Code and data in support of: Uncertainty in determining carbon dioxide removal potential of biochar

A quantitative and systematic assessment of uncertainty in life-cycle assessment is critical to informing sustainable development of carbon dioxide removal (CDR) technologies. Biochar is the most commonly sold form of CDR to date, and it can be used in applications ranging from concrete to agricultural soil amendments. Previous analyses of biochar rely on modeled or estimated life-cycle data and suggest a cradle-to-gate range of 0.20–1.3 kg CO2 net removal per kg of biomass feedstock, driven by differences in energy consumption, pyrolysis temperature, and feedstock sourcing. Herein, we quantify the distribution of CDR possible for biochar production with a compositional life-cycle inventory model paired with scenario-aware Monte Carlo simulation in a “best practice” (incorporating lower transportation distances, high pyrolysis temperatures, high energy efficiency, recapture of energy for drying and pyrolysis energy requirements, and co-generation of heat and electricity) and “poor pract..., , , # Uncertainty in determining carbon dioxide removal potential of biochar

README for Biochar Uncertainty Sceniaro Aware Monte Carlo Simulation code

**Accompanies publication:** Kane, Seth, et al. \"Uncertainty in determining carbon dioxide removal potential of biochar.\" Environmental Research Letters (2024). doi: 10.1088/1748-9326/ad99e9

Prepared by: Seth Kane and Ahmad Bin Thaneya

**Prepared on:** 10.4.2024

**Last edited on:** 08.01.2025

**Last edited by:** Seth Kane

**Last ran in:** MATLAB R 2024a (Vers. 24.1.0.2628055), Python Vers. 3.12.8, and Microsoft Excel Vers. 16.91

**Contents:**

**Visual_framework.pdf:**

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Flow diagram describing the location of input data to each model, interconnection of models contained herein, and description and location of results in the below-described file structure.
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**Folder: Predictive pyrolysis model uncertainty code**

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Contains the MATLAB code that determines model error distributions from the residuals of the validation datas...