The International Journal of Life Cycle Assessment

, Volume 17, Issue 8, pp 1028–1041 | Cite as

Life cycle assessment (LCA) applied to the process industry: a review

  • Leslie Jacquemin
  • Pierre-Yves Pontalier
  • Caroline Sablayrolles



Life cycle assessment (LCA) methodology is a well-established analytical method to quantify environmental impacts, which has been mainly applied to products. However, recent literature would suggest that it has also the potential as an analysis and design tool for processes, and stresses that one of the biggest challenges of this decade in the field of process systems engineering (PSE) is the development of tools for environmental considerations.


This article attempts to give an overview of the integration of LCA methodology in the context of industrial ecology, and focuses on the use of this methodology for environmental considerations concerning process design and optimization.


The review identifies that LCA is often used as a multi-objective optimization of processes: practitioners use LCA to obtain the inventory and inject the results into the optimization model. It also shows that most of the LCA studies undertaken on process analysis consider the unit processes as black boxes and build the inventory analysis on fixed operating conditions.


The article highlights the interest to better assimilate PSE tools with LCA methodology, in order to produce a more detailed analysis. This will allow optimizing the influence of process operating conditions on environmental impacts and including detailed environmental results into process industry.


Life cycle assessment Process systems engineering Environmental design and optimization Eco-friendly processes Industrial ecology 


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Leslie Jacquemin
    • 1
    • 2
  • Pierre-Yves Pontalier
    • 1
    • 2
  • Caroline Sablayrolles
    • 1
    • 2
  1. 1.Laboratoire de Chimie Agro-industrielleUniversité de Toulouse, INP-ENSIACET, LCAToulouseFrance
  2. 2.INRA, UMR 1010 CAIToulouseFrance

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