Quantifying and comparing the cumulative greenhouse gas emissions and financial viability of heavy-duty transportation pathways for the Northeastern, United States. (1st September 2022) - Frank, Jenny; Brown, Tristan; Ha, HakSoo; Slade, Dave; Haverly, Martin; Malmsheimer, Robert
Highlights: Measures the financial viability and cumulative greenhouse gas emissions production. Models Class 8 heavy-duty truck scenarios under different cargo scenarios. Uses an internalized social cost of carbon metric as a financial benefit. Includes a comprehensive sensitivity analysis for several variables. Abstract: The rapid reduction in transportation sector fossil carbon emissions is essential to achieving long-term climate goals set by state and local governments. This study examines diverse scenarios for operational greenhouse gas (GHG) emission reductions in freight transport within the Northeastern United States and quantifies both the cumulative GHGs and the net present values (NPV). This study considers commercialized Class 8 heavy-duty trucks that operate on petroleum diesel or bio-based diesel fuel and a battery-electric option that has not yet reached commercialization and applies an investment timing methodology along with a comprehensive sensitivity analysis. The low fossil carbon scenarios incorporate the social cost of carbon as an internalized benefit. For the baseline weight-limited cargo scenario, this study finds that the bio-based diesel to battery-electric scenario produces the highest NPV and lowest operational carbon impact, while the bio-based diesel option is responsible for the second highest NPV and second lowest operational carbon impact. Under a volume-limited cargo option (10% discount rate), the bio-based diesel to battery-electric scenario yields the highest NPV, followed by the bio-based diesel scenario. The sensitivity analysis reveals that several factors impact the NPVs. Additionally, this study shows the significant impact of the timing of emission reductions on the cumulative operational carbon impact generated.