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Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data

Commercial trucks are essential elements of the nation's supply chain system. Meanwhile, intensive truck movements contribute significantly to system externalities, such as energy use and air pollution. However, collecting detailed fleet composition and distribution of operational patterns remains a barrier to accurately accounting for these impacts. The recently released 2021 US Vehicle Inventory and Use Survey (US VIUS) fills a critical gap in understanding commercial truck fleet distributions, their operations, and business constraints at the national scale. This study aims to understand the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and calibrate the fleet inputs in regulatory emission models to assess the potential emission implications of the VIUS-derived fleet composition. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to improve fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The study also investigates potential emission reduction benefits under various forecasted fleet electrification scenarios. The energy consumption and critical air pollutant rates by vehicle types are compared between MOVES4 and US VIUS fleets for both current and future scenarios to provide insights into the latest U.S. commercial vehicle fleet characteristics and their implications on energy and emissions. This study helps policymakers and practitioners advance the commercial fleet generation for emission models. It also deepens the understanding of the emission reduction potential of the commercial fleet under various fleet projections.

2021 US VIUS↗

Commercial Fleet Level Emissions and Energy Tracker (COFLEET) v1.0

This tool generates the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and assess the fleetwide energy and emission outcomes. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to generate fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The tool also provides fleet turnover and emission forecasts under various forecasted fleet electrification scenarios. This tool helps policymakers and practitioners advance the commercial fleet generation for emission models. This study also provides some sample datasets for state and local transportation/air quality agencies to test, which can reduce the estimation bias associated with using MOVES default fleets.

Xu, Xiaodan [Lawrence Berkeley National Laboratory↗

Understanding Advanced Vehicle Technology Adoption Potential in Commercial Fleets Across Major Trucking Sectors

Adopting advanced vehicle technologies, such as battery-electric, hybrid, and hydrogen fuel cell vehicles, can be an effective strategy for reducing fleet owners' operating costs. However, different trucking sectors, such as private and for-hire carriers and short- or long-haul operations, may face unique challenges in adopting those vehicle technologies due to their own operational needs and budget constraints. Current studies on fleet-wide vehicle technology projections frequently overlook such sectoral differences and fail to capture variation in adoption potential across sectors. This study addresses this gap by analyzing the disparities in the total cost of ownership (TCO) and payback period (PBP) among a large and heterogeneous sample of fleet owners. It aims to understand the sectoral differences in the long-term potential for adopting advanced vehicle technologies. Utilizing the 2021 US Vehicle Inventory and Use Survey (US VIUS), which offers data on various commercial vehicle sectors, their operational patterns, and current vehicle assets, this research estimates the TCO and PBP for individual trucks over multiple future years. The results reveal variation in the cost-effectiveness of different vehicle technologies across trucking sectors, as well as the potential technology landscape in both the short and long term. The findings from this study can inform policymakers and practitioners on how to prioritize sectors with lower barriers for advanced vehicle technology adoption and support industries that face challenges in switching to advanced vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗