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DOE OSTI · 3013262

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

Abstract

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.

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BibTeXRIS

Xu, Xiaodan [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000296509156), Yang, Hung-Chia [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Laarabi, Haitam [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Poliziani, Cristian [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Birky, Alicia [National Renewable Energy Laboratory (NREL), Golden, CO (United States)] (ORCID:0000000179257324), Jeong, Kyungsoo [National Renewable Energy Laboratory (NREL), Golden, CO (United States)] (ORCID:0000000322530136), Lu, Hongyu [Georgia Institute of Technology, Atlanta, GA (United States)], Guensler, Randall [Georgia Institute of Technology, Atlanta, GA (United States)], Spurlock, C. Anna [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]. 2025-10-08. Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data. https://doi.org/10.1080/15568318.2025.2566755

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