Zooming in on the Water-Energy Nexus

I co-developed a methodology for estimating U.S. manufacturing water use at the County level, for different subsectors (e.g. Primary Metals, Textile Mills, Food). The results were published in Environmental Science and Technology, an American Chemical Society publication.

In edition to developing the methodology, I wrote the Python code to clean and analyze disparate data from a wide variety of sources, including the U.S. census. I used pandas to clean and structure the data and leveraged plotly in combination with custom plotting tools to create interactive visualizations and choropleth maps.

With these metrics and visualizations, our funders at the Department of Energy could prioritize research dollars for technology that would have the greatest impact across the most water-intensive sectors in US manufacturing.