We developed a physically-based environmental account of U.S. food production systems and integrated these data into the Environmental-Input-Output Lifecycle Assessment (EIO-LCA) model. The extended model was used to characterize and compare the food, energy, and water (FEW) intensities of every U.S. economic sector. The model was then applied to every Bureau of Economic Analysis (BEA) metropolitan statistical area (MSA) to determine their FEW usages.
By integrating this physical data, the extended EIO-LCA model can determine the food resource use in units of mass (kg) or energy content (kcal), water use (kGal), and energy use (TJ) of any economic activity within the United States. We have analyzed every economic sector to determine its FEW intensities per dollar of economic output. This data was applied to each of the 382 MSAs to determine their total and per capita FEW usages by allocating MSA economic spending to the corresponding FEW intensities of US economic sectors. Additionally, a longitudinal study was performed for the Los Angeles-Long Beach-Anaheim, CA metropolitan statistical area to examine trends from this singular MSA and compare it to the overall results.
Results show a strong correlation between GDP and energy use, and between food and water use across sectors. There is also a weaker correlation between food and energy use. The longitudinal study indicates that these correlations have been consistent over the past decade. For MSAs, economic output increases linearly with population. So too, does FEW resource use. Comparing MSAs on a per capita basis reveals that central and southern California tend to be more resource intensive than many other parts of the country, while much of Florida has abnormally low resource requirements.
The results of this study enable a more complete understanding of food, energy, and water as key ingredients to a functioning economy. With the food data added to the EIO-LCA framework, researchers will be able to better study the food-energy-water nexus and gain insight into how these three vital resources are interconnected. Applying this extended model to MSAs has demonstrated that all three resources are important to a city’s vitality, though the exact proportion of each resource may differ across urban areas.