Steve Peterson

Using system dynamics to model the transition to biofuels in the United States

Today, the U.S. consumes almost 21 million barrels of crude oil per day; approximately 60% of the U.S. demand is supplied by imports. The transportation sector alone accounts for two-thirds of U.S. petroleum use. Biofuels, liquid fuels produced from domestically-grown biomass, have the potential to displace about 30% of current U.S. gasoline consumption. Transitioning to a biofuels industry on this scale will require the creation of a robust biomass-to-biofuels system-of-systems that operates in concert with the existing agriculture, forestry, energy, and transportation markets. The U.S. Department of Energy is employing a system dynamics approach to investigate potential market penetration scenarios for cellulosic ethanol, and to aid decision makers in focusing government actions on the areas with greatest potential to accelerate the deployment of biofuels and ultimately reduce the nationpsilas dependence on imported oil.

Modeling biofuel expansion effects on land use change dynamics

Increasing demand for crop-based biofuels, in addition to other human drivers of land use, induces direct and indirect land use changes (LUC). Our system dynamics tool is intended to complement existing LUC modeling approaches and to improve the understanding of global LUC drivers and dynamics by allowing examination of global LUC under diverse scenarios and varying model assumptions. We report on a small subset of such analyses. This model provides insights into the drivers and dynamic interactions of LUC (e.g., dietary choices and biofuel policy) and is not intended to assert improvement in numerical results relative to other works. Demand for food commodities are mostly met in high food and high crop-based biofuel demand scenarios, but cropland must expand substantially. Meeting roughly 25% of global transportation fuel demand by 2050 with biofuels requires >2 times the land used to meet food demands under a presumed 40% increase in per capita food demand. In comparison, the high food demand scenario requires greater pastureland for meat production, leading to larger overall expansion into forest and grassland. Our results indicate that, in all scenarios, there is a potential for supply shortfalls, and associated upward pressure on prices, of food commodities requiring higher land use intensity (e.g., beef) which biofuels could exacerbate.

Ethanol Distribution, Dispensing, and Use: Analysis of a Portion of the Biomass-to-Biofuels Supply Chain Using System Dynamics

The Energy Independence and Security Act of 2007 targets use of 36 billion gallons of biofuels per year by 2022. Achieving this may require substantial changes to current transportation fuel systems for distribution, dispensing, and use in vehicles. The U.S. Department of Energy and the National Renewable Energy Laboratory designed a system dynamics approach to help focus government action by determining what supply chain changes would have the greatest potential to accelerate biofuels deployment. The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain. The model provides a framework for developing scenarios and conducting biofuels policy analysis. This paper focuses on the downstream portion of the supply chain–represented in the distribution logistics, dispensing station, and fuel utilization, and vehicle modules of the Biomass Scenario Model. This model initially focused on ethanol, but has since been expanded to include other biofuels. Some portions of this system are represented dynamically with major interactions and feedbacks, especially those related to a dispensing station owner’s decision whether to offer ethanol fuel and a consumer’s choice whether to purchase that fuel. Other portions of the system are modeled with little or no dynamics; the vehicle choices of consumers are represented as discrete scenarios. This paper explores conditions needed to sustain an ethanol fuel market and identifies implications of these findings for program and policy goals. A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously. Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.

Biomass Scenario Model Scenario Library: Definitions, Construction, and Description

Understanding the development of the biofuels industry in the United States is important to policymakers and industry. The Biomass Scenario Model (BSM) is a system dynamics model of the biomass-to-biofuels system that can be used to explore policy effects on biofuels development. Because of the complexity of the model, as well as the wide range of possible future conditions that affect biofuels industry development, we have not developed a single reference case but instead developed a set of specific scenarios that provide various contexts for our analyses. The purpose of this report is to describe the scenarios that comprise the BSM scenario library. At present, we have the following policy-focused scenarios in our library: minimal policies, ethanol-focused policies, equal access to policies, output-focused policies, technological diversity focused, and the point-of-production- focused. This report describes each scenario, its policy settings, and general insights gained through use of the scenarios in analytic studies.

A decision support tool for evaluating the effectiveness and logistical considerations of biodosimetry methods: Comparing guidelines and new technologies for the response to a nuclear event

This paper introduces an early prototype of a decision support tool (DST) for evaluating the effectiveness and logistical considerations of biodosimetry methods. Biodosimetry methods allow the estimation of an individuals radiation exposure and facilitate the process of screening the population into treatment categories following a potential large-scale nuclear or radiological event. The DST was implemented using STELLA® software with preliminary comparisons among six biodosimetry methods, including the current federal guidelines. Preliminary results under the models assumptions show a great variability among methods on their efficiency for screening large numbers of potential victims. In the future, a revised version of the DST would be a useful tool for the emergency response community to evaluate the effectiveness of various strategies for preattack stockpiling and capacity building, and postattack distribution and dispensing of biodosimetry technologies.