Waqas, M.A.; Hashemi, Fatemeh; Mogensen, Lisbeth; Brandão, M.; de Rosa, M. and Knudsen, Marie Trydeman (2024) Evaluating methods to estimate carbon sequestered in biomass and its climate change effects. Poster at: 14th International Conference on Life Cycle Assessment of Food 2024 (LCA Food 2024) “Healthy food systems for a healthy planet”, Barcelona, Spain, 8-11 September 2024.
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Summary in the original language of the document
By 2040, the global average temperature is expected to surpass the critical threshold of 1.5 degrees Celsius above the pre-industrial level. (Stein, 2022). The need for swift, consistent, and substantial carbon dioxide (CO2) removal from the atmosphere is crucial in order to avert the consequences of climate change. The potential for carbon (C) storage in tree-based systems is promising. However, there is no agreement on how to account for tree biomass C storage in LCA to assess the climate change effects. This study examines various methods for quantifying biomass C storage by trees and explores the climate change effects through a case study on agroforestry in Denmark.
This research work evaluated and compared four distinct strategies to measure biomass C sequestration: C-budget models, allometric models, parametric models, and process-based growth models. In addition, it summarized and compared several impact assessment methods, including Moura-Costa, Clift & Brandao, Lashof, ILCD, Clift and Brandao, C-seq, dynamic LCA, Müller‐Wenk and Brandão, the PAS 2050, and GWPbio.
LCA practitioners commonly apply four different methods to estimate biomass C sequestration: process-based growth models, general and specific allometric models, C-budget models, and parametric models. Different approaches to estimating biomass C storage can vary significantly and result in more variations over longer time periods. General models may not very well represent the specific plant species or site climate and soil characteristics. More sophisticated models that consider all such factors typically estimate lower levels of biomass C accumulation. Incorporating tree biomass into a LCA by estimating its climate change effect is challenging and the different approaches yielded varying results due to differences in accounting for time dynamics, reference states etc. Thus, the methods used to account for temporary C sequestration in LCA can influence the outcomes and are sensitive to time perspectives (Brandão et al., 2019).
This paper examines nine methods to evaluate the influence of C sequestration in tree biomass on climate change. Our research suggests that the results of these methods can change depending on the assessment time length and approach selected. It is essential to examine various aspects of impact assessment techniques when interpreting findings. A comprehensive approach is necessary to accurately estimate C storage and its climate effect. This approach should consider the temporal factors, the complexity of the system, the reference state, and the uncertainties associated with the methods. Enhancing the LCA tool with updated methodologies to estimate and characterize biogenic C sequestration can improve accuracy in the future.
EPrint Type: | Conference paper, poster, etc. |
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Type of presentation: | Poster |
Agrovoc keywords: | Language Value URI English life cycle analysis http://aims.fao.org/aos/agrovoc/c_9000105 English carbon sequestration http://aims.fao.org/aos/agrovoc/c_331583 English woody plants http://aims.fao.org/aos/agrovoc/c_26837 English agroforestry http://aims.fao.org/aos/agrovoc/c_207 |
Subjects: | Crop husbandry > Production systems Environmental aspects > Air and water emissions Environmental aspects |
Research affiliation: | European Union > Horizon 2020 > MIXED Denmark > AU - Aarhus University > Faculty of Science and Technology > Department of Agroecology Denmark > Organic RDD 6 > OUTFIT Denmark > Organic RDD 9 > SustainFood |
Horizon Europe or H2020 Grant Agreement Number: | 862357 |
Deposited By: | Knudsen, Researcher Marie Trydeman |
ID Code: | 55399 |
Deposited On: | 01 Apr 2025 10:04 |
Last Modified: | 01 Apr 2025 10:04 |
Document Language: | English |
Status: | Published |
Refereed: | Peer-reviewed and accepted |
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