Emma Moynihan

Bio: Emma Moynihan is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Nexus (standard) & Ventilation (architecture). The author has an hindex of 1, co-authored 2 publications receiving 1 citations.

Optimization-Based Systems Modeling for the Food-Energy-Water Nexus

Abstract: Optimization-based methods for the food-energy-water nexus can assist decision-making on critical infrastructure but are limited in scope and applicability. We provide an overview of optimization-based systems modeling techniques for operations researchers and systems modelers for the nexus. We find that the literature has contributed to the understanding of nexus interdependencies and has provided a framework for sustainability studies. We observe that the majority of the papers expand bottom-up models for one or two nexus components into the three, which may lead to asymmetric representation of the three sectors. Socioeconomic and political economy drivers are often exogenous to the models. The vast majority of papers can be further enhanced to account for local priorities, and the underlying decision-making process of stakeholders across the supply chains and at the interdependencies. Greater regional downscaling and technological detail along with more robust data could also enhance nexus systems modeling.

Data-Driven Modeling of Operating Characteristics of Hydroelectric Generating Units

Abstract: Hydroelectric generation is a potential flexible electricity source that can ease the transition to a decarbonized energy economy. As such, using scarce hydroelectric generating resources efficiently is important. We examine approaches to represent the operating characteristics of hydroelectric resources. Many hydroelectric-plant owners use water tables or generic unit characteristics for operational planning. Such practice may be inefficient, as it does not account for unit-specific operating-characteristic changes or time-related impacts, e.g., plant degradation. We demonstrate a data-driven approach to modeling plant operations that is unit-specific and depends solely on observable and controllable variables. Numerical results using historical data for four hydroelectric units illustrate the proposed methodology.

Optimization Based Modeling for the Food Supply Chain's Resilience to Outbreaks

Abstract: Scant research focuses on the resiliency of food supply chain networks to outbreaks, despite the estimated 600 million global foodborne illnesses annually. Outbreaks that cross country, state and provincial lines are virulent due to the number of people they can affect and difficulty controlling them. Research is needed on food supply chain networks, which are not well-characterized in relation to foodborne illnesses or generally. This paper introduces the United States Food, Energy, and State Transportation (US-FEAST) model and demonstrates its applicability via analysis of a hypothetical demand shock resulting from multistate food contamination. US-FEAST is an optimization-based model across all fifty states with yearly timesteps to 2030. It is a framework integrating food system data from multiple individual data sources. To calibrate, we develop a bilevel optimization routine to generate synthetic, state-level data and provide estimates of otherwise unavailable data at the intersections of the food and transportation systems. The results of US-FEAST elucidate potential heterogenous state-level variations in response, regional changes in food flows, vulnerabilities in the supply chain, and implications for food system resilience. While the generated data and scenarios are not empirical evidence, they provide insights to aid in planning by projecting outcomes and intervention effects. Our results estimate a 23% beef production decrease and 4% price decrease provide a road map toward data needs for quantifying food system resilience to foodborne illness. US-FEAST and its framework may have global utility for studying food safety in national and international food supply chain networks.

Biofuel Economy, Development, and Food Security

Abstract: This paper describes the biofuel economy and food security in the current scenario, focusing on the competing demands for food and fuel. The biofuel economy is expected to increase rapidly in the twenty-first century. This increase may, however, disrupt the agri-food system that threatens food security. Understanding the diverse aspects of the agriculture landscape to meet the demands for food and biofuel that rely on agricultural biomass is essential to satisfy the needs of the exponentially growing global population. The concepts of industrial symbiosis and circular economy offer potential solutions to sustain the biofuel economy without putting at risk the supply of food and utilizing wastes and residues from the farm, including the refuse from food processing plants, as raw materials for biofuel generation are probable ways to optimize the overall productivity of agriculture towards addressing the requirements for food and biofuel. Also, adopting Smart Agriculture/Agriculture 4.0 is explored for the management of the entire agri-food supply chain from pre-production to post-harvest stage to sustain the biofuels endeavour without disrupting the food supply. Agriculture 4.0 can provide a holistic view of the agri-food system crucial in a circular economy to ensure efficiency in biofuel production and food security.