Spé éval Bilan Environnemt R14

**Informations générales**:
**Référence **:2024-1608

**Attributs du poste**:
**Intitulé du poste**:
Spé éval bilan environnemt R14 H/F

**Statut**:
Post-Doc

**Contrat**:
CDD Terme Précis

**Si CDD (durée exprimée en mois)**:
18

**Temps de travail**:
Temps plein

**Localisation du poste**:
**Lieu d'exercice**:
RUEIL-MALAISON

**Description du poste**:
**Contexte**:
In order to achieve carbon neutrality by 2050, comply with the Paris agreements and secure its energy supplies, France needs to reduce the part of fossil fuels in its energy mix (RTE 2022a; Ministère de la transition énergétique 2023). To achieve this, the country needs to massively develop its renewable energy (REN) production capacity (RTE 2022a), particularly onshore and offshore wind power (RTE 2022b). Planning the siting of wind turbines is in the hands of French territories (Ministère de la transition énergétique 2023). It is therefore important that the latter have at their disposal tools that enable them to assess the impacts of wind turbine siting ex ante, so that they can make decisions without regrets, i.e. a wind turbine siting that has the fewest possible impacts per unit of energy produced and gives rise to the fewest transfers of impacts. One tool for this type of assessment is Life Cycle Assessment (LCA). This is a standardised method for assessing the environmental impact of a product or service over its entire life cycle, i.e. from the extraction of raw materials to the end of its life (ISO 14040; ISO 14044).
Numerous LCA studies assess the environmental impact of onshore and offshore wind turbines (Kylili 2022). These studies have shown that their environmental impacts depend on technological, geographical and temporal parameters, associated with Life Cycle Inventories (LCI) (Sacchi et al. 2019; Kouloumpis et Azapagic 2022; Besseau et al. 2019; Chen et al.

**Mission(s) principale(s) et activités**:
The aim of this postdoctoral research project is to provide a decision aid methodology for any French territories, for the choice of the implementation of offshore and onshore wind turbines based on environmental considerations. As such, this postdoctoral research project will answer the following research question as a priority: How to perform regionalised LCA, i.e. encompassing the location where an inventory dataset occurs (Mutel et Hellweg 2023), of the French wind fleet? To answer this question, the postdoctoral researcher will develop a methodology for carrying out LCAs with regionalised parameterised LCIs and a regionalised assessment of environmental impacts, which can be applied to the French wind fleet. The entire French wind fleet will be studied to have a methodology applicable for every wind farm of every French territory. Depending on the progress of the work, another question will be addressed: How to choose the best locations and types of wind turbines for the implementation of a wind farm over a French territory? To answer this question, a methodology for optimising the environmental impacts of wind farms in terms of the value chain of wind turbines and local design of the wind farms will be developed.

**Déplacements à prévoir**:
ponctuels et de courtes durées

**Compétences techniques et aptitudes**:
Skills required:

- Mastery of LCA methodology.
- Good programming skills preferably in MATLAB, Python or R.

Skills appreciated:

- Python programming skills.
- Knowledge of the Brightway2 package.
- Knowledge of GIS tools (e.g. QGIS, ArcGIS, etc.).

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.

**Langues**:
Anglais (Courant)

**Diplôme(s), niveau d'études**:
PhD in LCA, obtained less than 3 years ago.

**Expérience(s) professionnelle(s) souhaitée(s)**:
Débutant accepté