Abstract
21st-century modeling of greenhouse gas (GHG) emissions from bioenergy crops is necessary to quantify the extent to which bioenergy production can mitigate climate change. For over 30 years, the Century-based biogeochemical models have provided the preeminent framework for belowground carbon and nitrogen cycling in ecosystem and earth system models. While monthly Century and the daily time-step version of Century (DayCent) have advanced our ability to predict the sustainability of bioenergy crop production, new advances in feedstock generation, and our empirical understanding of sources and sinks of GHGs in soils call for a re-visitation of DayCent's core model structures. Here, we evaluate current challenges with modeling soil carbon dynamics, trace gas fluxes, and drought and age-related impacts on bioenergy crop productivity. We propose coupling a microbial process-based soil organic carbon and nitrogen model with DayCent to improve soil carbon dynamics. We describe recent improvements to DayCent for simulating unique plant structural and physiological attributes of perennial bioenergy grasses. Finally, we propose a method for using machine learning to identify key parameters for simulating N2O emissions. Our efforts are focused on meeting the needs for modeling bioenergy crops; however, many updates reviewed and suggested to DayCent will be broadly applicable to other systems.
Original language | English |
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Pages (from-to) | 774-788 |
Number of pages | 15 |
Journal | GCB Bioenergy |
Volume | 12 |
Issue number | 10 |
DOIs | |
State | Published - Oct 1 2020 |
Funding
We thank Ilsa Kantola for providing us with Miscanthus and switchgrass biomass data from UIUC Energy Farm. This work was funded by the DOE Center for Advanced Bioenergy and Bioproducts Innovation (U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE‐SC0018420) and by the National Science Foundation (Award Number DEB‐1553049). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Energy. We thank Ilsa Kantola for providing us with Miscanthus and switchgrass biomass data from UIUC Energy Farm. This work was funded by the DOE Center for Advanced Bioenergy and Bioproducts Innovation (U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-SC0018420) and by the National Science Foundation (Award Number DEB-1553049). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Energy.
Funders | Funder number |
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DOE Center for Advanced Bioenergy and Bioproducts Innovation | |
Office of Biological and Environmental Research | DE-SC0018420 |
National Science Foundation | DEB‐1553049 |
U.S. Department of Energy | |
University of Illinois at Urbana-Champaign | |
Office of Science | |
Biological and Environmental Research | DE‐SC0018420 |
Keywords
- NO
- bioenergy
- biogeochemical modeling
- drought
- plant age dynamics
- soil