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A global, independent scientific assessment of Carbon Dioxide Removal

This body of work covers some important technology policy challenges that will be posed by the deployment of electric and automated vehicles in personal mobility, ridesourcing, and long haul trucking. Substantial electrification of road transport is critical to deep decarbonization. Self-driving technology continues to inch towards wider commercial deployment, despite well-publicized setbacks. Policymaking must grapple with a deeply uncertain technology landscape and trade-offs between multiple societal objectives. I attempt to help inform public policy by carefully navigating the uncertainty present in the deployment of these technologies and highlighting how trade-offs between multiple objectives might materialize. First, I look at the potential energy impact of automation on electric vehicle range. Will electrification and automation of light vehicles develop in sync? I find that automation will incur expected penalties of 10-15% on electric vehicle range, due to the energy consumption of computing and sensors. This suggests that deliberate technology choices towards efficient computing and aerodynamics will be needed to drive electrification of automated vehicles. In long haul trucking, I investigate the potential job impacts from automation of highway driving. I draw on detailed shipment data to show that replacing all highway driving with automated trucking will lead to more than 90% of operator-hours lost to automation. I find limited evidence to support industry claims that increased short haul jobs will compensate for the operator-hours lost on highways. Third, I present a novel agent based model that can answer a series of research questions related to electric vehicle deployment in ridesourcing. Companies such as Uber and Lyft have committed to fully-electrify their fleets by 2030 in the United States. Should policy incentivize larger battery pack sizes or greater investments in dedicated fast-charging infrastructure for ridesourcing? I instantiate the agent based model to study the lifecycle externalities of fully-electric ridesourcing in the city of Chicago, across different levels of battery size and fast-charging infrastructure. I estimate that greenhouse gas externalities are in the range of 10-13¢ per trip, with lower externalities associated with smaller battery packs. Compared to today, fully electrifying ridesourcing can cut greenhouse gas externalities in Chicago by 50-60%. Solely targeting reductions in greenhouse gas emissions, however, comes at the cost of increases in traffic externalities such as congestion

The study of Heating, Ventilation and Air Conditioning (HVAC) system performance is important to understand its energy consumption, especially for electric vehicles. The purpose of this thesis is to develop a methodology to simulate the flow within the Scania S20H cab while also capturing the thermal properties of the fluid and solids within the cab. This is done by setting up a heat-up simulation of a stationary cab in STAR-CCM+ (Siemens Industry Software Inc, Plano TX,USA). The thesis speaks about the limitations with the current methodologies and delves into the theoretical aspects of such a scenario. The new method is a complete Computational Fluid Dynamics (CFD) method that involves conjugate heat transfer, shell modeling and temperature dependent Heat Transfer Coefficient (HTC). A benchmark case is run to understand the uncertainties introduced by virtue of the shell model. When its effects are understood and deemed minimal in the context of thesis, a steady state case for the full truck model is simulated. After it was found that the physics is well captured, a fully transient case is run to validate the model against the experimental data. The simulations best capture the behaviour of low insulation and low thickness areas such as the windshield. The gap between the simulation and experiment increases with increasing thickness and insulation. The model is found to perform mostly well with some variations between regions in the cab. The thesis satisfied its objectives in developing a methodology to better ease the conceptual design process. Additionally, guidelines for the workflow of the methodology are presented along with the limitations and scope for improvement.

Weight, computational load, sensor load, and possibly higher drag may increase the energy use of automated electric vehicles (AEVs) relative to human-driven electric vehicles (EVs), although this increase may be offset by smoother driving. We use a vehicle dynamics model to show that automation is likely to impose a minor penalty on EV range and have negligible effect on battery longevity. As such, while some commentators have suggested that the power and energy requirements of automation mean that the first automated vehicles (AVs) will be gas-electric hybrids, we conclude that this need not be the case. We also find that drivers need to place only a modest value on the time saved by automation for its benefits to exceed direct costs., Comment: 25 pages, 4 figures, 14 pages of Supporting Information

The Paris Agreement was the culmination of a series of high level government meetings over many years. It aimed to bring together a very complex set of agendas, vested interests and political ambition into a unified framework for action.