UC Davis Institute of Transportation Studies

Bicycles and other forms of micromobility have been anecdotally used in past disasters to help save lives and improve community recovery. However, research and practice are scarce on this resilient transportation strategy, which limits its usefulness and possible benefits. To fill this gap, our paper investigates the potential role bicycles and micromobility in facilitating (or limiting) disaster response and recovery. Given the lack of exploration on the topic, we convened an online workshop where we conducted brainstorming and focus group discussions with disaster experts from various government agencies, not-for-profit organizations, academia, and policy groups. We present a synthesis of that discussion, along with a review of the existing literature. We conclude there is strong potential for bicycles and micromobility for different disaster phases, hazard types, and groups of people. However, multiple barriers exist related to implementation and safety, suggesting a need for future research and policy in the transportation and emergency management fields and practices.

At present, the City of Davis, surrounding communities, and the UC Davis campus are struggling with many of the same transportation problems that plague larger urban centers including increasing traffic, limited parking, and challenges to effective operation of the public transit system. The campus is expecting to grow by 6,000 students in the next ten years (plus approximately 3,000 faculty and staff) and is developing a Long-Range Development Plan (LRDP) that will serve to guide this growth. This plan will include housing, traffic control, parking, alternative transportation modes, and interactions with the broader community. The development of the LRDP provides a unique opportunity for the Institute of Transportation Studies-Davis (ITS-Davis), the University of California (UC)-wide partners for Advanced Transit and Highways (PATH) program, and Caltrans to provide input and advice on mobility options that will help the campus accommodate the expected growth while minimizing negative transportation impacts. The integrated nature of the LRDP also provides an opportunity to look at transportation options from a broader perspective than is usually possible under traditional planning scenarious. Thus creating an opportunity to evaluate a variety of innovative advanced information and mobility packages that could be implemented on a pilot scale in the coming years. These advanced technologies include dynamic ridesharing, carsharing, neighborhood electric vehicles, linkages between housing and access to shared-use automobiles, integration between modes, information kiosks, and other mobility packages that might prove effective at reducing the demand for single occupancy vehicles associated with campus.

Efforts to encourage bicycling to school can achieve numerous societal benefits, including improved childhood health, reduced traffic congestion, and even long-term effects such as increased bicycling skill and attitudes. Most of the literature on children bicycling to school focuses on the influence of infrastructure interventions, yet relatively few studies have robustly evaluated the influence of encouragement efforts. This study seeks to examine the effects of three encouragement efforts undertaken at primary and secondary schools in Davis, California: the Active4.me scanning program, the Monkey Money incentive system, and the national Bike-to-School Day celebration. I use a binomial regression to statistically analyze bicycle rack count data and Safe Routes to School classroom tallies collected by city employees and local volunteers. After accounting for the schools’ physical environment and characteristics, as well as the influence of weather and the natural environment, I find that all three of the encouragement efforts increase levels of bicycling to school. I conclude by suggesting that these encouragement programs have the potential for lasting influence by providing children with the skills and confidence to bicycle later in life. I also note the value of further state support for the parent volunteers who operate these encouragement programs, in order to allow the spread of similar encouragement programs across a variety of cities, including disadvantaged communities.

Life changes are often associated with changes in travel behavior, due to a break in habitual travel cues and the introduction of a novel travel context. Universities provide a particularly appropriate setting to examine how these life changes can bring about changes in travel attitudes, 27 norms, and skills – which together form a psychological construct called “motility” that describes the capability for travel. In this study, I pool data from seven years of the University of California, Davis’ annual campus travel survey to create a longitudinal panel, and use a retrospective survey to collect the bicycling behaviors, attitudes, and skills of undergraduates every year since they graduated from high school. I find that, on average, UCD undergraduates’ pro-bicycling attitudes decrease slightly over time while bicycling skills increase substantially throughout college. I then use the retrospective panel data to estimate a statistical model to analyze the influence of bicycling exposure and experiences on skills and attitudes. I find that riding a bicycle at any point during college increases both pro-bicycling attitudes and bicycling skills, while exposure to high levels of bicycling appears not to influence attitudes or skills. This study provides confirmatory evidence for the motility approach and suggests possible policy avenues, such as incentivizing short-term bicycle use in order to shift perceptions and attitudes about bicycling, with the intent of fostering a positive feedback cycle between greater bicycling attitudes and skills and increased bicycle use.

The market introduction of plug-in electric vehicles (PEVs) is being partially driven by policy interventions. One type of intervention is reoccurring and non-financial incentives, these differ from financial purchase incentives which are a one-time financial incentive associated with the purchase of a PEV. Reoccurring and non-financial incentives include special lane access for PEVs (e.g. HOV/carpool lanes, bus lanes), parking incentives, charging infrastructure development, road toll fee waivers, and licensing incentives. They also include disincentives such as gasoline tax or annual vehicle taxes. The impact of these incentives differs between regions partially due to differences in traffic conditions, travel patterns, consumer preferences, and other local variations. Due to these differences, it is challenging to rank the importance of these incentives, however existing research shows that they all can have a positive impact on PEV adoption. Policymakers wishing to promote the introduction of PEVs will need to consider local travel patterns, the regulatory environment, and consumer preferences to determine the most viable policy interventions for their region.

This paper contributes to research investigating the impact of automated and partially automated vehicles on travel behavior. This contribution comes from taking a first look at the impact of partially/semi-automated (SAE Level 2) vehicles on travel behavior and potential correlations with vehicle miles travelled (VMT). The results of this study are taken from a questionnaire survey of 3,001 plug-in electric (PEV) owners in the USA, of which 347 own a partially-automated vehicle (e.g Tesla Model S with Autopilot). This study looks at the VMT of different vehicle types in the survey including plug-in hybrids (PHEVs), battery electric vehicles (BEVs), and semi-automated BEVs. This comparison reveals that semi-automated BEVs have significantly higher VMT compared to other vehicle types. Least squares regression is used to understand VMT in semi-automated BEVs further. This reveals a significant relationship between commute distance, age, household income, house type, and the frequency of autopilot use, and annual VMT. It is possible that the results are showing a self-selection causality as owners of these vehicles already drove more prior to them selecting a semi-automated BEV. Nevertheless, this model indicates that as the frequency of autopilot use increases, so does annual VMT. Due to the potential for two ways causality this study cannot determine whether there is a causal relationship between the use of semi-automated vehicle technology and additional VMT. It is hoped that this first look at the impact of partially-automated BEVs will encourage more research and debate in this area with the aim of improving policy responses to partially and fully automated vehicles.

Models show that to avert dangerous levels of climate change, global carbon dioxide emissions must fall to zero later this century. Most of these emissions arise from energy use. Davis et al. review what it would take to achieve decarbonization of the energy system. Some parts of the energy system are particularly difficult to decarbonize, including aviation, long-distance transport, steel and cement production, and provision of a reliable electricity supply. Current technologies and pathways show promise, but integration of now-discrete energy sectors and industrial processes is vital to achieve minimal emissions. Net emissions of CO2 by human activities - including not only energy services and industrial production but also land use and agriculture - must approach zero in order to stabilize global mean temperature. Energy services such as light-duty transportation, heating, cooling, and lighting may be relatively straightforward to decarbonize by electrifying and generating electricity from variable renewable energy sources (such as wind and solar) and dispatchable ("on-demand") nonrenewable sources (including nuclear energy and fossil fuels with carbon capture and storage). However, other energy services essential to modern civilization entail emissions that are likely to be more difficult to fully eliminate. These difficult-to-decarbonize energy services include aviation, long-distance transport, and shipping; production of carbon-intensive structural materials such as steel and cement; and provision of a reliable electricity supply that meets varying demand. Moreover, demand for such services and products is projected to increase substantially over this century. The long-lived infrastructure built today, for better or worse, will shape the future.

Here, we review the special challenges associated with an energy system that does not add any CO2 to the atmosphere (a net-zero emissions energy system). We discuss prominent technological opportunities and barriers for eliminating and/or managing emissions related to the difficult-to-decarbonize services; pitfalls in which near-term actions may make it more difficult or costly to achieve the net-zero emissions goal; and critical areas for research, development, demonstration, and deployment. It may take decades to research, develop, and deploy these new technologies.

DOI Link: https://doi.org/10.1126/science.aas9793

The California Regional Multisector Air Quality Emissions (CA-REMARQUE) model is developed to predict changes to criteria pollutant emissions inventories in California in response to sophisticated emissions control programs implemented to achieve deep greenhouse gas (GHG) emissions reductions. Two scenarios for the year 2050 act as the starting point for calculations: a business-as-usual (BAU) scenario and an 80% GHG reduction (GHG-Step) scenario. Each of these scenarios was developed with an energy economic model to optimize costs across the entire California economy and so they include changes in activity, fuels, and technology across economic sectors. Separate algorithms are developed to estimate emissions of criteria pollutants (or their precursors) that are consistent with the future GHG scenarios for the following economic sectors: (i) on-road, (ii) rail and off-road, (iii) marine and aviation, (iv) residential and commercial, (v) electricity generation, and (vi) biorefineries. Properly accounting for new technologies involving electrification, biofuels, and hydrogen plays a central role in these calculations. Critically, criteria pollutant emissions do not decrease uniformly across all sectors of the economy. Emissions of certain criteria pollutants (or their precursors) increase in some sectors as part of the overall optimization within each of the scenarios. This produces nonuniform changes to criteria pollutant emissions in close proximity to heavily populated regions when viewed at 4km spatial resolution with implications for exposure to air pollution for those populations. As a further complication, changing fuels and technology also modify the composition of reactive organic gas emissions and the size and composition of particulate matter emissions. This is most notably apparent through a comparison of emissions reductions for different size fractions of primary particulate matter. Primary PM_2.5 emissions decrease by 4% in the GHG-Step scenario vs. the BAU scenario while corresponding primary PM_0.1 emissions decrease by 36%. Ultrafine particles (PM_0.1) are an emerging pollutant of concern expected to impact public health in future scenarios. The complexity of this situation illustrates the need for realistic treatment of criteria pollutant emissions inventories linked to GHG emissions policies designed for fully developed countries and states with strict existing environmental regulations.