International Corporation 

### Air Sciences

(Revised)

FINAL

LADCO NONROAD EMISSION INVENTORY PROJECT FOR LOCOMOTIVE, COMMERCIAL MARINE,

AND RECREATIONAL MARI NE EMISSION SOURCES

Prepared for

Michael Koerber Lake Michigan Air Director Consortium 2250 E. Devon Ave., Suite 250 Des Plaines, IL 60018

Prepared by

Christian E. Lindhjem ENVIRON International Corporation 101 Rowland Way, Suite 220
Novato, CA 94945-5010

December 2004

101 Rowland Way, Suite 220, Novato, CA 94945 415.899.0700December 2004



### i TABLE OF CONTENTS

Page

1.0 INTRODUCTION.......................................................................................................... 1-1

2.0 LOCOMOTIVE EMISSION SOURCES .................................................................... 2-1

3.0 COMMERCIAL MARINE EMISSIONS.................................................................... 3-1

4.0 RECREATIONAL MARINE ....................................................................................... 4-1

5.0 REFERENCES............................................................................................................... 5 -1

APPENDICES

Appendix A: Class I Railway Sy stem Descriptions and Maps Appendix B: Regressions Results Of Scaled Wisconsin Survey Results Appendix C: County Allocation Maps Appendix D: Geographic Allocati on Comparison Tables (CD Rom) Appendix E: County Emission Estimates (CD Rom)

TABLES

Table 1-1. Summary of comme rcial marine activity cate gories and data source.................. 1-2 Table 2-1. Rail categories.................................................................................................... .. 2-1

Table 2-2. Emission factor estimates used in this work (grams per gallon). ........................ 2-2

Table 2-3. National fuel c onsumption (AAR, 2003)............................................................. 2-3 Table 2-4. Comparison of fuel consumption (gallons) allocation method and railroad activity survey estimates..................................................... 2-3 Table 2-5. Class II/III national summary activity rates......................................................... 2-4

Table 2-6. AMTRAK Mi dwest operations............................................................................ 2-5

Table 2-7. AMTRAK state fuel consumption estimates. ...................................................... 2-5 Table 2-8. 2003 Fuel consumption for METRA rail............................................................. 2-6 Table 2-9. METRA rail line mileage by county.................................................................... 2-8

Table 2-10. METRA rail annual fuel consumption estimate by county. ................................ 2-9

Table 2-11. Illinois Class I railroad fuel consumption estimates............................................ 2-9

Table 2-12. Locomotive emissions in Illinois (tons per year)............................................... 2-10 Table 2-13. Indiana Class I railroad fuel consumption. ........................................................ 2-10

Table 2-14. Locomotive emissions in Indiana (tons per year).............................................. 2-10 Table 2-15. Michigan Class I railroad fuel consumption...................................................... 2-11

Table 2-16. Locomotive emissions in Michigan (tons per year)........................................... 2-11 Table 2-17. Ohio Class I railroad fuel consumption. ............................................................ 2-11December 2004



### ii Table 2-18. Locomotive emissions in Ohio (tons per year).................................................. 2-12

Table 2-19. Wisconsin Class I ra ilroad fuel consumption. ................................................... 2-12

Table 2-20. Locomotive emissions in Wisconsin (tons per year). ........................................ 2-12

Table 3-1. Commercial vessel types...................................................................................... 3-1

Table 3-2. Marine e ngine categories. .................................................................................... 3-2

Table 3-3. Baseline emission factor s for category 1 marine engines (taken from Table 5-3, EPA 1999B).................................................................... 3-2 Table 3-4. EPA (1999c, 2003) baseline emission factors for category 2 and 3 engines...................................................................................... 3-3 Table 3-5. Marine engi ne test cycles..................................................................................... 3-3 Table 3-6. Fuel consumption (gall ons of diesel) by river system. ........................................ 3-5 Table 3-7. Example: activity apportionment along the Illinois River................................... 3-5 Table 3-8. Emission factors (g/g allon) used for push boats.................................................. 3-6 Table 3-9. Relative monthly freight tran sfers through selected locks in 1999...................... 3-7 Table 3-10. Emission rates (g/ton- mile) for push boats assuming 549 (ton-mile/gallon) fuel consumption rate. ............................................................. 3-9 Table 3-11. Relative activity of freight transfers. ................................................................... 3-9 Table 3-12. Relative monthly activ ity of freight transfers. ................................................... 3-11 Table 3-13. Ports with significant deep dr aft traffic in the LADCO States. ......................... 3-12 Table 3-14. Summary emission estimates for the detailed ports (tons/year). ENVIRON, 2002. .......................................................................... 3-13 Table 3-15. Great Lakes freight tonnage (1000 tons) by port............................................... 3-14 Table 3-16. Emission rate (gram per ton-mile) for deep draft vessels.................................. 3-16 Table 3-17. Sample ferry runs in the LADCO area .............................................................. 3-17

Table 3-18. Selected fe rry-operating hours........................................................................... 3-17 Table 3-19. Fish landings in 2002 (NMFS, 2003). ............................................................... 3-18 Table 3-20. Five state emissions (t ons/year) by vessel type for near

shore emissions .................................................................................................. 3-20 Table 3-21. Mid-Lake deep-draft ve ssel activity by Lake (tons/yr)...................................... 3-21

Table 3-22. Commercial marine emissions (tons/year) by state this work and NEI............. 3-21

Table 4-1. List of Variables from the 1989- 1990 Wisconsin Recreationa l Boating Study... 4-1 Table 4-2. Month of year allocation of annual boating activity (WI DNR, 1991)................ 4-2 Table 4-3. Day of week allocation of weekly boating activity (WI DNR, 1991). ................ 4-3 Table 4-4. Time of day a llocation (WI DNR, 1991)............................................................. 4-3 Table 4-5. Sample comparison of relative state allocation of boating activity. .................... 4-4 Table 4-6. Regression statis tics for geographic allocation by boat and water type. ............. 4-7 Table 4-7. Outboard population fractions by power level and fuel type............................... 4-8 Table 4-8. Personal watercraft popul ation fractions by power level..................................... 4-8 Table 4-9. Inboard population fractions by power level and fuel type. ................................ 4-8 Table 4-10. State boat registrations......................................................................................... 4- 9

Table 4-11. Annual emission es timates (tons) for 2002........................................................ 4-10December 2004



### iii FIGURES

Figure 2-1. METRA rail system. ............................................................................................ 2-7 Figure 3-1. Example push boat (Port of M ilwaukee, http://www.port.mil.wi.us/)................. 3-4 Figure 3-2. Great Lake s freight links...................................................................................... 3-8 Figure 3-3. Example of a tug. ............................................................................................... 3- 10 Figure 3-4. Cleveland harbor................................................................................................ 3- 11 Figure 3-5. Washington Island Ferry.................................................................................... 3-16 Figure 3-6. Excursion ve ssel in Green Bay. ......................................................................... 3-16 Figure 3-7. Coast Guard cutter ............................................................................................. 3-1 9 Figure 3-8. Primary smaller vesse ls used by Coast Guard units .......................................... 3-20 Figure 4-1. Wisconsin county allocation of boa ting activity (this work and EPA default).... 4-4December 2004

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### 1-1 1.0 INTRODUCTION

This report outlines the results of the work to improve the emission inventories for the offroad emission categories: locomotives, commerci al marine, and pleasure craft. This work identified the available sources of equipment activity information for local emission sources for overall and by county activity estimates. Th e emission inventory im provements outlined in this work resulted in revised county-level annual emissions estimates including background data on equipment ownership and activity. S ection 2 describes the Locomotive estimates,

Section 3 describes the Commercial Marine estimates, and Section 4 describes the

Recreational Marine estimates.

LOCOMOTIVE SUMMARY

Because the LADCO area, and Chicago in particul ar, is an important rail center, all of the largest Class I railways [Burlington Northern Santa Fe (BNSF), Union Pacific, CSXT, Norfolk Southern, Kansas City-Southern, Ca nadian National, Canadian Pacific, and AMTRAK] have significant operati ons. The four most important railways in the US (Union Pacific, BNSF, Norfolk Southern, and CSX) and the major passenger operations of AMTRAK and the local Chicagoland METRA provided estimates of their activity in the area. Other large and small railways were estimated using nati onal activity estimates and national to county allocation methods described in Section 2 to pr ovide regional estimates of their activity. The largest source of uncertainty in the emissions estimates rests with the three large Class I railroads that did not provide summary data, Ka nsas City Southern, Canadian Pacific, and

Canadian National and their subsidiaries.

Locomotive activity is reported as two basic cate gories as fuel consumption of by either linehaul or switching engines. The reporting Clas s I railways provided line- haul activity by gross ton-miles (GTM) converted to fuel consumptio n using system-wide average fuel consumption rates. Switching engine activity was proportioned by number of locomotives at each yard with average annual usage and fuel consumption. So me Class I railroads, Norfolk Southern and CSX provided only line-haul activity and switchi ng rail activity was apportioned according to the line-haul activity. Switching en gine fuel consumption is usua lly less than 10% of Class I rail activity. However, for Class I railroads unable to supply activity estimates, fuel consumption was estimated using system-wid e fuel consumption estimates provided by Association of American Railroad’s (AAR) “A nalysis of Class I Railroads” or “Railroad Facts” and distributed across each State using th e ratio of regional and national miles of road operation.

The LADCO region also includes several dozen short line and regional railways, which do not maintain accessible records of activity. They may maintain total annual railway activity, which may span more than one State or County, but surveying each railway was impractical for this work. Nationally, the fuel consumption of re gional and short line railroads have been responsible for well under 10% of all locomotive fuel consumption, so the regional and short line railroads are of less concern than the Class I rail activity. To estimate short line and regional railway activity, annual survey results conducted to date were used to estimate national average estimates of fuel consumpti on per employee for these short line and regionalDecember 2004

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### 1-2 railroads. Data on the revenues and number of employees for each of the 75 short line and regional railways were purchased from Dun and Bradstreet or from the “Profiles of US Railroads” from the AAR, providing a basis fo r an estimate of overall activity for these railways without surveying each one. The regi onal and short line railways activity were allocated to the Counties of operation using syst em track mileage available from maps of the transportation network.

The local Chicago METRA passenger ra il company (http://www.metrarail.com/ ) locomotive activity were determined from annual activit y estimates provided by METRA for each of their regular routes. AMTRAK estimates were provided by fuel consumption es timates for a sample

set of their trains from which all routes were estimated based on the number of trains and mileage.

COMMERCIAL MARINE EMISSION ESTIMATES

Commercial marine emissions consist of several different categories of vessel types shown in the Table 1-1. Each category has its own uni que operations and specific considerations. To estimate emissions from each category, each of several unique activity data sources and engine types and emissions rates were used to estima te regional emissions. Section 3 provides a detailed description of the revised emission estimates for commercial marine vessel activity

and emissions.

Table 1-1. Summary of commercial marine activity categories and data source.

Commercial Marine Category Spatial Range Activity Estimation

Data Source Large Deep Draft Near Port Ports and Army Corps of Engineers Large Deep Draft Mid-Lake Army Corps of Engineers

Barge Traffic Inland Rivers Tennessee Valley Authority Fuel Consumption Estimation

Barge Traffic Lake Traffic Army Corps of Engineers Freight

Carried

Tug Near Port Coast Guard Vessel List and Selected Surveys

Ferries Regular Route Coast Guard Vessel List and Selected Surveys

Excursion Near Home Port Coast Guard Vessel List Dredging Area by Contract Army Corps of Engineers Contracts Commercial Fishing Dock State Registration

Military Near shore and

Mid-Lake Coast Guard Fuel Purchases



### For deep draft vessels, ocean-going and large la ker vessels, the activity estimates consisted of two spatially distinct areas of near port and mid-lake activity. The near port emission estimates were derived from earlier work by scaling the emission estimates provided in work performed

for EPA. Mid-lake emissions from deep draft vessel traffic was estimated using the waterway link ton-mile freight activity provided by the Army Corps of Engineers. The emission ratesDecember 2004

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### 1-3 per ton-mile were estimated using cruise conditi on emissions for the ports with specific vessel calls and freight transf ers previously studied.

For tug and tow vessels, those involved in barg e traffic, the primarily activity was found along the river systems of the Mississippi, Ohio, and Illinois rivers. The Tennessee Valley Authority (TVA) provided estimates from their barge- costing model for the LADCO region by river system. The general waterway activity estima tes from TVA was distributed along waterways using freight tonnage activity at locks provide d by the Army Corps of Engineers and distance

between locks to estimate relative ton-miles of freight transfers for different segments of the river activity. Less important but for complete ness, lake barge (as distinguished from large ocean-going or “laker”) traffic was estimated using Army Corps freight transfers within 2 miles of shore, where barges are limited by the Co ast Guard, distinct of the mid-lake deep draft vessel activity.

Ferries and excursion craft were identified th rough Coast Guard vessel catalogues available from the Army Corps of Engineers. Each ve ssel’s registered port was provided to spatially

allocate the base emissions fo r vessels that provide day trip s and other excursion activity.

Dredge activity is also regulated and contracted by the Army Corps. Emission estimates per ton of dredged material were estimated by surv ey for the Houston State Implementation Plan

and used in this work to convert emissions in the LADCO area with the Army Corps dredged

material contracts.

For commercial fishing vessels, State registratio ns for Michigan and catch tonnage were the primary sources of information to estimate vess el counts by State. Selected vessels were

identified to estimate the annual operations.

RECREATIONAL MARINE EMISSION ESTIMATES

Recreational marine vessels represent an important category of off-road hydrocarbon emissions. The impact of thes e emissions depends upon both the overall emissions and the spatial and temporal allocation of those emission s. Section 4 provides a de tailed description of the revised county-level estimates of recreational boating activity.

EPA in its NONROAD emissions model has us ed national equipmen t population estimates distributed to each county through a modified water surface area method. This modified allocation reduced the impact of oceans and Gr eat Lakes on water surface area by restricting the distance offshore used in the allocation, wher e a greater distance offshore was used for inboard vessels than for outboard or personal watercraft.

This work improved the vessel population estimate s using State registration data and developed an improved allocation method informed by an extensive survey conducted in Wisconsin. The boat population for each State was derived from State vessel registrati on and distributed among the equipment types (inboard, outboard, persona l watercraft, and sailboat auxiliary and other types) and power level groupings us ed in EPA’s NONROAD model.December 2004

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### 1-4 A spatial allocation method was developed using the results of the targeted survey conducted by Wisconsin in 1989 – 1990. The Wisconsin DNR surveys provided activity rates by county of operation and provided additional specificity to distinguish activity on the Mississippi and St. Croix border rivers, from Great Lakes, a nd all other inland lake and river activity. The Wisconsin survey results were used to iden tify and develop relationships for important

variables to describe the attractiveness of wate r bodies. The relative rates of boating activity by water surface area (distinguishing Great Lakes from other water surface area), boating registration, and distance from point of re gistration to water body were found to be the important spatial allocation variables.December 2004

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### 2-1 2.0 LOCOMOTIVE EMISSION SOURCES

INTRODUCTION

Locomotives are usually the most important s ource of NOx, PM, and SOx emissions from offroad engines. Rail activity is especially importa nt in the LADCO states, because the Chicago and other metropolitan areas in the LADCO st ates represent import ant rail centers.

Rail activity is typically broken into 5 subcat egories shown in Table 2-1 from the National Emission Inventory. (EPA, 2001) Class I railroad operations are the largest and most important railroads and have been split into two categorie s, which ENVIRON considered to be their linehaul (SCC 2285002006) and switching (SCC 2285002010) ac tivity. Smaller rail (Class II and III; SCC 2285002007) include a large number of railroad s and wide variety of operations including line-haul and switching operations. It was useful to se parate switching activity from line-haul activity for both Class I and II/III because the emissions are usually specific to a given yard and such engines have different operating prof iles. AMTRAK operates the only continuous passenger rail system (SCC 2285002008), though there may be small (weekend) excursion lines operating sporadically and largely unidenti fied. The only commuter line (SCC 2285002009) that operates in the LADCO area is the METRA system in and around the Chicago metropolitan area.

Table 2-1. Rail categories.

SCC Description Comment

2285002006 Class I operations Union Pacific (UP), Burlington Northern Santa Fe (BNSF), Norfolk Southern (NS), CSX, Kansas City Southern (KCS), Canadian

National 1 

### , Canadian Pacific (CP) 2


### 2285002007 Class II/III operations Regional and local railroads 2285002008 Passenger Trains AMTRAK

2285002009 Commuter lines METRA 3


### 2285002010 Yard Operations Class I yard rail and small switching railroads
1 – Illinois and Wisconsin Central also included in Canadian National Grand Trunk (CNGT)

2 – Soo Line included 3 – One other line operates an electric rail system only.



### The primary activity unit used to determine emissi ons is gallons of fuel consumed. To provide a perspective on emissions from different categor ies, Class I switching fuel consumption was on average less than 10% of line-haul fuel c onsumption nationwide in 2002. (AAR, 2003) Small regional and switching rail was ju st over 6% of Class I line-haul consumption for the same period. The passenger and commuter rail systems were easily identified for this study and provided activity data specific to the system.

Emission rates used in this work were deri ved from EPA documents provided as support documentation for the 1997 locomotive emission standards. (EPA, 1997) The emission rates per gallon of fuel consumed are higher with switchin g engines because the duty cycle is on average lower power with a significant am ount of idle, so the engine doe s not operate as efficiently as possible. Emission rates are higher for smaller rail systems than Class I railroad operations because they have been expected to convert mo re slowly to lower emissions engines. (EPA,December 2004

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### 2-2 2004a) EPA (2004b) provided the a mmonia emission rates using the latest available data. The

emission rates used in this wo rk are shown in Table 2-2.

Table 2-2. Emission factor estimates used in this work (grams per gallon). Engine Type HC CO NOx PM SOx 1 

### NH3 2



### Precontrolled 1999 Line-haul 10 26.6 270 6.7 16.7 0.116 Precontrolled 1999 Switching 21 38.1 362 9.2 16.7 0.116 Including emission reductions expected with the EPA rulemaking (% Reduction)

2002 Class I Line-haul 9.99 (0.1%) 26.6 238.3 (11.8%) 6.7 16.7 0.116

2002 Class I Switching 21 38.1 355.8 (1.7%) 9.2 (0.02%) 16.7 0.116

2002 Class II/III Line-haul 10 26.6 268.9 (0.4%) 6.7 16.7 0.116

2002 Class II/III Switching 21 38.1 360.5 (0.4%) 9.2 16.7 0.116

2002 Passenger 9.99 (0.1%) 26.6 253.0 (6.3%) 6.7 16.7 0.116

1 – Reported as SO 2 and derived from an average sulfur level of 2600 ppm. (EPA, 2004c) 2 – EPA (2004b)



### The different emission rates do not match the SCC definitions exactly. The primary differences are that Class II/III switching has been treated with distinct emission factors compared to the Class II/III line-haul because of duty cycle differe nces, and commuter rail has the same emission factors as other passenger rail.

CLASS I RAILROADS

Because the Class I railroads were expected to be the most significant rail operations in most areas including the LADCO states , every Class I railroad was as ked for information about their rail operation. A summary description of the Class I railroads’ opera tions is provided in Appendix A.

Union Pacific (UP) and Burli ngton Northern Santa Fe (BNSF) provided the most favorable responses. They supplied estimates of fuel cons umption by rail line (using internal estimates of ton-mile freight movements) for line-haul engi nes, and the number of switching engines plus hours of operation specific to each yard in their syst em. Norfolk Southern (NS) and CSX were able to provide similar estimates for their line-ha ul freight movements, but were unable to detail their switching rail activity beyond the Cook County yards. These railroads provided activity by county in terms of ton-mile of freight movement s and estimated fuel consumption using typical system-wide fuel consumption per ton-mile.

For other Class I railroads (Canadian Nati onal, also called the Grand Trunk (CNGT) and

includes the Illinois and Wisconsin Central railro ads; Canadian Pacific (CP), includes the Soo Line; and Kansas City Southern (KCS)) who did not provide estimates of relative activity in the LADCO states, an alternative method was used to estimate state fuel consumption. The US national fuel consumption for each railroad was pr orated against the rela tive system mileageDecember 2004

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### 2-3 within each state as a fraction of the railroad’s reported US national system. (AAR, 2003) A summary of the national fuel consumption and tr ack miles estimates are shown in Tables 2-3.

Table 2-3. National fuel consumption (AAR, 2003).

Railroad Line-haul Switching Track Miles CNGT 108,013,647 15,135,382 9,831 CP 42,198,000 3,060,000 4,701 KCS 51,256,604 4,057,180 4,359 CSX 514,107,567 56,172,596 40,299 NS 433,678,710 38,810,939 38,515
UP 1,176,963,998137,902,327 54,901 BNSF 1,091,248,247 57,434,118 49,728

Total 3,417,466,773312,572,542 169,554



### The method using track mileage to allocate na tional fuel consumption may in some cases misallocate activity because all tr ack mileage does not carry the same average freight traffic. Shown in Table 2-4 is a comparison of the rail road submissions and the approximate method for those Class I railroads that provided informati on. It appeared that the method using track miles

underestimated the travel of the States of Illinoi s, Indiana, and Ohio (the major states for eastwest rail transit) and overestimated the activit y in Michigan. For Wisc onsin, the over allocation of UP’s activity was compensated by an underestimate of the BNSF activity.

Table 2-4. Comparison of fuel consumption (ga llons) allocation method and railroad activity survey estimates. Track Mileage Method Railroad Submittal Comparison

Railroad Line-Haul Switching Line-Haul Switching Line-Haul Switching

Illinois

UP 48,706,985 5,706,892 65,872,943 2,549,894 74% 224%

BNSF 31,665,686 1,666,615 90,473,204 1,979,760 35% 84%

NS 1 

### 14,547,914 1,301,927 24,641,165 2,205,196 59% 59%

CSX 1 

### 13,382,437 1,462,196 16,342,788 1,785,651 82% 82%

Total of 4 108,303,022 10,137,630197,330,100 8,520,501 55% 119%

Wisconsin

UP 20,773,358 2,433,969 7,291,797 940,654 285% 259%

BNSF 5,990,805 315,306 24,729,689 247,470 24% 127%

Total of 2 26,764,163 2,749,275 30,800,568 1,188,124 84% 231%

Indiana

NS 1 

### 17,272,832 1,545,787 55,229,790 4,942,645 31% 31%

CSX 1 

### 24,353,739 2,660,947 41,506,808 4,535,131 59% 59%

Total of 2 41,626,571 4,206,734 96,736,598 9,477,776 43% 44% Michigan

NS 1 

### 7,240,177 647,941 4,757,649 425,773 152% 152%

CSX 1 

### 10,690,641 1,168,084 7,095,267 775,245 151% 151%

Total of 2 17,930,818 1,816,025 11,852,916 1,201,018 151% 151%

Ohio

NS 1 

### 25,143,569 2,250,158 80,738,318 7,225,464 31% 31%

CSX 1 

### 29,124,980 3,182,263 76,181,371 8,323,755 38% 38%

Total of 2 54,268,549 5,432,421156,919,689 15,549,219 35% 35%
1 – Switching estimated as a % of line-haul totalDecember 2004

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### 2-4 The results here are a function of the railways that submitted information. Canadian National and

Canadian Pacific and their US subsidiaries are important operators in Wisconsin and Michigan, while Kansas City Southern primarily operates w ithin Illinois of the LADC O states. In general, more rail activity was provided by surveys than wa s estimated using national to state allocation based on track mileage.

CLASS II/III REGIONAL, SHORTLINE , AND SWITCHING RAILROADS

In order to estimate potentially important small rail activity, the national fuel consumption per railroad employee was used and associated wi th local employment information. Benson (2004) prepared the national estimates of fuel consumption and employees shown in Table 2-5 from annual surveys conducted by ASLRRA (1999). Na tionally, Class II/III rail is of lesser importance than the Class I rail, which consumed nearly 20 times th e fuel that these smaller rail systems consume nationwide. The fuel consump tion and employees estimates in Table 2-5 are national summary estimates, a nd correspond to 10,000 gallons per employee. By contrast, the Class I railroad fuel consumption per employee ranges from 16,000 to 31,000 gallons per employee, possibly due to longer haul trips wher e fewer employees are required per ton-mile of operation.

Table 2-5. Class II/III national summary activity rates.

Year Employees Fuel Consumption (gallons)
1993 24,000 200,000,000
1994 25,000 225,000,000
1995 24,000 225,000,000
1996 24,000 200,000,000

1997 No data available
1998 23,000 210,000,000
1999 23,000 220,000,000
2000 22,000 220,000,000
2001 22,000 220,000,000



### This estimate of fuel consumption per employee was used in this work to estimate the smaller rail fuel consumption rates using estimates of the number of employees for each company as provided from a purchased database of Dun & Brad street (D&B). The estim ate of the number of employees was used to estimate the fuel consum ption of each railroad in each state. The AAR

and D&B data also indicated whether the railroad was considered a typical (line-haul) railroad or only provided switching services, so the appropriate emission fact ors for line-haul or switching operations were applied to the correct operation.

PASSENGER RAIL

AMTRAK provided an estimate of 2.35 gall ons per train-mile of travel. AMTRAK ( www.amtrak.com ) provides the weekly schedules for all trains in the Midwest including track mileage on their web site. ENVIRON used the AMTRAK schedules to estimate the number of trains and mileage for each train (both ways). These trains are shown in Table 2-6. The 2.35December 2004

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### 2-5 gallons per train-mile fuel consumption figure was applied to the weekly mileage multiplied by

52 for an annual estimate in Table 2-7.

Table 2-6. AMTRAK Midwest operations.

Route Miles Train (number) Weekly

Trains (Both Ways) Route to Terminus or

Exit of LADCO IL IN MI OH WI

Chicago Zephyr (5 & 6) 14 Chicago – Burlington IA 205 0 0 0 0

Cardinal / Hoosier State (51 & 50) 6 Chicago – Cincinnati OH 9 266 0 24 0

Cardinal / Hoosier State (317 & 318) 14 Chicago – Indianapolis IN 9 187 0 0 0

City of New Orleans (58 & 59) 14 Chicago – Cairo IL 365 0 0 0 0

Empire Builder (7 & 8) 14 Chicago – La Crosse WI 18 0 0 0 263 Hiawatha (329 – 342) 96 Chicago – Milwaukee WI 18 0 0 0 68 Illinois routes (347 & 348) 14 Chicago – Quincy IL 310 0 0 0 0

Illinois routes (391 & 392) 14 Chicago – beyond

Carbondale IL 333 0 0 0 0

Lakeshore Ltd. (48 & 49) 14 Chicago – Erie PA 9 146 0 280 0 Michigan (350 – 355) 42 Chicago – Pontiac MI 9 41 252 0 0 Michigan (364 & 367) 14 Chicago – Port Huron MI 9 41 267 0 0 Southwest Chief 14 Chicago – Keokuk IA 220 0 0 0 0 Texas Eagle (21 & 22 or 421 & 422) 14 Chicago – St. Louis MO 284 0 0 0 0

Three Rivers (40 – 45) 28 Chicago – Youngstown OH 9 146 0 244 0 AMTRAK communication 14 Chicago – Grand Rapids MI 9 41 126 0 0



### Table 2-7. AMTRAK state fuel consumption estimates.

Fuel Consumption (gallons per year) Train (number) IL IN MI OH WI

Chicago Zephyr (5 & 6) 350,714 0 0 0 0 Cardinal / Hoosier State (51 & 50) 6,599 195,031 0 17,597 0 Cardinal / Hoosier State (317 & 318) 15,397 319,920 0 0 0

City of New Orleans (58 & 59) 624,442 0 0 0 0 Empire Builder (7 & 8) 30,794 0 0 0 449,940 Hiawatha (329 – 342) 211,162 0 0 0 797,722 Illinois routes (347 & 348) 530,348 0 0 0 0 Illinois routes (391 & 392) 569,696 0 0 0 0 Lakeshore Ltd. (48 & 49) 15,397 249,777 0 479,024 0 Michigan (350 – 355) 46,192 210,428 1,293,365 0 0 Michigan (364 & 367) 15,397 70,143 456,784 0 0
Southwest Chief 376,376 0 0 0 0 Texas Eagle (21 & 22 or 421 & 422) 485,867 0 0 0 0

Three Rivers (40 – 45) 30,794 499,554 0 834,870 0 Chicago – Grand Rapids 15,397 70,143 215,561 0 0

Total 3,324,573 1,614,995 1,965, 709 1,331,491 1,247,662December 2004

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### 2-6 To allocate AMTRAK activity by county, an approximate estimate of the relative mileage in each county was used to apportion the fuel consum ption for each of the specific trains shown in

Table 2-7.

COMMUTER RAIL

The largest and only diesel powered commuter line in the LADCO area is the METRA rail systems. METRA (2004) provided fuel consumption information by rail line as shown in Table 2-8 and mileage along each line by county in Table 2-9. A sample of the schedule for the UP-N line is provided to show that all trains do not r un to the end of each line and the relative weekday and weekend activity. Figure 2-1 shows the rail lines including county boundaries.

Table 2-8. 2003 Fuel consumption for METRA rail.

Fuel (gallons) Lines Comments

4,219,993 BNSF Several trains predominately in Cook Co. 10,516,523 UP (W, N, and NW) N – M through F; From Kenosha 9 trains N – M through F; From Waukegan 16 trains N – M through F; From Winnetka 3 trains N – M through F; From Highland Park 3 trains N – Saturday; Kenosha 5, Waukegan 6 N – Sunday; Kenosha 3, Waukegan 5 M-F; 31 per day, Sat = 11, Sun = 8 5,415,909 MD (W and N) Line splits into two
2,945,881 RI

572,350 NCS 549,761 SW 268,564 HC 0 ME All electric rail line merging with the South Shore LineDecember 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 2_Locomotive Emission Sources.doc 

### 2-7 Figure 2-1. METRA rail system.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 2_Locomotive Emission Sources.doc 

### 2-8 Table 2-9. METRA rail line mileage by county.

Carrier/Line Additional Description Mile post County Mile post County Mile post County Mile post County Mile post

Rock Island

District Main Line 0.0 Cook 25.8 Will 40.2

Rock Island

District Beverly

Branch 9.9 Cook 16.5

Rock Island

District LaSalle - Beverly 0.0 Cook 16.5

SouthWest

Service 0.0 Cook 28.9 Heritage Corridor 0.0 Cook 26.7 Will 37.2 Burlington

Northern Santa Fe 0.0 Cook 16.2 DuPage 34.6 Kane 37.5 Union Pacific West 0.0 Cook 14.7 DuPage 33.0 Kane 35.5 Milwaukee District West 0.0 Cook 16.2 DuPage 26.2 Cook 34.0 Kane 39.8 Union Pacific Northwest 0.0 Cook 31.7 Lake 35.7 McHenry 63.1

Union Pacific McHenry

Branch 43.2 McHenry 50.6

Union Pacific OTC to McHenry 0.0 Cook 31.7 Lake 35.7 McHenry 50.6

Milwaukee District North 0.0 Cook 23.0 Lake 49.5

North Central

Service 0.0 Cook 31.1 Lake 52.8
Union Pacific North 0.0 Cook 20.5 Lake 45.2 Kenosha, WI 51.6



### It was beyond the scope of this study to ab solutely determine the emissions and fuel consumption by county for the METRA system given the large number of routes and train types. There are many issues that could affect relative fuel consumpti on including number of starts, weight (number of cars and passenge r load) of each train, idle time, empty train runs (used for scheduling purposes), and range of each train (for instance, not all trains start\run to the end of line.). This is demonstrated in Table 2-8 for th e sample of trains along the UP-N line where the number of trains varies widely by the route and last station north.

However, it was necessary to pr ovide the best estimate of rela tive activity by county to reflect greater activity in Cook County, rather than only using the prorated track mileage because all

trains do not run to the end of the line. Because the number of trains running to the end of each

line is a fraction of all trains along that line, in this work the commuter emissions were distributed to each county using the full mileage within Cook County, half the track mileage in adjoining counties, and one quarter the mileage for outlying counties. The one-quarter estimate was applied to Kenosha (WI) along the UP-N, McHenry (IL) along the UP-NW, and Lake (IL) along the MD-N and NCS lines shown above. This a pproximately reflects the relative activity in

terms of number of trains on the outer reaches of each line based on the train schedules provided for the UP-North line where approximately one quart er of trains run to Kenosha and many trains stop at Waukegan only halfway through Lake C ounty. The modified mileage for each county was used to apportion the fuel c onsumption as shown in Table 2-10.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 2_Locomotive Emission Sources.doc 

### 2-9 Table 2-10. METRA rail annual fuel consumption estimate by county.

Illinois Wisconsin Line Cook DuPage Kane Lake McHenry Kenosha UP (all) 6,895,776 947,885 127,451 1,481,942 898,350 165,119

BNSF 2,546,141 1,442,027 231,825 0 0 0 MD (all) 4,137,306 437,938 257,481 583,184 0 0

NCS 487,113 0 0 85,237 0 0

HC 224,434 0 0 0 0 0

RI 2,410,266 0 0 0 0 0

SWS 549,761 0 0 0 0 0
Total 17,250,797 2,827,851 616,757 2,150,363 898,350 165,119



### It may be warranted to further investigate this allocation scheme if a specific local emission inventory is required, but it should al so be realized that all freight traffic (well defined data was available for BNSF, UP, and NS-freight railway s) is not as well unders tood as this commuter system. Therefore, any errors in the allocation method for the METRA commuter rail added considerably less uncertainty to overall emissions allocations than might be expected with such an approximate method. Also, a misallocation will not affect the overall emissions estimates, only to which county those emissions were allocated. And the allocation method used here is more accurate in apportioning METRA’s activity than using track mileage alone.

The only other commuter rail line, the Northern Indiana Commuter Transit District (formerly the South Shore line) commuter rail, only runs an el ectric rail line. This operation only operates two small diesel locomotives and only to pick-up non functioning electric trai ns during rare power problems.

SUMMARY

The fuel consumption activity estimates for the Cl ass I railroads operating in Illinois are shown in Table 2-11. Because of the response fr om UP, BNSF, NS, CSX, AMTRAK and METRA, about 90% of the State’s locomotive activity wa s estimated to be determined through these

survey responses.

Table 2-11. Illinois Class I railroad fuel consumption estimates.

Predicted Fuel Consumption Company Supplied Fuel Consumption Estimates

Railroad State Track

Miles Line-haul Switching Line-haul Switching CNGT 1389 15,261,007 2,138,444 --- --- CP 356 3,195,594 231,729 --- --- KCS 128 1,505,126 119,137 --- --- CSX 1 

### 1049 13,382,43 7 1,462,19 6 16,342,788 1,785,651

NS 1 

### 1292 14,547,914 1,301,92 7 24,641,165 2,205,196

UP 1 

### 2272 48,706,98 5 5,706,892 65,872,943 2,549,894

BNSF 1 

### 1443 31,665,68 6 1,666,61 5 90,473,204 1,979,760

METRA --- --- 24,323,862 --- AMTRAK --- --- 3,324,573 --- Class II/III 6,180,000 8,840,000 --- ---
1- Company fuel consum ption estimates used for emissions estimatesDecember 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 2_Locomotive Emission Sources.doc 

### 2-10 The emissions comparison with the NEI estimates is provided in Table 2-12. This work shows considerably more locomotive emissions than estimated by the NEI in Illinois due to the submissions by CSX, NS, UP, BNSF, AMTRAK, and METRA. It is possible that the estimates in Table 2-12 are still a significant underestimat e because the other Class I railroads have rail activity rates per track mile within Illinois di sproportional to the system-wide averages used

here.

Table 2-12. Locomotive emissions in Illinois (tons per year).

Estimate THC CO NOx PM10 PM2.5 SO2 NH3
NEI – EPA 2004 2,093 5,321 53,707 1,335 1,202 3,287 0
This work 3,225 8,196 74,448 2,056 1,850 4,988 35



### Indiana is also a significant ra il state where all major eastern ra ilroads operate feeding primarily into the regional Chicago terminals. The larges t unknown activity is from the Canadian railroads (CNGT and CP) that have signifi cant operations primarily acro ss northern Indiana within the State. The fuel consumption estimates used for Indiana are shown in Table 2-13.

Table 2-13. Indiana Class I railroad fuel consumption.

Predicted Fuel Consumption Company Supplied Fuel Consumption Estimates

Railroad State

Track

Miles Line-haul Switching Line-haul Switching CNGT 81 889,951 124,704 --- --- CP 291 2,612,129 189,419 --- --- KCS 0 0 0 --- --- CSX 1 

### 1909 24,353,739 2,660,94 7 41,506,808 4,535,131

NS 1 

### 1534 17,272,832 1,545,78 7 55,229,790 4,942,645

UP 1 

### 6 --- --- --- --- BNSF 1 

### 0 --- --- --- --- AMTRAK --- --- 1,614,995 --- Class II/III 2,330,000 6,293,500 --- ---



### Because the CSX and NS data was so much highe r than would be predicted using the average national allocation, the emission es timates in this work were hi gher than the NEI as shown in

Table 2-14. Because CSX and NS dominate the rail activity, the activity estimates in this work likely represent well over 90% of the rail activity in the State.

Table 2-14. Locomotive emissions in Indiana (tons per year).

Estimate THC CO NOx PM10 PM2.5 SO2 NH3
1999 NEI 977 2,434 24,493 610 549 1,482 0
This work 1,520 3,730 33,813 933 840 2,214 15



### Michigan has the least rail activity within the L ADCO States and has significant activity from

both of the Canadian railroads that did not supply activity estimate s. In all, the survey results were responsible for less than 50% of the Stat e’s rail activity estimates. The Canadian National railway would be the next largest railroad to obt ain information to improve the State’s estimated railroad emissions inventory.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 2_Locomotive Emission Sources.doc 

### 2-11 Table 2-15. Michigan Class I railroad fuel consumption.

Predicted Fuel Consumption Company Supplied Fuel Consumption

Estimates

Railroad State

Track

Miles Line-haul Switching Line-haul Switching CNGT 1012 11,118,890 1,558,031 --- --- CP 262 2,351,814 170,542 --- --- KCS 0 0 0 --- --- CSX 1 

### 838 10,690,641 1,168,084 7,095,267 775,245

NS 1 

### 643 7,240,17 7 647,941 4,757,649 425,773

UP 1 

### 0 0 0 --- --- BNSF 1 

### 0 0 0 --- --- AMTRAK --- --- 1,965,709 --- Class II/III 4,400,000 2,250,000 --- ---

Table 2-16. Locomotive emissions in Michigan (tons per year).

Estimate THC CO NOx PM10 PM2.5 SO2 NH3
1999 NEI 2,357 2,237 8,583 220 198 520 0
This work 439 1,071 9,863 267 240 632 4



### Ohio was estimated to be the second most ac tivity LADCO State with respect to locomotive activity. From the actual CSX and NS data provid ed, it is clear that th e allocation method would have significantly underestimated CSX and NS activity as shown in Table 2-17. These survey results represent over 90% of the rail activity within Ohio estimated in this work.

Table 2-17. Ohio Class I railroad fuel consumption.

Predicted Fuel Consumption Company Supplied Fuel Consumption

Estimates

Railroad State

Track

Miles Line-haul Switching Line-haul Switching

CNGT 0 0 0 --- --- CP 0 0 0 --- --- KCS 0 0 0 --- --- CSX 1 

### 2283 29,124,98 0 3,182,263 76,181,371 8,323,755

NS 1 

### 2233 25,143,569 2,250,15 8 80,738,318 7,225,464

UP 1 

### 0 00 --- --- BNSF 1 

### 0 00 --- --- AMTRAK --- --- 1,331,491 --- Class II/III 6,376,500 1,890,000 --- ---



### Emissions for Ohio prepared in this work are shown in Table 2-18 and we re higher than the NEI estimates. This is a reasonable result give n the major east-west routes across Ohio. The

difference between the NEI and this work was due primarily to the data provided by CSX and

Norfolk Southern.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 2_Locomotive Emission Sources.doc 

### 2-12 Table 2-18. Locomotive emissions in Ohio (tons per year).

Estimate THC CO NOx PM10 PM2.5 SO2 NH3
1999 NEI 1,384 3,403 34,178 851 766 2,052 0
This work 2,250 5,641 51,063 1,413 1,272 3,400 24



### The Wisconsin estimates used survey results for le ss than half of the overa ll rail activity and was dependent largely upon the allocatio n method used to estimate the activity of the CNGT and CP railroads. The activity estimates for these two railroads represent half the locomotive activity estimated for this State. The major lines of ac tivity for these two railroads in Wisconsin are located between Chicago and Duluth for CNGT and between Chicago and La Crosse for CP. Wisconsin Central, owned by CNGT, operates many miles of track in Wisconsin where not all lines are heavily used. From the available data, it is unclear if the estim ates for CNGT and CP

were under or overestimated because UP would ha ve been overestimated but BNSF would have been underestimated using the relative track mil eage to allocate nationa l fuel consumption.

Table 2-19. Wisconsin Class I railroad fuel consumption.

Predicted Fuel Consumption Company Supplied Fuel Consumption Estimates Railroad State

Track

Miles Line-haul Switching Line-haul Switching CNGT 1655 27,975,366 3,920,040 --- --- CP 587 7,680,690 556,967 --- --- KCS 0 0 0 --- --- CSX 1 

### 000 --- --- NS 1 

### 000 --- --- UP 1 

### 969 20,773,35 8 2,433,969 7,291,797 940,654

BNSF 1 

### 273 5,990,80 5 315,30 6 24,729,689 247,470

METRA --- --- 165,119 --- AMTRAK --- --- 1,247,662 --- Class II/III 480,000 0 --- ---

Table 2-20. Locomotive emissions in Wisconsin (tons per year).

Estimate THC CO NOx PM10 PM2.5 SO2 NH3
1999 NEI 439 1,117 11,287 278 250 743 0
This work 905 2,299 20,755 577 519 1,399 10



### In conclusion, the emissions estimated here are hi gher than those currently estimated in the NEI, but are likely still lower than occurs within the LADCO States . The underestimates would most likely be more significant in Indi ana and Ohio where the little surv ey data that exists shows the

most dramatic underestimates.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 3_Co mmercial Marine Emi ssions Draft 06.doc 

### 3-1 3.0 COMMERCIAL MARINE EMISSIONS

INTRODUCTION

Commercial marine emissions comprise a wide variety of vessel types and uses. Table 3-1 describes the different types of data sources used to estimate commercial marine activity. In some cases, it was necessary to split the activity of similar vessels based on the available activity data. For instance, the Tennessee Valley Au thority (TVA, 2003) provided accurate fuel consumption estimates for push boats only on river systems while the same types of vessels that operate in the Great Lakes (primarily Lake Mi chigan between Milwaukee or Burn Harbor and Chicago) were estimated from other freight data by link as provided by the US Army Corps of Engineers (USACE, 2003).

Table 3-1. Commercial vessel types.

Source Definition Purpose Geographic

Area Data Source

River Traffic TVA and USACE Lock

Statistics Push Boats Barge Freight Lake Traffic USACE Freight Links

Tugs Vessel assist and support functions Near port USACE Vessel Lists

Mid-Great Lakes USACE Freight Links EPA Port Study Deep draft Laker and oceangoing large vessels Near port EPA Port Study

Ferries River or lake ferrying Regular routes USACE Vessel Lists

Other Commercial

Vessels Excursion boats primarily Near dock USACE Vessel Lists

Dredges Dredging projects Varies USACE Dredging

Contracts

Commercial Fishing Market fishing Great Lakes State registration and catch tonnage

Military Coast Guard and Navy Great Lakes Coast Guard Fuel

Purchases



### It is necessary to define our vessel type terms especially for potentially confusing types. Push boats and tugs are typically vess els of similar design except push boats purpose are exclusive to pushing barges while tugs are se lf-propelled support vessels with a V-shaped bow designed for vessel assist and other general pur poses usually near port rather than strictly in long-haul freight movements. Deep draft vessels ar e generally defined as those with drafts greater than 14 feet, and in the Great Lakes are ocean-going and ‘laker’, primarily freighter (such as bulk carriers or tankers), vessels with the ability to tolerate storm conditions mid-lake. (Push boats (tug and barge combinations) carry other frei ght, but these are restricted to within 5 miles of shore.) Other vessels include ferries, excursion boats (including such vessels that might be used for group day trips, dinner cruises, and casinos ), dredges (of various types), a nd commercial fishing vessels. In other areas, such as in the U.S. gulf coast or ne ar Naval ports, supply vess els (for off-shore oil wells or cable-laying) and military ve ssels are often found in high numbers.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 3_Co mmercial Marine Emi ssions Draft 06.doc 

### 3-2 EMISSION FACTORS

EPA defines three categories of marine diesel engines in Table 3-2, those primarily used for commercial operations, by the cyli nder displacement. The engine s correspond primarily to those used for propulsion power on large deep draft ve ssels (Category 3), auxiliary engines on large vessels and propulsion power for mid-sized (lar ger ferries, tugs, and excursion) vessels (Category 2), and smaller vessels (Category 1).

Table 3-2. Marine engine categories.

Engine Category Displacement (l/cylinder) Category 1 < 5.0 Category 2 5.0 < disp. < 30 Category 3 >30



### EPA revised emission factor estimates in the Re gulatory Impact Analysis (RIA) and published a rulemaking for commercial marine vessels. (EPA, 1999a &1999b) In the RIA (EPA, 1999b),

EPA estimated the emission factors in accordance w ith the defined engine categories. In Tables

3-3 and Table 3-4 are the EPA-estimated base emission factors for marine engines for each category of engine. These emission factors were used for both propulsion and auxiliary engines.

Table 3-3. Baseline emission factors for category 1 marine engines (taken from Table 5-3, EPA 1999B).

Power Range [kW] HC [g/kW-hr] NOx [g/kW-hr] CO [g/kW-hr] PM [g/kW-hr]

Category 1

37-75 0.27 11 2.0 0.90

75-130 0.27 10 1.7 0.40

130-225 0.27 10 1.5 0.40

225-450 0.27 10 1.5 0.30

450-560 0.27 10 1.5 0.30

560-1000 0.27 10 1.5 0.30

1000+ 0.27 13 2.5 0.30 Category 2 Category 2 0.13 13.4 2.5 0.32



### For Category 3 engines, EPA (2003) estimated em ission rates as shown in Table 3-4. The SO2 emissions for Category 3 engines relies on fuel su lfur content of 3 wei ght % sulfur fuel. But because Category 2 engines were assumed used for auxiliary power, a lower emission rate (0.83 g/hp-hr emission rate translates to the 16.7 g/gallon emission rate, same as locomotives) was used to estimate emissions during ho telling (while vesse l is at berth).December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 3_Co mmercial Marine Emi ssions Draft 06.doc 

### 3-3 Table 3-4. EPA (1999c, 2003) baseline emission factors for category 2 and 3 engines.

Engine Category HC [g/hp-hr] NOx [g/hp-hr] CO [g/hp-hr] PM [g/hp-hr] SO2 [g/hp-hr]

#

2 (5-30 l/cylinder) 0.10 9.96 1.85 0.24 0.83

# 3 Medium Speed (> 300 rpm) (> 30 l/cylinder) 0.395 12.38 0.52 1.31 9.56

# 3 Slow Speed (< 300 rpm) (> 30 l/cylinder) 0.395 17.60 0.82 1.29 9.69



### Emission estimates will be determined either by multiplying engine power, load factor, and hours per year of operation or on the basis of th e number of gallons of fuel consumed. The technique must be made flexible because ac tivity data is available in many formats.

The first method needs to have more information about each vessel. The vessel characteristic in terms of the installed engine power is often available from vessel registration information. However, the data for annual activity in hours and especially load factor is much more difficult to gather. Surveys can be conducted to gather th is information, but usually vessel operators can only estimate the number of hours of operation.

To estimate the engine load, there are two engine test cycles that EPA has used to represent engine duty cycles, the E-3 (and E-2 for constant speed engines typically with variable pitch propellers) and E-5 cycles desc ribed by the ISO (1996) as for he avy-duty and diesel craft less than 24 meters in length roughly corresponding to commercial and recreational use. In Table 3-5 are the two potential test cycle load factors available; E5 for general-purpose smaller marine diesel engines and E3 for ship propulsion and ot her heavy-duty marine applications. The load for the E-3 and E-2 test cycle is 69% average in-u se load, while the E-5 test cycle is 34% of propulsion load. If it could be determined that th e vessels found in the Coast Guard list were used for commercial purposes including ferries or other commercial functi ons then the E-3 load

factor was used. Else the lower E-5 load factor was used primar ily for vessels that were obvious excursion vessels including casi nos and other similar types.

Table 3-5. Marine engine test cycles.

Power E5 Cycle E3 Cycle

100 0.08 0.2

75 0.13 0.5

50 0.17 0.15

25 0.32 0.15

0 0.3 0 Avg. Load 34 69December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 3_Co mmercial Marine Emi ssions Draft 06.doc 

### 3-4 Often fuel consumption can be easier obtained wh ich reflects the total activity (power, load factor, and hours) of a vessel or group of vessels. However, a fuel consumption estimate must be made to convert the specific emission factors prov ided in Tables 3-3 and 3-4. The specific fuel consumption rate of 0.345 lb-fuel/g allon (and 7.1 lb/gallon diesel fu el density) was used for this work as taken from EPA (1997) used to convert locomotive specific emissions to gallons units.

PUSH BOATS

Tugs pushing barge traffic (Figure 3-1 is an example) is one of the primary vessel operation types producing commercial marine emissions in the LADCO region. Barges are usually pushed by tugs specifically designed for river movement s, though in fair weather barges may be pushed near (within 5 miles) shore on the Great Lakes. The major river systems in the LADCO region are the Mississippi, Ohio , and Illinois rivers. The freight mo vements and lock statistics (USACE, 2004) are well documented through river lock systems down to the Mississippi – Ohio

confluence.

Figure 3-1 . Example push boat (Port of Milwaukee, http://www.port.mil.wi.us/ ).



### The Tennessee Valley Authority (TVA, 2003) has b een using freight movement data and lock performance data to estimate fuel consumption by river system in their ‘barge costing model’. There are many factors affecting the fuel consum ption including the confi guration of the barges (how many barges can be operated per tug, the nu mbers of empty barges, the wait (idle) time at each lock, and other factors used by TVA to es timate fuel consumption along each route.

River Barge Traffic

The fuel consumption by barge traffic on rive r systems was provided by TVA (2003) and are shown in the Table 3-6. The estimates provided he re reflect only the rive r freight transfers and show the relative magnitude of activity along ea ch river segment. The Calumet-SAG Channel, Chicago Sanitary and Ship Canal, and the S outh Branch of the Chicago River are all found exclusively within Cook County, while the other river systems re flect activity through multiple

counties.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 3_Co mmercial Marine Emi ssions Draft 06.doc 

### 3-5 Table 3-6. Fuel consumption (gallons of diesel) by river system.

River System 1998 1999 2000 2001 Calumet-SAG Channel 573,518 517,008 274,349 187,364 Chicago Sanitary and Ship Canal 596,678 647,159 614,426 523,492 Chicago River, South Branch 19,789 39,889 27,606 26,655
Illinois 35,554,221 36,849,299 28,564,949 28,890,213 Ohio 84,238,537 83,085,263 94,373,783 93,529,533 Mississippi above the Missouri 51,261,419 64,649,042 52,607,979 44,360,390 Mississippi Between Missouri and Ohio 34,264,628 40,760,732 35,507,994 36,180,816



### The geographic allocation of the fuel consumpti on was accomplished using lock freight statistics available from the Army Corp of Engineers ( http://www.iwr.usace.army.mil/ndc/lpms/lpms.htm ). 

### The latest (as of January 2004) fi nal data available for these lock statistics was for calendar year 1999. The freight statistics through each lock were used to estimate the ton-miles for river segments. The ton-miles between two locks were calculated using the aver age freight tonnage of two locks multiplied by the river mileage between th e two locks as demonstrated for the Illinois River in Table 3-7. For river segments below or a bove the last available lock, the freight of the

last lock was used if no other es timates were available. The ton- mile estimate for each river link, between each lock or at the end of the river syst em such as the Ohio-Mississippi confluence, was normalized across each river syst em to allocate the total fuel consumption by river system in

Table 3-6.

Table 3-7. Example: activity apportionment along the Illinois River.

Illinois River

Lock Miles 1999 k Ton kTon-mile Apportioned

Thomas J. O’Brien 1 

### 326.5 7,372

Cook Co. Line 1 

### 298 est.
110,669 1.3% Lockport 291.1 16,039
81,888 0.9%
Brandon Road 286 16,074
245,202 2.8%
Dresden Island 271.5 17,747
496,345 5.7%
Marseilles 244.6 19,156
275,672 3.2%
Starved Rock 231 21,384
1,924,601 22.2%
Peoria 157.7 31,129
2,585,671 29.8% LaGrange 80.2 35,598
2,953,044 34.0%
Mississippi 2 

### 0 38,044 est.

Totals 8,673,094 100.0%

1 – Lock above the SAG Channel confluenc e (confluence is roughly equivalent to the Cook Co. line shown here) so activity contained in Chicago – South Branch and Sanitary and Ship Canal activity estimates 2 - Estimated based on added tonnage along Mississippi riverDecember 2004

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### 3-6 The procedure used here to apportion the fuel consumption was developed because the freight tonnage typically increases as th e river flows. So the fuel cons umption and therefore emissions are better apportioned to th e lower reaches of the river using this method.

The fuel consumption for each between-lock rive r segment was apportioned to the county using the relative river mileage within each county for each segment. For the Illinois River, the fuel consumption and emissions were allocated to th e county that encompassed or were split between two Illinois counties if they bordered the river. For the Mississippi and Ohio rivers, the fuel consumption and emissions were divided by two to reflect that these rivers form the borders of

the LADCO states and states outs ide of the region of interest.

Once the fuel consumption was estimated the em issions were predicted based on the typical engines installed on push boats. The Army Corp s of Engineers (USACE, Vessel Characteristics, 2004) provides vessel characteristics for push boats. Because the emission factors depend primarily upon the power of the engines (as Ta ble 3-3 shows, Categor y 1 engines above 1000kW had similar emission factors to Category 2 engine s) the fraction of the power available in push boats registered in the LADCO states was divided into those with propulsion power above and below 2680 horsepower (assuming 2 engines with rated power of 1000 kW). Smaller engines provided only 20% of the push boat power and 80% by larger engines, so the average emission factor for push boats was determine using thes e fractions and the estimates in Table 3-3 for engines between 225 –1000 kW and those above 1000 kW. The emission factors in specific units (g/kW-hr or g/hp-hr) were convert ed gallon units using the specifi c fuel consumption estimate of 0.345 lb/hp-hr and fuel density of 7.1 lb/gallon as used to convert specific emissions to gallons units in the EPA’s (1997) locomotive emissions estimates. The emission factors used in this

work are shown in Table 3-8.

Table 3-8. Emission factors (g/gallon) used for push boats.

Engine\Pollutant HC NOx CO PM SO2 NH3

<1000 kW 4.14 153.4 23.0 4.6

>1000 kW 4.14 199.4 38.3 4.6 Avg. 4.14 190.2 35.3 4.6 16.7 0.116



### The lock freight statistics provide a measure of seasonal allocation of barg e activity. A review of the locks where the Army Corps of Engineers (20 04) presents summary resu lts indicates that the latitude and the demand along each river system a ffect the seasonal activity. As shown in Table 3-9, an Illinois River lock near Beardstown, IL and the lower Ohio River lock demonstrate very little monthly variability compared with the al location using the number of days. The further north along the Mississippi River, the more seasonal variability is demonstrable as shown by the northern most lock in Table 3-9, lock #25 where l ittle activity occurs in January and February.December 2004

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### 3-7 Table 3-9. Relative monthly freight transfers through selected locks in 1999.

Month # of Days LaGrange Lock Beardstown,

Illinois Lock #25 on Mississippi

North of Illinois

River Lock #27

on Mississippi

St.Louis,

MO Lock #52

on Ohio Paducah,

KY

January 0.085 0.067 0.000 0.037 0.079

February 0.077 0.117 0.000 0.061 0.085

March 0.085 0.092 0.065 0.077 0.090

April 0.082 0.074 0.099 0.084 0.082
May 0.085 0.089 0.114 0.100 0.089

June 0.082 0.085 0.115 0.098 0.083
July 0.085 0.080 0.119 0.097 0.085

August 0.085 0.082 0.125 0.100 0.080
Septembe r 0.082 0.070 0.093 0.083 0.078

October 0.085 0.072 0.109 0.092 0.082

November 0.082 0.072 0.106 0.091 0.085

December 0.085 0.101 0.055 0.079 0.083



### Great Lakes Barge Traffic

For freight transfers on the Great Lakes, the Coast Guard restricts barge traffic within 5 miles of shore ( http://www.port.mil.wi.us/bargewebpage.html ), so freight transfers within these limits were considered to be barge only. The links that are outlined by USAC E (2004) and shown in Figure 3-2 where barge links roughly correspond to those blue links ringing the shore. Some freight transfers between the outlet of the Illin ois River system (through the Chicago river, SAG Channel, or Chicago Sanitary and Ship Canal) to other Great Lakes ports such as Burns Harbor or Indiana Harbor may be more direct.December 2004

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### 3-8 Figure 3-2. Great Lakes freight links.



### The tonnage along each freight li nk was provided by USACE (2004) with descriptions of each link. The links described as Lake “Spines,” and those described as “Access” links coming from large ports serving deep draft ve ssels were sorted out leaving only links ar ound the lake rather

than those in the middle of the lakes. The links described in this data include lengths and longitude and latitude where the links lengths and position are only approximate representations but the actual vessel movements may not be restricted to these specific positions.

The tonnage and link lengths were multiplied to estimate ton-miles of freight movements. The fuel consumption associated w ith these vessel movements was a ssumed to be 548.8 ton-miles per gallon, the same as the lower Miss issippi between the Missouri and Ohio rivers and the most fuel efficient push boats freight transfers within the LADCO region. The best estimate of fuel consumption was used because the Lake transf ers have no significant locks, turns, passing traffic, or current to conte nd with, as opposed to river move ments, which reduce the fuel efficiency of these freight movements. The fuel consumption estimate was then used to convert

the Table 3-8 emission rates to units useful for es timating emissions with ton-mile as the activity

indicator and shown in Table 3-10.December 2004

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### 3-9 Table 3-10. Emission rates (g/ton-mile) for push boats assuming 549 (ton-mile/gallon) fuel consumption rate.

HC CO NOx PM – 10 SO2 NH3

0.0075 0.0643 0.3465 0.0084 0.0304 0.0002



### The monthly allocation of Great Lakes barge traffic will depend upon a number of factors associated with ice management and freight carrie d in the barges. Two sources of data were used to estimate the monthly allocation of activity, lo ck statistics from the Army Corps of Engineers (2004) at the St. Marys River Locks at Sault Ste. Marie, and the barge freight transfers at Burns Harbor. In Table 3-11, are shown th e relative activity at th ese two sites demonstr ating either little (Burn Harbor) or significant (S ault Ste. Marie) monthly variab ility. The monthly Burns Harbor (Arcadis, 1999) barge activity mimi cs that of the northern Illinoi s River activity both of which do not demonstrate much month-to-month activity vari ation though with slightly lower transfers in August and September and higher transfers in Marc h and April. The northern activity is affected by ice and other navigational challenges affectin g transfers during January, February, and March.

Table 3-11. Relative activity of freight transfers.

Month # of Days 1999 Sault

Ste. Marie 1996 Burns

Harbor Barge-only January 0.085 0.019 0.073
February 0.077 0.000 0.054

March 0.085 0.013 0.196
April 0.082 0.092 0.121
May 0.085 0.116 0.099

June 0.082 0.111 0.067
July 0.085 0.115 0.075
August 0.085 0.112 0.040 September 0.082 0.111 0.038

October 0.085 0.111 0.060

November 0.082 0.104 0.058

December 0.085 0.097 0.119



### OTHER TUGS

Tugs, as defined here with an example shown in Figure 3-3, are working ve ssels other than those push boats used to transport freight. These tugs ar e used in a variety of other activities such as providing assist to larger deep draft vessels near ports, short movements of barges in and around ports, and as supply vessels or other sundry needs throughout th e Great Lakes area or along the major river systems.December 2004

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### 3-10 Figure 3-3. Example of a tug.



### The Coast Guard provides through the Army Corp s (USACE, Vessel Charact eristics, 2004) the number of vessels and their characteristics, inst alled power and other data , for a wide variety of boats and distinguishes tugs from push boats. Th e vessels, identified as tugs, were associated with emissions in the county of the port of registry as provided through the Army Corps information. It is likely that some or all of th e boats also operate outside the county of the port listed for a significant fraction of their time.

The activity of these vessels is unknown, so a small survey of vessel operators in the LADCO states was undertaken to identify a reasonable ho ur per year estimate. The survey response from five operators included activity estimates for a to tal of 35 tugs of which 6 were no longer in service. The average annual usage, includi ng those no longer in service, was 1831 hours and used for emissions estimates. It is possible that this was an underestimate because newer vessels may have replaced those tugs that are no longer in service and are not yet in the Army Corps data. The annual usage estimate of 2309 hours for el iminating the responses from those tugs no longer in service may be more appropriate. B ecause these vessels are workboats, the E3 test cycle load factor of 0.69 was used to estimate emissions.

DEEP DRAFT VESSELS

Estimates for the deep draft vessel relied on por t call information available for the ports of Cleveland, shown in Figure 3-4, and Burns Harbor . (Arcadis, 1999) This port call information was used to estimate the near port emissions and was used to estimate emission rates during

cruise conditions to estimate th e emission rates for mid-Lake tr affic. The mid-Lake traffic activity estimates were available only in term s of ton-miles of freight movements, so the

emission rates under cruise conditions were divide d by the tons moved by deep draft vessels at

Cleveland and Burns Harbor. The mid-Lake tra ffic was distinguished only by State, so the county designation was left off.December 2004

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### 3-11 Figure 3-4. Cleveland harbor.



### The monthly activity of deep draft vessels was taken from three source s, which all showed similar patterns in Table 3-12. The Sault Ste. Marie (USACE, 2004) and St. Lawrence Seaway (2003) at Welland Canal (between the Lakes Erie and Ontario) data did not distinguish between barge and deep draft vessel fr eight but showed similar relative monthly activity to the Burns Harbor (Arcadis, 1999) freight transfers to and from only deep draft vessels. The January – March activity was significantly reduced or non- existent due to ice and other navigational

barriers in the winter. Burns Har bor data showed increased activ ity before (November) and after (April and May) the winter slack period.

Table 3-12. Relative monthly activity of freight transfers.

Month # of Days 1999

Sault Ste. Marie 1996 Burns

HarborDeep draftonly 1996-7 Port

of ClevelandDeep Draftonly St. Lawrence Seaway 2002

January 0.085 0. 019 0.000 0.007 0.000
February 0.077 0. 000 0.000 0.000 0.000

March 0.085 0.013 0.000 0.000 0.009

A pril 0.082 0.092 0.121 0.072 0.082
May 0.085 0.116 0.141 0.088 0.112

June 0.082 0.111 0.081 0.088 0.111
July 0.085 0.115 0.101 0.239 0.107

A ugust 0.085 0.112 0.101 0.121 0.110
September 0.082 0. 111 0.071 0.085 0.112

October 0.085 0. 111 0.081 0.098 0.132

November 0.082 0. 104 0.202 0.176 0.127

December 0.085 0. 097 0.101 0.026 0.099December 2004

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### 3-12 Near Port Activity

The ports studied by EPA (ENVIRON, 2002 and Ar cadis, 1999) are shown in the Table 3-13. Each of the ports was associated with either Cl eveland or Burns Harbor in order to use similar vessel characteristics (vessel power, speed, time at berth, and other activity parameters). The number of vessel calls by vessel type (though bulk carriers were the primar y vessel type) at each port was determined from information availabl e from the USACE (Army Corps) and reported by Arcadis (1999) for the in-use year 1996.

Table 3-13. Ports with significant deep draft traffic in the LADCO States. Cleveland Harbor, OH Burns Waterway Harbor, IN Duluth-Superior, MN & WI Port of Chicago, IL Indiana Harbor, IN Stoneport, MI Port of Detroit, MI Calcite, MI Lorain Harbor, OH Port Inland, MI Toledo Harbor, OH Marblehead, OH Presque Isle Harbor, MI Milwaukee Harbor, WI Ashtabula Harbor, OH Port Dolomite, MI Gary Harbor, IN Fairport Harbor, OH Taconite Harbor, MN Alpena Harbor, MI Escanaba, MI Green Bay Harbor, WI
Two Harbors, MN Monroe Harbor, MI St. Clair, MI Muskegon Harbor, MI Conneaut Harbor, OH Drummond Island, MI Silver Bay, MN Charlevoix Harbor, MI Marine City, MI Buffington Harbor, IN Sandusky Harbor, OH Huron Harbor, OH Ludington Harbor, MI Erie Harbor, PA Grand Haven Harbor, MI



### The emissions in ENVIRON (2002) were calcula ted by associating and summing the product of the vessel trips or calls, vessel power, average load factor by mode of operation and time in mode for all modes of operation. The equation us ed for calculating emissions from vessels is shown below. The vessel and engine types were kept as distinct as possible to allow subtotals by vessel, mode, and engine type for each port.

Emissions = Trips * Power * LF in mode * Time in mode * EF

Trips - number of trips or vessel calls by vessel and engine type Power - rated power of propulsion engine by vessel and engine type LF - load factor (fraction of rated power) by mode Time - average time for each mode by vessel and engine type per call or trip EF - emission factor in mode and by engine type

The vessel power was assumed to have a load fa ctor of 10% for hotelli ng and 80% at cruise, following the estimates provided in BAH (1991). The 10% load figure for hotelling is usually supplied by smaller on board auxiliary engines oper ating at a higher fractional load, but 10% was associated with the installed power of vessel, th e only available for this work. The hotelling load varies according to the type of unloading that occu rs at berth, whether the vessel self unloads orDecember 2004

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### 3-13 shore-based equipment performs the unloadi ng. The load for modes (reduced speed and maneuvering) was estimated using the averag e speed during those modes and the hydrodynamic theory that relates the engine load to the cube of speed.

The emission factors for transit modes were those for Category 3 medium or slow speed engines as defined for this work and Category 2 engine s for hotelling modes. The PM emission rate depends in large measure upon the fuel sulfur level. For this work, fuel sulfur of 3% was used

for transit modes and a lower value of about 3000 ppm for the marine diesel for the hotelling mode. Using these activity and emission factors, emission estimates were made for each Great Lakes port with significant deep draft vessel activity and shown in Table 3-14.

Table 3-14. Summary emission estimates for the detailed ports (tons/year). ENVIRON, 2002.

Port Emissions (tons/year)

HC CO NOx PM SO2

Cleveland 9 36 243 16 111

Burns Harbor 2 10 82 5 36 Duluth-Superior, MN & WI 15 67 449 28 191
Indiana Harbor, IN 5 20 139 10 68 Port of Detroit, MI 6 24 168 12 79 Lorain Harbor, OH 6 26 176 12 80 Toledo Harbor, OH 7 31 209 13 90 Presque Isle Harbor, MI 3 14 95 6 44 Ashtabula Harbor, OH 4 17 114 8 53 Gary Harbor, IN 2 8 54 4 26
Taconite Harbor, MN 2 8 52 4 24 Escanaba, MI 3 12 80 5 37 Two Harbors, MN 2 7 48 3 23 St. Clair, MI 2 11 75 5 31 Conneaut Harbor, OH 2 12 78 5 31 Silver Bay, MN 2 7 47 3 22 Marine City, MI 1 4 25 2 12 Sandusky Harbor, OH 4 18 121 8 52 Ludington Harbor, MI 1 2 16 1 8 Port of Chicago, IL 4 18 146 9 65 Stoneport, MI 3 16 136 9 60 Calcite, MI 3 17 138 9 61
Port Inland, MI 2 10 87 6 38 Marblehead, OH 2 8 69 4 31
Milwaukee Harbor, WI 2 9 75 5 33 Port Dolomite, MI 1 7 58 4 26 Fairport Harbor, OH 3 19 136 7 46 Alpena Harbor, MI 2 11 95 6 42 Green Bay Harbor, WI 1 5 38 2 17
Monroe Harbor, MI 1 3 23 1 10 Port of Buffalo, NY 1 5 37 2 14 Muskegon Harbor, MI 1 4 33 2 15 Drummond Island, MI 1 3 27 2 12 Charlevoix Harbor, MI 1 3 28 2 12 Buffington Harbor, IN 0 2 16 1 7 Huron Harbor, OH 1 3 21 1 9
Erie Harbor, PA 3 19 134 7 43 Grand Haven Harbor, MI 1 3 25 2 11December 2004

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### 3-14 The emission estimates described in this repor t were adjusted to 2002 using freight tonnage available from the USACE (2004) Waterborne Commerce reports. Th e ratio of 2002 and 1996 freight tonnage, shown in Table 3-15 for all ports in the LADCO states including many not in Table 3-14, for each port was used to adjust th e 1996 emission estimates from the EPA report.

Table 3-15. Great Lakes freight tonnage (1000 tons) by port.

PORTS 1996 2002 2002/1996 Total (Great Lakes) 181,773 167,226 Waukegan Harbor, IL 469 552 1.18 Chicago River (Main And North Branch), IL 700 1269 1.81 Chicago River, South Branch, IL 1088 2197 2.02 Lake Calumet, IL 2327 1,078 0.46 Calumet Harbor And River, IL And IN 20167 11,034 0.55 Port Of Chicago, IL 27886 20,403 0.73
Indiana Harbor, IN 16893 13,839 0.82 Burns Waterway Harbor, IN 9848 8,621 0.88 Two Harbors (Agate Bay), MN 10662 14,895 1.40 Duluth-Superior Harbor, MN And WI 41398 44,161 1.07
Taconite Harbor, MN 8,408 645 0.08 Presque Isle Harbor, MI 8959 10,592 1.18 Marquette Harbor, MI 1,598 923 0.58 Drummond Island, MI 1682 1,221 0.73 St. Mary’s River, MI 78,939 80,330 1.02 St. Mary’s Falls Canal, MI 75,353 73,968 0.98 Grays Reef Passage, MI 8,152 11,799 1.45 Charlevoix Harbor, MI 1,666 1,343 0.81
Manistee Harbor, MI 460 1,457 3.17 Ludington Harbor, MI 1,237 492 0.40 Muskegon Harbor, MI 2,172 2,187 1.01 Grand Haven Harbor And Grand River, MI 971 883 0.91
Holland Harbor, MI 407 621 1.53 St. Joseph Harbor, MI 447 602 1.35 Cheboygan Harbor, MI 276 272 0.99
Milwaukee Harbor, WI 2,858 3,127 1.09 Port Washington Harbor, WI 546 354 0.65 Manitowoc Harbor, WI 312 421 1.35 Green Bay Harbor, WI 2,176 2,078 0.95 Alpena Harbor, MI 2,345 3,218 1.37
Menominee Harbor And River, MI And WI 191 429 2.25 Saginaw River, MI 5,264 5,819 1.11 St. Clair River, MI 78,546 79,341 1.01
Port Huron, MI 581 299 0.51 Marysville, MI 1,068 1,323 1.24 St. Clair, MI 5,427 4,506 0.83 Marine City, MI 4,116 3,713 0.90 Channels in Lake St. Clair 67,111 68,697 1.02
Detroit River, MI 75,023 74,653 1.00 Detroit Harbor, MI 8,224 5,810 0.71 Rouge River, MI 9,307 10,018 1.08 Ecorse, MI 797 1,105 1.39 Port Of Detroit, MI 18,604 17,306 0.93December 2004

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### 3-15 PORTS 1996 2002 2002/1996 Monroe Harbor, MI 1,794 1,008 0.56 Calcite, MI 8,669 8,575 0.99
Escanaba, MI 9,253 4,645 0.50 Stoneport, MI 7,990 7,455 0.93 Toledo Harbor, OH 13,032 11,115 0.85 Kelley’s Island, OH 371 1,289 3.47 Sandusky Harbor, OH 3,408 4,455 1.31 Lorain Harbor, OH 15,978 6,672 0.42 Cleveland Harbor, OH 16,721 11,412 0.68 Fairport Harbor, OH 2,770 2,326 0.84 Ashtabula Harbor, OH 9,523 9,838 1.03 Conneaut Harbor, OH 5,714 10,474 1.83
Erie Harbor, PA 1,434 1,362 0.95 Dunkirk Harbor, NY 398 450 1.13 Buffalo Harbor, NY 1,590 1,288 0.81 Niagara River, NY 274 398 1.45 Port Of Buffalo, NY 1,864 1,686 0.90 Oswego Harbor, NY 511 324 0.63
Illinois River, IL 39,679 40,204 1.01 Calumet-Sag Channel, IL 12,636 6,749 0.53 Chicago Sanitary And Ship Canal, IL 20,493 17,059 0.83 Illinois Waterway, IL 46,236 43,032 0.93



### Mid-Lake Traffic

To estimate the mid-lake deep draft vessel activi ty, USACE (2004) freight links (links shown in Figure 3-2) tonnage data was us ed to provide estimates of activity. The USACE uses text descriptions, and the links for the deep draft vessel in the middle of each lake are labeled “spines” with “access” links to each of those spin es. The freight links along the “spine” of each lake and the “access” to each spine were defined as those associated with deep draft vessels because these shipping lanes are outside of the ar ea designated as barge traffic. In the ENVIRON (2002) port emission estimates, the port emission s activity as outlined by Arcadis (1999) extends out 10 miles from port, so the length of each access link was reduced by 10 miles. Multiplying the freight tonnage by the length of each link provide s an activity indicator for deep draft vessels away from port.

In order to estimate emissions, the emission per t on-mile was estimated based on the cruise mode emission estimates for ports calls to Cleveland a nd Burn Harbor. The cruise mode was defined as 7 miles each way (14 miles both ways) and togeth er with the tonnage fo r each port in 1996 a tonmile estimate for the cruise mode emission was ma de. The emissions in gram per ton-mile during the cruise mode were estimated and these estimates are shown in Table 3-16. The average of the two ports was used to estimate mid-Lake emi ssions using the 2002 freight tonnage data from USACE (2004).December 2004

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### 3-16 Table 3-16. Emission rate (gram per ton-mile) for deep draft vessels.

Port 1996 Tonnage HC CO NOx PM SO2
Cleveland 14,138,830 0.0085 0.0164 0.3535 0.0309 0.2311
Burns Harbor 8,942,979 0.0058 0.0115 0.2486 0.0196 0.1459 Avg. 0.0071 0.0140 0.3101 0.0253 0.1885



### FERRIES, EXCURSION CRAFT, AND OTHER VESSELS

Ferries (Figure 3-5), excursion cr aft (Figure 3-6), and other vesse ls were taken from a list of vessels provided by the Coast Guard to the USACE (2004). The list includes the push boats, tugs, and other self-prope lled craft. The other self-propelled craft includes a wide variety of vessels registered in the U.S. including freight, passenger vessel of all types, and a very few support vessels. The freight vessels were excluded from review because the freight transfers were either covered under the categories of deep draft or push boats. The remaining vessels were primarily ferries and excursion vessels.

Figure 3-5. Washington Island Ferry.

Figure 3-6. Excursion vessel in Green Bay.December 2004

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### 3-17 Ferries are used for either transportation or excursion and many are operated only seasonally.

The ferries in the LADCO states are shown in Table 3-17 to conf irm that the Coast Guard lists provided the operating ferries and to estimate operating times to es timate engine loads over the course of the year.

Table 3-17. Sample ferry runs in the LADCO area.

State Port 1 Port 2 Other Ports &

Comments Bayfield La Point Madeline Island Sauk Columbia Merrimac Free Ferry

Cassfield Iowa Washington

Island Gills Rock Wisconsin

Milwaukee Muskegon New after 2002 Golden Eagle Iowa

Grafton Calhoun Co. Illinois

Brussels Ludington, MI Manitowoc, WI Badger Steamship Mackinac St. Ignace Mackinac City

Beaver Island Charlevoix

Manitou Islands Leland Algonac, MI Canada Michigan

Munising Grand Island Port Clinton Put-in-Bay \

Bass Islands Sandusky Pelee Island

Canada Ohio

Marblehead Kelley’s Island



### Some sample ferry runs were use to estimate th e annual activity where th e annual activity of a specific vessel could be estimated. These sample ferries shown in Table 3-18 produce a range of operating hours and are likely higher than typical for all vessels. Because these vessels are those operating at a higher rate than othe r ferry runs and excursion craft, and these schedules are likely maximum operating hours, an estimate of 1500 hours per year was used for all vessels in the USACE list. By contrast the survey data for tugs indicated an annua l usage of 1831 hours per year, so the reduced estimate of 1500 hours is reasonable for these seasonal operators.

Table 3-18. Selected ferry-operating hours.

Ferry Activity Description Operating Hours (per crossing estimate) Annual Activity

Estimate (hours/year) Badger (WI, MI) http://www.ssbadger.com/scheduleFares.asp 60 days 2 crossings 80 days of 4 crossings 4 hours running

1.5 hours at dock 1,840 running

690 at dock 2,530 total

Beaver Island (MI) http://www.bibco.com/ 706 crossings April –Dec. 2 hours running

1 hours at dock 1,412 running

706 at dock 2,118 total Jet Express (OH) (Maybe more than one boat) http://www.jet-express.com/schedules.html 5091 crossings May – Oct. 0.5 hours per crossing 2,546 total

Cassville (WI) http://www.cassville.org/ferry.html#Schedule 132 days 6 hours running per day 789 totalDecember 2004

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### 3-18 The load factor for ferries (labeled “Other Carriers (Specialized)” or “Other Carriers (Specialized)”) and other vesse ls including those labeled “Off shore Support” and “General cargo” were assumed to be workboats, so the 0.69 load factor was used to estimate emissions for these vessels. For “Passenger (Cruise)” and “Pas senger (Other)” (which include excursion craft such as found at the Wisconsin Dells) vessels, a lower load factor of 0.34 was used to estimate

emissions.

COMMERCIAL FISHING

Commercial fishing has a long tradition in the Great Lakes, but commercial fishing boats are a very small contribution to air emissions over th e Great Lakes. Commerci al fishing boats were provided in the State registrati on databases for Michigan and Wisconsin. As shown in Table 3-19 these two states have the most important commer cial fisheries. The emission estimate for Ohio was determined from a ratio of the fish landings and emissions estimates for the other two States. There are relatively few commercial fishing vessel s with 299 boats registered in Michigan and

74 in Wisconsin.

Table 3-19. Fish landings in 2002 (NMFS, 2003).

State Landings (tonnes) Value (million $)

Illinois 0 0

Indiana 0 0 Ohio 1,555 3.1 Michigan 4,291 7.4 Wisconsin 2,019 4.8



### The number of boats and operations are rather small compared with other commercial marine emission sources. However for completeness, comme rcial marine vessels were identified from the boat registrations in the Wisconsin and Mich igan and associated w ith recreational boats powered by engines greater than 100 horsepower, an arbitrary lower power estimate of installed power among these 300 – 400 comm ercially operated boats.

An approximate estimate of the annual usage for these boats was taken from information from an old commercial fishing vessel, the Barney Devine, purchased by the Wisconsin DNR ( http://dnr.wi.gov/org/water/fhp/fi sh/lakemich/Barney%20Devine.htm ) as a research vessel, which indicate that the engine had 10,000 hour s on 1972 engine in 2004 averaging 476 hours per year. (The engine is a 1972, 235hp Cummins.)

These boat totals, separated by diesel and gaso line inboard and outboard types based on the Michigan commercial fishing boats data, were used to create NONROAD commercial vessel NONROAD input files. The NONR OAD activity file was modified to use the 476 hours per year

estimate instead of the lower recreational hour s estimate. With the modified NONROAD input files, the emissions were then estimated for these boats. Th e geographic allocation of the registration county was available for Michigan, and the Great La kes counties inboard allocation

for the Wisconsin information.December 2004

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### 3-19 MILITARY VESSELS

The primary military vessels operating the Great Lakes are those of the Coast Guard 9 th 

### District. The Coast Guard vessels include both larger cutt ers using diesel fuel (s hown in Figure 3-7) and gasoline-fueled inboard and outboard engines (shown in Figure 3-8). The Coast Guard (2004) supplied fuel purchases for 2002 for the 9 th 

### District; 766,505 gallons of diesel and 209,216 gallons of gasoline.

The larger cutters of 140 feet or longer shown in Figure 3-7, typically us e Category 2 or larger Category 3 engines for propulsion (ins talled power typically 2500 hp; http://www.uscg.mil/d9/grumil/unit/sturgeonbay/cgcmobilebay/cgcmobilebay1.html ) and other smaller engines for auxiliary power. So the la rge (>1000kW) Category 1 engine emission factors were used because they were approximately equi valent to the Category 2 emission factors. These

emission factors were converted to emission in terms of gr ams per gallon using the fuel consumption assumption used by EPA in deve loping locomotive emission factors, where locomotive engines are similar to the reported ma ke and model of the marine engines used in

these cutters.

Figure 3-7. Coast Guard cutter.



### The gasoline-fueled engines used by the Coast Guard include both inboard and outboard engine types as shown in Figure 3-8. The average emissi on factors in units of gram per gallon were developed using the average emissions a nd fuel consumption estimates from the NONROAD2004 emissions model summing together the inboard and outboard categories.December 2004

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### 3-20 Figure 3-8. Primary smaller vessels used by Coast Guard units.



### The 9 th 

### District ( http://www.uscg.mil/d9/uscgd9.html ) encompasses the shores of the Great Lakes states of Minnesota, Wisc onsin, Michigan, Illinois, Indian a, Ohio, Pennsylvania and New

York. The emissions for the 9 th 

### District activity were apportioned to each county using the shoreline length for the Great La kes including parts of Minnesota, Pennsylva nia, and New York. Therefore only part of the 9 th 

### District’s activity occurs within the LADCO states.

EMISSION RESULTS

There are a number of ways to present summar y emission results for the Great Lakes region. The results presented here include two types of repor ting; one for vessels wh ere activity could be place into individual counties, and the other for th e mid-Lake traffic where barge and deep draft vessels move along shipping lanes in the Great Lakes. (One rare exception was the ferry SS Badger, which travels between Ludington, MI and Manitowoc, WI, but emissions were placed in Mason County, MI, which was labeled the homeport for the Badger.)

The first type of emission category reported here includes push boats alo ng river systems, deep draft vessels near (within 10 nautic al miles) of the port of call, tugs other than push boats, other self-propelled, and dredging. These are shown as a total in Table 3-20 for the 5-state LADCO

area.

Table 3-20. Five state emissions (tons/year) by vessel type for near shore emissions. Vessel Type HC CO NOx PM SO2 Deep Draft Vessels at Ports 171 777 5,670 364 2,495 Deep Draft Vessels (mid-Lake) 555 1,094 24,221 1,976 14,723
Push Boats on Rivers 527 4,492 24,219 586 2,127
Push Boats in Lakes 38 327 1,763 43 155 Tugs 164 1,519 7,900 182 662 Other self-propelled 25 164 1,045 40 259 Dredges 0 6 29 1 1 Commercial Fishing 18 120 9 1 1 Military vessels (Coast Guard) 100 312 151 4 17December 2004

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### 3-21 The second type of emission category is that asso ciated by Great Lake of interest and loosely

associated to the LADCO state emission totals. The emission results occur some distance from shore, so associating these emissions by county is misleading. In Tabl e 3-21 are the emission totals by Lake subtracting the La ke Superior traffic labeled as Minnesota, the Lake Erie traffic labeled as Pennsylvania and Ne w York, and Lake traffic la beled in Canadian waters.

Table 3-21. Mid-Lake deep-draft vessel activity by Lake (tons/yr). Vessel Type HC CO NOx PM SO2 Deep Draft Vessels
Lake Erie 62 122 2,693 220 1,637
Lake Huron 178 350 7,756 633 4,715 Lake Michigan 121 238 5,272 430 3,205 Lake Superior 195 384 8,499 693 5,166

Subtotal 555 1,094 24,221 1,976 14,723

Push Boats Lake Michigan 12 102 549 13 48

Lake Erie 10 88 472 11 41

Lake Huron 9 75 402 10 35 Lake Superior 7 63 340 8 30

Subtotal 38 327 1,763 43 155



### Lastly, a summary of commercia l marine emission estimated by State is shown in Table 3-22 including both county-specific emissions from Tabl e 3-20 and mid-Lake traffic in Table 3-21. In Table 3-22, it is helpful to keep in mind where the emissions are generated. So for instance, while most of the emissions occur along rivers in Illinois, they occur in the Great Lakes for Michigan.

Table 3-22. Commercial marine emissions (tons/year) by state this work and NEI.

State

Totals HC CO NOx PM – 10 SO2

This work for 2002

IL 424 3,520 19,430 513 2,112

IN 143 1,172 6,363 173 741

MI 609 1,886 22,839 1,675 12,175

OH 263 1,542 10,568 489 3,032

WI 159 691 5,805 347 2379 National Emission Inventory Estimates for 1999

IL 979 4,121 31,333 1,388 5,721

IN 754 3,175 24,130 1,056 4,172

MI 808 1,785 9,231 1,553 5,807

OH 1,376 5,795 44,020 1,911 7,326

WI 174 730 5,556 250 1,083December 2004

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### 4-1 4.0 RECREATIONAL MARINE

INTRODUCTION

Recreational marine boating activity is an importa nt source of VOC and CO emissions from offroad engine activity. While statewide emissi ons may be reasonably estimated using boating registration coupled with EPA NONROAD default average annua l usage, the geographic and temporal allocation could be an important consid eration of the impact of these emissions on air quality.

For this work, ENVIRON gathered boating registration da ta from the LADCO States to prepare revised NONROAD model input files that estimate typical annual activity. Survey data collected in Wisconsin (WI DNR, 1991) was used to prov ide temporal and geogra phic allocation within the Great Lakes states. The temporal allocations were taken directly from the survey results report and were provided by month, day, and hour to estimate temporal distributions. The greatest effort in this work, however, was give n to the geographic allo cation of boating activity, where the survey data provided a means to te st and determine a geographic allocation method

that could be used for other LADCO states. The default NONROAD geogr aphic allocation used an allocation method based directly on water su rface area where, for the Great Lakes, 0.25 miles

was used for outboards and 2 miles for inboards was used as the distance from shore to calculate

the water surface area. This work estimated the geographic allocation through the use of a proximity (of the boat registration address to wa ter surface area) and water surface area indicator to correlate the geographic allocation.

WISCONSIN BOATING SURVEY

In the summer and fall of 1989 and spring of 1990, the Department of Natural Resources of Wisconsin (WI DNR, 1991) conducted a survey of recreational boats in the state. The goal of the study was to assess the boating pressure on the lakes and inland waters, to allocate resources for boating safety and other enforcement, and gene rally to assist in pl anning and understanding recreational boating. The survey collected responses for several two-week periods of boating activity in 1989 and 1990. Responde nts were asked the county in which they boated, how much fuel was used, the county of their residence, and the type of boat used. This data was used to generate a relationship between the gallons of fuel burned, the water surface area, and the distance from the county of residence and the c ounty where the boating activity took place. The complete list of variables from the survey is listed below in Table 4-1.

Table 4-1. List of Variables from the 1989-1990 Wisconsin Recreational Boating Study.

Type of Boat Hull 

### Type of propulsion (inboard, out board, inboard/outboard, other pow ered, sail, sail with power, other non-powered)
Horsepower Boat length

Boat width

Was the boat used in Wisconsin during the two week period Which days during the two week period was the boat used Gallons of gasoline used during the two week periodDecember 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-2

Type of Boat Hull 

### Amount of money spent on gasoline Was the boat used on inland lakes, rivers , or streams during the two week period

List of the counties where the boat was used on inland water The number of days spent boating in each of these counties Name of the body of water wher e most of the boating occurred Was the boat used on any of the Wisconsin sect ions of Lake Michigan or Lake Superior coastline during the two week period

List of the counties off the Great La kes shores where the boating occurred The number of days spent boating in each of these counties Kind of activity involved while boating (fis hing, cruising/sailing, water skiing, swimming, etc.) While boating, was there contact with a DNR warden or other law enforcement

Did others interfere with th e respondents boating activity How crowded was the boating How satisfied was the respondent with the boating experience On the last day of boating, how many hours was the respondent on the water How many people were in the boating party How much money was spent on f ood, restaurants, auto, etc. In what state does the respondent live In what county does the respondent live The zip code of the respondent Area code and phone number of the respondent First name of the respondent

The report (WI DNR, 1991) of the survey resu lts provided summary estimates of the relative temporal activity of recreational boating. The data provided in this report were prorated for use in allocating emissions by month (Table 4-2), day of week (Table 4-3), and time of day (Table 4-4). Exact allocations can be used in NONROAD input files only for the month of year allocation provided in Table 4-2. The day of week allocat ions in the NONROAD model are only separated between weekday and weekend day. Seven distinct days are provided in the Wisconsin results shown in Table 4-3; though it should be noted that the weekdays and weekend days each had very similar weekly activity relative to one anot her with weekend days having more than twice the relative activity of wee kdays. The NONROAD model does not provide time of day emission estimates, but these could be useful in air quality modeling and so are repo rted here in Table 4-4.

Table 4-2. Month of year allocation of annual boating activity (WI DNR, 1991).

Month Boating Days Prorated

April 245325 4% May 936915 14%

June 1251969 18% July 1692314 24% August 1326508 19%
September 919134 13%

October 565316 8%



### Total 6937481 100%December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-3 Table 4-3. Day of week allocation of weekly boating activity (WI DNR, 1991). Day of Week % Responding Prorated Sunday 42 24% Monday 19 11% Tuesday 17 10% Wednesday 16 9%

Thursday 16 9%

Friday 20 11% Saturday 44 25%

Total 174 100%

Table 4-4. Time of day allocation (WI DNR, 1991).

Last Hour of

Period Fraction of Boating Starts Fraction of Boating

Finishes A verage Prorated

6 8.7% 3.8% 6.3%

9 23.6 0.9 12.3%

12 29.5 9.6 19.6%

15 19.1 16.7 17.9%

18 13.2 31.7 22.5%

21 5.9 28.7 17.3%

24 0 8.8 4.4%



### The raw database of survey results was provide d to ENVIRON to perform county allocations of boating activity. Using the zip c ode of the respondent, the county of registration was determined and used as the county of origin for each boat. Note that it is possible for a boat to be registered in a different county from where it is used. A sm all percentage (less than 2%) of the responses were Wisconsin registrations with addresses outside of Wisconsin.

In the survey, some of the res pondents boated in more than one county, but the number of gallons reported was for the whole two-week period. So for each boat, the total number of gallons was prorated to each county boated in by the number of days spent in that county. The activity in gallons of fuel consumed off the Great Lakes shores were distinguished from the activity on inland waters in the survey and were modeled se parately. All subsequent analysis was conducted on these two datasets indepe ndently of one another.

The boats were separated into four type categorie s: inboards, outboards, pow ered sail, and other. The inboards category included th e types “inboard” and “inboard/ou tboard” from the survey, the outboards category included just the “outboard,” the powered sail category included the “sail with power” category from the survey, and the ot her category included “oth er powered” from the survey. All boats labeled “oth er non-powered” or “sail” we re dropped. For the analysis, inboards and outboards were examined both sepa rately and together. The reason for these distinctions is that inboard engi nes have historically been 4-str oke while outboard engines were 2- stroke, and each type will continue to have engine designs unique for their use. The larger inboard and inboard\outboard engine s may also be associated with larger boats. Eventually all boat types were collapsed into only two categories, inboard a nd outboard. Personal watercraft (aka “JetSkis”) was allocated using the outboa rd allocation derived and described below.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-4 The geographic allocations of the Wisconsin survey results were used to determine the relative activity in each county for outboards and inboa rds. EPA has provided, in the most recent NONROAD model (NONROAD2002) , county allocations for out boards (and jet boats) and inboards using a modified water surface area, restri cting the water surface area assigned to Great Lakes, in allocating the boating activity to th e county. In Figure 4-1 is the comparison of the

outboard and inboard allocations found from the Wisconsin boating survey and default estimates used in the NONROAD model. There were significant differences between the default allocation and those from the survey results, best observe d when looking at the co unties with the largest shoreline length (Door County, FIPS – 55029) and highest inland water surface area (Winnebago County, FIPS – 55139). Table 4-5 demonstrates that Door County had much less activity than has been modeled while Winnebago County had considerably more re lative activity. More complete emissions allocation information for all St ates is available in th e Appendix C, D, and E.

Table 4-5. Sample comparison of relative state allocation of boating activity.

Inboard Outboard County Survey Data NONROAD

Default Survey Data NONROAD

Default

Door 10.8 % 17.8 % 3.3% 17.0% Winnebago 8.3% 1.1% 4.6% 1.2%

Figure 4-1. Wisconsin county allocation of boating activity (this work and EPA default). W I RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR INBOARD S

55001 55003

55005 55007

55009

55011 55013

55015 55017

55019

55021

55023

55025 55027 55029 55031

55033

55035 55037

55039 55041

55043

55045 55047

55049 55051

55053

55055 55057

55059 55061

55063

55065 55067 55069

55071 55073 55075

55077 55078

55079 55081 55083 55085

55087

55089 55091 55093 55095

55097 55099

55101 55103

55105 55107

55109

55111 55113

55115

55117 55119

55121

55123 55125

55127 55129

55131

55133 55135

55137 55139 55141

0.80 0.46

0.25 1.93

4.67

0.68 0.08

0.77 1.53

0.32

1.10

0.29

5.30 0.23 10.76 2.01

0.03

0.02 0.28

1.60 0.10

0.41

0.11 0.65

0.00 0.23

0.22

0.45 0.94

2.41 0.93

4.19

0.00 0.20 0.53

2.66 0.32 1.05

0.00 0.08

8.88 0.00 0.24 3.39

0.85

1.26 0.14 0.86 0.33

0.65 0.09

2.81 0.00

0.83 0.04

1.74

0.47 1.41

1.03

2.54 0.03

0.33

0.56 1.49

3.80 0.37

0.85

6.08 1.44

0.60 8.25 0.05

WI 2002 REC MARINE

INBOARDS: REVISED

0.00 to 0.09

0.09 to 0.32

0.32 to 0.65

0.65 to 1.05

1.05 to 2.54

2.54 to 11.00 WI RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR INBOARDS

55001 55003

55005 55007

55009

55011 55013

55015 55017

55019

55021

55023

55025 55027 55029 55031

55033

55035 55037

55039 55041

55043

55045 55047

55049 55051

55053

55055 55057

55059 55061

55063

55065 55067 55069

55071 55073 55075

55077 55078

55079 55081 55083 55085

55087

55089 55091 55093 55095

55097 55099

55101 55103

55105 55107

55109

55111 55113

55115

55117 55119

55121

55123 55125

55127 55129

55131

55133 55135

55137 55139 55141

0.33 10.80

0.22 5.96

1.32

0.21 0.48

0.63 0.25

0.03

0.18

0.22

0.29 0.20 17.76 1.92

0.09

0.06 0.08

0.35 0.26

0.29

0.00 0.21

0.04 1.44

0.10

0.21 0.30

4.15 6.54

0.22

0.01 0.12 0.19

7.95 0.25 1.50

0.07 0.06

8.20 0.06 1.66 0.91

0.03

7.24 0.13 0.12 0.32

0.13 0.21

3.98 0.03

0.04 0.15

0.11

0.09 0.77

0.14

6.62 0.08

0.06

0.17 1.19

0.17 0.35

0.04

0.20 0.11

0.09 1.14 0.14

WI REC MARINE

INBOARDS: DEFAULT

0.00 to 0.07

0.07 to 0.14

0.14 to 0.21

0.21 to 0.35

0.35 to 2.00

2.00 to 18.00

WI RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR OUTBOARDS

55001 55003

55005 55007

55009

55011 55013

55015 55017

55019

55021

55023

55025 55027 55029 55031

55033

55035 55037

55039 55041

55043

55045 55047

55049 55051

55053

55055 55057

55059 55061

55063

55065 55067 55069

55071 55073 55075

55077 55078

55079 55081 55083 55085

55087

55089 55091 55093 55095

55097 55099

55101 55103

55105 55107

55109

55111 55113

55115

55117 55119

55121

55123 55125

55127 55129

55131

55133 55135

55137 55139 55141

1.22 0.67

1.56 2.07

1.97

1.06 1.13

0.60 2.76

0.31

1.58

0.63

3.50 1.29 3.34 0.87

0.42

0.58 0.30

1.05 1.46

0.72

0.02 1.25

0.33 1.81

0.34

0.97 0.53

1.20 0.55

2.15

0.28 0.85 1.39

0.73 1.79 2.19

0.86 0.42

0.78 0.04 2.05 7.05

0.43

0.20 0.08 0.18 1.72

1.19 0.77

1.75 0.04

1.26 0.68

0.24

1.32 3.74

1.83

1.22 0.34

0.60

0.47 8.35

1.84 1.41

1.16

4.95 2.12

0.87 4.56 0.03

WI 2002 REC MARINE

OUTBOARDS: REVISED

0.00 to 0.34

0.34 to 0.68

0.68 to 1.00

1.00 to 1.40

1.40 to 2.00

2.00 to 12.00 W I RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR OUTBOARD S

55001 55003

55005 55007

55009

55011 55013

55015 55017

55019

55021

55023

55025 55027 55029 55031

55033

55035 55037

55039 55041

55043

55045 55047

55049 55051

55053

55055 55057

55059 55061

55063

55065 55067 55069

55071 55073 55075

55077 55078

55079 55081 55083 55085

55087

55089 55091 55093 55095

55097 55099

55101 55103

55105 55107

55109

55111 55113

55115

55117 55119

55121

55123 55125

55127 55129

55131

55133 55135

55137 55139 55141

0.36 11.11

0.24 5.18

0.85

0.22 0.52

0.68 0.27

0.03

0.19

0.23

0.32 0.22 17.01 1.58

0.10

0.06 0.08

0.38 0.28

0.31

0.00 0.23

0.05 1.45

0.11

0.23 0.32

4.29 6.63

0.24

0.01 0.13 0.21

8.06 0.27 1.35

0.08 0.06

8.45 0.06 1.39 0.98

0.03

7.82 0.14 0.13 0.35

0.14 0.23

4.09 0.03

0.05 0.16

0.12

0.09 0.83

0.15

6.76 0.08

0.07

0.19 1.28

0.18 0.38

0.04

0.22 0.12

0.10 1.24 0.15

WI REC MARINE

OUTBOARDS: DEFAULT

0.00 to 0.08

0.08 to 0.15

0.15 to 0.23

0.23 to 0.38

0.38 to 1.60

1.60 to 18.00December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-5 ESTIMATION OF FACTORS AFFECTIN G GEOGRAPHIC DISTRIBUTION OF

BOATING ACTIVITY

The EPA NONROAD default county allocation for Wi sconsin is significantly different than the results calculated from the Wisconsin boating surv ey. This argues that a better allocation method

should be derived for the other 4 LADCO states . The Wisconsin boating survey was used to compare geographical allocation methods for use in States where such survey data is unavailable. The Wisconsin survey data results were used to determine the proper geographic allocation for Wisconsin. For other states where only registra tion and geographic information data (water surface area, proximity to population regions, and ot her information) is available, an allocation method was developed using corr elations from the Wisconsin data. Described below are the procedures that were used to test allocation variables and approaches.

For each boat category (inboards and outboards), the number of gallons consumed was totaled for each county of origin from the survey results. The survey responses indicated the ZIP code of the registration, so the number of boats in each county could be identified. This provided an estimate of the number of gallons consumed pa ired with the number of boats surveyed.

A proximity variable was define d to describe where the boats were housed compared to the county where they were used. It was of interest to demonstrate if the distance to the boating site influenced the relative activity per water surface area; for instance, to determine if the EPA

NONROAD model default information that rural water surface area gets equivalent boating activity as urban water surface area. The distan ce from the origin county (where boats are registered) to the destination county (where the fuel was consumed) was calculated, where the centroid of each county was used in determini ng these distances. Where the boating activity occurred in the same county as the county of or igin, the distance was calcu lated as one half the radius of the county, determined by assuming the county was shaped like a circle. (The half radius was calculated by dividing the land area by the circumference of the county.) One half the radius was used because the assumption is that the distance is always calculated from the centroid (or center of the circle) of the origin. With this assumption, the expected travel distance within the county would be, on aver age, one half the radius. Note that for this analysis, the only

records used were those for which we were able to calculate a distance (rec ords with zip codes or county designations) and for which the gallons used were not missing (though some boats had no activity during the survey period). If a respondent did not provide the gallons consumed (zero was an acceptable response), or if the county of origin was unknown or outside of the state of Wisconsin, the data was not used. There were 20.7% of inland boating events that did not meet these criteria, and 21.5% of Great Lakes boating events that did not meet these criteria, primarily because gallons consumed were not reported.

The variable “boats over distance” was calculated by taking the total number of boats for which there were valid data from an origin county and dividing this total by the distance from the origin to the destination. For a given de stination county, the su m of all “boats over distance” fractions

was taken over all the counties in the st ate “BoatsOverDistance” was calculated as:

BoatsOverDistance j 

### = 3 [no. of boats in county i]/[distance from county i to destination county j]

where the sum is conducted over all coun ties for each ‘destination’ countyDecember 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-6 A correlation of county activity was conducted to produce relative county-level activity estimates. The correlation was conducted on the gall ons of fuel consumed in each county by boat type, either outboard or inboar d. The correlation method, using the logarithmic transformation as shown in the equation below, minimized the infl uence of counties with extraordinarily large water surface area (or shoreline length) or proxim ity (“boatsoverdistance”) variable magnitudes. It also does not assume a priori that the proximity variable and water surface area are of equal importance, as the combination of the two variab les would and as was originally proposed for

this work.

Ln (gallons j 

### ) = a + b Ln{ 3 [boatsoverdistance] j 

### } + c Ln {water surface j 

### or shoreline length j 

### }



### To determine the relative activity allocation by county, the correlation of gallons of fuel

consumed in the Great Lakes needed to be co mparable to that consumed on inland waters.

Because the water surface area a nd the shoreline length variables could not be normalized in a similar manner to produce a relati ve variable, the total number of registered boats by type and annual gallons consumed in Wisconsin as calc ulated by the NONROAD model using the number of registered boats as the NON ROAD input population was used to scale the survey results. The scaled gallons consumed in Wisconsin counties in 2002 were used to produce correlations using the total boating population and water surface area (or shoreline length) as the explanatory variables. Using this technique, we could total the estimated gallons consumed in counties with both shoreline along the Great La kes and inland water due to ac tivity occurring on both. These 2002 scaled regression results were then applied directly to Illinoi s, Indiana, Michigan, and Ohio to produce gallons estimates for activity on both Great Lakes shores and inland waters.

The results of the regressions in Table 4-6 s how that both the water surface area and the proximity (sum of boats/distan ce) were significant explanator y variables of the geographic distribution of boating activ ity. Scatter plots of the regression results are provided in Appendix B,

and demonstrate that the fit was better leaving in outlier coun ties (Door and Winnebago) with high water surface areas. One exception was that the proximity variable was not statistically significant in the relative boating activity in the Great Lakes model for outboards, but it was left in the final regression because it was significant for the other situations (for inboards on both inland and Great Lakes waters, and inland water for outboards), and because it provided the best explanation of the results. The corr elations, as evidenced by the low R 2 

### , were not perfect explanations of the results, but do a good job explai ning the trends of the da ta as the scatter plots in Appendix B show. It is helpful to note that EPA has apportioned activity using only a modified (only by restricting the distance o ff-shore of the Great Lakes that is counted) water surface area indicator without any correlati on with allocation data. So this method was still considered superior to the EPA method in that it was ba sed upon survey data to test the hypothesis.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-7 Table 4-6. Regression statistics for geographic allocation by boat and water type.

Inland – Inboards R 2 

### = 0.379

Coefficient of Value Std. Error t value Pr(>|t|) (Intercept) 2.1374 2.5333 0.8437 0.4020 LogWaterSurfaceArea 0.9026 0.1712 5.2711 0.0000 LogBoatsOverDistance 1.5780 0.3960 3.9846 0.0002

Inland – Outboards R 2 

### = 0.462

Coefficient of Value Std. Error t value Pr(>|t|) (Intercept) 4.9979 3.1763 1.5735 0.1202 LogWaterSurfaceArea 0.7971 0.1085 7.3471 0.0000 LogBoatsOverDistance 1.0986 0.4131 2.6590 0.0097

Lakes – Inboards R 2 

### = 0.716

Coefficient of Value Std. Error t value Pr(>|t|) (Intercept) 0.0380 3.1576 0.0120 0.9906 LogShoreLineLength 1.3910 0.3005 4.6290 0.0006 LogBoatsOverDistance 1.8453 0.4404 4.1905 0.0013

Lakes – Outboards R 2 

### = 0.447

Coefficient of Value Std. Error t value Pr(>|t|) (Intercept) 9.4384 4.3602 2.1647 0.0513 LogShoreLineLength 0.7846 0.2526 3.1057 0.0091 LogBoatsOverDistance 0.4558 0.5193 0.8776 0.3974



### The magnitude of the coefficients in Table 4- 6 also provides an esti mate of the relative importance of each variable in explaining the geographic distribution. (However because the variables have not been normalized, the coeffici ent magnitudes can only be compared within a model rather than from one model to another.) Fo r instance, the magnitude of the coefficient of proximity variable for inboard boats correlations was higher than the coefficient for the same

variable in the outboard correlations . This result appear to be real istic in that outboard boats are likely smaller than inboard boats , and therefore should be more easily moved from one location

to another. This would indicat e that outboard activity allocati on is affected less by the travel distance from the point of origin to the destinat ion water than by the availability of water surface area. Also the proximity variable was less important for explaining Great Lakes outboard activity, as well as not bei ng statistically significant.

These regression results were used to describe th e relative activity of count ies in the States of Illinois, Indiana, Michigan, and Ohio. The count y boat population for each state, the county-tocounty distances, and the water surface area or shoreline length was used to estimate the number of gallons of fuel consumed in each county by each boat type. The estimated gallons of fuel

consumed calculated in this manner were then summed for inland and Great Lakes waters to provide a total estimate of the county activity. (Because the regressions were developed for Wisconsin, the fuel consumption estimates calculated here were only used to allocate the State total activity rather than used directly to estima te emissions.) This fuel consumption estimate was then normalized to produce a relative magnit ude estimate to rewrite the NONROAD allocation input file for each State. The raw (not regression s of the data) survey results were used for the Wisconsin NONROAD allocation input file. The outboard allocation corr elation was used to describe personal watercraft allo cation using the county registrations of personal watercraft in the

correlations.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-8 STATE REGISTRATIONS

The state boating registrations were mapped into NONROAD model input files using the national default allocation of power level gr ouping. The boating population from the registration data was typically separated into outboard, inboard (including ster ndrive), and personal watercraft (jet boats) but grouped across fuel t ype (either gasoline or diesel). (The NONROAD model accounts for 2-stroke and 4-stroke gasoli ne types through the use of a technical type description.) Summaries of the power distributions are shown in Tables 4-7 – 4-9. One exception to this distribution was the Michigan registration data where vessels were also segregated by fuel

type.

Table 4-7. Outboard population fractions by power level and fuel type.

SCC Description HP min HP max HP avg Fraction

of Total

2282005010 2-Str Outboard 1 3 2.412 1.6%

2282005010 2-Str Outboard 3 6 5.337 19.0%

2282005010 2-Str Outboard 6 11 8.76 16.3%

2282005010 2-Str Outboard 11 16 14.99 5.9%

2282005010 2-Str Outboard 16 25 21.54 15.6%

2282005010 2-Str Outboard 25 40 36 10.2%

2282005010 2-Str Outboard 40 50 49.34 5.3%

2282005010 2-Str Outboard 50 100 78.17 9.7%

2282005010 2-Str Outboard 100 175 139.4 12.0%

2282005010 2-Str Outboard 175 300 217.9 4.2%

2282020010 Dsl – Outboard 25 40 32.25 0.1%

Table 4-8. Personal watercraft population fractions by power level.

SCC Description HP min HP max HP avg Fraction

of Total

2282005015 2-Str Personal Water Craft 16 25 18.41 0.6%

2282005015 2-Str Personal Water Craft 25 40 36.75 7.2%

2282005015 2-Str Personal Water Craft 40 50 43.95 7.2%

2282005015 2-Str Personal Water Craft 50 100 73.46 66.0%

2282005015 2-Str Personal Water Craft 100 175 116.3 19.0%

Table 4-9. Inboard population fractions by power level and fuel type.

SCC Description HP min HP max HP avg Fraction

of Total

2282010005 4-Str Inboard/Sterndrive 3 6 5 0.04%

2282010005 4-Str Inboard/Sterndrive 6 11 10 0.03%

2282010005 4-Str Inboard/Sterndrive 11 16 15 0.02%

2282010005 4-Str Inboard/Sterndrive 25 40 30.47 0.07%

2282010005 4-Str Inboard/Sterndrive 50 100 59.55 0.62%

2282010005 4-Str Inboard/Sterndrive 100 175 149.7 62.11%

2282010005 4-Str Inboard/Sterndrive 175 300 211.1 28.94%

2282010005 4-Str Inboard/Sterndrive 300 600 380.8 1.20%December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-9 SCC Description HP min HP max HP avg Fraction

of Total

2282010005 4-Str Inboard/Sterndrive 600 750 630 0.00%

2282020005 Dsl – Inboard 6 11 9.74 0.38%

2282020005 Dsl – Inboard 11 16 14.92 0.20%

2282020005 Dsl – Inboard 16 25 21.41 0.43%

2282020005 Dsl – Inboard 25 40 31.2 0.24%

2282020005 Dsl – Inboard 40 50 42.4 0.05%

2282020005 Dsl – Inboard 50 100 73.63 0.35%

2282020005 Dsl – Inboard 100 175 144.9 1.18%

2282020005 Dsl – Inboard 175 300 223.1 2.37%

2282020005 Dsl – Inboard 300 600 387.1 1.50%

2282020005 Dsl – Inboard 600 750 677 0.08%

2282020005 Dsl – Inboard 750 1000 876.5 0.11%

2282020005 Dsl – Inboard 1000 1500 1233 0.06%

2282020005 Dsl – Inboard 1500 2000 1577 0.00%

2282020005 Dsl – Inboard 2000 3000 2289 0.02%



### The state registrations were collected and appor tioned according the boat type is shown in Table 4-10 for each of the five states. The boat types were apportioned into each of the three general types described above.

Table 4-10. State boat registrations.

State Inboards Outboards PWC Total

Illinois 50,992 227,098 30,663 308,753

Indiana 73,324 155,689 11,315 240,328

Michigan 101,161 gasoline 7,586 diesel 483,756 gasoline

545 diesel 65,395 658,443

Ohio 67,329 299,854 40,489 407,672

Wisconsin 87,635 500,313 Lumped with

Outboards 587,948



### The geographic allocation wa s mapped into NONROAD alloca tion input files (such as Wi_wib.alo and Wi_wob.alo for inboard a nd outboard allocation for Wisconsin). The NONROAD model prorates the allo cation values in these input f iles, so the numbers can be entered in any form (%, gallons, or fractions) as long as the values are appropriately relative to

one another.

RESULTS

The revised population and allocation input f iles were used when running the NONROAD2004

model to estimate annual emission totals. St ate total emission estim ates and NEI default estimates are shown in Table 4-11 using the year 2002 boat registrations for each state. The estimates in Table 4-11 put together inboar d, outboard, and personal watercraft. Because inboards only used 4-stroke diesel and gaso line engines, these ve ssels have higher NOx emissions and lower VOC emissions compared with the 2-stroke gasoline engines most oftenDecember 2004

G:\LADCO-nonroad\Report\RevFinal\Sec-4 LADCO Recreational Marine 10_5_04.doc 

### 4-10 used in outboard and personal watercraft engi nes. Therefore the rela tive mix of inboards, outboards, and personal watercraft can affect th e emission estimates in addition to the total

number of boats.

Table 4-11. Annual emission estimates (tons) for 2002.

State Type VOC CO NOx PM SO2 Revised 17,182 53,172 2,541 833 234 Illinois Default 19,607 51,747 1,477 961 129
Revised 12,420 41,654 2,206 590 203 Indiana Default 8,295 21,892 625 407 55
Revised 53,485 185,854 4,607 2,371 259 Michigan Default 41,814 110,357 3,149 2,049 275
Revised 20,831 64,081 3,034 990 283 Ohio Default 25,889 68,327 1,949 1,269 170
Revised 34,588 89,087 3,051 1,740 285 Wisconsin Default 19,953 52,662 1,501 978 131



### The more significant effort in this work is that of the county allocation estimates. The figures in Appendix C demonstrate the relative state to county allocation used in this work compared with the default allocation. Numeric tables of the grap hical results in Appendi x C are provided in and Excel file as Appendix D. Annual emission esti mates for recreational marine engines by county are provided in five Excel files la beled Appendix E-1, E-2, E-3, E-4, and E-5.

The revisions to the geographic allocations show two main f eatures. The importance of the proximity of the boat registration to the water su rface area has the effect of pulling more inboard activity to counties with larger population centers where the boat s are registered than the default

allocation. The second feature is the outboard ac tivity was pulled away from the Great Lakes toward inland water surface area and partially, though less than for inboards, affected by the proximity of the registration address.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 5_References.doc 

### 5-1 5.0 REFERENCES

AAR 2003. “Analysis of Class I Railroads, 2002 ,” and RR Industry Info: Railroad and States, http://www.aar.org/AboutTheI ndustry/StateInformation.asp , Association of American Railroads, 2003.

AMTRAK 2003. Personal communicati on from Ellen Jurczek, September 4, 2003.

Arcadis 1999. “Commercial Mari ne Activity for Great Lake a nd Inland River Ports in the United States.” Prepared for EPA by AR CADIS Geraghty & Mill er, Inc., EPA420-R-99- 019, September.

ASLRRA 1999. “1999 Annual Data Profile of the American Short Line & Regional Railroad Industry.” Developed by the American Short Line & Regional Rail road Association and the Upper Great Plains Transportation In stitute North Dakota State University. (Available online at: http://www.shor tlinedata.com/ )

BNSF 2003. Personal communication from Lyle Staley, September 10.

BTS 2002. 2002 National Transportation Atlas Data Shapefile Download Center. Bureau of Transportation Statistics, Washingt on, D.C. Internet address: http://websas.bts .gov/website/ntad02/

.

Benson, Doug. 2004. Personal communication, Fe bruary 19, 2004. See also ASLRRA 1999.

CSX 2004. Personal communications from Rick Nath, CSX Transportation Inc., August 4.

Coast Guard 2004 Personal communication with Renee Sykora, May 24.

ENVIRON 2002. “Commercial Marine Emissi on Inventory Development.” Prepared for the Environmental Protection Agency, April.

ERG 2001. “Documentation For The Draft 1999 Base Year Aircraft , Commercial Marine Vessel, And Locomotive National Emission I nventory For Criteria And Hazardous Air Pollutants.” Prepared by: Eastern Research Group, Inc. Prepared for: Emission Factor and Inventory Group (MD-14) Emissions, M onitoring and Analysis Division U.S. Environmental Protection Agency, October 29.

EPA 1997. “Locomotive Emission Standards.” Regulatory Support Docume nt, United States Environmental Protection Agency, Office of Mobile Sources, April. And EPA 1997, Emission Factors for Locomotives,” Envi ronmental Protection Agency, EPA420-F-97- 051, December.

EPA 1997 “Emission Factor for Locomotives.” Environmental Protection Agency, EPA420-F97-051, December.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 5_References.doc 

### 5-2 EPA. 1999a. “Control Of Air Pollution From Mari ne Compression-Ignition Engines.” Part 94, Code of Federal Regulations, December, 1999. Published in the Federal Register

December 29.

EPA. 1999b. “Final Regulatory Impact Anal ysis: Control of Emissions from CompressionIgnition Marine Engines.” EPA420-R-99-026, November.

EPA. 1999c. Michael Samulski. Personal communication, April 5.

EPA. 2001. Procedures Document For Nationa l Emission Inventory, Criteria Air Pollutants 1985-1999.” EPA-454/R-01-006, March.

EPA. 2004a. Personal communicati on with Charles Moulis, March 4.

EPA. 2004b. Personal communicati on with Craig Harvey, March 10.

EPA. 2004c. Personal communication with Lester Wyborny, March 11.

ISO 1996. “Reciprocating Intern al Combustion Engines – Exha ust Emission Measurement” Part 4 Test Cycles for Diffe rent Engine Applications.” International Standards Organization Regulations 8178, 1996 Edition.

Ladd, H. 1999 “U.S. Railroad Traffic A tlas.” Altamont Press, Modesto, CA.

METRA 2004. Personal communication with METRA staff, Mary McDonnell, 312-322-6939, Chris Wilson, 312-322-8024, John Gottlieb, 312-322-8978, March. http://metrarail.com/schedule.html

NMFS 2003. “Annual Landings.” National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Department of Commerce, Available Online at: http://www.st.nmfs.gov/st1/commerci al/landings/annual_landings.html last updated September 2003.

Norfolk Southern 2004. Personal comm unication from Gibson Barbee, March 8.

RPO Data Exchange Format http://www.ladco.org/tech/emi s/protocol/protocol.html

St. Lawrence Seaway 2003. “2002 Traffic Repor t.” Prepared by The St. Lawrence Seaway Management Corporation and The Saint La wrence Seaway Development Corporation.December 2004

G:\LADCO-nonroad\Report\RevFinal\Sec 5_References.doc 

### 5-3 TVA 2003. “River Efficiency, Fuel Taxes, and Modal Shifts.” Bray, L.G., Dager, CA., Henry, R.L., Koroa, C., TR News, Transportation Research Board, July – August 2002. Fuel Consumption Update, personal communica tion with C.A. Dager, July 2003.

Union Pacific 2003. Personal communi cation from Jon Germer. October 30.

USACE 2004. Data available online at: for River Barge, http://www.iwr.usace.army.mil/ ndc/lockchar/lockchar.htm , Vessel Characteristics, http://www.iwr.usace.army.mil/ ndc/veslchar/veslchar.htm , Waterborne Commerce, http://www.iwr.usace.army.mil/ndc/wcsc/wcsc.htm , Dredging, http://www.iwr.usace.army.mil/ndc/dredge/dredge.htm

.

Wisconsin Department of Natural Resources. 1991. “Boating Pressure on Wisconsin’s Lakes and Rivers, Results of the 1989-1990 Wiscons in Recreational Boating Study, Phase 1,”

Technical Bulletin 174.

### APPENDIX A

CLASS I RAILWAY SYSTEM DESCRIPTIONS AND MAPS

### CLASS I RAILWAY SYSTEM DESCRIPTIONS AND MAPS

The largest source of uncertainty in this study was the lack of sp ecific data Canadian National, and Canadian Pacific railways. Given below are descriptions of each Class I railway system and systems maps where available.

In estimating state emissions using the proportion of track miles in ea ch state to the US totals, the largest uncertainty would be experienced when track miles are used disproportional to the system-wide averages.

Canadian National (Including Grand Trunk, Illinois Ce ntral, and Wisconsin Central)

There are two main Canadian National (CN) frei ght routes in terms of GTW (Ladd, 1999) in the US where Gross Tons are greater than 20. The first one is from the Port Huron – Detroit Michigan area through to Junction City, WI. The second route is the old Illinois Central line from Chicago to Louisiana. However, there ar e many slightly less busy routes in Wisconsin, Northern Michigan, Iowa, and Illinois. These ar e shown schematically in Figure 2-1. Not all CN lines are shown, especially in Wisconsin and Illi nois where the tracks originally acquired by the

Wisconsin Central and Illinois Centra l railroads are now owned by CNGT.

The most likely route undercounted is the very high activity line thr ough Indiana where track miles is low yet the freight traffic is high. In Illinois, the track m ileage from Indiana through Appleton, WI and from Chicago south splitt ing near Effingham and passing on through Cairo and Metropolis are the busiest CN lines; originally the Illinois Central. These are the main areas

where emissions will be underest imated under the current method.

Figure A-1. Canadian National main US operations.

### Canadian Pacific

Canadian Pacific’s (CP) main route in th e US operates from Detroit through Glenwood, Minnesota and on through North Dakota or north into Canada. A less important line runs from Chicago through Illinois and Indian a to Louisville. This is shown in Figure 2-2, however not all lines are shown in this figur e, only the major operations.

Because the route from Chicago through Minnesota is the most heavily traveled, the most likely

area for underestimation in this work would be found along this line. This line runs from Chicago to Milwaukee, west to La Crosse, WI and on through Minnesota. Another area of

misallocation is the northern Indiana track that ha s more activity than the southern Indiana track. So while the Indiana state totals may be accurate , the CP activity in Indiana may be misallocated.

Figure A-2. Canadian Pacific’s main US operations.



### CSX

CSX is the third largest railroad operating in the US and is of similar size to Norfolk Southern, the fourth largest railroad. CSX operates in almost all states (except Wisconsin) east of the Mississippi and none to the west as is shown in their system map in Figure 2-3. The main routes are widely and evenly disperse d throughout its system. There are several main routes in the LADCO area including (1) Chicago to Evansville , IN, (2) Chicago to Youngstown, OH, (3) St. Elmo, IL to Ashtabula, OH, (4) Detroit to Ci ncinnati, and (5) Toledo to Huntington, WV.

### Figure A-3. System map for CSX (Blue) and shortlines (Red) with which CSX does business.



### Kansas City Southern

Kansas City Southern (KCS) operates only in Illinois among the LADCO states on trackage rights from Springfield, IL to Chicago and on tr acks it acquired in the purchase of Gateway Western from Springfield passing into Missouri at Pike, IL. A spur track from Roodhouse, IL to East St. Louis is also operated by KCS. The sc hematic of the main KCS operations in Figure 2-4 shows clearly that Illinois operati ons are less important in the ove rall activity of Kansas City

Southern.

### Figure A-4. Kansas City Southern’s main US operations.



### Norfolk Southern

Norfolk Southern’s operations are shown in their system map in Figure 2-5. Norfolk Southern is largely an east coast railroad but operates acro ss Ohio, Indiana, and Il linois handling east-west traffic with key transfer point s for the LADCO states in Cinc innati, Columbus, OH, Detroit, Toledo, near St. Louis and Louisville, KY.

Figure A-5. Norfolk Southern system map

.

### Burlington Northern Santa Fe

BNSF operates three main east-west lines radia ting from Chicago as shown in Figure 2-6. One

runs across northern Illinois a nd skirts east of the Mississipp i toward Minneapolis. Two run across northern Illinois crossing into Iowa at Burlington and Ft. Madison. One main north-south route runs from Paducah, KY to Galesburg, IL. However, there are many smaller routes in Illinois as well as a short run into Superior, WI at Duluth. The survey data reflects the relative activity along each of these lines.

Figure A-6. BNSF System Map.



### Union Pacific

The UP system map is shown below in Figur e 2-7. The more signifi cant UP operations in

LADCO states occur in and across Illinois wher e the Wisconsin operations are less significant than it might appear from this map. Union Paci fic does not operate in Indiana, Michigan, or

Ohio.

### Figure A-7. Union Pacific System Map.

### APPENDIX B

REGRESSIONS RESULTS OF SCALED

WISCONSIN SURVEY RESULTS

### 1 

## 13 14 15 16 17 18

Fitted Values12 14 16 18ln(Gallons)



### 2.14 + 0.903*LogWaterSurfaceArea + 1.58*LogBoatsOverDistance R-Squared: 0.379 

# Inland -- Inboards

13 14 15 16

Fitted Values12 14 16 18ln(Gallons)



### 2.37 + 0.886*LogWaterSurfaceArea + 1.55*LogBoatsOverDistance R-Squared: 0.339 

# Inland -- Inboa rds without Winnebago County

Figure B - 1 Scatter plot of inboard activity on inland water.

### 2 

## 14 15 16 17 18

Fitted Values13 14 15 16 17 18 19ln(Gallons)



### 5 + 0.797*LogWaterSurfaceArea + 1.1*LogBoatsOverDistance R-Squared: 0.462 

# Inland -- Outboards

14 15 16 17 18

Fitted Values13 14 15 16 17 18 19ln(Gallons)



### 4.73 + 0.806*LogWaterSurfaceArea + 1.13*LogBoatsOverDistance R-Squared: 0.444



# Inland -- Outboards without Winnebago County

Figure B - 2 Scatter plot of outboard activity on inland water.

### 3 

## 14 15 16 17 18

Fitted Values14 15 16 17 18ln(Gallons)



### 0.038 + 1.39*LogShoreLineLength + 1.85*LogBoatsOverDistance R-Squared: 0.716 

# Lakes -- Inboards

14 15 16 17

Fitted Values14 15 16 17 18ln(Gallons)



### 0.392 + 1.31*LogShoreLineLength + 1.83*LogBoatsOverDistance R-Squared: 0.662 

# Lakes -- Inboards without Door County

Figure B - 3 Scatter plot of inboard activity on Great Lakes.

### 4 

## 15.0 15.5 16.0 16.5 17.0

Fitted Values14.5 15.0 15.5 16.0 16.5 17.0 17.5ln(Gallons)



### 9.44 + 0.785*LogShoreLineLength + 0.456*LogBoatsOverDistance R-Squared: 0.447 

# Lakes -- Outboards

15.0 15.2 15.4 15.6 15.8 16.0

Fitted Values14.5 15.0 15.5 16.0 16.5ln(Gallons)



### 10.1 + 0.509*LogShoreLineLength + 0.498*LogBoatsOverDistance R-Squared: 0.246 

# Lakes -- Outboards wi thout Door County

Figure B - 4 Scatter plot of outboard activity on Great Lakes.

### APPENDIX C

RECREATIONAL MARINE COUNTY ALLOCATION MAPSIL RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR 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.070.040.020.030.010.070.110.160.040.010.080.020.000.190.0246.590.020.000.070.080.010.340.010.000.010.060.000.100.180.010.020.240.000.090.010.090.010.020.080.020.080.040.120.010.240.090.020.0545.900.190.020.060.040.020.010.400.030.090.050.200.020.120.160.020.010.070.060.040.030.060.080.170.040.000.070.010.010.130.090.010.210.140.030.080.020.020.060.000.030.130.030.030.020.000.020.020.020.120.710.090.200.17IL 2002 REC MARINEINBOARDS: REVISED0.00 to 0.010.01 to 0.020.02 to 0.040.04 to 0.080.08 to 0.160.16 to 50.00IL RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR 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.590.650.100.020.060.191.230.880.320.000.270.130.021.200.0631.270.080.030.030.300.020.100.020.000.050.350.020.800.690.190.130.410.020.810.130.670.100.060.590.140.510.320.720.110.130.160.080.1340.020.530.080.160.060.030.020.290.100.190.160.620.130.511.000.110.030.320.380.240.140.350.180.460.240.000.760.140.100.510.760.061.000.410.140.350.160.060.380.000.020.370.240.110.180.020.050.060.270.490.490.830.220.61IL REC MARINEINBOARDS: DEFAULT0.00 to 0.020.02 to 0.100.10 to 0.160.16 to 0.320.32 to 0.600.60 to 50.00IL RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR OUTBOARDS1700117003170051700717009170111701317015170171701917021170231702517027170291703117033170351703717039170411704317045170471704917051170531705517057170591706117063170651706717069170711707317075170771707917081170831708517087170891709117093170951709717099171011710317105171071710917111171131711517117171191712117123171251712717129171311713317135171371713917141171431714517147171491715117153171551715717159171611716317165171671716917171171731717517177171791718117183171851718717189171911719317195171971719917201172030.400.350.160.120.050.320.660.690.260.040.440.160.021.040.1231.880.140.030.210.380.060.560.050.000.100.410.030.790.960.140.130.730.030.500.130.510.090.100.620.160.600.250.560.130.520.320.070.2734.150.660.170.250.180.100.070.740.160.420.310.870.170.540.840.160.040.380.360.270.180.340.320.810.330.030.430.110.100.560.620.100.970.660.280.420.150.130.340.030.130.650.260.200.150.020.160.130.160.531.450.760.650.72IL 2002 REC MARINEOUTBOARDS: REVISED0.00 to 0.100.10 to 0.150.15 to 0.300.30 to 0.500.50 to 0.650.65 to 50.00IL RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR OUTBOARDS1700117003170051700717009170111701317015170171701917021170231702517027170291703117033170351703717039170411704317045170471704917051170531705517057170591706117063170651706717069170711707317075170771707917081170831708517087170891709117093170951709717099171011710317105171071710917111171131711517117171191712117123171251712717129171311713317135171371713917141171431714517147171491715117153171551715717159171611716317165171671716917171171731717517177171791718117183171851718717189171911719317195171971719917201172030.620.680.100.020.070.201.280.920.330.000.280.130.021.250.0730.080.080.030.030.320.020.100.020.000.050.370.020.830.720.200.130.430.020.850.130.700.100.070.620.150.530.330.750.120.130.170.080.1339.930.550.080.170.070.030.020.300.100.200.170.650.130.531.050.120.030.330.400.250.150.370.180.480.250.000.800.150.100.530.800.071.050.430.150.370.170.070.400.000.020.380.250.120.180.020.050.070.280.520.520.870.230.63IL REC MARINEOUTBOARDS: DEFAULT0.00 to 0.050.05 to 0.110.11 to 0.180.18 to 0.380.38 to 0.700.70 to 50.00IN RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR INBOARDS18001180031800518007180091801118013180151801718019180211802318025180271802918031180331803518037180391804118043180451804718049180511805318055180571805918061180631806518067180691807118073180751807718079180811808318085180871808918091180931809518097180991810118103181051810718109181111811318115181171811918121181231812518127181291813118133181351813718139181411814318145181471814918151181531815518157181591816118163181651816718169181711817318175181771817918181181830.051.220.290.000.000.160.550.700.550.380.520.240.260.330.330.090.320.700.411.100.090.100.180.540.550.560.250.621.750.090.330.090.330.340.940.330.230.160.200.210.590.564.881.5525.783.740.280.333.741.150.260.582.230.130.620.301.760.090.510.500.370.450.3520.680.550.120.540.080.290.000.570.130.070.150.612.620.710.260.580.000.270.310.230.840.950.140.500.130.230.240.690.64IN 2002 REC MARINEINBOARDS: REVISED0.00 to 0.120.12 to 0.250.25 to 0.350.35 to 0.560.56 to 0.900.90 to 50.00IN RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR INBOARDS18001180031800518007180091801118013180151801718019180211802318025180271802918031180331803518037180391804118043180451804718049180511805318055180571805918061180631806518067180691807118073180751807718079180811808318085180871808918091180931809518097180991810118103181051810718109181111811318115181171811918121181231812518127181291813118133181351813718139181411814318145181471814918151181531815518157181591816118163181651816718169181711817318175181771817918181181830.060.440.370.000.000.060.680.440.310.120.440.000.500.930.250.120.120.370.810.620.000.000.310.810.441.620.120.560.750.060.250.060.310.120.810.680.190.000.250.120.191.312.681.1227.904.110.500.121.060.870.680.252.680.120.440.251.000.061.370.370.810.750.7521.861.740.120.310.000.250.000.560.370.060.370.442.181.060.370.500.000.560.190.441.121.250.251.060.310.120.060.560.37IN REC MARINEINBOARDS: DEFAULT0.00 to 0.120.12 to 0.240.24 to 0.400.40 to 0.700.70 to 1.201.20 to 30.00IN RECREATIONAL MARINE: 2002 REVISEDALLOCATION DISTRIBUTION FOR OUTBOARDS18001180031800518007180091801118013180151801718019180211802318025180271802918031180331803518037180391804118043180451804718049180511805318055180571805918061180631806518067180691807118073180751807718079180811808318085180871808918091180931809518097180991810118103181051810718109181111811318115181171811918121181231812518127181291813118133181351813718139181411814318145181471814918151181531815518157181591816118163181651816718169181711817318175181771817918181181830.091.460.470.000.000.210.780.920.790.640.860.350.560.700.510.170.520.910.841.600.160.210.320.790.811.090.381.091.230.130.650.130.470.481.250.600.400.270.360.380.691.134.472.2715.443.080.560.422.531.490.550.822.700.210.790.522.430.180.990.780.610.900.7513.521.100.210.750.160.480.000.920.250.100.350.902.721.270.450.810.000.420.560.441.391.260.260.950.290.360.380.880.91IN 2002 REC MARINEOUTBOARDS: REVISED0.00 to 0.200.20 to 0.400.40 to 0.700.70 to 0.890.89 to 1.251.25 to 50.00IN RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR OUTBOARDS18001180031800518007180091801118013180151801718019180211802318025180271802918031180331803518037180391804118043180451804718049180511805318055180571805918061180631806518067180691807118073180751807718079180811808318085180871808918091180931809518097180991810118103181051810718109181111811318115181171811918121181231812518127181291813118133181351813718139181411814318145181471814918151181531815518157181591816118163181651816718169181711817318175181771817918181181830.070.500.430.000.000.070.780.500.350.140.500.000.571.060.280.140.140.430.920.710.000.000.350.920.501.840.140.640.850.070.280.070.350.140.920.780.210.000.280.140.211.493.051.2824.752.980.570.141.210.990.780.283.050.140.500.281.130.071.560.430.920.850.8519.721.990.140.350.000.280.000.640.430.070.430.502.481.210.430.570.000.640.210.501.281.420.281.210.350.140.070.640.43IN REC MARINEOUTBOARDS: DEFAULT0.00 to 0.120.12 to 0.300.30 to 0.500.50 to 0.900.90 to 1.401.40 to 30.00MI RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR INBOARDS26001260032600526007260092601126013260152601726019260212602326025260272602926031260332603526037260392604126043260452604726049260512605326055260572605926061260632606526067260692607126073260752607726079260812608326085260872608926091260932609526097260992610126103261052610726109261112611326115261172611926121261232612526127261292613126133261352613726139261412614326145261472614926151261532615526157261592616126163261650.600.621.251.130.861.610.530.222.630.601.820.110.110.110.510.863.040.100.070.042.660.020.051.710.340.080.162.390.050.080.734.380.050.061.240.060.050.270.190.060.310.470.030.243.380.110.440.262.979.090.870.710.890.120.520.110.054.630.150.063.350.142.060.990.100.260.040.030.063.321.210.340.179.790.132.210.610.061.260.490.2916.200.07MI 2002 REC MARINEINBOARDS: REVISED0.00 to 0.060.06 to 0.120.12 to 0.340.34 to 0.860.86 to 2.402.40 to 20.00MI RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR INBOARDS26001260032600526007260092601126013260152601726019260212602326025260272602926031260332603526037260392604126043260452604726049260512605326055260572605926061260632606526067260692607126073260752607726079260812608326085260872608926091260932609526097260992610126103261052610726109261112611326115261172611926121261232612526127261292613126133261352613726139261412614326145261472614926151261532615526157261592616126163261652.649.712.392.760.400.870.680.050.581.332.480.030.020.042.310.533.290.020.010.012.530.020.011.220.020.020.980.550.000.021.413.320.000.023.200.100.010.040.040.020.0412.660.020.025.380.020.042.433.050.321.823.941.840.030.850.010.020.490.030.032.380.040.081.870.025.750.020.010.032.594.620.130.010.490.041.591.800.000.311.150.030.310.02MI REC MARINEINBOARDS: DEFAULT0.00 to 0.020.02 to 0.040.04 to 0.600.60 to 1.801.80 to 3.003.00 to 20.00MI RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR OUTBOARDS26001260032600526007260092601126013260152601726019260212602326025260272602926031260332603526037260392604126043260452604726049260512605326055260572605926061260632606526067260692607126073260752607726079260812608326085260872608926091260932609526097260992610126103261052610726109261112611326115261172611926121261232612526127261292613126133261352613726139261412614326145261472614926151261532615526157261592616126163261651.071.011.721.182.460.450.821.691.051.452.180.970.901.051.482.791.760.950.520.421.370.380.471.511.680.740.902.120.390.670.951.430.380.541.440.880.431.821.490.601.950.640.391.172.150.812.080.962.131.221.131.761.291.120.600.870.511.161.180.661.451.265.650.800.910.660.470.380.681.591.312.861.131.181.200.471.650.411.031.311.531.460.74MI 2002 REC MARINEOUTBOARDS: REVISED0.00 to 0.500.50 to 0.800.80 to 1.201.20 to 1.401.40 to 2.002.00 to 20.00MI RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR OUTBOARDS26001260032600526007260092601126013260152601726019260212602326025260272602926031260332603526037260392604126043260452604726049260512605326055260572605926061260632606526067260692607126073260752607726079260812608326085260872608926091260932609526097260992610126103261052610726109261112611326115261172611926121261232612526127261292613126133261352613726139261412614326145261472614926151261532615526157261592616126163261652.7810.262.502.800.320.800.450.050.481.352.520.030.020.042.420.442.910.020.010.012.120.030.011.060.020.020.950.370.000.021.253.270.000.023.340.110.010.040.040.020.0413.460.020.025.460.030.042.522.750.241.844.011.870.040.750.020.020.350.030.042.380.050.091.910.026.050.020.020.032.664.770.140.020.300.041.571.770.000.261.190.030.170.02MI REC MARINEOUTBOARDS: DEFAULT0.00 to 0.020.02 to 0.210.21 to 1.201.20 to 2.002.00 to 5.005.00 to 20.00OH RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR INBOARDS390013900339005390073900939011390133901539017390193902139023390253902739029390313903339035390373903939041390433904539047390493905139053390553905739059390613906339065390673906939071390733907539077390793908139083390853908739089390913909339095390973909939101391033910539107391093911139113391153911739119391213912339125391273912939131391333913539137391393914139143391453914739149391513915339155391573915939161391633916539167391693917139173391750.030.040.086.230.040.070.080.070.100.070.030.100.130.020.130.090.0226.220.010.050.3112.910.070.010.240.030.050.130.020.110.230.060.010.100.050.070.030.030.040.020.100.0613.760.040.070.1410.627.700.020.240.000.120.040.170.050.030.080.060.040.160.0714.670.030.030.090.040.490.050.020.110.081.020.050.030.020.230.340.300.120.030.010.030.180.070.140.020.060.03OH 2002 REC MARINEINBOARDS: REVISED0.00 to 0.030.03 to 0.050.05 to 0.080.08 to 0.130.13 to 0.300.30 to 50.00OH RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR INBOARDS390013900339005390073900939011390133901539017390193902139023390253902739029390313903339035390373903939041390433904539047390493905139053390553905739059390613906339065390673906939071390733907539077390793908139083390853908739089390913909339095390973909939101391033910539107391093911139113391153911739119391213912339125391273912939131391333913539137391393914139143391453914739149391513915339155391573915939161391633916539167391693917139173391750.030.050.0516.380.030.010.090.070.060.100.020.080.120.030.050.080.0119.140.010.060.3010.760.060.010.070.010.050.100.030.140.120.040.000.160.070.100.020.020.030.030.030.0518.380.030.030.1810.756.110.010.180.000.030.060.220.040.030.050.090.030.170.1211.630.050.050.100.050.330.030.000.070.101.010.080.030.030.100.160.410.090.000.010.020.160.100.020.030.070.04OH REC MARINEINBOARDS: DEFAULT0.00 to 0.020.02 to 0.040.04 to 0.070.07 to 0.100.10 to 0.230.23 to 30.00OH RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR OUTBOARDS390013900339005390073900939011390133901539017390193902139023390253902739029390313903339035390373903939041390433904539047390493905139053390553905739059390613906339065390673906939071390733907539077390793908139083390853908739089390913909339095390973909939101391033910539107391093911139113391153911739119391213912339125391273912939131391333913539137391393914139143391453914739149391513915339155391573915939161391633916539167391693917139173391750.120.150.239.540.170.240.310.210.230.280.110.290.340.080.400.330.0720.530.060.180.709.420.210.040.550.090.230.320.070.400.440.170.030.380.150.240.130.130.120.090.370.2013.610.190.240.4110.776.910.060.590.000.280.180.520.160.140.220.250.130.550.268.230.090.130.280.181.090.160.070.310.300.760.210.100.080.630.720.730.430.090.050.110.440.290.390.070.150.11OH 2002 REC MARINEOUTBOARDS: REVISED0.00 to 0.100.10 to 0.160.16 to 0.250.25 to 0.400.40 to 0.700.70 to 50.00OH RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR OUTBOARDS390013900339005390073900939011390133901539017390193902139023390253902739029390313903339035390373903939041390433904539047390493905139053390553905739059390613906339065390673906939071390733907539077390793908139083390853908739089390913909339095390973909939101391033910539107391093911139113391153911739119391213912339125391273912939131391333913539137391393914139143391453914739149391513915339155391573915939161391633916539167391693917139173391750.040.060.0617.140.040.010.100.080.070.110.020.090.140.030.060.090.0120.240.010.070.339.780.070.010.080.010.060.110.030.160.140.050.000.180.080.110.020.020.040.030.030.0619.310.040.040.2111.105.760.010.210.000.040.070.250.050.040.060.100.040.200.149.770.060.060.120.060.370.030.000.080.110.330.090.040.040.120.180.460.100.000.010.020.180.120.020.030.080.05OH REC MARINEOUTBOARDS: DEFAULT0.00 to 0.020.02 to 0.040.04 to 0.070.07 to 0.100.10 to 0.230.23 to 30.00WI RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR INBOARDS5500155003550055500755009550115501355015550175501955021550235502555027550295503155033550355503755039550415504355045550475504955051550535505555057550595506155063550655506755069550715507355075550775507855079550815508355085550875508955091550935509555097550995510155103551055510755109551115511355115551175511955121551235512555127551295513155133551355513755139551410.800.460.251.934.670.680.080.771.530.321.100.295.300.2310.762.010.030.020.281.600.100.410.110.650.000.230.220.450.942.410.934.190.000.200.532.660.321.050.000.088.880.000.243.390.851.260.140.860.330.650.092.810.000.830.041.740.471.411.032.540.030.330.561.493.800.370.856.081.440.608.250.05WI 2002 REC MARINEINBOARDS: REVISED0.00 to 0.090.09 to 0.320.32 to 0.650.65 to 1.051.05 to 2.542.54 to 11.00WI RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR INBOARDS5500155003550055500755009550115501355015550175501955021550235502555027550295503155033550355503755039550415504355045550475504955051550535505555057550595506155063550655506755069550715507355075550775507855079550815508355085550875508955091550935509555097550995510155103551055510755109551115511355115551175511955121551235512555127551295513155133551355513755139551410.3310.800.225.961.320.210.480.630.250.030.180.220.290.2017.761.920.090.060.080.350.260.290.000.210.041.440.100.210.304.156.540.220.010.120.197.950.251.500.070.068.200.061.660.910.037.240.130.120.320.130.213.980.030.040.150.110.090.770.146.620.080.060.171.190.170.350.040.200.110.091.140.14WI REC MARINEINBOARDS: DEFAULT0.00 to 0.070.07 to 0.140.14 to 0.210.21 to 0.350.35 to 2.002.00 to 18.00WI RECREATIONAL MARINE: 2002 REVISED ALLOCATION DISTRIBUTION FOR OUTBOARDS5500155003550055500755009550115501355015550175501955021550235502555027550295503155033550355503755039550415504355045550475504955051550535505555057550595506155063550655506755069550715507355075550775507855079550815508355085550875508955091550935509555097550995510155103551055510755109551115511355115551175511955121551235512555127551295513155133551355513755139551411.220.671.562.071.971.061.130.602.760.311.580.633.501.293.340.870.420.580.301.051.460.720.021.250.331.810.340.970.531.200.552.150.280.851.390.731.792.190.860.420.780.042.057.050.430.200.080.181.721.190.771.750.041.260.680.241.323.741.831.220.340.600.478.351.841.411.164.952.120.874.560.03WI 2002 REC MARINEOUTBOARDS: REVISED0.00 to 0.340.34 to 0.680.68 to 1.001.00 to 1.401.40 to 2.002.00 to 12.00WI RECREATIONAL MARINE: DEFAULT ALLOCATION DISTRIBUTION FOR OUTBOARDS5500155003550055500755009550115501355015550175501955021550235502555027550295503155033550355503755039550415504355045550475504955051550535505555057550595506155063550655506755069550715507355075550775507855079550815508355085550875508955091550935509555097550995510155103551055510755109551115511355115551175511955121551235512555127551295513155133551355513755139551410.3611.110.245.180.850.220.520.680.270.030.190.230.320.2217.011.580.100.060.080.380.280.310.000.230.051.450.110.230.324.296.630.240.010.130.218.060.271.350.080.068.450.061.390.980.037.820.140.130.350.140.234.090.030.050.160.120.090.830.156.760.080.070.191.280.180.380.040.220.120.101.240.15WI REC MARINEOUTBOARDS: DEFAULT0.00 to 0.080.08 to 0.150.15 to 0.230.23 to 0.380.38 to 1.601.60 to 18.00

### APPENDIX D

GEOGRAPHIC ALLOCATION COMPARISON TABLES

(CD ROM)

### APPENDIX E

COUNTY EMISSION ESTIMATES

(CD ROM)