Social and biophysical models to integrate local food systems, climate dynamics, built forms, and environmental impacts in the Urban Food-Energy-Water Systems nexus
Systems frameworks that analyze the Urban FEWS nexus have only recently been proposed. Developing such frameworks is challenging because urban FEW systems are characterized by disconnected processes for production, distribution, consumption, and cycling of food, energy, and water systems. In addition, the effects of changes in climate and land use, built forms, and their impacts on food supply, energy conservation and consumption, and environmental outcomes (e.g., water quality) are often considered in isolation. Our proposed work will address problems related to urban food systems, which alone cause 20% to 50% of human impact on the environment as a result of high population densities, heavy reliance on external food sources, and failure to recycle nutrients. To conduct robust analyses of urban FEW systems it is necessary to consider interactions within the urban system itself, as well as trans-boundary interactions with areas both adjacent to and further removed from the system. While frameworks emphasizing the biophysical elements of urban FEW systems and interactions among them have been presented, previous efforts failed to closely integrate social, biophysical, and climatic models to characterize the urban FEW system-of-systems. Urban areas are where over 50% of people in the world and 80% of people in the US live and work. Human choices drive significant changes in both social and physical landscapes, so it is imperative to integrate social dynamics in analyses of the urban FEWS nexus.
Mar 03, 2020
Posted Jan 22, 2020 9:47 am
Dense urban areas use up more energy, water and food resources than they can produce themselves, forcing them to rely on external sources. But a team of researchers is imagining bold new ways to make Midwestern cities more self-reliant.
The Sustainable Cities Research Team recently received a $2.5 million grant from the National Science Foundation to develop a framework for analysis of food, energy and water systems for greater Des Moines, which includes the city and the surrounding six-county area, and to formulate scenarios that could result in a more sustainable city. The team includes scientists from a wide range of disciplines at Iowa State University, the University of Northern Iowa and University of Texas at Arlington.
The group intends for its results to inform decisions about food production, energy use, environmental outcomes and related policies that would apply to a large number of cities in rain-fed climates similar to Des Moines. Their innovative approach could help cities conserve building and transportation energy, reduce environmental impacts and improve city sustainability.
Oct 03, 2021
The presentation was based on Sedigheh Ghiasi’s MS in Architecture thesis, which she will also defend this fall.
Title: An interactive GIS-based method to enable homeowners and architects to determine feasible roof areas for photovoltaic (PV) panels
Sep 21, 2021
The Iowa UrbanFEWS project values sharing our research beyond academia. When Mustard Seed Community Farm, a local non-profit in Ames, Iowa reached out to a PhD student on the team, a roundtable discussion about food systems emerged.
Tiffanie Stone led the discussion - her research with the project is focused on understanding the environment and social impacts of different types of food systems.
Sep 14, 2021
Diba Malekpour Koupaei, PhD candidate in the Civil Engineering Department at Iowa State University, presented the team’s most recent research efforts on developing a workflow for the integration of high-resolution tree geometries in urban energy simulation models at the same conference. Her paper, titled “A framework for integrating high-resolution trees in urban energy use models”, focused on the development of an improved modelling framework for estimating the amount and timing of shading from trees and its effects on cooling and heating energy use in residential buildings.
This work is supported by the National Science Foundation, Award # 1855902. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.