Page 68 - 2417
P. 68
François et al. Carbon Footprints 2026, 5, 22 Page 21 of 22
2. Benoist, A. Eléments d’adaptation de la méthodologie d’analyse de cycle de vie aux carburants végétaux : cas de la première génération -
Adapting life-cycle assessment to biofuels: some elements from the first generation case. Theses. École Nationale Supérieure des Mines
de Paris, 2009. https://pastel.hal.science/pastel-00005919 (accessed 2026-04-09).
3. Kendall, A.; Chang, B.; Sharpe, B. Accounting for time-dependent effects in biofuel life cycle greenhouse gas emissions calculations.
Environ. Sci. Technol. 2009, 43, 7142-7. DOI PubMed
4. Lang‐quantzendorff, L.; Beermann, M. Time‐differentiating methods for life cycle assessment of the industry transition toward climate
neutrality: a review. J. Ind. Ecol. 2025, 29, 1523-50. DOI
5. Breton, C.; Blanchet, P.; Amor, B.; Beauregard, R.; Chang, W. Assessing the climate change impacts of biogenic carbon in buildings: a
critical review of two main dynamic approaches. Sustainability 2018, 10, 2020. DOI
6. Tiruta-barna, L.; Pigné, Y.; Navarrete Gutiérrez, T.; Benetto, E. Framework and computational tool for the consideration of time
dependency in Life Cycle Inventory: proof of concept. J. Clean. Prod. 2016, 116, 198-206. DOI
7. Beloin-saint-pierre, D.; Heijungs, R.; Blanc, I. The ESPA (enhanced structural path analysis) method: a solution to an implementation
challenge for dynamic life cycle assessment studies. Int. J. Life. Cycle. Assess. 2014, 19, 861-71. DOI
8. Cardellini, G.; Mutel, C. L.; Vial, E.; Muys, B. Temporalis, a generic method and tool for dynamic life cycle assessment. Sci. Total.
Environ. 2018, 645, 585-95. DOI PubMed
9. Cardellini, G.; Mutel, C. Temporalis: an open source software for dynamic LCA. JOSS. 2018, 3, 612. DOI
10. Müller, A.; Diepers, T.; Jakobs, A.; et al. Time-explicit life cycle assessment: a flexible framework for coherent consideration of
temporal dynamics. Int. J. Life. Cycle. Assess. 2025, 30, 3052-71. DOI PubMed PMC
11. JORF. Décret n° 2021-1004 du 29 juillet 2021 relatif aux exigences de performance énergétique et environnementale des constructions
de bâtiments en France métropolitaine - Légifrance. 2021. https://www.legifrance.gouv.fr/jorf/id/JORFSCTA000043877244 (accessed
2026-04-09).
12. CIRAIG. dynCO2: Dynamic carbon footprinter 2010. https://ciraig.org/index.php/project/dynco2-dynamic-carbon-footprinter/ (accessed
2026-04-09).
13. Levasseur, A.; Lesage, P.; Margni, M.; Deschênes, L.; Samson, R. Considering time in LCA: dynamic LCA and its application to global
warming impact assessments. Environ. Sci. Technol. 2010, 44, 3169-74. DOI PubMed
14. Shimako, A. H.; Tiruta-Barna, L.; Bisinella de Faria, A. B.; Ahmadi, A.; Spérandio, M. Sensitivity analysis of temporal parameters in a
dynamic LCA framework. Sci. Total. Environ. 2018, 624, 1250-62. DOI PubMed
15. Resch, E.; Andresen, I.; Cherubini, F.; Brattebø, H. Estimating dynamic climate change effects of material use in buildings-timing,
uncertainty, and emission sources. Build. Environ. 2021, 187, 107399. DOI
16. Füchsl, S.; Huber, J.; Fröhling, M.; Röder, H. Balancing the green carbon cycle - biogenic carbon within life cycle assessment. Int. J.
Life. Cycle. Assess. 2025, 30, 2300-13. DOI
17. Lueddeckens, S.; Saling, P.; Guenther, E. Temporal issues in life cycle assessment - a systematic review. Int. J. Life. Cycle. Assess. 2020,
25, 1385-401. DOI
18. Collins, F. Inclusion of carbonation during the life cycle of built and recycled concrete: influence on their carbon footprint. Int. J. Life.
Cycle. Assess. 2010, 15, 549-56. DOI
19. Abernethy, S.; Jackson, R. B. Global temperature goals should determine the time horizons for greenhouse gas emission metrics.
Environ. Res. Lett. 2022, 17, 024019. DOI
20. Tiruta-barna, L. A climate goal-based, multicriteria method for system evaluation in life cycle assessment. Int. J. Life. Cycle. Assess.
2021, 26, 1913-31. DOI
21. Zieger, V.; Lecompte, T.; Guihéneuf, S.; et al. Climate change metrics: bridging IPCC AR6 updates and dynamic life cycle assessments.
Earth. Syst. Dynam. 2025, 16, 2003-19. DOI
22. Francois, C.; Batot, G.; Ventura, A. Université Gustave Eiffel. Dynamic global warming potential (GWP) and Global Temperature
Potential (GTP) indicators calculation workbook. https://doi.org/10.57745/LVMVIU (accessed 2026-04-15).
23. Levasseur, A.; de Schryver, A.; Hauschild, M.; et al. Greenhouse gas emissions and climate change impacts. In Global Guidance for Life
Cycle Impact Assessment Indicators, Vol. 1; United Nations Environment Programme, 2016; p. 60-79. https://www.researchgate.net/publ
ication/319402340_Greenhouse_gas_emissions_and_climate_change_impacts (accessed 2026-04-15).
24. Intergovernmental Panel on Climate Change (IPCC). The earth’s energy budget, climate feedbacks and climate sensitivity. In Climate
Change 2021 - The Physical Science Basis; Cambridge University Press, 2023; pp 923-1054. DOI
25. Joos, F.; Roth, R.; Fuglestvedt, J. S.; et al. Carbon dioxide and climate impulse response functions for the computation of greenhouse gas
metrics: a multi-model analysis. Atmos. Chem. Phys. 2013, 13, 2793-825. DOI
26. Hodnebrog, Ø.; Aamaas, B.; Fuglestvedt, J. S.; et al. Updated global warming potentials and radiative efficiencies of halocarbons and
other weak atmospheric absorbers. Rev. Geophys. 2020, 58, e2019RG000691. DOI PubMed PMC
