Research

Using the Social Hotspot Database (SHDB) and the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model to explore how social and environmental impact changes if restructuring the supply chain by onshoring parts for the battery production process for Class 8 heavy-duty electric trucks from China to the US.

Applying the Social Hotspot Database (SHDB) to compare the potential societal impacts of battery electric and fuel cell electric power systems for Class 8 heavy-duty trucks. This research evaluates cradle-to-gate supply chains for a lithium-ion battery pack and a Proton Exchange Membrane Fuel Cell (PEMFC) system, including raw material production, component manufacturing, and final assembly.

Conducting an in-depth social life cycle assessment (S-LCA) for heavy-duty truck electric batteries and fuel cell batteries to assess the social and socio-economic aspects of various truck powertrains and their positive and negative impacts from cradle to gate.

Assessing the environmental impacts of supercommuting in the Northern California Megaregion. The purpose of the research is to assess the prevalence of and trends in very long-distance commuting, and how supercommuting contributes to transportation-linked greenhouse gas (GHG) emissions.

Using the American Housing Survey (AHS), the project estimates the vehicle miles traveled (VMT) by unit square feet and number of bedrooms per unit while controlling for demographics relevant to VMT.

Using life cycle assessment (LCA) to estimate the size and spatial distribution of the environmental, social, and economic impacts of a supply chain on each life cycle stage to understand the policy effects involved. Improve the understanding of the policy environment in ways that support a more integrated, resilient, and trusted supply chain.

The California Air Resources Board (CARB) approved a first-of-its-kind rule that requires a phased-in transition toward zero-emission for medium- and heavy-duty vehicles, which is known as the Advanced Clean Fleet (ACF) Regulation. Understand and summarize the ACF Regulation, the technologies that can meet the zero-emission requirements, and factors that will influence the pace of adoption of zero-emission trucks and estimate growth in demand for trucking services.

Applied a discrete choice model to explore traveler’s mode choices and estimate cross-price and cross-time elasticities for TNC services and transit versus other modes, using the travel diary survey data collected by Metropolitan Transportation Commission (MTC) targeting TNC users.

Quantified the impact of the built environment on travel-related CO2 emissions to inform planners of built environment interventions for low-carbon transportation, using the 2019 data from Zhongshan.

Used the Zhongshan data to estimate the nonlinear and interaction effects of the built environment and motorcycles/E-bikes on car ownership, and inferred implications for mitigating the growth of car ownership.

Applied a machine learning algorithm to examine the influential factors of metro ridership in Shenzhen, identified their threshold and moderating effects, and proposed land use planning guidelines adaptive to the network position of stations.