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Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making (2014)

Chapter: Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports

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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Suggested Citation:"Appendix C - Origin-Destination Corridors and Modal Assignment at Selected Ports." National Academies of Sciences, Engineering, and Medicine. 2014. Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making. Washington, DC: The National Academies Press. doi: 10.17226/22241.
×
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

43 The description of each port’s freight flows is broken into two parts: (1) the description of the most important origin- destination corridors and (2) the modal assignments for these corridors. For easier reading, all tonnages in the modal assignment parts are stated in thousands; therefore, a number such as “753” indicates 753,000. Duluth, MN (Great Lakes) Duluth Origin-Destination Corridors There were no FAF3 data available for waterborne ship- ments into or out of the port of Duluth. However, the Corps was able to provide a breakdown of the tonnages and values for the primary waterborne corridors between Duluth and other U.S. Great Lakes ports. Tables C-1 through C-4 sum- marize these corridors. Duluth Modal Assignments by Corridor Table C-5 is a copy of Table 1 in the main body of this report that showed the commodity flow statistics for Duluth for easy reference. For the surface transportation segments, iron ore is 100 per- cent transported by rail on the Mountain Iron-Duluth rail segment; coal is 100 percent transported by rail on the Staples- Duluth segment. A very high percentage of the 38,300 tons of iron ore produced in Minnesota in 2010 was transported by rail on the Duluth, Missabe, and Iron Range Railway (DM&IR), so the researchers assigned 100 percent of iron ore traffic to this segment. Figure C-1 shows the relevant rail segments. A complete analysis of the waterborne traffic network to which Duluth/Superior is connected was beyond the scope of this study. In order to show how the model would work, the researchers developed a case in which Burns Harbor and/or St. Clair would need dredging in addition to Duluth/Superior for the tonnage increases to occur. The researchers used the numbers provided by the Corps to allocate waterborne flows to Duluth-Burns Harbor and Duluth-St. Clair River. All other flows were allocated to a fictitious “all other ports” segment with the assumption that no ports other than Burns and St. Clair would present constraints. Figure C-2 shows the rel- evant waterway segments. There were no relevant highway segments for Duluth. Hampton Roads, VA (Coastal) Hampton Roads Origin-Destination Corridors Using FAF3 data, the researchers summarized the primary corridors for these commodities. As it turns out, CPT data indicate that the only commodity using the bottom 3 ft of water depth is export coal. Therefore, while the total cargo mix is very diverse and geographically dispersed, the model focused exclusively on export coal, making Hampton Roads one of the simpler port communities to evaluate. Table C-6 and Table C-7 summarize the coal movements. A brief description of the other commodities handled at Hampton Roads can be found in the body of the report. Hampton Roads Modal Assignments by Corridor In the case of Hampton Roads, the researchers discovered that the only cargo flow that used the 47–50 ft stratum of the ship channel was export coal. Coal is delivered to the port exclusively by rail. The average export coal tonnages at Newport News and Nor- folk Harbor were used to allocate the coal tonnages to the two servicing railroads: CSX and Norfolk Southern. It was assumed that all export coal would be moved by rail and that the propor- tion of coal shipped out of each of the two terminal areas would be similar to the proportion of coal transported by each of the A P P E N D I X C Origin-Destination Corridors and Modal Assignment at Selected Ports

44 Commodity Category (Code) Coal, Lignite & Coal Coke (10) 19,825 Iron Ore and Iron & Steel Waste & Scrap (44) 15,630 Total 35,455 Total All Commodities 40,721 Average Annual Tonnage 2006–2010 (in 000s) Table C-5. Commodity tonnage—Duluth. [48.1% of all Waterborne Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share Wyoming 45.9% Rail 100% Montana 45.8% Rail 100% All Others (95 entries) 8.3% Table C-1. Inbound coal for shipment from Duluth, MN (FAF3 data). [38.3 % of all Waterborne Commodity Flows] Domestic Origin % of Total Mode Modal Share Burns Harbor, IN 33.5% Water 100% Indiana Harbor, IN 19.0% Water 100% Detroit River, MI 14.7% Water 100% Gary, IN 13.4% Water 100% All Others (9 entries) 19.4% Table C-4. Outbound iron ore shipped from Duluth, MN (Corps data). [38.3% of all Waterborne Commodity Flows—100.0% of FAF3 data sampled] Domestic Origin % of Sample Total Mode Modal Share Remainder of Minnesota 100.0% Rail Multi 59% 41% Table C-3. Inbound iron ore for shipment from Duluth, MN (FAF3 data). [48.1% of all Waterborne Commodity Flows] Domestic Origin % of Total Mode Modal Share St. Clair River, MI 58.4% Water 100% North Marquette, MI 11.8% Water 100% Monroe, MI 7.4% Water 100% Muskegon Harbor, MI 6.0% Water 100% All Others (13 entries) 16.4% Table C-2. Outbound coal shipped from Duluth, MN (Corps data). two railroads because each terminal is served by only one of the two railroads. Figure C-3 shows the relevant rail segments. For the waterborne segments, the researchers simply divided the tonnage coming into and out of Hampton Roads between Norfolk Harbor and Newport News Channel based on his- torical data from Waterborne Commerce Statistics (11). The effect of increased tonnage was factored in by taking the total potential increase and dividing it between the two port areas based on their share of coal shipments for the period of 2006 to 2010. Figure C-4 shows the relevant waterway segments. There were no relevant highway segments for Hampton Roads.

45 Table C-6. Coal imports for Hampton Roads, VA. [2.4% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share Richmond VA MSA 100% Rail 100% Table C-7. Coal exports for Hampton Roads, VA. [59.9% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share Norfolk VA-NC MSA (VA Part) 100% Rail 100% Figure C-1. Rail segments for Duluth, MN. Figure C-2. Waterway segments for Duluth, MN.

46 Figure C-3. Rail segments for Hampton Roads, VA. Figure C-4. Waterway segments for Hampton Roads, VA.

47 Huntington, WV (Inland) Huntington Origin-Destination Corridors The researchers examined the top origin-destination water- way segment pairs in terms of tonnage. They totaled all of the tonnage handled by those waterway segments—not just ton- nage included in the top origin-destination flows, but all of the tonnage that moved through these waterway segments—until the segment set included at least 80 percent of the tonnage associated with the Port of Huntington (origins in the port, destinations in the port, and traffic passing through the port).7 Twenty-three river segments were selected as a result of this analysis for coal. The researchers performed a thorough exami- nation of the 23 river segments and identified approximately 212 docks located at approximately 170 different facilities on these segments that could have handled any of the four selected commodities. The researchers identified 102 coal docks. The remainder could handle one of the remaining three commodi- ties or a combination of two or more of the four commodities. While this project relies on the facilities data described earlier, a close inspection of the dataset revealed inconsistencies between Port Series8 report information and port facility spreadsheet information, particularly when applicable Port Series reports are more dated. Google Earth imaging also suggests some lim- ited inconsistencies between information contained in Corps’ datasets and actual facility usage. The researchers conducted a similar analysis of the other three major commodity categories: sand and gravel; distillate/fuel oil; and gasoline, jet fuel, and kerosene. With all four commodities, a total of 30 segments were identified as origins or destinations on the waterway. The fact that only seven new segments were added with the additional three commodities illustrates the dominant position of coal in the tonnage figures and the high level of industrialization along the river. Table C-8 lists the segments. 7The actual percentage was 84.3 percent. 8This report series was discontinued by the Corps during the execution of the research project. The U. S. Army Corps of Engineers Navigation Data Center used to produce Port Series report books that described the physical and inter- CPT Segment Number CPT River Segment Description Approximate Geography 200367 Monongahela River, PA and WV (Mile 016 to Mile 128) From Grays Landing Lock and Dam to Maxwell Lock and Dam 200380 Monongahela River, PA and WV (Mile 016 to Mile 128) Lock and Dam 3 to mouth of Youghiogheny River (McKeesport, PA) 200728 Ohio River, OH WV PA-LRP (Mile 808 to Mile 981) Chester, WV, to New Cumberland Lock and Dam 200729 Ohio River, OH WV PA-LRP (Mile 808 to Mile 981) New Cumberland Lock and Dam to Pike Island Lock and Dam 200730 Ohio River, OH WV PA-LRP (Mile 808 to Mile 981) Pike Island Lock and Dam to point downstream of Clarington, OH 200739 Ohio River, OH WV PA-LRP (Mile 808 to Mile 981) Hannibal Locks and Dam to Willow Island Locks and Dam 200800 Ohio River, KY OH WV PA-LRH (Mile 796 to Mile 807) Junction with Muskingum River at Marietta, OH, to junction with Little Kanawha River at Parkersburg, WV 200900 Ohio River, KY OH WV PA-LRH (Mile 715 to Mile 795) Mouth of Kanawha River to Racine Locks and Dam 201010 Ohio River, KY OH WV PA-LRH (Mile 664 to Mile 714) Huntington, WV, to Gallipolis Locks and Dam 201020 Ohio River, KY OH WV PA-LRH (Mile 664 to Mile 714) Huntington, WV, to Mouth of Big Sandy River 201120 Ohio River, KY OH WV PA-LRH (Mile 512 to Mile 663) Greenup Lock and Dam to Concord, KY 201129 Ohio River, KY OH WV PA-LRH (Mile 512 to Mile 663) Concord, KY, to Meldahl Lock and Dam 201130 Ohio River, KY OH WV PA-LRH (Mile 512 to Mile 663) Meldahl Lock and Dam to point just upstream of New Richmond, OH 201140 Ohio River, KY OH WV PA-LRH (Mile 512 to Mile 663) Point just upstream of New Richmond, OH, to Mouth of Licking River (Cincinnati, OH) 201210 Ohio River, IL KY IN OH-LRL (Mile 435 To Mile 511) Lawrenceburg, IN, to location upstream (WNW) of Hamilton, KY 201219 Ohio River, IL KY IN OH-LRL (Mile 435 to Mile 511) Location upstream (WNW) of Hamilton, KY, to Markland Locks and Dam Table C-8. Origin-destination river segments for Huntington. (continued on next page) modal (infrastructure) characteristics of the coastal, Great Lakes, and inland ports of the United States. That information is now published in the Master Docks dataset. This dataset was available at http://www.navigationdatacenter. us/ports/data/mdplus_public_extract.zip as of February 19, 2014.

48 CPT Segment Number CPT River Segment Description Approximate Geography 201220 Ohio River, IL KY IN OH-LRL (Mile 435 to Mile 511) Markland Locks and Dam to mouth of Kentucky River (Carrollton, KY) 201230 Ohio River, IL KY IN OH-LRL (Mile 435 to Mile 511) Mouth of Licking River (Cincinnati, OH) to Lawrenceburg, IN 201310 Ohio River, IL KY IN OH-LRL (Mile 196 to Mile 434) Mouth of Kentucky River (Carrollton, KY) to downtown Louisville, KY 201330 Ohio River, IL KY IN OH-LRL (Mile 196 to Mile 434) West side of downtown Louisville, KY to Leavenworth, IN 201349 Ohio River, IL KY IN OH-LRL (Mile 196 to Mile 434) Lewisport, KY, to Newburgh Lock and Dam 201710 Ohio River, IL KY-MVS (Mile 000 to Mile 043) Lock and Dam 52 to just upstream of Joppa, IL 201919 Kanawha River, WV (Mile 00 to Mile 58) Winfield, WV to confluence with Ohio River 202020 Big Sandy River, KY WV (Mile 000 to Mile 232) All of Big Sandy River 212917 Kanawha River, WV (Mile 59 to Mile 95) London Locks and Dam to Longacre, WV 212918 Kanawha River, WV (Mile 59 to Mile 95) London Locks and Dam to Marmet Locks and Dam 222120 Upper Mississippi, MO IL-MVS (Mile 000 to Mile 117) From point just downstream of Chester, IL, to mouth of Ohio River 221920 Upper Mississippi, MO IL-MVS (Mile 118 to Mile 195) From south of St. Louis to junction with Kaskaskia River 235180 Lower Mississippi, LA-MVN (Mile 107 to Mile 227) From Garyville, LA, to Jefferson, LA, just downstream of Highway 90 Bridge 271500 Lower Mississippi, LA-MVN (Mile 039 to Mile 087) From Algiers Canal to Freeport Sulphur Canal Table C-8. (Continued). Super Segment CPT Segments Segment 1 (Monongahela River) 200367 200380 Segment 2 (Upper Ohio River) 200728 200729 200730 200739 200800 200900 Segment 3 (Kanawha River) 212917 212918 201919 Segment 4 (Ohio River— Huntington) 201010 201020 Segment 5 (Big Sandy River) 202020 Segment 6 (Lower Ohio River) 201120 201129 201130 201140 201210 201219 201220 210230 201310 201330 210349 201710 Segment 7 (Upper Mississippi River) 221920 222120 Segment 8 (Lower Mississippi River) 235180 271500 Table C-9. Consolidated river segments for Huntington. After a thorough examination of these segments, the researchers determined that many of the segments could be combined into consolidated segments while still maintain- ing the origin-destination flows of the various commodities. This was done by consolidating segments based on their geo- graphical position relative to proposed maintenance projects. This made the model simpler to execute and understand. Table C-9 shows how the consolidated segments were formed. Huntington Modal Assignments by Corridor There are no significant rail or highway flows associated with the waterborne cargo for Huntington. A very high per- centage of the shipments take place between waterfront facili- ties. While there is rail traffic through the area, there did not appear to be any significant rail flows for any waterborne ori- gins or destination associated with the segments included in the analysis. A detailed examination of the segments indicated that in a high percentage of cases, the origin/destination site was the actual origin or final destination of the product in its transported state (prior to consumption or transformation). Waterborne flows were allocated based on a detailed analysis of trip data provided by the Corps. The researchers developed segment flows and then extrapolated those numbers to reach a tonnage amount equal to the total tonnage for Huntington. Figure C-5 shows the relevant waterway segments.

49 Plaquemines, LA (Dual Coastal/Inland) Plaquemines Origin-Destination Corridors The tables below that report domestic cargo flows show a percentage based on all commodity flows in the table. Although domestic cargo flows are not shown in the sum- mary totals provided in Table 4 (of the main report) in the introductory descriptions of the case study ports, the percent- ages in all of the following tables are expressed as a percentage Figure C-5. Waterway segments for Huntington, WV. of the Table 4 total tonnage in order to allow the reader to evaluate the relative volume of cargo included in the tables. Using FAF3 data, the researchers summarized the primary corridors for these commodities. Tables C-10 through C-28 summarize these corridors. There were no corn and wheat imports for Plaquemines, Louisiana. Crude exports are negligible for Plaquemines. There are negligible oilseed imports for Plaquemines, Louisiana. [2.6% of all Commodity Flows]* Domestic Destination % of FAF3 Total Mode Modal Share Raleigh-Durham NC CMSA 45.0% Multi Truck 78% 22% Tampa FL MSA 25.0% Multi Water 78% 19% Atlanta GA-AL CMSA (GA Part) 20.0% Rail 88% All Others (3 entries) 10.0% *The Corps and FAF data did not agree on the distribution of coal with regard to imports, exports, and coastwise shipments. The Corps reported significant coastwise shipments where FAF had none. The researchers split coastwise shipments into imports/exports using the percentages for total coal for purposes of computing this number. Table C-10. Coal imports for Plaquemines, LA.

50 [Total Domestic: 6.6% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 97.2% Water 100% All Others (23 entries) 2.8% Table C-15. Crude oil domestic outbound for Plaquemines, LA. [Total Domestic: 6.6% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 67.8% Water 100% Houston TX CMSA 16.9% Water 100% All Others (39 entries) 15.3% Table C-14. Crude oil domestic inbound for Plaquemines, LA. [9.5% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share New Orleans LA CMSA 88.1% Unknown 84% All Others (3 entries) 11.9% Table C-13. Crude oil imports for Plaquemines, LA. [15.8% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share Remainder of Illinois 30.4% Water Rail 65% 19% Minneapolis-St. Paul MN-WI CMSA (MN Part) 18.6% Water 100% Miami FL MSA 8.4% Multi Water 55% 38% Remainder of Missouri 6.5% Water 100% New Orleans LA CMSA 6.2% Water Rail Truck 52% 26% 16% St. Louis MO-IL CMSA (MO Part) 5.4% Water 100% Kansas City MO-KS CMSA (KS Part) 4.2% Rail Water 69% 25% New York NY-NJ-CT-PA CMSA (CT Part) 3.8% Other/Unknown Multi 76% 22% All Others (37 entries) 16.5% Table C-12. Corn and wheat exports for Plaquemines, LA. [11.0% of all Commodity Flows]* Domestic Origin % of FAF3 Total Mode Modal Share New York NY-NJ-CT-PA CMSA (CT Part) 79.8% Other/Unknown Multi 72% 21% Baltimore MD MSA 5.3% Truck Rail 64% 32% All Others (9 entries) 14.9% *The Corps and FAF data did not agree on the distribution of coal with regard to imports, exports, and coastwise shipments. The Corps reported significant coastwise shipments where FAF had none. The researchers split coastwise shipments into imports/exports using the percentages for total coal for purposes of computing this number. Table C-11. Coal exports for Plaquemines, LA.

51 [Total Domestic: 7.3% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share Chicago IL-IN-WI CMSA (IL Part) 50.0% Water 100% New Orleans LA CMSA 36.5% Water 100% All Others (6 entries) 13.5% Table C-18. Asphalt domestic inbound for Plaquemines, LA. [3.2% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share New Orleans LA CMSA 95.1% Pipeline Water Multi 43% 34% 12% All Others (5 entries) 4.9% Table C-20. Fuel oil imports for Plaquemines, LA. [Total Domestic: 7.3% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 52.3% Water 100% Lake Charles LA CMSA 15.9% Houston TX CMSA 12.0% All Others (9 entries) 19.8% Table C-19. Asphalt domestic outbound for Plaquemines, LA. [6.4% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 82.9% Water Pipeline 67% 20% All Others (12 entries) 17.1% Table C-17. Asphalt exports for Plaquemines, LA. [0.0% of all Commodity Flows]* Domestic Destination % of FAF3 Total Mode Modal Share Houston TX CMSA 56.9% Pipeline Multi 66% 24% Baton Rouge LA CMSA 9.8% Pipeline Water 52% 45% New Orleans LA CMSA 9.2% Water Pipeline 66% 21% Remainder of Kentucky 6.0% Water 80% All Others (42 entries) 18.1% *The Corps did not report any asphalt imports, whereas FAF3 reported a small amount. The FAF3 commodity flows are shown for the sake of completeness, even though they are a small number and were not reported by the Corps. Table C-16. Asphalt imports for Plaquemines, LA. [1.8% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 99.6% Pipeline Water Multi 43% 34% 13% All Others (2 entries) 0.4% Table C-21. Fuel oil exports for Plaquemines, LA.

[Total Domestic: 10.3% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 60.1% Water 100% Beaumont TX MSA 12.9% Water 100% Houston TX CMSA 7.0% Water 100% All Others (23 entries) 20.0% Table C-23. Fuel oil domestic outbound for Plaquemines, LA. [Total Domestic: 5.5% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share Mississippi 18.2% Water 100% Remainder of Missouri 13.3% Water 100% Arkansas 13.0% Water 100% Remainder of Illinois 12.2% Water 100% Iowa 11.4% Water 100% St. Louis MO-IL CMSA (MO Part) 8.1% Water 100% Memphis TN-MS-AR MSA (TN Part) 6.4% Water 100% All Others (6 entries) 17.4% Table C-25. Oilseed domestic inbound for Plaquemines, LA. [6.6% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share Minneapolis-St. Paul MN-WI CMSA (MN Part) 18.0% Water 100% Remainder of Illinois 15.9% Water Rail 75% 19% St. Louis MO-IL CMSA (MO Part) 15.8% Water 95% New York NY-NJ-CT-PA CMSA (NY Part) 13.3% Truck 96% New Orleans LA CMSA 7.1% Truck Water 43% 38% Memphis TN-MS-AR MSA (TN Part) 5.2% Multi 83% Kansas City MO-KS CMSA (KS Part) 3.8% Rail Truck 67% 31% Mississippi 3.4% Water 92% All Others (62 entries) 17.5% Table C-24. Oilseed exports for Plaquemines, LA. [Total Domestic: 10.3% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 44.1% Water 100% Remainder of Louisiana 37.6% Water 100% All Others (3 entries) 18.3% Table C-22. Fuel oil domestic inbound for Plaquemines, LA. [0.0% of all Commodity Flows]* Domestic Destination % of FAF3 Total Mode Modal Share New Orleans LA CMSA 62.7% Pipeline Truck Water 52% 25% 23% Houston TX CMSA 34.1% Pipeline Multi Water 40% 38% 22% All Others (34 entries) 3.2% *The Corps did not report any gasoline imports, whereas FAF3 reported a small amount. The FAF3 commodity flows are shown for the sake of completeness, even though they are a small number and were not reported by the Corps. Table C-26. Gasoline imports for Plaquemines, LA.

53 [1.5% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 100% Pipeline Truck Water 52% 25% 23% Table C-27. Gasoline exports for Plaquemines, LA. [Total Domestic: 4.0% of all Commodity Flows] Origin % of FAF3 Total Mode Modal Share New Orleans LA CMSA 44.2% Water 100% Tampa FL MSA 21.8% Water 100% Houston TX CMSA 19.3% Water 100% All Others (3 entries) 14.7% Table C-28. Gasoline domestic outbound for Plaquemines, LA. Figure C-6. Waterway segments for Plaquemines, LA. Plaquemines Modal Assignments by Corridor In developing the original modal breakdown based on the FAF3 data, the researchers had to use the New Orleans MSA because there was nothing explicitly for Plaquemines in the FAF3 dataset. This showed a high percentage of flows by water, with significant amounts of tonnage taking place by rail and truck in certain instances. However, a close examina- tion of the Port of Plaquemines, its surrounding infrastruc- ture, and its historical freight flows indicates that very little moves into or out of Plaquemines by truck or rail. It is almost entirely a transfer point between inland waterway barges and deep sea vessels or direct shipments into and out of waterside facilities. Given this background, the researchers assigned all traffic into and out of Plaquemines to the water mode. The research- ers simply divided the tonnage between internal traffic ( Mississippi River) and deep sea traffic (Gulf of Mexico). Figure C-6 shows the relevant waterway segments.

54 [0.8% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share Idaho 63.5% Rail 97% Philadelphia PA-NJ-DE-MD CMSA (PA Part) 18.9% Rail Truck 73% 24% All Others (7 entries) 17.6% Table C-32. Fertilizer imports for Portland, OR. [10.8% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share Remainder of Washington 77.9% Truck 91% Los Angeles CA CMSA 8.4% Multi Truck 51% 49% All Others (23 entries) 13.7% Table C-31. Chemical exports for Portland, OR. [2.0% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share Montana 51.3% Truck 90% Remainder of Washington 20.4% Truck 92% Idaho 8.2% Truck 100% All Others (47 entries) 20.0% Table C-30. Chemical imports for Portland, OR. [37.9% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share Portland OR-WA MSA (OR Part) 24.0% Other/ Unknown 97% Philadelphia PA-NJ-DE-MD CMSA (NJ Part) 18.8% Other/ Unknown 92% Remainder of Washington 16.6% Rail Truck 52% 35% Los Angeles CA CMSA 12.5% Rail Multi Water 51% 27% 20% Minneapolis-St. Paul MN-WI CMSA (MN Part) 10.5% Multi Rail Water 47% 31% 19% All Others (19 entries) 17.5% Table C-29. Wheat exports for Portland, OR. Portland, OR (Coastal) Portland (Coastal) Origin-Destination Corridors Using FAF3 data, the researchers summarized the primary corridors for the highest volume commodities. Tables C-29 through C-38 summarize these corridors. There were no wheat imports for Portland, Oregon. There were no gasoline exports for Portland, OR. Fuel oil exports were negligible. Manufactured exports were negligible. Portland (Coastal) Modal Assignments by Corridor The modal allocations for Portland were very detailed and complex. Table C-39 is a copy of Table 5 (from the main report) that provides the control totals that were used to accomplish the modal allocations. The FAF3 “% of all commodity flows,” shown in the first line of Tables C-40 through C-49 (37.9 percent in Table C-40), only accounts for 70.3 percent of the total tonnage flows in FAF for Coastal, Imports, and Exports—the “Total All Com- modities” value of 24,911 thousand tons shown in Table C-39.

55 [0.2% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share Portland OR-WA MSA (OR Part) 74.9% Truck 100% Remainder of Oregon 11.2% Truck 100% All Others (18 entries) 13.9% Table C-35. Fuel oil imports for Portland, OR. [0.5% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share San Francisco CA CMSA 24.9% Truck 97% Portland OR-WA MSA (OR Part) 18.2% Truck 88% Los Angeles CA CMSA 11.9% Truck Rail 52% 41% Memphis TN-MS-AR MSA (TN Part) 7.4% Multi 92% Birmingham AL CMSA 7.4% Multi 95% New York NY-NJ-CT-PA CMSA (CT Part) 7.2% Multi 88% Miami FL MSA 6.1% Truck 94% All Others (71 entries) 16.9% Table C-38. Iron and steel exports for Portland, OR. [4.1% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share Portland OR-WA MSA (OR Part) 62.7% Truck 84% Remainder of Oregon 19.5% Truck Rail 54% 45% All Others (71 entries) 17.8% Table C-37. Iron and steel imports for Portland, OR. [3.9% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share Los Angeles CA CMSA 78.1% Truck 99% Portland OR-WA MSA (OR Part) 13.7% Truck 94% All Others (85 entries) 8.3% Table C-36. Manufactured imports for Portland, OR. [0.9% of all Commodity Flows] Domestic Destination % of FAF3 Total Mode Modal Share Houston TX CMSA 52.7% Truck 100% Portland OR-WA MSA (OR Part) 43.4% Truck 100% All Others (18 entries) 3.9% Table C-34. Gasoline imports for Portland, OR. [9.2% of all Commodity Flows] Domestic Origin % of FAF3 Total Mode Modal Share Portland OR-WA MSA (OR Part) 55.5% Truck 100% Remainder of Oregon 17.2% Truck 100% Remainder of Washington 10.8% Multi Truck 68% 32% All Others (10 entries) 16.5% Table C-33. Fertilizer exports for Portland, OR.

56 [37.9% of all Commodity Flows] (53.9%) Domestic Origin % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Portland OR-WA MSA (OR Part) 24.0% 29.1% Other/ Unknown (Truck) 100% 3838a Philadelphia PA-NJ-DE- MD CMSA (NJ Part) 18.8% 22.8% Other/ Unknown (Rail) 100% 2791b POR1 276 POR2/ POR3 Remainder of Washington 16.6% 20.1% Rail 60% 1620 POR2 Truck 40% 1080 Los Angeles CA CMSA 12.5% 15.2% Rail 52% 1633 POR1 Multi 28% Water 20% 408 Minneapolis-St. Paul MN-WI CMSA (MN Part) 10.5% 12.8% Multi 48% 963 POR1 Rail 32% 413 POR2 Water 20% 408 All Others (19 entries) 17.5% 0% TOTAL 13,430 a Rounding error was applied here. b With the special assignments noted in the text, POR1 originally receives 4740 and POR2 receives 2950 for a 62/38 split, but it should be 70/30 (5387/2309). The Phil split was adjusted to make it work. Table C-40. Wheat exports for Portland, OR. Commodity Category (Code) Average Annual Tonnage 2006–2010 (in 000s) Wheat (62) 9,441 Other Chemicals and Related Products (32) 3,178 Fertilizers (31) 2,484 Gasoline, Jet Fuel, Kerosene (22) 2,182 Distillate, Residual & Other Fuel Oils; Lube Oil & Greases (23) 1,212 All Manufactured Equipment, Machinery and Products (70) 977 Primary Non-Ferrous Metal Products; Fabricated Metal Products (54)/ Primary Iron and Steel Products (Ingots, Bars, Rods, etc.) (53) 1,129 Total 20,603 Total All Commodities 24,911 Table C-39. Commodity tonnages for Portland-Coastal. In order to account for all tonnage, the percentages listed in the column labeled “% of FAF3 Total” had to be inflated. The inflated percentage is shown following the original percentage in the column labeled “Adjusted % of FAF3 Total.” This, of course, assumes that the extrapolated tonnage would have the same corridor and modal distribution as the FAF3 tonnage. Also, the last row in each table, labeled “All Others,” is assumed to follow roughly the same patterns as all of the other cargo does. It is further assumed that even if the assignments are in error, the absolute values are small enough that they will not influence the final outcomes. The “All Other” statistics are rolled up into the designated corridors in each table. For grain, the total rail split should be roughly 70 percent Union Pacific Railroad (UP) and 30 percent BNSF Railway Co. (BNSF). The distribution of rail traffic for grain export from Portland, Oregon, is based on the railroads’ access to the port and the dedicated port facilities of the railroads. UP has three access lines into the general port area while BNSF has only one access line into the city of Portland. UP has five large rail terminal yards in or near the port while BNSF has only two yards in the port area on the Oregon side of the Columbia River. In other words, UP has 71 percent of the rail yard infrastructure (five out of seven). The total rail access to Portland is four lines; of these, UP has three. This equates to UP having 75 percent of the existing rail lines into the port area. Based on the access availability between UP and BNSF and the three extra rail yards UP possesses, the research team determined that 70 percent of the traffic must be handled by UP. UP handles a high percentage of chemical and fertilizer shipments in the Portland area, so 100 percent of these ship- ments were assigned to UP. In order to facilitate the analysis, modal shares shown in Appendix C only include the shares that would account for at least 80 percent of the total corridor traffic, according to FAF3. Given that this is anywhere between 80 and 100 per- cent of each corridor’s reported tonnage, the researchers assigned any tonnage not accounted for to the listed modes in proportion to each mode’s share of the total. Therefore, in Tables 40 through 50, the modal shares account for 100 per- cent of each corridor’s traffic. The relevant rail segments for Portland-Coastal are shown in Figure C-7 and Figure C-8. Figure C-9 shows the relevant waterway segments. Figure C-10 shows the relevant highway segments. In Table C-40, there are 13,430 tons, 100 percent of which is coming into the port for export. Based on expert knowledge

57 [2.0% of all Commodity Flows] (2.8%) Domestic Destination % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Montana 51.3% 64.2% Truck 100% 455 Remainder of Washington 20.4% 25.5% Truck 100% 181 Idaho 8.2% 10.3% Truck 100% 73 All Others (47 entries) 20.0% 0% 709 Truck tons = 709 tons Table C-41. Chemical combined for Portland, OR. [10.8% of all Commodity Flows] (15.4%) Domestic Origin % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Remainder of Washington 77.9% 90.3% Truck 100% 3455 Los Angeles CA CMSA 8.4% 9.7% Multi (Rail) 51% 189 POR1 Truck 49% 182 All Others (23 entries) 13.7% 0% 3826 Truck tons = 3,637 Table C-42. Chemical exports for Portland, OR. [0.8% of all Commodity Flows] (1.1%) Domestic Destination % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Idaho 63.5% 77.1% Rail 100% 219 POR 1 Philadelphia PA-NJ-DE-MD CMSA (PA Part) 18.9% 22.9% Rail 75% 48 POR 1 Truck 25% 16 All Others (7 entries) 17.6% 0% 283 Truck tons = 16 Table C-43. Fertilizer imports for Portland, OR. [9.2% of all Commodity Flows] (13.1%) Domestic Origin % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Portland OR-WA MSA (OR Part) 55.5% 66.5% Truck 100% 2168 Remainder of Oregon 17.2% 20.6% Truck 100% 671 Remainder of Washington 10.8% 12.9% Multi (Rail) 68% 286 POR1 Truck 32% 135 All Others (10 entries) 16.5% 0% 3260 Truck tons = 2,974 Table C-44. Fertilizer exports for Portland, OR.

58 [3.9% of all Commodity Flows] (5.5%) Domestic Destination % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Los Angeles CA CMSA 78.1% 85.2% Truck 100% 1178 Portland OR-WA MSA (OR Part) 13.7% 14.8% Truck 100% 205 All Others (85 entries) 8.3% 0% 1383 Truck tons = 1,383 Table C-47. Manufactured imports for Portland, OR. [0.2% of all Commodity Flows] (0.3%) Domestic Destination % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Portland OR-WA MSA (OR Part) 74.9% 87.0% Truck 100% 61 Remainder of Oregon 11.2% 13.0% Truck 100% 9 All Others (18 entries) 13.9% 0% 70 Truck tons = 70 Table C-46. Fuel oil imports for Portland, OR. [0.9% of all Commodity Flows] (1.3%) Domestic Destination % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Houston TX CMSA 52.7% 54.8% Truck 100% 175 Portland OR-WA MSA (OR Part) 43.4% 45.2% Truck 100% 144 All Others (18 entries) 3.9% 0% 319 Truck tons = 319 Table C-45. Gasoline imports for Portland, OR. of commodity flows in the northwest, the “Other/Unknown” tonnages in this table were assigned to rail with the excep- tion of “Other/Unknown” appearing in a Portland-Portland corridor; these were assigned to truck. After all the neces- sary adjustments, rail shipments accounted for 7,696 tons, 57.3 percent of the total. Truck shipments accounted for 4,983 tons (37.1 percent), and water accounted for 751 tons (5.6 percent) of the total. Rail shipments are handled by Union Pacific (UP) and Burlington Northern Santa Fe (BNSF) railroads. Tonnages were assigned based on the routes and the railroad that would be expected to carry wheat on that route. Seventy per- cent of the rail traffic was assigned to UP, 5,387 tons. This was assigned to segment POR1. Thirty percent of the rail shipments were assigned to BNSF, 2,309 tons, and this was assigned to segment POR2. (The “Remainder of Washington” is considered to be Spokane and was assigned 100 percent to BNSF.) The final split for wheat was: UP: 5,387 tons, BNSF: 2,309 tons, trucks: 4,983 tons, and water: 751 tons. In Table C-42, the “Multi” mode is assigned to Rail. Because the commodity flow is chemicals, this would be 100 percent UP. In Table C-44, the “Multi” mode is assigned to Rail. Because the commodity flow is fertilizer, this would be 100 percent UP. There were no gasoline exports. There were no fuel oil exports. There were no manufactured exports. In Table C-49, the “Multi” mode is assigned to Rail. Because of the points of origin, this would be 100 percent UP.

Figure C-7. Rail segments for Portland, OR—Columbia River portion. [4.1% of all Commodity Flows] (5.8%) Domestic Destination % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment Portland OR-WA MSA (OR Part) 62.7% 76.3% Truck 100% 1108 Remainder of Oregon 19.5% 23.7% Truck 55% 189 POR1 Rail 45% 155 All Others (71 entries) 17.8% 0% 1452 Truck tons = 1,297 Table C-48. Iron and steel imports for Portland, OR. [0.5% of all Commodity Flows] (0.7%) Domestic Origin % of FAF3 Total Adjusted % of FAF3 Total Mode Modal Share Tonnage Rail Segment San Francisco CA CMSA 24.9% 30.0% Truck 100% 53 Portland OR-WA MSA (OR Part) 18.2% 21.9% Truck 100% 38 Los Angeles CA CMSA 11.9% 14.3% Truck 56% 14 POR1 Rail 44% 11 Memphis TN-MS-AR MSA (TN Part) 7.4% 8.9% Multi (Rail) 100% 16 POR1 Birmingham AL CMSA 7.4% 8.9% Multi (Rail) 100% 16 POR1 New York NY-NJ-CT- PA CMSA (CT Part) 7.2% 8.7% Multi (Rail) 100% 15 POR1 Miami FL MSA 6.1% 7.3% Truck 100% 13 All Others (71 entries) 16.9% 176 Truck tons = 118 Table C-49. Iron and steel exports for Portland, OR.

60 Figure C-9. Waterway segments for Portland, OR–coastal. Figure C-8. Rail segments for Portland, OR—complete.

61 Figure C-10. Highway segments for Portland, OR. Table C-50 provides the final modal breakdown for Portland- Coastal cargo. An examination of the port area revealed that the truck traffic to and from the main terminals (especially Terminal 6) are serviced by four main arteries. The tonnage assigned to the truck mode for Portland-Coastal was distributed across these four routes using annual average daily truck counts. The total number of trucks was calculated by dividing total truck tonnage by 25 tons, and this number was then distributed according to existing truck traffic levels on each link. Of all the case studies, this is the only one where highways are involved in moving significant amounts of project depth cargo. The researchers analyzed the main highway corridors in Portland to see if additional project depth cargo would cause severe congestion. Congestion on any specific route in a large metropolitan region, no matter how much the travel times increase or how much higher the passenger or freight volume, will always be a small portion of the regional total. The key aspect with sig- nificant freight corridors is the increase in travel time and the decrease in travel time reliability along the route. Congestion will increase with higher volume more rapidly in corridors that already see stop-and-go speeds. Corridors that already have more traffic volume than can be handled efficiently suf- fer even more when there is additional volume on the route; not only does more passenger and freight movement join the congestion, but traffic speeds decline for everyone. Conges- tion effects will be particularly large in the peak travel peri- ods, especially if freight has no alternative mode or route. Figure C-11 illustrates that the effects of doubling total port tonnage throughput will most likely have a relatively insig- nificant effect on total delay over the corridors in the vicinity of the port during typical terminal operating hours of 6 a.m. to 7 p.m. While the curve moves up slightly, the shape of the curve does not undergo a significant change, that is, the traffic levels are not pushing congestion into an extreme increase. Rail Tons Truck Tons Water Tons Rail Assignment POR1 POR2 7696 4983 751 5387 2309 0 709 0 189 3637 0 189 267 16 0 267 286 2974 0 286 0 319 0 0 70 0 0 1383 0 155 1297 0 155 58 118 0 58 Total 8651 15506 751 Total 6342 2309 Total Rail/Truck/Water 24,908 Rounding error of -3 Table C-50. Summary of modal assignments for Portland-Coastal.

62 Figure C-11. Port of Portland—hours of delay from existing and 100 percent additional tonnage.

63 Portland, OR (Inland) Portland (Inland) Origin-Destination Corridors Portland-Inland was analyzed identically to Huntington, West Virginia. The network for Portland is not as extensive as the network for Huntington, and there is no single com- modity that dominates Portland-Inland tonnage as coal does for Huntington, West Virginia. After analyzing the highest vol- ume commodity groups, 18 segments were selected for analy- sis. Those segments are listed in Table C-51. After a thorough examination of these segments, the researchers determined that many of the segments could be combined into consolidated segments while still maintain- ing the origin-destination flows of the various commodi- ties. This was done by consolidating segments based on their geographical position relative to proposed maintenance projects. This made the model simpler to execute and under- stand. Table C-52 shows how the consolidated segments were formed. CPT Segment Number CPT River Segment Description Approximate Geography 857220 Richmond Harbor, CA San Francisco Bay Area 849700 Clearwater River, ID (Mile 0 toMile 2) From east side of Lewiston, ID, to junction with Snake River on west side 848750 Snake River, OR WA and ID (Mile 000 to Mile 146) From Ice Harbor Lock and Dam to junction with Columbia River at Burbank, WA 848719 Snake River, OR WA and ID (Mile 000 to Mile 146) From Lower Granite Lock and Dam to Little Goose Lock and Dam 848709 Snake River, OR WA and ID (Mile 000 to Mile 146) From junction with Snake River at Lewiston, ID, to Lower Granite Lock and Dam 848610 Columbia River, OR WA-NWS(Mile 326 to Mile 329) From Highway 395 bridge in Pasco, WA, to south side of Pasco 848518 Columbia River, OR WA-NWP(Mile 290 to Mile 325) From junction with Snake River at Burbank, WA, to point downstream from Wallula, WA 848320 Columbia River, OR WA-NWP(Mile 192 to Mile 290) From point downstream from Wishram, WA, to The Dalles Lock and Dam 848309 Columbia River, OR WA-NWP(Mile 192 to Mile 290) From Umatilla, WA, to John Day Lock and Dam 848219 Columbia River, OR WA-NWP(Mile 107 to Mile 192) From Hood River, OR, to Bonneville Lock and Dam 848210 Columbia River, OR WA-NWP(Mile 107 to Mile 192) From the Dalles Lock and Dam to Hood River, OR 848100 Columbia River, OR WA-NWP(Mile 106) From just downstream of I-5 in Portland, OR, to junction with Oregon Slough 847800 Columbia River, OR WA-NWP(Mile 102 to Mile 105) From junction with Oregon Slough to junction with Willamette River 847620 Willamette River, OR (Mile 014to Mile 162) From West Linn, OR, to Toe Island 847500 Willamette River, OR (Mile 004to Mile 013) From Toe Island to junction with Multnomah Channel 847100 Oregon Slough, OR (Mile 0 toMile 4) All of Oregon Slough 846500 Columbia River, OR WA-NWP (Mile 050 to Mile 068) From junction with Cowlitz River to junction with Clatskanie River 841900 Other Puget Sound Area Ports, WA Puget Sound, WA Table C-51. Origin-destination river segments for Portland-Inland. Super Segment CPT Segments Segment 1 (Snake and Clearwater Rivers) 849700 848709 848719 848750 Segment 2 (Columbia River above Snake River) 848610 Segment 3 (Columbia River—John Day to Snake River) 848518 848309 848320 Segment 4 (Columbia River—Willamette River to John Day) 848210 848219 848100 847800 Segment 5 (Willamette River) 847620 847500 Segment 6 (Lower Columbia River) 847100 846500 Segment 7 (Coast below Columbia River) 857220 Segment 8 (Coast above Columba River) 841900 Table C-52. Consolidated river segments for Portland-Inland.

64 Figure C-12. Waterway segments for Portland, OR–Inland. Portland (Inland) Modal Assignments by Corridor As in the case of Huntington, there are no significant rail or highway flows associated with the waterborne cargo for Hun- tington. Much of the cargo is originally delivered to the river terminal via a short truck haul. There is no urban traffic to contend with and only minor congestion issues, so highway segments were not included in the analysis. A very high per- centage of the shipments moves directly to waterfront facili- ties in Portland for eventual export. Waterborne flows were allocated based on a detailed analysis of trip data provided by the Corps. Researchers developed segment flows using CPT data and then extrapolated those numbers to reach a tonnage amount equal to the total tonnage for Portland-Inland. Fig- ure C-12 shows the relevant waterway segments.

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TRB’s National Freight Cooperative Research Program (NCFRP) Report 32: Integrating MTS Commerce Data with Multimodal Freight Transportation Performance Measures to Support MTS Maintenance Investment Decision Making investigates the feasibility of evaluating potential navigation operation and maintenance projects on the Marine Transportation System (MTS) as they relate to both waterborne commerce and landside freight connections.

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