Michael-ljn/pathways-H2-prod-within-PBs
Publication repository: Pathways to global hydrogen production within planetary boundaries
Pathways to global hydrogen production within planetary boundaries
Available at: Lejeune, M., Kara, S., Hauschild, M.Z. et al. Pathways to global hydrogen production within planetary boundaries. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70168-x.
1. Code availability
Important
The underlying code lce.jl for data pre-processing is not provided in this repository. As demonstrated in the Tutorial, the code is not required for reproducing the results. Therefore, access to this code can be provided upon reasonable request to the corresponding authors.
We provide in the code used to generate results. However, we used an in-house software for data formatting and processing lce.jl, which is not publicly available yet. The software is currently hard to use for external users and undocumented. We recommend using PULPO which is already comprehensive enough to perform the analysis. That said, we are working on making lce.jl open-source in the future.
The code used for the planetary boundary chart is available here.
2. Results
All results can be found in Source data Folder.
3. Replication
3.1 AR6 scenario ensemble
The AR6 dataset is publicly available:
Byers, E. et al. (2022) ‘AR6 Scenarios Database’. Integrated Assessment Modeling Consortium & International Institute for Applied Systems Analysis. Available at: https://doi.org/10.5281/ZENODO.5886911.
The data set can be filtered using the list of scenarios considered.
3.2 Premise scenario ensemble
We generated prospective life cycle assessment data using Premise. The notebook used to generate scenarios is available here. To run this code, you will need:
- access to ecoinvent database (here we used 3.9.1).
- decryption key from the premise developers.
3.3 Optimisation model
For replication of results, we provide a simple tutorial with step by step instructions using Activity-browser, ScenarioLink, Microsoft Excel and JuMP.jl. Experienced python developers can also adapt the optimisation code to python using the pyomo pacakage
4. Relevant publications to check out
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Bachmann, M. et al. (2023) ‘Towards circular plastics within planetary boundaries’, Nature Sustainability, 6(5), pp. 599–610. Available at: https://doi.org/10.1038/s41893-022-01054-9.
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Kätelhön, A., Bardow, A. and Suh, S. (2016) ‘Stochastic Technology Choice Model for Consequential Life Cycle Assessment’, Environmental Science & Technology, 50(23), pp. 12575–12583. Available at: https://doi.org/10.1021/acs.est.6b04270.
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Heijungs, R. and Suh, S. (2002) The computational structure of life cycle assessment. Dordrecht: Springer-Science + Business Media (Eco-efficiency in industry and science, 11).
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Lade, S.J. et al. (2020) ‘Human impacts on planetary boundaries amplified by Earth system interactions’, 3(2), pp. 119–128. Available at: https://doi.org/10.1038/s41893-019-0454-4.
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Lechtenberg, F. et al. (2024) ‘PULPO: A framework for efficient integration of life cycle inventory models into life cycle product optimization’, Journal of Industrial Ecology, n/a(n/a). Available at: https://doi.org/10.1111/jiec.13561.