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SUMMARY Freight emissions are expected to grow by 30% by 2050 due to increases in demand and the shift to less efficient modes of transportation. In the United States, freight currently represents 28% of transportation energy use, or 8% of overall energy use. Improved logistics is one method for reducing freight emissions, but making informed logistics decisions requires improved tools for measuring emissions from transportation in the supply chain. A large number of tools are currently available to estimate the emissions from transportation, using a variety of approaches. These approaches can be grouped into four general categories: models and simulation; surveys; Life Cycle Assessment methods; and econometric methods. The diversity of approaches reflects the needs of the many different stakeholders interested in the issue. In order to provide a common basis for calculating the carbon footprint of transportation in the supply chain, a standard definition was proposed based on a review of existing programs and methods. This definition involves a focus on energy consumed by transportation vehicles used to move goods between locations, adopts a well-to-wheel view for considering the emissions required to produce that energy, and includes the six greenhouse gases referred to as the Kyoto gases. This definition is consistent with emerging standards in Europe, captures the upstream portion of the fuel cycle necessary to compare alternative fuels and vehicles, and focuses on transportation rather than supporting logistics activities. Drawing on existing research in supply chain management, LCA, and accounting, a set of five criteria for evaluating existing carbon measurement tools were developed. 1. Breadthâthe scope of activities included in the measurement2. Depthâthe range of direct and indirect emissions included in themeasurement3. Precisionâthe level of detail provided by the measurement4. Comparabilityâthe degree with which measurements can be comparedacross time and organizations5. Verifiabilityâthe degree of assurance in the results and methodologyThe first three criteria together capture how relevant a measure is for decision-making. The final two criteria provide a measure of how well suited the tool is for external reporting, captured by the ability to compare the results with other organizations and to accurately and faithfully represent the actual performance. Together these five criteria cover the major characteristics of a tool needed for both internal and external use. Higher degrees of performance across these categories increase the relevance of the results to making decisions; the ability to incorporate the results into benchmarking and information sharing; and the trustworthiness of claims based on the results. The current tools were evaluated using the Analytic Hierarchy Process (AHP), a quantitative method for making complex decisions. The process relies on humans 1
estimating the magnitude of difference between choices by making simple comparisons. The AHP process is well suited to group decision making, where consensus must be reached between many group members. In a workshop held at MIT a group of 16 stakeholders used the AHP process to evaluate the importance of the five evaluation criteria. The results indicated strong preference for comparability as the most important criterion, with a relative weighting of 39%. Of the remaining criteria, breadth and verifiability were judged to be next most important, with weightings of 19% and 18% respectively. Precision and depth were judged to be least important, with relative weightings of 13% and 11%. The existing tools were evaluated within each of the five criteria using a set of standards. These evaluations were combined with the relative weightings of each criterion to produce an overall score for each tool. The scores demonstrate how different approaches to the design of tools can produce results that score similarly. Tools that can produce highly comparable results with consistent system boundaries and methods scored well, despite the lack of breadth offered by programs primarily tailored for single modes. Other high scoring tools provide consistent methodologies across all four primary modes of transportation, but lack the ability to provide more precise ratings at the specific carrier or shipment level. Based on the evaluations of existing tools, a direction for future tools was identified. The primary requirements of a future tool are to provide a consistent set of well-to-wheel emissions factors across all four major modes, use a consistent system boundary, and produce performance indicators that measure both total emissions and relative emissions. This could be based on transparent, open data and methods that make use of average levels of performance or it could collect data from specific carriers and routes. The latter approach would provide more precision in the results, but at a cost of some transparency and verifiability. Design elements for a future tool were presented based on three-tier architecture. The primary role of the control tier is to define how data is input to the tool and what results are returned to the user. In direct input the user enters the necessary information directly without requiring support from the logic provided by the tool. The model tier is responsible for the actual calculation of the emissions within the tool. It must support the inputs from the control tier, interface with the data tier, and handle the logic of emissions calculation. The data tier must contain all the data needed to perform the actual calculations. This primarily consists of emissions factors at multiple levels of detail. Two possible development plans for a future tool were presented. A basic tool would require little more than a form for data entry linked to data tables of emissions factors and locations. The advanced tool would expand on the capabilities of the basic tool through a more advanced user interface, actual route calculations, and a dynamic set of emissions factors that could be updated based on data provided by users. Timelines for development of both tools was presented with a breakdown of time by task. 2
