What are we doing?
Welcome to CACEE Lab @ Texas A&M University!
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.
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
2025-02-05
Dr. Shuang Zhang contributes to a new paper in Nature.This study highlights the potential of enhanced weathering (EW) on U.S. agricultural lands to sequester 0.16–0.30 GtCO2 annually by 2050, with further increases by 2070. The detailed carbon cycle analysis emphasizes the intergenerational benefits of EW, temporary air quality improvements, and declining CDR costs to $100–150 per ton CO2 by mid-century, positioning EW as a viable support for achieving net-zero emissions. Beerling, D. J., Kantzas, E. P., Lomas, M. R., Taylor, L. L., Zhang, S., Kanzaki, Y., et al. (2025). Transforming US agriculture for carbon removal with enhanced weathering. Nature, 1–10. https://doi.org/10.1038/s41586-024-08429-2
Dr. Shuang Zhang contributes to a new paper in Nature.This study highlights the potential of enhanced weathering (EW) on U.S. agricultural lands to sequester 0.16–0.30 GtCO2 annually by 2050, with further increases by 2070. The detailed carbon cycle analysis emphasizes the intergenerational benefits of EW, temporary air quality improvements, and declining CDR costs to $100–150 per ton CO2 by mid-century, positioning EW as a viable support for achieving net-zero emissions. Beerling, D. J., Kantzas, E. P., Lomas, M. R., Taylor, L. L., Zhang, S., Kanzaki, Y., et al. (2025). Transforming US agriculture for carbon removal with enhanced weathering. Nature, 1–10. https://doi.org/10.1038/s41586-024-08429-2
2025-02-01
Dr. Shuang Zhang contributes to a new paper in Applied Geochemistry. This study uses random forest models to predict future salinity (sodium) and alkalinity fluxes in 226 U.S. rivers under varying population densities and climate scenarios from 2040 to 2100. The findings highlight regional differences in sodium flux changes and the complex effects of temperature and precipitation on alkalinity flux, emphasizing the need for adaptive river management strategies. E, B., Zhang, S., Carter, E., Meem, T. J., & Wen, T. (2025). Predicting salinity and alkalinity fluxes of U.S. freshwater in a changing climate: Integrating anthropogenic and natural influences using data-driven models. Applied Geochemistry, 180, 106285. https://doi.org/10.1016/j.apgeochem.2025.106285
Dr. Shuang Zhang contributes to a new paper in Applied Geochemistry. This study uses random forest models to predict future salinity (sodium) and alkalinity fluxes in 226 U.S. rivers under varying population densities and climate scenarios from 2040 to 2100. The findings highlight regional differences in sodium flux changes and the complex effects of temperature and precipitation on alkalinity flux, emphasizing the need for adaptive river management strategies. E, B., Zhang, S., Carter, E., Meem, T. J., & Wen, T. (2025). Predicting salinity and alkalinity fluxes of U.S. freshwater in a changing climate: Integrating anthropogenic and natural influences using data-driven models. Applied Geochemistry, 180, 106285. https://doi.org/10.1016/j.apgeochem.2025.106285
2025-01-14
Dr. Shuang Zhang publishes a new paper in Environmental Research Letters. This study introduces a dynamic river network (DRN) model to assess how enhanced weathering (EW) impacts river carbonate chemistry in North American watersheds. The model reveals that while carbon loss during river transport is generally low (<5%), certain river pathways show significantly higher degassing (>15%), highlighting the need for regional evaluations of EW’s effectiveness as a carbon mitigation strategy. Zhang, S., Reinhard, C. T., Liu, S., Kanzaki, Y., & Planavsky, N. J. (2025). A framework for modeling carbon loss from rivers following terrestrial enhanced weathering. Environmental Research Letters, 20(2), 024014. https://doi.org/10.1088/1748-9326/ada398
Dr. Shuang Zhang publishes a new paper in Environmental Research Letters. This study introduces a dynamic river network (DRN) model to assess how enhanced weathering (EW) impacts river carbonate chemistry in North American watersheds. The model reveals that while carbon loss during river transport is generally low (<5%), certain river pathways show significantly higher degassing (>15%), highlighting the need for regional evaluations of EW’s effectiveness as a carbon mitigation strategy. Zhang, S., Reinhard, C. T., Liu, S., Kanzaki, Y., & Planavsky, N. J. (2025). A framework for modeling carbon loss from rivers following terrestrial enhanced weathering. Environmental Research Letters, 20(2), 024014. https://doi.org/10.1088/1748-9326/ada398