Sustainable Process Design under uncertainty analysis: targeting environmental indicators

Carina L. Gargalo, Rafiqul Gani

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This study focuses on uncertainty analysis of environmental indicators used to support sustainable process design efforts. To this end, the Life Cycle Assessment methodology is extended with a comprehensive uncertainty analysis to propagate the uncertainties in input LCA data to the environmental indicators. The resulting uncertainties in the environmental indicators are then represented by empirical cumulative distribution function, which provides a probabilistic basis for the interpretation of the indicators. In order to highlight the main features of the extended LCA, the production of biodiesel from algae biomass is used as a case study. The results indicate there are considerable uncertainties in the calculated environmental indicators as revealed by CDFs. The underlying sources of these uncertainties are indeed the significant variation in the databases used for the LCA analysis. The extended LCA procedure is flexible and generic and can handle various sources of uncertainties in environmental impact analysis. This is expected to contribute to more reliable calculation of impact categories and robust sustainable process design.
Original languageEnglish
Title of host publicationProceedings of the 25th European Symposium on Computer Aided Process Engineering
EditorsKrist V. Gernaey, Jakob K. Huusom, Rafiqul Gani
Volume37
PublisherElsevier
Publication date2015
Pages2579-2584
DOIs
Publication statusPublished - 2015
Event25th European Symposium on Computer Aided Process Engineering : 12th International Symposium on Process Systems Engineering - Copenhagen, Denmark
Duration: 31 May 20154 Jun 2015
http://www.pse2015escape25.dk/

Conference

Conference25th European Symposium on Computer Aided Process Engineering
CountryDenmark
CityCopenhagen
Period31/05/201504/06/2015
Internet address
SeriesComputer Aided Chemical Engineering
ISSN1570-7946

Keywords

  • Systematic methodology
  • Separation processes
  • Ionic liquid
  • Extractive distillation

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