This paper describes a GIS-based intermodal network model for the shipment of coal in the United States. The purpose of this research was to investigate the role played by railways, waterways, and highways in the movement of coal from its source area to point of use, and to highlight the implications these movements have for the U.S. economy. The project team modeled coal movements across the U.S. intermodal transportation network using the Energy Information Administration’s 2010 data, which provided detailed origin, destination, primary mode, and volume information for coal shipments. The model identifies the optimum routes for coal shipments based on a rate structure that accounts for the relative costs of shipping by each of the modes. The model, as well as available statistics, reveals the dominance of coal mined from the Powder River Basin. Compared to other sources—principally, the Appalachian Basin—coal from Mountain West is significantly less expensive, thus giving it a significant comparative advantage. Both Texas and Illinois, the two largest coal consumers by state, obtain virtually all of their coal from the West or from within state. Appalachian Basin coal serves domestic and export markets primarily in the East and Southeastern U.S. Only the Ohio River provides significant movement of Central Appalachian Basin coal to the west and south. Although this modeling relies on 2010 data, a look at more recent trends in coal prices and mining indicate that the Powder River Basin continues to dominate, while production and industry employment have steadily declined in the Appalachian Basin. The shift away from coal and toward natural gas as a primary energy source argues for the region’s coal extraction industries remaining in a depressed state, which could produce negative economic consequences for transportation industries. Carrier and port facilities will need to adopt a more diversified shipping portfolio to accommodate for these losses. It is possible that the loss of coal will open up opportunities for other commodity shipments on the inland waterways. This modeling demonstrates the potential for such integrated models to accommodate energy - related or similar data, and serves as a tool for freight planners in identifying energy transportation corridors of significance. It could potentially be used to analyze the movement of other commodities, which could let industry stakeholders identify new markets to tap into. Further, the model and analysis can help inform MAP-21 related efforts to develop a National Freight Network and National Freight Strategic Plan.

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© 2016 University of Kentucky, Kentucky Transportation Center

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