ALIGNED D1.2 Description of scientific methods (T1.3 Framework for Life Cycle Impact Assessment)
Creators: name: Hamelin, Lorie
name: Javourez, Ugo
name: Arbault, Damien
Publisher: name: Zenodo
Year: 2024
Subjects: life cycle assessment
biobased
industrial ecology
life cycle impact assessment
climate change
biodiversity
characterization factor

description: Methods for Life Cycle Impact Assessment

This repository contains:

·       Guide on the Life Cycle Impact Assessment (LCIA) for bio-based products – Climate change

This document presents a synthesis of the latest research and existing climate change assessment frameworks tailored to LCA, and the corresponding ALIGNED guidance. The guidance covers the strategies to adopt to include dynamic carbon flows accounting in the LCIA phase and discusses the need to distinguish biogenic from fossil carbon when assessing climate change in LCAs. Period-specific characterization factors (CF) for Global Warming Potential (GWP) and Global Temperature Potential (GTP) for different time horizons are defined, compared and their implications discussed. As for each component of ALIGNED’s methodological framework, a guidance formulated as a tiered approach is proposed.

·       Guide on the Life Cycle Impact Assessment (LCIA) for bio-based products – Biodiversity

This document presents a synthesis of the latest research and existing biodiversity impacts assessment frameworks tailored to LCA, and the corresponding ALIGNED guidance. The latest characterization factors related to impacts on biodiversity of the main greenhouse gas (GHG) emissions are made available for import in real case LCAs. As for each component of ALIGNED’s methodological framework, a guidance formulated as a tiered approach is proposed.

·       Tool for deriving dynamic characterization factors for climate chance

This Excel spreadsheet contains an estimation of year-specific characterization factors (CF) for GWP100 (both Levasseur and Ventura methods), GWP500, GTP50 and GTP100, along with the calculation of characterized score for time-distributed CO2, CH4 and N2O inventories. Instructions on how to use the score in real case LCA studies are also provided in the following tutorials.

·       Tutorial on including time-dependencies in the estimation of climate change midpoint scores of bio-based productions – Tier 1  

This document is the stepwise procedure corresponding to the Tier 1 of ALIGNED guidance to include time-dependencies in the calculation of climate change impact scores. It is directed towards LCA practitioners with no previous experience in including temporal considerations in LCAs.

·       Tutorial on including time-dependencies in the estimation of climate change midpoint scores of bio-based productions – Tier 2 and 3

This document is the stepwise procedure corresponding to the Tier 2 of ALIGNED guidance to include time-dependencies in the calculation of climate change impact scores. As Tier 3 is an extension of Tier 2, instructions for Tier 3 are provided in the same document.

·       Dataset with the Biodiversity characterization factors

This Excel spreadsheet contains the characterization factors of biodiversity impacts from GHG emissions in different six future scenarios and time horizon, provided by Iordan et al., (2023). It contains both the raw data from the reference and their ready-to-use formatted versions for bw2 import as a LCIA method. The data corresponding to the six combinations of (future scenarios, time horizon) are also available in six separate excel spreadsheets entitled: “gPAF_2050_RCP26”, “gPAF_2100_RCP26”, “gPAF_2050_RCP45”, “gPAF_2100_RCP45”, “gPAF_2050_RCP85”, “gPAF_2100_RCP85” to facilitate their reuse in the import tutorial (below).

·       Tutorial to import biodiversity characterization factors (.ipynb and html files)

This python notebook tutorial contains instructions and code to import the biodiversity characterization factors (CF) from Iordan et al., (2023) as an LCIA method in a Brightway2 project to quantify global biodiversity impacts from 20 GHGs. The .html version allows to visualize the notebook for biodiversity characterization factors import without python.