Our group broadly uses data-driven and model-driven approaches to quantify the patterns of element flux and isotope behavior involved in the global carbon and biogeochemical cycles, especially under periods of climatic perturbations. Extensive data mining, data assimilation, large-scale spatial-temporal statistical analysis, and machine learning are frequently used in our research projects. We hope geo-statistics and machine learning could reveal the intrinsic patterns of nature’s processes that are sometimes extremely difficult to be captured by classical physical process models. With that being said, in areas where data is extremely limited or data-driven approaches are not suitable, numerical modeling (e.g., modeling the global carbon cycle) also serves as a critical tool in our research.
Recent News
2024-11-05 Dr. Shuang Zhang, as chair of the science working group on carbon leakage in downstream rivers and the ocean, contributed to developing a community quantification standard for Enhanced Rock Weathering (ERW) under Cascade Climate, a philanthropically-backed nonprofit. This work led to the release of “Foundations for Carbon Dioxide Removal Quantification in Enhanced Rock Weathering Deployments,” a critical document that establishes rigorous, standardized quantification for advancing ERW research and deployment. Conducted from October 2023 to August 2024, this effort involved over 50 academic scientists worldwide, 20+ ERW project developers, and various civil society organizations. More information about this “Foundations” can be found here.
2024-10-29 Dr. Shuang Zhang, Yating Li, and Xiying Sun participated in the 2024 Undergraduate Research (UGR) Expo, which drew nearly 400 students. The purpose of the UGR Expo is to guide students through the topics they need to consider before getting started in research, such as defining their passion, understanding the research process, exploring potential careers in research, and establishing mentoring relationships. Dr. Zhang’s team presented on the theme of Carbon Dioxide Removal.
2024-09-01 Dr. Shuang Zhang has a new NSF grant (subaward): MCA: Incorporating Stream Biogeochemistry into Carbon Assessment of Enhanced Rock Weathering: A Machine Learning and Dynamic River Network Modelling Approach. 09/01/2024 - 08/31/2027. Dr. Rebecca Neumann (University of Washington) is the PI, with Dr. Zhang as the Co-PI.