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ProLCA – treatment of uncertainty in infrastructure LCA

Larsson Ivanov, Oskar LU ; Honfi, Daniel; Santandrea, Fabio and Stripple, Håkan (2018) Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018) p.1735-1742
Abstract
The construction, operation and maintenance of transportation infrastructure require energy and materials which impact the environment. Large infrastructure projects thus use resources intensively and leave a significant environmental footprint. To demonstrate and support the sustainability of such large-scale projects, life cycle assessment (LCA) has become a common tool to evaluate environmental impacts in all stages of infrastructure life cycle, from raw material production through end-of-life management. However, the various phases of the assessment are all associated with uncertainties. If decisions are made without consideration of these uncertainties, they might be misleading and suboptimal. In this paper, results are presented... (More)
The construction, operation and maintenance of transportation infrastructure require energy and materials which impact the environment. Large infrastructure projects thus use resources intensively and leave a significant environmental footprint. To demonstrate and support the sustainability of such large-scale projects, life cycle assessment (LCA) has become a common tool to evaluate environmental impacts in all stages of infrastructure life cycle, from raw material production through end-of-life management. However, the various phases of the assessment are all associated with uncertainties. If decisions are made without consideration of these uncertainties, they might be misleading and suboptimal. In this paper, results are presented where variations associated with different parameters and tools for life cycle assessment have been considered using probabilistic methods. A categorization of common uncertainties in LCA is also included. The most influential parameters can be identified with sensitivity analysis methods, since for LCA with a large number of parameters it may be unreasonable to incorporate all in a probabilistic simulation. For a limited amount of influential variables, Monte Carlo simulation has been used to assess the effects of uncertainties on the results. A bridge has been used as a case study to find important aspects in infrastructure LCA. The results indicate that if the most influential parameters are considered as random variables, it is possible to estimate the uncertainty and increase the validity of the life cycle assessment. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Life Cycle Analysis and Assessment in Civil Engineering
editor
Caspeele, Robby; Taerwe, Luc; Frangopol, Dan M.; ; and
pages
1735 - 1742
publisher
CRC Press
conference name
Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018)
conference location
Ghent, Belgium
conference dates
2018-10-28 - 2018-10-31
ISBN
9781138626331
9781351857574
language
English
LU publication?
yes
id
e377ed01-d969-4c84-8b2a-ed3b4f02e6d0
date added to LUP
2019-04-16 09:21:54
date last changed
2019-04-17 13:53:38
@inproceedings{e377ed01-d969-4c84-8b2a-ed3b4f02e6d0,
  abstract     = {The construction, operation and maintenance of transportation infrastructure require energy and materials which impact the environment. Large infrastructure projects thus use resources intensively and leave a significant environmental footprint. To demonstrate and support the sustainability of such large-scale projects, life cycle assessment (LCA) has become a common tool to evaluate environmental impacts in all stages of infrastructure life cycle, from raw material production through end-of-life management. However, the various phases of the assessment are all associated with uncertainties. If decisions are made without consideration of these uncertainties, they might be misleading and suboptimal. In this paper, results are presented where variations associated with different parameters and tools for life cycle assessment have been considered using probabilistic methods. A categorization of common uncertainties in LCA is also included. The most influential parameters can be identified with sensitivity analysis methods, since for LCA with a large number of parameters it may be unreasonable to incorporate all in a probabilistic simulation. For a limited amount of influential variables, Monte Carlo simulation has been used to assess the effects of uncertainties on the results. A bridge has been used as a case study to find important aspects in infrastructure LCA. The results indicate that if the most influential parameters are considered as random variables, it is possible to estimate the uncertainty and increase the validity of the life cycle assessment. },
  author       = {Larsson Ivanov, Oskar and Honfi, Daniel and Santandrea, Fabio and Stripple, Håkan},
  editor       = {Caspeele, Robby and Taerwe, Luc and Frangopol, Dan M.},
  isbn         = {9781138626331},
  language     = {eng},
  location     = {Ghent, Belgium},
  pages        = {1735--1742},
  publisher    = {CRC Press},
  title        = {ProLCA – treatment of uncertainty in infrastructure LCA},
  year         = {2018},
}