Carbon dioxide capture and storage (CCS) involves the capture of CO2 at a large industrial facility, such as a power plant, and its transport to a geological (or other) storage site where CO2 is sequestered. Previous work has identified pipeline transport of liquid CO2 as the most economical method of transport for large volumes of CO2. However, there is little published work on the economics of CO2 pipeline transport. The objective of this paper is to estimate total cost and the cost per tonne of transporting varying amounts of CO2 over a range of distances for different regions of the continental United States. An engineering-economic model of pipeline CO2 transport is developed for this purpose. The model incorporates a probabilistic analysis capability that can be used to quantify the sensitivity of transport cost to variability and uncertainty in the model input parameters. The results of a case study show a pipeline cost of US$ 1.16 per tonne of CO2 transported for a 100 km pipeline constructed in the Midwest handling 5 million tonnes of CO2 per year (the approximate output of an 800 MW coal-fired power plant with carbon capture). For the same set of assumptions, the cost of transport is US$ 0.39 per tonne lower in the Central US and US$ 0.20 per tonne higher in the Northeast US. Costs are sensitive to the design capacity of the pipeline and the pipeline length. For example, decreasing the design capacity of the Midwest US pipeline to 2 million tonnes per year increases the cost to US$ 2.23 per tonne of CO2 for a 100 km pipeline, and US$ 4.06 per tonne CO2 for a 200 km pipeline. An illustrative probabilistic analysis assigns uncertainty distributions to the pipeline capacity factor, pipeline inlet pressure, capital recovery factor, annual O&M cost, and escalation factors for capital cost components. The result indicates a 90% probability that the cost per tonne of CO2 is between US$ 1.03 and US$ 2.63 per tonne of CO2 transported in the Midwest US. In this case, the transport cost is shown to be most sensitive to the pipeline capacity factor and the capital recovery factor. The analytical model elaborated in this paper can be used to estimate pipeline costs for a broad range of potential CCS projects. It can also be used in conjunction with models producing more detailed estimates for specific projects, which requires substantially more information on site-specific factors affecting pipeline routing.