Resource families
- Biomass and residues
- Organic and plastic wastes
- Industrial, secondary and alkaline materials
MODULE 01
Resource Supply & Secondary Feedstocks
What carbon and material resources are actually available?
Move from resource inventories to constrained, spatial and seasonal supply. Biomass is one resource family; wastes, secondary carbon and industrial by-products are first-class parts of the system.
Open lesson →
MODULE 01Availability
- Spatial and seasonal supply
- Technical to deployable potential
- Soil, land and nutrient constraints
CURRICULUM
6 lessons
165 min
01Biomass, wastes and secondary carbonBeginner · 24 minA resource taxonomy broad enough for agriculture, forests, organic wastes, plastics, industrial by-products and mineral or alkaline streams.02Feedstock characteristics and conversion fitBeginner · 26 minWhy moisture, ash, composition, particle form and variability often matter more than nominal resource labels.03Spatial, seasonal and temporal supplyIntermediate · 28 minWhy an annual total cannot describe collection radius, storage pressure, supply reliability or changing land use.04Soil, land and nutrient constraintsIntermediate · 30 minResidue removal and dedicated biomass must be read through soil cover, organic matter, nutrients, erosion, water and land competition.05Resource assessment and supply curvesIntermediate · 30 minHow inventories become quantity–cost relationships while retaining sustainability, geography and uncertainty.06Wastes, by-products and secondary feedstocksIntermediate · 27 minHow current fate, contamination, regulation and avoided treatment shape the value of waste-derived resources.
EVIDENCE LIBRARY
Research, models & tools
A curated starting shelf for this teaching area.
TOOLS
Related tools
ORNL / U.S. DOE
BioenergyKDF
A discovery portal for U.S. biomass resource data, analyses and bioenergy tools.
- Use it when
- Where can analysts find documented resource and pathway data?
- Limits
- Datasets differ in date, resolution and assumptions and must be reconciled before use.
Inputs, outputs & scope
- Inputs
- Search terms, geography, resource classes and analysis needs.
- Outputs
- Datasets, metadata, reports and links to analysis tools.
- Typical applications
- Resource assessments, supply curves, scenario framing and provenance discovery.
USDA NRCS / Colorado State University
COMET-Farm
A web tool for estimating farm-scale greenhouse-gas emissions and soil-carbon changes under management scenarios.
- Use it when
- How might a farm's current and alternative practices differ in GHG emissions and carbon sequestration?
- Limits
- Screening estimates depend on user inputs and model applicability; they do not replace project-specific measurement and verification.
Inputs, outputs & scope
- Inputs
- Location, soils, crops, livestock, energy use and detailed management histories or scenarios.
- Outputs
- Comparative farm GHG estimates and soil-carbon changes by scenario.
- Typical applications
- Management screening, farm carbon planning and contextualizing residue or soil-carbon decisions.
Colorado State University
DayCent
A daily time-step ecosystem model for carbon and nitrogen flows among soil, vegetation and atmosphere.
- Use it when
- How do management and environmental conditions affect soil carbon and greenhouse-gas fluxes?
- Limits
- Parameterization and validation determine credibility; model structure cannot replace field evidence.
Inputs, outputs & scope
- Inputs
- Climate, soil properties, vegetation, land use and management schedules.
- Outputs
- Carbon and nitrogen pools, productivity, water states and trace-gas fluxes.
- Typical applications
- Soil-carbon baselines, residue-removal scenarios and agricultural GHG accounting.
CASE STUDIES
Examples from Wang Group
2023Conversion
Mixed plastics wastes upcycling with high-stability single-atom Ru catalyst
A conversion case for discussing mixed-plastic heterogeneity, catalyst stability and why selectivity must be read with feedstock composition.
2023Resources
Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes
Shows how machine learning and Van Krevelen space can make feedstock–product relationships legible without turning the model into the research question itself.
2025Deployment
Assessing the Techno-Economic Feasibility of Bamboo Residue-Derived Hard Carbon
Connects regional bamboo-residue supply, process assumptions and discounted cash flow to a deployability question for hard carbon.
REFERENCES
References & further reading
- Food and Agriculture Organization of the United Nations (2026). Sustainable and circular bioeconomy: glossary and key terms.Open source ↗
- U.S. Department of Energy (2024). 2023 Billion-Ton Report: An Assessment of U.S. Renewable Carbon Resources.https://doi.org/10.23720/BT2023/2316165 ↗
- European Commission (2018). Guidance on cascading use of biomass with selected good practice examples on woody biomass.https://doi.org/10.2873/68553 ↗
- U.S. Department of Energy (2024). Feedstock-Conversion Interface Consortium: Crosscutting Analysis Research.Open source ↗
- Zhu, Li and Wang (2019). Machine learning prediction of biochar yield and carbon contents in biochar based on biomass characteristics and pyrolysis conditions.https://doi.org/10.1016/j.biortech.2019.121527 ↗
- Noon and Daly (1996). GIS-based biomass resource assessment with BRAVO.https://doi.org/10.1016/0961-9534(95)00065-8 ↗
- Welfle, Gilbert and Thornley (2014). Increasing biomass resource availability through supply chain analysis.https://doi.org/10.1016/j.biombioe.2014.08.001 ↗
- Oak Ridge National Laboratory / U.S. Department of Energy (2026). Bioenergy Knowledge Discovery Framework.Open source ↗
- Stetson et al. (2012). Corn Residue Removal Impact on Topsoil Organic Carbon in a Corn-Soybean Rotation.https://doi.org/10.2136/sssaj2011.0420 ↗
- Guzman and Al-Kaisi (2014). Residue Removal and Management Practices Effects on Soil Environment and Carbon Budget.https://doi.org/10.2136/sssaj2013.10.0426 ↗
- Barrios Latorre et al. (2024). Exploring the benefits of intermediate crops: Is it possible to offset soil organic carbon losses caused by crop residue removal?.https://doi.org/10.1016/j.agsy.2024.103873 ↗
- Hakala et al. (2016). Field trial results of straw yield with different harvesting methods, and modelled effects on soil organic carbon.https://doi.org/10.1016/j.biombioe.2016.08.021 ↗
- Natural Resource Ecology Laboratory, Colorado State University (2026). DayCent Model.Open source ↗
- Natural Resource Ecology Laboratory, Colorado State University (2026). CENTURY Model.Open source ↗
- Zedong Zhang, Jia Wang, Xiaohu Ge, Shule Wang, Ang Li, Runze Li, Ji Shen, Xiao Liang, Tao Gan, Xiaodong Han, Xusheng Zheng, Xuezhi Duan, Dingsheng Wang, Jianchun Jiang, Yadong Li (2023). Mixed plastics wastes upcycling with high-stability single-atom Ru catalyst.https://doi.org/10.1021/jacs.3c09338 ↗
- Shule Wang, Yiying Wang, Ziyi Shi, Kang Sun, Yuming Wen, Lukasz Niedzwiecki, Ruming Pan, Yongdong Xu, Ilman Nuran Zaini, Katarzyna Jagodzińska, Christian Aragon-Briceno, Chuchu Tang, Thossaporn Onsree, Nakorn Tippayawong, Halina Pawlak-Kruczek, Pär Göran Jönsson, Weihong Yang, Jianchun Jiang, Sibudjing Kawi, Chi-Hwa Wang (2023). Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes.https://doi.org/10.1038/s42004-023-01077-z ↗
- Senqiang Qin, Chenghao Yu, Yanghao Jin, Gaoyue Zhang, Wei Xu, Ao Wang, Mengmeng Fan, Kang Sun, Shule Wang (2025). Assessing the Techno-Economic Feasibility of Bamboo Residue-Derived Hard Carbon.https://doi.org/10.3390/app15137113 ↗