Bridging geochemical observations with continental growth and emergence: A new modeling approach with heterogeneous crustal reservoirs

Understanding how Earth became a habitable planet requires knowing how its interior and surface evolved over time. The oldest rocks are rare and often difficult to interpret, which makes it hard to reconstruct Earth’s early history. This project will develop new ways to interpret chemical signals preserved in rocks so that scientists can better understand how the Earth formed and changed through time. By linking these signals to large-scale planetary processes, the research will improve our understanding of Earth’s evolution and may also help scientists study other rocky planets. The project will support student research and engage local schools through science outreach, helping to expand training of the future scientific workforce. This project will develop next-generation geochemical box models that incorporate key physical and chemical processes previously neglected or oversimplified, including finite-time mantle mixing, compositional heterogeneity in both mantle and crustal reservoirs, and age-dependent crustal recycling and reworking. The modeling framework will be extended to assimilate multiple observational constraints, including global detrital zircon age-isotope datasets and geochemical data from olivine-hosted melt inclusions, and will be systematically explored using computationally efficient Monte Carlo approaches to establish quantitative mass-balance constraints on the compositions of the continental crust and depleted mantle. The resulting framework will provide a unified and extensible platform for testing competing hypotheses of crust-mantle differentiation and for generating testable predictions regarding Earth’s chemical and physical evolution. 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. NSF Award ID: 2535856 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Jun Korenaga | Institution: Yale University, NEW HAVEN, CT | Award Amount: $386,921 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2535856 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2535856.html