Dawn Kataoka Manley

Implications of Modeling Range and Infrastructure Barriers to Adoption of Battery Electric Vehicles

Compared with traditional vehicles, light-duty battery electric vehicles (BEVs) currently have price premiums and noncost limitations, such as reduced range, sparse public recharging infrastructure, and long recharge times. These additional limitations can be captured in different ways in a consumer choice model. Three approaches are implemented to noncost barrier modeling, and results are compared. A penalty approach quantifies limitations as additional costs to the consumer, and two threshold approaches determine BEV suitability by the frequency that daily driving distance exceeds the vehicle range. GPS-based trip data are used to form ensemble distributions of low-, medium-, and high-intensity driving distances to support the analysis. All approaches show limited (5%) adoption of BEVs by 2050, and the BEV mileage fraction trails the stock fraction because of the use of substitute vehicles for high-mileage trips and adoption biased toward lower driving intensity segments. In fact, a majority of the electrified miles driven stem from plug-in hybrid electric vehicles, not BEVs. Of the BEVs, the powertrains offering 150- to 250-mi ranges are responsible for more than 50% of sales. Results also hint that longer-range BEVs act as primary household vehicles, but lower-range BEVs serve as secondary household vehicles. A parametric exploration shows that mechanisms to mitigate the hardship of the noncost barriers can significantly increase adoption rates but that reducing battery price alone does not. However, these mechanisms can be different for different modeling approaches.

Heavy Duty Vehicle Futures Analysis.

This report describes work performed for an Early Career Research and Development project. This project developed a heavy-duty vehicle (HDV) sector model to assess the factors influencing alternative fuel and efficiency technology adoption. This model builds on a Sandia light duty vehicle sector model and provides a platform for assessing potential impacts of technological advancements developed at the Combustion Research Facility. Alternative fuel and technology adoption modeling is typically developed around a small set of scenarios. This HDV sector model segments the HDV sector and parameterizes input values, such as fuel prices, efficiencies, and vehicle costs. This parameterization enables sensitivity and trade space analyses to identify the inputs that are most associated with outputs of interest, such as diesel consumption and greenhouse gas emissions. Thus this analysis tool enables identification of the most significant HDV sector drivers that can be used to support energy security and climate change goals.

System dynamics of the competition of municipal solid waste to landfill, electricity, and liquid fuel in California

Increasing concern regarding the cost, security, and environmental impact of fossil fuel energy use is driving research and investment towards developing the most strategic methods of converting biomass resources into energy. Analyses to date have examined theoretical limitations of biomass-to-energy through resource availability assessments, but have not thoroughly challenged competing tradeoffs of biomass conversion into liquid fuel versus electricity. Existing studies have focused on energy crops and cellulosic residues for biomass-toenergy inputs, however the conversion of these biomass resources is often less energetically efficient compared to fossil energy sources. Waste streams are beginning to be recognized as valuable biomass to energy resources. Municipal solid waste (MSW) is a low-cost waste biomass resource with a well-defined supply infrastructure and does not compete for land area or food supply, making it a potentially attractive renewable feedstock for energy conversion. The Waste Biomass to Energy Pathway model (WBEM) described here demonstrates a system dynamics approach to analyze the impact of converting MSW biomass to either bioelectricity or liquid fuel. The WBEM incorporates macro-scale feedback from supply chain costs, energy sector impacts, and greenhouse gas (GHG) production within the competing pathways of MSW to 1) landfill, 2) electricity, and 3) liquid fuel within California.

Guiding optimal biofuels

In the current study, processes to produce either ethanol or a representative fatty acid ethyl ester (FAEE) via the fermentation of sugars liberated from lignocellulosic materials pretreated in acid or alkaline environments are analyzed in terms of economic and environmental metrics. Simplified process models are introduced and employed to estimate process performance, and Monte Carlo analyses were carried out to identify key sources of uncertainty and variability. We find that the near-term performance of processes to produce FAEE is significantly worse than that of ethanol production processes for all metrics considered, primarily due to poor fermentation yields and higher electricity demands for aerobic fermentation. In the longer term, the reduced cost and energy requirements of FAEE separation processes will be at least partially offset by inherent limitations in the relevant metabolic pathways that constrain the maximum yield potential of FAEE from biomass-derived sugars.

Summary and results of the joint WMD-DAC/Alameda County bioterrorism response plan exercise.

On June 12,2003, the Alameda County Public Health Department and Sandia National Laboratories/CA jointly conducted an exercise that used a Weapons of Mass Destruction-Decision Analysis Center (WMD-DAC) bioterrorism attack simulation to test the effectiveness of the countys emergency response plan. The exercise was driven by an assumed release (in the vicinity of the Berkeley Marina), and subsequent spread, of a small quantity of aerosolized, weapons-grade anthrax spores. The simulation used several key WMD-DAC capabilities, namely: (1) integration with an atmospheric dispersion model to calculate expected dose levels in the affected areas, (2) a individual-tracking capability for both infected and non-infected persons as they made decisions, sought treatment, and received prophylaxis drugs, and (3) a user interface that allows exercise participants to affect the scenario evolution and outcome. The analysis of the countys response plan included documenting and reviewing the decisions made by participants during the exercise. Twenty-six local and regional officials representing the health care system, emergency medical services and law enforcement were involved in responding to the simulated attack. The results of this joint effort include lessons learned both by the Alameda County officials regarding implementation of their bioterrorism response plan and by the Sandia representatives about conducting exercises of this type. These observations are reviewed in this report, and they form a basis for providing a better understanding of group/individual decision processes and for identifying effective communication options among decision makers.