PULPO: A framework for efficient integration of life cycle inventory models into life cycle product optimization
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Date
2024-12
Publication Type
Journal Article
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yes
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Abstract
This work presents the PULPO (Python-based user-defined lifecycle product optimization) framework, developed to efficiently integrate life cycle inventory (LCI) models into life cycle product optimization. Life cycle optimization (LCO), which has found interest in both the process systems engineering and life cycle assessment (LCA)communities, leverages LCA data to go beyond simple assessments of a limited number of alternatives and identify the best possible product systems configuration subject to a manifold of choices, constraints, and objectives. However, typically, aggregated inventories are used to build the optimization problems. Contrary to existing frame-works, PULPO integrates whole LCI databases and user inventories as a backbone for the optimization problem, considering economy-wide feedback loops between fore-and background systems that would otherwise be omitted. The open-source implementation combines functions from Brightway2 for the manipulation of inventory data and pyomo for the formulation and solution of the optimization problem. The advantages of this approach are demonstrated in a case study focusing on the design of optimal future global green methanol production systems from captured CO2 and electrolytic H2. It is shown that the approach can be used to assess sector-coupling with multi-functional processes and prospective background databases that would otherwise be impractical to approach from a standalone LCA perspective. The use of PULPO is particularly appealing when evaluating large-scale decisions that have a strong impact on socioeconomic systems, resulting in changes in the technosphere on which the background system is based and which is often assumed constant in standard LCO approaches regardless of the decisions taken.
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Publication status
published
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Journal / series
Volume
28 (6)
Pages / Article No.
1449 - 1463
Publisher
Wiley
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Edition / version
Methods
Software
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Date collected
Date created
Subject
Ecoinvent; Industrial ecology; Life cycle optimization; Methanol; Multi-scale; Technosphere-wide
Organisational unit
09655 - Guillén Gosálbez, Gonzalo / Guillén Gosálbez, Gonzalo
Notes
Funding
180544 - NCCR Catalysis (phase I) (SNF)