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Master of Environmental Data Science

Evaluating Steel Plant Emissions in the United States

Group Members: Erica Bishop, Ruth Enriquez, Amritpal (Amrit) Sandhu, Michael Zargari

Faculty Advisors: Roland Geyer

Client: Global Energy Monitor




Globally, iron and steel production account for 11% of carbon dioxide emissions. In the US, most steel plants already use electric arc furnace (EAF) technology, rather than the coal-powered furnaces prevalent in the rest of the world. This energy-intensive industry is facing increasing pressure to decarbonize, and EAF technologies provide a promising path for electrification. However, electrification will only be beneficial if the emissions-intensity of the electricity powering these plants is low. Determining the emissions intensity of steel production is especially critical for the Inflation Reduction Act (IRA), which provides $6 billion in funding for heavy industry decarbonization under the Advanced Industries Deployment Program (AIDP).

Our project will estimate carbon emissions for steel plant locations in the US and map them in Tableau. This map will use Global Energy Monitor’s open source steel plant production data, emissions intensity data from electricity maps, and emissions data from the EPA’s Greenhouse Gas Reporting Program to identify which steel plants are the most carbon-intense. Results from this analysis and the interactive map will be used to make recommendations for decarbonization spending under the AIDP. The plant-level analysis from this project will empower steel producers and consumers, including clean energy developers, to steer the industry toward a low-carbon future. 

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