Publications

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The same water that makes Norfolk, Virginia an ideal home for international ports and naval installations is also increasingly flooding large parts of the city and the surrounding Hampton Roads region. This report describes the development of a process to analyze the resilience of urban regions to the shocks and stresses that those cities care about, and applies this process to address flooding in Norfolk and Hampton Roads. The goal is to provide Norfolk city officials and regional asset owners with actionable information to plan the infrastructure improvements that will most greatly enhance the regions resilience to flooding. Results suggest that there are wide - ranging impacts of a major acute flooding event beyond the Hampton Roads region. A single four - day, 100 - year flood event in Hampton Roads would cause on the order of $355 - 606 million in detrimental impacts to global production, with greater impacts occurring in the future as net sea levels rise. This report highlights the infrastructure behaviors, interdependencies, and the economic analyses that determine these impacts.

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The current expansion of natural gas (NG) development in the United States requires an understanding of how this change will affect the natural gas industry, downstream consumers, and economic growth in order to promote effective planning and policy development. The impact of this expansion may propagate through the NG system and US economy via changes in manufacturing, electric power generation, transportation, commerce, and increased exports of liquefied natural gas. We conceptualize this problem as supply shock propagation that pushes the NG system and the economy away from its current state of infrastructure development and level of natural gas use. To illustrate this, the project developed two core modeling approaches. The first is an Agent-Based Modeling (ABM) approach which addresses shock propagation throughout the existing natural gas distribution system. The second approach uses a System Dynamics-based model to illustrate the feedback mechanisms related to finding new supplies of natural gas - notably shale gas - and how those mechanisms affect exploration investments in the natural gas market with respect to proven reserves. The ABM illustrates several stylized scenarios of large liquefied natural gas (LNG) exports from the U.S. The ABM preliminary results demonstrate that such scenario is likely to have substantial effects on NG prices and on pipeline capacity utilization. Our preliminary results indicate that the price of natural gas in the U.S. may rise by about 50% when the LNG exports represent 15% of the system-wide demand. The main findings of the System Dynamics model indicate that proven reserves for coalbed methane, conventional gas and now shale gas can be adequately modeled based on a combination of geologic, economic and technology-based variables. A base case scenario matches historical proven reserves data for these three types of natural gas. An environmental scenario, based on implementing a $50/tonne CO 2 tax results in less proven reserves being developed in the coming years while demand may decrease in the absence of acceptable substitutes, incentives or changes in consumer behavior. An increase in demand of 25% increases proven reserves being developed by a very small amount by the end of the forecast period of 2025.

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Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

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Sandia National Laboratories has developed several models to analyze potential consequences of homeland security incidents. Two of these models (the National Infrastructure Simulation and Analysis Center Agent-Based Laboratory for Economics, N-ABLE{trademark}, and Loki) simulate detailed facility- and product-level consequences of simulated disruptions to supply chains. Disruptions in supply chains are likely to reduce production of some commodities, which may reduce economic activity across many other types of supply chains throughout the national economy. The detailed nature of Sandia's models means that simulations are limited to specific supply chains in which detailed facility-level data has been collected, but policymakers are often concerned with the national-level economic impacts of supply-chain disruptions. A preliminary input-output methodology has been developed to estimate national-level economic impacts based upon the results of supply-chain-level simulations. This methodology overcomes two primary challenges. First, the methodology must be relatively simple to integrate successfully with existing models; it must be easily understood, easily applied to the supply-chain models without user intervention, and run quickly. The second challenge is more fundamental: the methodology must account for both upstream and downstream impacts that result from supply-chain disruptions. Input-output modeling typically estimates only upstream impacts, but shortages resulting from disruptions in many supply chains (for example, energy, communications, and chemicals) are likely to have large downstream impacts. In overcoming these challenges, the input-output methodology makes strong assumptions about technology and substitution. This paper concludes by applying the methodology to chemical supply chains.

Tensions between the energy and water sectors occur when demand for electric power is high and water supply levels are low. There are several regions of the country, such as the western and southwestern states, where the confluence of energy and water is always strained due to population growth. However, for much of the country, this tension occurs at particular times of year (e.g., summer) or when a region is suffering from drought conditions. This report discusses prior work on the interdependencies between energy and water. It identifies the types of power plants that are most likely to be susceptible to water shortages, the regions of the country where this is most likely to occur, and policy options that can be applied in both the energy and water sectors to address the issue. The policy options are designed to be applied in the near term, applicable to all areas of the country, and to ease the tension between the energy and water sectors by addressing peak power demand or decreased water supply.