The United States population consumes more meat per capita than any country except for Australia and roughly 80% of this consumption occurs in U.S. cities. This meat is sourced from distant regions, which shields urban dwellers from the environmental and societal burdens associated with its production. Studies of urban metabolism have illuminated the aggregate impacts of material and energy stocks and flows, but such modeling lacks the spatial detail necessary to analyze transboundary flows ('teleconnections') or the specific drivers of urban demand. Cities (and society) lack the requisite knowledge and tools to mitigate impacts due to the consumption of products (including meat). This project addresses this gap by addressing three questions: 1) What are the environmental impacts associated with meat consumption in U.S. cities? 2) Where are key 'hotspots' along meat supply chains? 3) What population segments are driving the consumption? The project will develop a spatially-explicit life cycle assessment (LCA) approach to model and map the urban hoofprint of twenty U.S. cities.

This model, MeatS2 (Meat Sustainable Supply-Chain), operates at two spatial scales: within the city (urban meat demand by demographic groups) and along the production supply chain (hotspots of environmental and social impact). The model will be applied to beef, pork, and chicken (the hoofprint) and considers five indicators: greenhouse gas emissions, water scarcity, land use, nutrient loading (nitrates and phosphates), and particulate matter (PM2.5). Complementing the twenty-city analysis will be in-depth hoof print modeling of Los Angeles. To build the MeatS2 model, the project team weds concepts and methods from industrial ecology and geography (esp. political ecology, GIS, and environmental justice). This will be a large-scale study of how and where urban meat consumption in U.S. cities drives environmental and social change. Results from the research may have the potential to fundamentally influence the field of urban sustainability, which has traditionally used the built environment as the primary measure of a city's sustainability. This study may also have a transformative impact on the current state of knowledge of the drivers of the urban environmental footprint. For example, numerous studies identify income-level as the primary determinant, but based on initial evidence, an hypothesis to be explored is that lower-income segments of the urban population actually have larger hoot prints than those in higher-income brackets. Although the empirical focus is on livestock, MeatS2 seeks to offer a robust, generalizable methodology to model other transboundary resource flows and consumption drivers of a city's metabolism. Through the coupling of LCA with geospatial tools (i.e. GIS) and underutilized datasets (e.g. supermarket scanner data), this work targets to significantly advance urban metabolism modeling and analysis. Over time, this interdisciplinary synthesis may lead to new (and unexpected) knowledge breakthroughs in both industrial ecology and geography. By comparing the environmental impacts of meat consumption with other key urban metabolic drivers (e.g. transportation and buildings) and by linking producers and consumers in meat supply chains across disparate geographies, this study intends to challenge and strengthen plans, strategies, and policies designed to foster urban sustainability. Project findings will reach broader society through Hoofprint, a public-facing, web-based geovisualization tool that allows users to interactively explore hoofprints, meatsheds, and meat justice dimensions within and across the twenty U.S. cities. To further democratize knowledge about meat and the profound role that consumption has on distal regions and peoples, the research team will curate and teach The Hoofprint of Cities, a multimedia sustainability case module designed to promote engaged participatory learning. This online case will be freely available for educators, students, stakeholders, and the general public.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2018-07-15
Budget End
2022-06-30
Support Year
Fiscal Year
2018
Total Cost
$313,049
Indirect Cost
Name
Regents of the University of Michigan - Ann Arbor
Department
Type
DUNS #
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109