Publications

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Climate change is a long-term process that will trigger a range of multi-dimensional demographic, economic, geopolitical, and national security issues with many unknowns and significant uncertainties. At first glance, climate-change-related national security dimensions seem far removed from today's major national security threats. Yet climate change has already set in motion forces that will require U.S. attention and preparedness. The extent and uncertainty associated with these situations necessitate a move away from conventional security practices, toward a small but flexible portfolio of assets to maintain U.S. interests. Thoughtful action is required now if we are to acquire the capabilities, tools, systems, and institutions needed to meet U.S. national security requirements as they evolve with the emerging stresses and shifts of climate change.

The Alternative Liquid Fuels Simulation Model (AltSim) is a high-level dynamic simulation model which calculates and compares the production and end use costs, greenhouse gas emissions, and energy balances of several alternative liquid transportation fuels. These fuels include: corn ethanol, cellulosic ethanol from various feedstocks (switchgrass, corn stover, forest residue, and farmed trees), biodiesel, and diesels derived from natural gas (gas to liquid, or GTL), coal (coal to liquid, or CTL), and coal with biomass (CBTL). AltSim allows for comprehensive sensitivity analyses on capital costs, operation and maintenance costs, renewable and fossil fuel feedstock costs, feedstock conversion ratio, financial assumptions, tax credits, CO{sub 2} taxes, and plant capacity factor. This paper summarizes the structure and methodology of AltSim, presents results, and provides a detailed sensitivity analysis. The Energy Independence and Security Act (EISA) of 2007 sets a goal for the increased use of biofuels in the U.S., ultimately reaching 36 billion gallons by 2022. AltSim's base case assumes EPA projected feedstock costs in 2022 (EPA, 2009). For the base case assumptions, AltSim estimates per gallon production costs for the five ethanol feedstocks (corn, switchgrass, corn stover, forest residue, and farmed trees) of $1.86, $2.32, $2.45, $1.52, and $1.91, respectively. The projected production cost of biodiesel is $1.81/gallon. The estimates for CTL without biomass range from $1.36 to $2.22. With biomass, the estimated costs increase, ranging from $2.19 per gallon for the CTL option with 8% biomass to $2.79 per gallon for the CTL option with 30% biomass and carbon capture and sequestration. AltSim compares the greenhouse gas emissions (GHG) associated with both the production and consumption of the various fuels. EISA allows fuels emitting 20% less greenhouse gases (GHG) than conventional gasoline and diesels to qualify as renewable fuels. This allows several of the CBTL options to be included under the EISA mandate. The estimated GHG emissions associated with the production of gasoline and diesel are 19.80 and 18.40 kg of CO{sub 2} equivalent per MMBtu (kgCO{sub 2}e/MMBtu), respectively (NETL, 2008). The estimated emissions are significantly higher for several alternatives: ethanol from corn (70.6), GTL (51.9), and CTL without biomass or sequestration (123-161). Projected emissions for several other alternatives are lower; integrating biomass and sequestration in the CTL processes can even result in negative net emissions. For example, CTL with 30% biomass and 91.5% sequestration has estimated production emissions of -38 kgCO{sub 2}e/MMBtu. AltSim also estimates the projected well-to-wheel, or lifecycle, emissions from consuming each of the various fuels. Vehicles fueled with conventional diesel or gasoline and driven 12,500 miles per year emit 5.72-5.93 tons of CO{sub 2} equivalents per year (tCO{sub 2}e/yr). Those emissions are significantly higher for vehicles fueled with 100% ethanol from corn (8.03 tCO{sub 2}e/yr) or diesel from CTL without sequestration (10.86 to 12.85 tCO{sub 2}/yr). Emissions could be significantly lower for vehicles fueled with diesel from CBTL with various shares of biomass. For example, for CTL with 30% biomass and carbon sequestration, emissions would be 2.21 tCO{sub 2}e per year, or just 39% of the emissions for a vehicle fueled with conventional diesel. While the results presented above provide very specific estimates for each option, AltSim's true potential is as a tool for educating policy makers and for exploring 'what if?' type questions. For example, AltSim allows one to consider the affect of various levels of carbon taxes on the production cost estimates, as well as increased costs to the end user on an annual basis. Other sections of AltSim allow the user to understand the implications of various polices in terms of costs to the government or land use requirements. AltSim's structure allows the end user to explore each of these alternatives and understand the sensitivities implications associated with each assumption as well as the implications for bottom line economics, energy use, and greenhouse gas emissions.

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The Alternative Liquid Fuels Simulation Model (AltSim) is a high-level dynamic simulation model which calculates and compares the production costs, carbon dioxide emissions, and energy balances of several alternative liquid transportation fuels. These fuels include: corn ethanol, cellulosic ethanol, biodiesel, and diesels derived from natural gas (gas to liquid, or GTL) and coal (coal to liquid, or CTL). AltSim allows for comprehensive sensitivity analyses on capital costs, operation and maintenance costs, renewable and fossil fuel feedstock costs, feedstock conversion efficiency, financial assumptions, tax credits, CO{sub 2} taxes, and plant capacity factor. This paper summarizes the preliminary results from the model. For the base cases, CTL and cellulosic ethanol are the least cost fuel options, at $1.60 and $1.71 per gallon, respectively. Base case assumptions do not include tax or other credits. This compares to a $2.35/gallon production cost of gasoline at September, 2007 crude oil prices ($80.57/barrel). On an energy content basis, the CTL is the low cost alternative, at $12.90/MMBtu, compared to $22.47/MMBtu for cellulosic ethanol. In terms of carbon dioxide emissions, a typical vehicle fueled with cellulosic ethanol will release 0.48 tons CO{sub 2} per year, compared to 13.23 tons per year for coal to liquid.

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What will be the effect of Iraqi domestic instability on Iraqi oil production Negotiations for Iranian nuclear technology on Iranian oil supplies Saudi commitment to expanded oil production President Putin's policies on Russian oil and natural gas supplies President Chavez's policies on Venezuelan oil supplies Instability in Nigeria Higher oil prices on world economic growth Effect of economic growth on oil demand in China, India, U.S., etc. Higher oil prices on non-OPEC oil supplies

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The Hydrogen Futures Simulation Model (H{sub 2}Sim) is a high level, internally consistent, strategic tool for exploring the options of a hydrogen economy. Once the user understands how to use the basic functions, H{sub 2}Sim can be used to examine a wide variety of scenarios, such as testing different options for the hydrogen pathway, altering key assumptions regarding hydrogen production, storage, transportation, and end use costs, and determining the effectiveness of various options on carbon mitigation. This User's Guide explains how to run the model for the first time user.

The Electricity Generation Cost Simulation Model (GenSim) is a user-friendly, high-level dynamic simulation model that calculates electricity production costs for variety of electricity generation technologies, including: pulverized coal, gas combustion turbine, gas combined cycle, nuclear, solar (PV and thermal), and wind. The model allows the user to quickly conduct sensitivity analysis on key variables, including: capital, O&M, and fuel costs; interest rates; construction time; heat rates; and capacity factors. The model also includes consideration of a wide range of externality costs and pollution control options for carbon dioxide, nitrogen oxides, sulfur dioxide, and mercuty. Two different data sets are included in the model; one from the US. Department of Energy (DOE) and the other from Platt's Research Group. Likely users of this model include executives and staff in the Congress, the Administration and private industry (power plant builders, industrial electricity users and electric utilities). The model seeks to improve understanding of the economic viability of various generating technologies and their emissions trade-offs. The base case results, using the DOE data, indicate that in the absence of externality costs, or renewable tax credits, pulverized coal and gas combined cycle plants are the least cost alternatives at 3.7 and 3.5 cents/kwhr, respectively. A complete sensitivity analysis on fuel, capital, and construction time shows that these results coal and gas are much more sensitive to assumption about fuel prices than they are to capital costs or construction times. The results also show that making nuclear competitive with coal or gas requires significant reductions in capital costs, to the $1000/kW level, if no other changes are made. For renewables, the results indicate that wind is now competitive with the nuclear option and is only competitive with coal and gas for grid connected applications if one includes the federal production tax credit of 1.8cents/kwhr.

The Global Energy Futures Model (GEFM) is a demand-based, gross domestic product (GDP)-driven, dynamic simulation tool that provides an integrated framework to model key aspects of energy, nuclear-materials storage and disposition, environmental effluents from fossil and non fossil energy and global nuclear-materials management. Based entirely on public source data, it links oil, natural gas, coal, nuclear and renewable energy dynamically to greenhouse-gas emissions and 12 other measures of environmental impact. It includes historical data from 1990 to 2000, is benchmarked to the DOE/EIA/IEO 2001 [5] Reference Case for 2000 to 2020, and extrapolates energy demand through the year 2050. The GEFM is globally integrated, and breaks out five regions of the world: United States of America (USA), the Peoples Republic of China (China), the former Soviet Union (FSU), the Organization for Economic Cooperation and Development (OECD) nations excluding the USA (other industrialized countries), and the rest of the world (ROW) (essentially the developing world). The GEFM allows the user to examine a very wide range of ''what if'' scenarios through 2050 and to view the potential effects across widely dispersed, but interrelated areas. The authors believe that this high-level learning tool will help to stimulate public policy debate on energy, environment, economic and national security issues.

Recent terrorist attacks in the United States have increased concerns about potential national security consequences from energy supply disruptions. The purpose of this Laboratory Directed Research & Development (LDRD) is to develop a high-level dynamic simulation model that would allow policy makers to explore the national security consequences of major US. energy supply disruptions, and to do so in a way that would integrate energy, economic and environmental components. The model allows exploration of potential combinations of demand-driven energy supplies that meet chosen policy objectives, including: Mitigating economic losses, measured in national economic output and employment levels, due to terrorist activity or forced outages of the type seen in California; Control of greenhouse gas levels and growth rates; and Moderating US. energy import requirements. This work has built upon the Sandia US. Energy and greenhouse Gas Model (USEGM) by integrating a macroeconomic input-output framework into the model, adding the capability to assess the potential economic impact of energy supply disruptions and the associated national security issues. The economic impacts of disruptions are measured in terms of lost US. output (e.g., GDP, sectoral output) and lost employment, and are assessed either at a broad sectoral level (3 sectors) or at a disaggregated level (52 sectors). In this version of the model, physical energy disruptions result in quantitative energy shortfalls, and energy prices are not permitted to rise to clear the markets.

Critical infrastructures underpin the domestic security, health, safety and economic well being of the United States. They are large, widely dispersed, mostly privately owned systems operated under a mixture of federal, state and local government departments, laws and regulations. While there currently are enormous pressures to secure all aspects of all critical infrastructures immediately, budget realities limit available options. The purpose of this study is to provide a clear framework for systematically analyzing and prioritizing resources to most effectively secure US critical infrastructures from terrorist threats. It is a scalable framework (based on the interplay of consequences, threats and vulnerabilities) that can be applied at the highest national level, the component level of an individual infrastructure, or anywhere in between. This study also provides a set of key findings and a recommended approach for framework application. In addition, this study develops three laptop computer-based tools to assist with framework implementation-a Risk Assessment Credibility Tool, a Notional Risk Prioritization Tool, and a County Prioritization tool. This study's tools and insights are based on Sandia National Laboratories' many years of experience in risk, consequence, threat and vulnerability assessments, both in defense- and critical infrastructure-related areas.

Nuclear power is an important and, the authors believe, essential component of a secure nuclear future. Although nuclear fuel cycles create materials that have some potential for use in nuclear weapons, with appropriate fuel cycles, nuclear power could reduce rather than increase real proliferation risk worldwide. Future fuel cycles could be designed to avoid plutonium production, generate minimal amounts of plutonium in proliferation-resistant amounts or configurations, and/or transparently and efficiently consume plutonium already created. Furthermore, a strong and viable US nuclear infrastructure, of which nuclear power is a large element, is essential if the US is to maintain a leadership or even participatory role in defining the global nuclear infrastructure and controlling the proliferation of nuclear weapons. By focusing on new fuel cycles and new reactor technologies, it is possible to advantageously burn and reduce nuclear materials that could be used for nuclear weapons rather than increase and/or dispose of these materials. Thus, the authors suggest that planners for a secure nuclear future use technology to design an ideal future. In this future, nuclear power creates large amounts of virtually atmospherically clean energy while significantly lowering the threat of proliferation through the thoughtful use, physical security, and agreed-upon transparency of nuclear materials. The authors must develop options for policy makers that bring them as close as practical to this ideal. Just as Atoms for Peace became the ideal for the first nuclear century, they see a potential nuclear future that contributes significantly to power for peace and prosperity.