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A growing demand for passenger and freight transportation, combined with limited capital to expand the United States (U.S.) rail infrastructure, is creating pressure for a more efficient use of the current line capacity. This is further exacerbated by the fact that most passenger rail services operate on corridors that are shared with freight traffic. A capacity analysis is one alternative to address the situation and there are various approaches, tools, and methodologies available for application. As the U.S. continues to develop higher speed passenger services with similar characteristics to those in European shared-use lines, understanding the common methods and tools used on both continents grows in relevance. There has not as yet been a detailed investigation as to how each continent approaches capacity analysis, and whether any benefits could be gained from cross-pollination. This paper utilizes more than 50 past capacity studies from the U.S. and Europe to describe the different railroad capacity definitions and approaches, and then categorizes them, based on each approach. The capacity methods are commonly divided into analytical and simulation methods, but this paper also introduces a third, ''combined simulationanalytical'' category. The paper concludes that European rail studies are more unified in terms of capacity, concepts, and techniques, while the U.S. studies represent a greater variation in methods, tools, and objectives. The majority of studies on both continents use either simulation or a combined simulation-analytical approach. However, due to the significant differences between operating philosophy and network characteristics of these two rail systems, European studies tend to use timetable-based simulation tools as opposed to the non-timetable-based tools commonly used in the U.S. rail networks. It was also found that validation of studies against actual operations was not typically completed or was limited to comparisons with a base model.

The biomass supply chain is one of the most critical elements of large-scale bioenergy production and in many cases a key barrier for procuring initial funding for new developments on specific energy crops. Most productions rely on complex transforming chains linked to feed and food markets. The term 'supply chain' covers various aspects from cultivation and harvesting of the biomass, to treatment, transportation, and storage. After energy conversion, the product must be delivered to final consumption, whether it is in the form of electricity, heat, or more tangible products, such as pellets and biofuels. Effective supply chains are of utmost importance for bioenergy production, as biomass tends to possess challenging seasonal production cycles and low mass, energy and bulk densities. Additionally, the demand for final products is often also dispersed, further complicating the supply chain. The goal of this paper is to introduce key components of biomass supply chains, examples of related modeling applications, and if/how they address aspects related to environmental metrics and management. The paper will introduce a concept of integrated supply systems for sustainable biomass trade and the factors influencing the bioenergy supply chain landscape, including models that can be used to investigate the factors. The paper will also cover various aspects of transportation logistics, ranging from alternative modal and multi-modal alternatives to introduction of support tools for transportation analysis. Finally gaps and challenges in supply chain research are identified and used to outline research recommendations for the future direction in this area of study.

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The need to build an efficient procurement system has been recognized as one of the main obstacles to the extension of the bioenergy industry. Transportation is a key component of that system, as it accounts for a significant portion of the delivered cost. One of the most critical factors affecting transportation cost is the interrelationship between feedstock sources and facility locations, including plant and off‐plant transfer / storage facilities. At the same time, biomass energy sustainability is sensitive to the performance of each component in the entire process. The main goal of this study is to build a mixed integer linear programming (MILP) model that uses region‐specific data to minimize sustainable transportation costs. This consists of economic, environmental, and societal factors. The upstream air emissions as a result of residues collection at the forest, transloading, and transportation by truck or multimodally (truck and rail), which include greenhouse gases (GHG), particulate matter (PM), and nitrogen oxides (NOx), are calculated and included in the analysis. The model was tested on a case study that evaluated transportation costs for nine alternative plant locations in the state of Wisconsin. The results revealed that when equally weighed, external (social and environmental) costs accounted for a considerable portion of total transportation cost (approximately 26–37%). The study also shows that total upstream GHG and air emissions increased as the plant capacity increased, due to the longer transportation distances, but per unit emissions decreased. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd

Freight transportation of goods and commodities is a necessity and is often a significant portion of the overall investment in industrial development, especially in the natural resource industry. The economic costs of developing infrastructure have long been factored into the project costs, but environmental or social impacts have received less attention. In addition, alternative transportation modes are rarely compared from both economic and environmental perspectives. This paper performs a Life Cycle Assessment (LCA) for truck-only, multimodal and rail transportation options to transport ore and concentrate. In this paper, LCA is performed in SimaPro for construction/manufacturing, operations, maintenance, and end of life phases to obtain the overall Global Warming Potential (GWP) in terms of kilogram equivalents of CO2 (kg CO2eq). After emissions from alternative options have been defined, the cost of each option can be investigated through Life Cycle Cost Analysis (LCCA) This paper also discusses the past work on LCCA and its application to transportation projects. The final part provides a methodology to convert the emission results from LCA for integration with the costs from LCCA.

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