This document proposes analyzing US freight rail networks to determine which intermodal transport hubs could best utilize increased infrastructure spending. The analysis would consider freight volumes originating from different regions, catalog existing hubs, and define suitable hubs for investment to maximize energy efficiency and social/economic benefits. Top exporting regions are identified, and secondary factors like economic conditions would also be considered to select final candidate hubs.

1. Analysis of Intermodal Transport Hubs Best Suited for Increased Federal Infrastructure Spending Marco A. Falconi GIS 200 E86L Fall 2009

4. CO 2 Emissions by Mode

8. Sample of FAF Commodity Database 324, 177 Origin-Destination Pairs Domestic 08 Origin O Destination D Commodity Mode Mdol Kton VA Virgi VA MI Detro MI Chemical prods. Truck 0.830222574958635 0.215314541062031 MA rem MA TX rem TX Textiles/leather Air & Truck 0.830234060626129 3.16998459511795E-02 OR Portl OR MT MT Basic chemicals Truck 0.830241442901975 24.6375538053975 ND ND MI Detro MI Cereal grains Truck 0.83027766431505 14.7188048195552 CT rem CT TX Dalla TX Paper articles Truck 0.830287575877158 0.567660672986829 VA rem VA NC rem NC Building stone Truck 0.830294330652075 7.82399555046327 PA Phila PA RI RI Tobacco prods. Truck 0.830298304076233 6.5874880357497E-03 NC Green NC NC Charl NC Transport equip. Other Intermodal 0.830320552960404 1.74889004230499E-02 NC Green NC IN India IN Transport equip. Other Intermodal 0.830320552960404 0.403119154751301 IN Chica IN IN India IN Precision instruments Truck 0.830397547647117 0.128123379706235 CA San J CA FL Miami FL Furniture Other Intermodal 0.830399110021491 3.32289108037949E-02 TN Memph TN ID ID Machinery Other Intermodal 0.830444551255483 1.21110635429621 WA rem WA UT rem UT Pharmaceuticals Pipeline & Unknown 0.830482038851016 1.20491437911987E-02