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Evaluation of particulate matter (PM) due to transportation systems is of interest to public health professionals and policymakers in California and Southern California, specifically. Poor air quality can lead to short-term eye, throat, and nose irritations, as well as long-term cancers. While PM can be reduced through new regulations including bus-only lane projects, carpooling, and the adoption of clean air vehicles, there is a need for highly accurate, yet cost-effective sensors which can assess the efficacy of these improvements. UCLA will develop a field-portable computational imaging and deep-learning enhanced aerosol analysis device, termed c-Air, to characterize PM due to transportation systems. In addition to particle counting and sizing, UCLA will further enhance its system above the current gold standard by classifying particles based upon physical features and volatility using computational imaging and deep learning.

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The project aims to present an in-depth understanding of the public EV charging infrastructure in the present and future transportation electrification for public agencies, such as SCAG. One contribution is to provide an integrated eTranSym tool, which can simulate the travel and charging behaviors of every EV user, assess disparities in charging infrastructure distribution among communities, and predict the future demand for public charging facilities. The eTranSym tool helps prioritize underserved communities and assists the spatial-varying investment of the public charging infrastructure.

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This project reports on changes and evolving operations in public transit during the COVID-19 pandemic. With a focus on transit ridership and transit service hours, this project first tracks where, how, and why transit supply and demand has changed. Since reaching an April 2020 nadir both nationally and in California, transit ridership has recovered slowly: as of July 2022, boardings were 61 percent and 56 percent of their respective national and California baselines. In California, service has been restored faster than riders have returned. This project next examines and showcases what established strategies for increasing transit ridership remain relevant in and post-pandemic.

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Aviation is a difficult sector to decarbonize. The high energy and power requirements of flight make electrification challenging and low-carbon liquid fuels face their own technical and practical hurdles. While much of the attention on air transportation pertains to passenger travel, the relatively smaller air cargo industry faces similar challenges to decarbonization as the passenger airline industry. In the face of a difficult to decarbonize aviation sector, carbon savings may be realized by facilitating modal shifts from air transportation to less-polluting ground transportation where feasible. California’s effort to build a high-speed rail network for interregional travel in California is an example of such a strategy and features prominently in the state’s Scoping Plan as one pathway towards meeting 2050 GHG emissions reduction targets in the transportation sector. Luskin Center for Innovation researchers propose conducting an exhaustive search of the relevant peer reviewed and grey literature on studies that examine the economic and environmental effects of policies, programs, and projects aimed at shifting passenger and cargo movements from the air to the ground.

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As the market share of zero-emissions hydrogen and electric vehicles increases in California, the motor vehicle fuel tax becomes less applicable as a user fee, and declining revenues could produce shortfalls for maintaining the transportation system. The authors of SB1 sought policy options to raise usage-based revenues from electric and zero-emissions transportation system users.This research was specified in SB1 as a study for the University of California at Davis. Professor Martin Wachs, an internationally-renowned transportation finance expert member of the SB 1077 Road User Charge Technical Advisory Committee, is assisting research at UC Davis with this study.

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