Fuel Economy Testing of Autonomous Vehicles

<p>Environmental pollution and energy use in the light-duty transportation sector are currently regulated through fuel economy and emissions standards, which typically assess quantity of pollutants emitted and volume of fuel used per distance driven. In the United States, fuel economy testing consists of a vehicle on a treadmill, while a trained driver follows a fixed drive cycle. By design, the current standardized fuel economy testing system neglects differences in how individuals drive their vehicles on the road. As autonomous vehicle (AV) technology is introduced, more aspects of driving are shifted into functions of decisions made by the vehicle, rather than the human driver. Yet the current fuel economy testing procedure does not have a mechanism to evaluate the impacts of AV technology on fuel economy ratings, and subsequent regulations such as Corporate Average Fuel Economy targets. This paper develops a method to incorporate the impacts of AV technology within the bounds of current fuel economy test, and simulates a range of automated following drive cycles to estimate changes in fuel economy. The results show that AV following algorithms designed without considering efficiency can degrade fuel economy by up to 3%, while efficiency-focused control strategies may equal or slightly exceed the existing EPA fuel economy test results, by up to 10%. This suggests the need for a new near-term approach in fuel economy testing to account for connected and autonomous vehicles. As AV technology improves and adoption increases in the future, a further reimagining of drive cycles and testing is required.</p

Decisions to reduce greenhouse gases from agriculture and product transport: LCA case study of organic and conventional wheat

A streamlined hybrid life cycle assessment is conducted to compare the global warming potential (GWP) and primary energy use of conventional and organic wheat production and delivery in the US. Impact differences from agricultural inputs, grain farming, and transport processes are estimated. The GWP of a 1 kg loaf of organic wheat bread is about 30 g CO2-eq less than the conventional loaf. When organic wheat is shipped 420 km farther to market, organic and conventional wheat systems have similar impacts. These results can change dramatically depending on soil carbon accumulation and nitrous oxide emissions from the two systems. Key parameters and their variability are discussed to provide producers, wholesale and retail consumers, and policymakers metrics to align their decisions with low-carbon objectives.</p

Cost and benefit estimates of partially-automated vehicle collision avoidance technologies

<p>Many light-duty vehicle crashes occur due to human error and distracted driving. Partially-automated crash avoidance features offer the potential to reduce the frequency and severity of vehicle crashes that occur due to distracted driving and/or human error by assisting in maintaining control of the vehicle or issuing alerts if a potentially dangerous situation is detected. This paper evaluates the benefits and costs of fleet-wide deployment of blind spot monitoring, lane departure warning, and forward collision warning crash avoidance systems within the US light-duty vehicle fleet. The three crash avoidance technologies could collectively prevent or reduce the severity of as many as 1.3 million U.S. crashes a year including 133,000 injury crashes and 10,100 fatal crashes. For this paper we made two estimates of potential benefits in the United States: (1) the upper bound fleet-wide technology diffusion benefits by assuming all relevant crashes are avoided and (2) the lower bound fleet-wide benefits of the three technologies based on observed insurance data. The latter represents a lower bound as technology is improved over time and cost reduced with scale economies and technology improvement. All three technologies could collectively provide a lower bound annual benefit of about $18 billion if equipped on all light-duty vehicles. With 2015 pricing of safety options, the total annual costs to equip all light-duty vehicles with the three technologies would be about$13 billion, resulting in an annual net benefit of about $4 billion or a$20 per vehicle net benefit. By assuming all relevant crashes are avoided, the total upper bound annual net benefit from all three technologies combined is about $202 billion or an$861 per vehicle net benefit, at current technology costs. The technologies we are exploring in this paper represent an early form of vehicle automation and a positive net benefit suggests the fleet-wide adoption of these technologies would be beneficial from an economic and social perspective.</p

Compilation of U.S. City Climate Adaptation Plans

This document presents a compilation of climate adaptation plans from cities with a population larger a population larger than 300,000 in 2019 according to the U.S. Census Bureau City and Town Population Totals between 2010 and 2019. In addition, we also included the most populated city for each U.S. State to ensure every U.S. State was represented in our assessment. This search was completed by May 2020. For each of the 87 cities assessed, but we found only 48 cities that had a standalone climate adaptation plan (or climate assessment report) published before May 2020. 5 out of 48 plans were county-level plans. 1 out of 48 is a regional-level plan. For the 48 cities, we collected information about whether the city’s local government has published an adaptation plan. We used the pattern “city of XXXX climate adaptation plan” as a keyword, replacing the XXXX symbols with the name of the city, in a Google-based search. We also substituted the word “adaptation” with “resilience” to account for commonly used terms in the climate adaptation and resilience field. We complemented the search by individually looking for climate adaptation plans published in the local government website under the Sustainability or Environment office and also the Georgetown Climate Center database. This search also revealed climatic assessments or action plans for some cities. For our analysis, an adaptation plan differs from an action plan in that the former includes sector-targeted strategies to adapt the dynamic city environment to changing climate conditions, while the latter’s focus is to mitigate greenhouse gases emissions. We considered climate assessment reports as an adaptation plan because these contain information that is intended for decision-making. It is often the case that there is little difference between these two document types (adaptation plans and assessment reports), however, we identified 3 categories: 1) Adaptation plan only, 2) Assessment report only, 3) Adaptation plan and assessment report. As mentioned above, adaptation plans include a list of actions or strategies that the city is planning given changing climate conditions. Information about changing climate conditions come from assessment reports commissioned by the local government or other national and international reports. An assessment report lists the changes in climate variables at the city location and often also include a vulnerability analysis, however, no specific actions are recommended. Finally, an adaptation plan can also include a detailed assessment of the observed and future changes in climate variables at the city. </p

Framework for Incorporating Downscaled Climate Output into Existing Engineering Methods: Application to Precipitation Frequency Curves

<div><p>To improve the resiliency of designs, particularly for long-lived infrastructure, current engineering practice must be updated to incorporate a range of future climate conditions that are likely to be different from the past. However, a considerable mismatch exists between climate model outputs and the data inputs needed for engineering designs. This paper provides a framework for incorporating climate trends into design standards and applications, including selecting the appropriate climate model source based on the intended application, understanding model performance and uncertainties, addressing differences in temporal and spatial scales, and interpreting results for engineering design. The framework is illustrated through an application to depth-duration-frequency curves, which are commonly used in stormwater design. A change factor method is used to update the curves in a case study of Pittsburgh. Extreme precipitation depth is expected to increase in the future for Pittsburgh for all return periods and durations examined, requiring revised standards and designs. Doubling the return period and using historical, stationary values may enable adequate design for short-duration storms; however, this method is shown to be insufficient to enable protective designs for longer-duration storms.</p><div><br></div></div><div></div

Greenhouse gas implications of using coal for transportation: Life cycle assessment of coal-to-liquids, plug-in hybrids, and hydrogen pathways

Using coal to produce transportation fuels could improve the energy security of the United States by replacing some of the demand for imported petroleum. Because of concerns regarding climate change and the high greenhouse gas (GHG) emissions associated with conventional coal use, policies to encourage pathways that utilize coal for transportation should seek to reduce GHGs compared to petroleum fuels. This paper compares the GHG emissions of coal-to-liquid (CTL) fuels to the emissions of plug-in hybrid electric vehicles (PHEV) powered with coal-based electricity, and to the emissions of a fuel cell vehicle (FCV) that uses coal-based hydrogen. A life cycle approach is used to account for fuel cycle and use-phase emissions, as well as vehicle cycle and battery manufacturing emissions. This analysis allows policymakers to better identify benefits or disadvantages of an energy future that includes coal as a transportation fuel. We find that PHEVs could reduce vehicle life cycle GHG emissions by up to about one-half when coal with carbon capture and sequestration is used to generate the electricity used by the vehicles. On the other hand, CTL fuels and coal-based hydrogen would likely lead to significantly increased emissions compared to PHEVs and conventional vehicles using petroleum-based fuels.</p

Life cycle assessment and grid electricity: what do we know and what can we know?

The generation and distribution of electricity comprises nearly 40% of U.S. CO(2), emissions, as well as large shares of SO(2), NO(x), small particulates, and other toxins. Thus, correctly accounting for these electricity-related environmental releases is of great importance in life cycle assessment of products and processes. Unfortunately, there is no agreed-upon protocol for accounting for the environmental emissions associated with electricity, as well as significant uncertainty in the estimates. Here, we explore the limits of current knowledge about grid electricity in LCA and carbon footprinting for the U.S. electrical grid, and show that differences in standards, protocols, and reporting organizations can lead to important differences in estimates of CO(2) SO(2), and NO(x) emissions factors. We find a considerable divergence in published values for grid emissions factor in the U.S. We discuss the implications of this divergence and list recommendations for a standardized approach to accounting for air pollution emissions in life cycle assessment and policy analyses in a world with incomplete and uncertain information.</p

Estimating Potential Increases in Travel with Autonomous Vehicles for the Non-Driving, Elderly and People with Travel-Restrictive Medical Conditions

<p>Automated vehicles represent a technology that promises to increase mobility for many groups, including the senior population (those over age 65) but also for non-drivers and people with medical conditions. This paper estimates bounds on the potential increases in travel in a fully automated vehicle environment due to an increase in mobility from the non-driving and senior populations and people with travel-restrictive medical conditions. In addition, these bounding estimates indicate which of these demographics could have the greatest increases in annual vehicle miles traveled (VMT) and highlight those age groups and genders within these populations that could contribute the most to the VMT increases. The data source is the 2009 National Household Transportation Survey (NHTS), which provides information on travel characteristics of the U.S. population. The changes to light-duty VMT are estimated by creating and examining three possible travel demand wedges. In demand wedge one, non-drivers are assumed to travel as much as the drivers within each age group and gender. Demand wedge two assumes that the driving elderly (those over age 65) without medical conditions will travel as much as a younger population within each gender. Demand wedge three makes the assumption that working age adult drivers (19-64) with medical conditions will travel as much as working age adults without medical conditions within each gender, while the driving elderly with medical any travel-restrictive conditions will travel as much as a younger demographic within each gender in a fully automated vehicle environment. The combination of the results from all three demand wedges represents an upper bound of 295 billion miles or a 14% increase in annual light-duty VMT for the US population 19 and older. Since traveling has other costs besides driving effort, these estimates serve to bound the potential increase from these populations to inform the scope of the challenges, rather than forecast specific VMT scenarios. <strong></strong></p

Effect of Crude Oil Carbon Accounting Decisions on Meeting Global Climate Budgets

The Intergovernmental Panel on Climate Change quantified a cumulative remaining carbon budget beyond which there is a high likelihood global average temperatures will increase more than 2 °C above preindustrial temperature. While there is global participation in mitigation efforts, there is little global collaboration to cooperatively mitigate emissions. Instead, countries have been acting as individual agents with independent emission reduction objectives. However, such asymmetric unilateral climate policies create the opportunity for carbon leakage resulting from the shift in embodied carbon emissions within trade networks. In this analysis, we use an optimization-based model of the global crude trade as a case study to demonstrate the importance of a cooperative, system-level approach to climate policy in order to most effectively, efficiently, and equitably achieve carbon mitigation objectives. To do this, we first characterize the cost and life cycle greenhouse gas emissions associated with the 2014 crude production and consumption system by aggregating multiple data sources and developing a balanced trade matrix. We then optimize this network to demonstrate the potential for carbon mitigation through more efficient use of crude resources. Finally, we implement a global carbon cap on total annual crude emissions. We find that such a cap would require crude consumption to drop from 4.2 gigatons (Gt) to 1.1 Gt. However, if each country had an individual carbon allocation in addition to the global cap consistent with the nationally determined contribution limits resulting from the 2015 United Nations Climate Change Conference, allowable consumption would further decrease to approximately 770 million metric tonnes. Additionally, the carbon accounting method used to assign responsibility for embodied carbon emissions associated with the traded crude further influences allowable production and consumption for each country. The simplified model presented here highlights how global cooperation and a system-level cooperative approach could guide climate policy efforts to be more cost effective and equitable, while reducing the leakage potential resulting from shifting trade patterns of embodied carbon emissions. Additionally, it demonstrates how the spatial distribution of crude consumption and production patterns change under a global carbon cap given various carbon accounting strategies

The economic costs of reducing greenhouse gas emissions under a US national renewable electricity mandate

The electricity sector is the largest source of greenhouse gas emissions (GHGs) in the U.S. Many states have passed and Congress has considered Renewable Portfolio Standards (RPS), mandates that specific percentages of electricity be generated from renewable resources. We perform a technical and economic assessment and estimate the economic costs and net GHG reductions from a national 25 percent RPS by 2025 relative to coal-based electricity. This policy would reduce GHG emissions by about 670 million metric tons per year, 11 percent of 2008 U.S. emissions. The first 100 million metric tons could be abated for less than $36/metric ton. However, marginal costs climb to$50 for 300 million metric tons and to as much as $70/metric ton to fulfill the RPS. The total economic costs of such a policy are about$35 billion annually. We also examine the cost sensitivity to favorable and unfavorable technology development assumptions. We find that a 25 percent RPS would likely be an economically efficient method for utilities to substantially reduce GHG emissions only under the favorable scenario. These estimates can be compared with other approaches, including increased R&D funding for renewables or deployment of efficiency and/or other low-carbon generation technologies.</p