To comply with the Paris Agreement and achieve carbon neutrality by 2050, France aims to reduce its industrial sector's greenhouse gas emissions by 81% from 2015 levels by 2050.

Various decarbonization strategies are available, including the adoption of new technologies like alternative fuels (e.g., hydrogen, ammonia) and CO2 capture, as well as optimizing current processes through electrification and industrial symbiosis. The LCA-SPLEEN project supports the development of these new industrial pathways by providing metrics to measure environmental performance and detect potential pollution transfers.

As part of the LCA-SPLEEN project, this postdoctoral research project aims to enhance the environmental assessment of territorial trajectories for decarbonising industry by focusing on the interpretation step of territorial LCA.  Presenting all the impact results for each midpoint category is not effective for using LCA in a decision-making process. As such, this postdoctoral research project will answer the following research question: How to objectively reduce the number of indicators to consider during decision-making ?

The tasks of the post-doc are as follows (they may evolve depending on the candidate’s affinities):

• Propose a transparent and objective framework to reduce the number of impact categories to be considered for decision-making:
  • Propose a method for incorporating uncertainties in characterization factors when assessing impacts. For each impact category, explain the approach to adopt to determine whether a difference in results between two solutions is significant
  • Define a method to contextualize the absolute result in each impact category and identify whether the severity of the impact is negligible or not. For example, this could be done by contextualizing the indicators within their cause-and-effect chain (midpoint to areas of protection) or within the framework of planetary boundaries
  • Apply the methods described in the previous two points to at least one case study as a proof of concept
• Help with communicating results:
  • Identify the key information to be provided to stakeholders in order to meet the objective of the territorial LCA and help them make informed decisions
  • Find the best way to present this information (e.g. type of graph, construction of a new aggregate indicator, etc.)

This work will be promoted by participation in conferences within and outside the PEPR SPLEEN and by the writing of at least one scientific article. The development of training material for the methods developed would also be a plus, to enable the method to be disseminated.

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Hard skills:

• Good skills in statistics and data management (uncertainty calculation)
• Good programming skills preferably in Python
• Knowledge of LCA

Soft Skills:

• Rigour and precision
• Analytical mind and ability to solve complex problems
• Good communication and presentation skills
• Ability to work in a team and independently
• Good mastery of English
• Ability to publish in peer-reviewed journals with high impact factors
  
  

PhD obtained less than 3 years ago

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