Revised Inventory Guidan ce For Locomotive Emissions”; Report No. SR2004-06-01. Prepared for Southeastern States Air Resource Managers (SESARM), June 2004. http://www.metro4-sesarm.org/pubs/railroad/FinalGui dance.pdf

3. Sierra Research, Inc., “Research Project: Devel opment of Railroad Emission Inventory Methodologies”; Report No. SR2004-06-02. Prepared f or Southeastern States Air Resource9

Managers (SESARM), June 2004. http://www.metro4- sesarm.org/pubs/railroad/FinalMethodologies.pdf

4. Environ, “Draft LADCO 2005 Locomotive Emissions”. P repared for Lake Michigan Air Director Consortium, Feb 2007. http://www.ladco.org/reports/technical_support_docu ment/references/ladco_2005_locomotive_e missions.021406.pdf

5. Southern Research Institute, “NYSERDA Clean Diesel Technology: Non-Road Field Demonstration Program, Development of the 2002 Loco motive Survey for New York State”; Agreement Number 8958. Prepared for the New York St ate Energy Research And Development Authority (NYSERDA), Feb. 09, 2007. http://www.nyserda.org/publications/LocomotiveSurve yReportwithAppendices.pdf

6. Surface Transportation Board R-1 Reports, available at: http://www.stb.dot.gov/stb/industry/econ_reports.ht ml

.
7. M. Bergin; M. Harrell; J. McDill; M. Janssen; L. Dr iver; R. Fronczak; R. Nath,; and D. Seep. "ERTAC Rail: A Collaborative Effort in Building a R ailroad-Related Emissions Inventory Between Eastern States Air Protection Agencies and Participation with the Railroad Industry," 18th Annual International Emission Inventory Confer ence. Baltimore, MD. April 14 - 17, 2009. Paper and presentation available at: http://www.epa.gov/ttn/chief/conference/ei18/sessio n6/bergin.pdf

8. Confidential database was provided with assistance from Raquel Wright of the Federal Railroad Administration. Similar public data is available f rom the Bureau of Transportation Statistics in the NTAD 2009 shapefile data (data is representativ e for the year 2007): http://www.bts.gov/publications/national_transporta tion_atlas_database/2009

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9. Freight Railroads in the United States 2008. Assoc iation of American Railroads. Available at: http://www.aar.org/~/media/AAR/InCongress_Railroads States/2008unitedstates.ashx

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10. EPA Technical Highlights: Emission Factors for Loc omotives, EPA Office of Transportation and Air Quality, EPA-420-F-09-025, April 2009. http://www.epa.gov/otaq/regs/nonroad/locomotv/420f0 9025.pdf

11. Estimating Ammonia Emissions From Anthropogenic Non agricultural Sources - Draft Final Report by E.H. Pechan & Assoc. April 2004. Prepare d for EPA/STAPPA-ALAPCO Emission Inventory Improvement Program. Supported by persona l communication (5/6/2010) with Craig Harvey, US EPA, OTAQ, and Robert Wooten, NC DENR. http://www.epa.gov/ttnchie1/eiip/techreport/volume0 3/eiip_areasourcesnh3.pdf

12. “Conversion Factors for Hydrocarbon Emission Compon ents,” EPA420-R-05-015, December

2005. Docket Document EPA-HQ-OAR-2003-0190-0411. http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2005/42 0r05015.pdf

, http://www.epa.gov/otaq/regs/nonroad/420r08001a.pdf

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13. U.S. Environmental Protection Agency. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990- 2005, EPA 430-R-07-002, Annex 3.2, (April 2007), we b site: http://www.epa.gov/climatechange/emissions/usinvent oryreport.html10

Appendix A: ERTAC Rail Data Workgroup

REPRESENTATIVE ORGANIZATION

Matt Harrell IL EPA Michelle Bergin (Co-Chair) and Byeong Kim GA EPD Mark Janssen (Co-Chair) LADCO

Julie McDill and Patrick Davis MARAMA Laurel Driver US EPA OAQPS

Robert Fronczak AAR

Steven Sullivan ASLRRA

Rick Nath CSX David Seep and Lyle Staley BNSF Ken Roberge CPR

Carl Akins and Peter Conlon KCS

Erika Akkerman CN

M. John Germer UP

Brent Mason and Richard Russell NS

Joanne Maxwell Amtrak

Appendix B: Source and Year of Data Utilized for E ach Inventory

Data 

### Year Source



### Class I Line-Haul

Annual Line-Haul Fuel Use

and Gross Ton-Miles 2007 STB R-1 Reports (CP data for D&H is for 2008.)

Line-haul fleet mix for

emission factors 2008 Each Class I railroad

Link-level tonnage 2007 FRA confidential database

Class I Railyards (Switcher Locomotives)

Annual Switcher Fuel Use 2008 R-1 Reports

Switcher fleet mix for

emission factors 2008 Each Class I railroad

Link-level tonnage or Density Code (for activity estimate) 2007 FRA confidential database

Class II and III Locomotives

Annual Total Fuel Use 2008 ASLRRA Annual Report (20 08)

Track length and railroad 2007 FRA confidential dat abase

Estimated fleet mix for

emission factors Discussions with ASLRRA and Class II and III representatives.