  Recent computing needs have lead technology companies to develop large scale,
highly optimized data centers. These data centers represent large loads on
electric power networks which have the unique flexibility to shift load both
geographically and temporally. This paper focuses on how data centers can use
their geographic load flexibility to reduce carbon emissions through clever
interactions with electricity markets. Because electricity market clearing
accounts for congestion and power flow physics in the electric grid, the carbon
emissions associated with electricity use varies between (potentially
geographically close) locations. Using our knowledge about this process, we
propose a new and improved metric to guide geographic load shifting, which we
refer to as the locational marginal carbon emission $\lambda_{\text{CO}_2}$. We
compare this and three other shifting metrics on their ability to reduce carbon
emissions and generation costs throughout the course of a year. Our analysis
demonstrates that $\lambda_{\text{CO}_2}$ is more effective in reducing carbon
emissions than more commonly proposed metrics that do not account for the
specifics of the power grid.
