Life cycle assessment of water-based acrylic floor finish maintenance programs

Thabrew, Lanka; Lloyd, Shannon M.; Cypcar, Christopher C.; Hamilton, John D.; Ries, Robert

doi:10.1007/s11367-007-0323-7

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…Data generation and analysis is where transdisciplinary learning and working are encouraged to the greatest extent possible (Scholz and Tietje 2002; Wiek, Binder, et al 2006). For example, if a company plans to make their products environmentally friendly, the research‐and‐development group may require intensive analysis of the product's manufacturing, use, and end‐of‐life effects (Thabrew et al 2008). Their focus may be initially limited to the processes and relevant data specifically related to manufacturing.…”

Section: Introductionmentioning

confidence: 99%

Application of life cycle thinking in multidisciplinary multistakeholder contexts for cross‐sectoral planning and implementation of sustainable development projects

Thabrew

Ries

2009

Integr Envir Assess & Manag

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Development planning and implementation is a multifaceted and multiscale task mainly because of the involvement of multiple stakeholders across sectors and disciplines. Even though top-down sectoral planning is commonly practiced, bottom-up cross-sectoral planning involving all relevant stakeholders in a transdisciplinary learning environment has been recognized as a better option, especially if the goal is to drive development projects toward sustainable implementation (Rowe and Fudge 2003; Müller et al. 2005; Global Development Research Center 2008). Even though many planning approaches have this goal, there are limited decision frameworks that are suitable for achieving consensus among stakeholders from multiple disciplines with sectoral objectives and priorities. In most instances, the upstream and downstream effects of development decisions are not thoroughly investigated or communicated with the relevant stakeholders, strongly affecting cross-sectoral integration in the real world (Wiek, Brundiers, et al. 2006). This article presents methodological aspects of developing a stakeholder based life cycle assessment framework (SBLCA) for upstream-downstream decision analysis in a multistakeholder development planning context. The applicability of the framework is demonstrated using simple examples extracted from a pilot case study conducted in Sri Lanka for sustainable posttsunami reconstruction at a village scale. The applicability of SBLCA in specific planning stages, how it promotes transdisciplinary learning and cross-sectoral stakeholder integration in phases of project cycles, and how local stakeholders can practice life cycle thinking in their village development planning and implementation are discussed.

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Section: Introductionmentioning

confidence: 99%

Application of life cycle thinking in multidisciplinary multistakeholder contexts for cross‐sectoral planning and implementation of sustainable development projects

Thabrew

Ries

2009

Integr Envir Assess & Manag

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Stochastic and epistemic uncertainty propagation in LCA

Clavreul

Guyonnet²,

Tonini

et al. 2013

Int J Life Cycle Assess

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Purpose: When performing uncertainty propagation, most LCA practitioners choose to represent uncertainties by single probability distributions and to propagate them using stochastic methods. However the selection of single probability distributions appears often arbitrary when faced with scarce information or expert judgement (epistemic uncertainty). Possibility theory has been developed over the last decades to address this problem. The objective of this study is to present a methodology that combines probability and possibility theories to represent stochastic and epistemic uncertainties in a consistent manner and apply it to LCA. A case study is used to show the uncertainty propagation performed with the proposed method and compare it to propagation performed using probability and possibility theories alone.Methods: Basic knowledge on the probability theory is first recalled, followed by a detailed description of epistemic uncertainty representation using fuzzy intervals. The propagation methods used are the Monte Carlo analysis for probability distribution and an optimisation on alpha-cuts for fuzzy intervals. The proposed method (noted IRS) generalizes the process of random sampling to probability distributions as well as fuzzy intervals, thus making the simultaneous use of both representations possible.Results and discussion: The results highlight the fundamental difference between the probabilistic and possibilistic representations: while the Monte Carlo analysis generates a single probability distribution, the IRS method yields a family of probability distributions bounded by an upper and a lower distribution.The distance between these two bounds is the consequence of the incomplete character of information pertaining to certain parameters. In a real situation, an excessive distance between these two bounds might motivate the decision-maker to increase the information base regarding certain critical parameters, in order to reduce the uncertainty. Such a decision could not ensue from a purely probabilistic calculation based on subjective (postulated) distributions (despite lack of information), because there is no way of distinguishing, in the variability of the calculated result, what comes from true randomness and what comes from incomplete information.Conclusions: The method presented offers the advantage of putting the focus on the information rather than deciding a priori of how to represent it. If the information is rich, then a purely statistical representation mode is adequate, but if the information is scarce, then it may be better conveyed by possibility distributions.3

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Using Eco-Indicator 99 to Evaluate Building Technologies under Life Cycle Assessment Uncertainties

Pushkar

2014

J. Archit. Eng.

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Life cycle assessment of water-based acrylic floor finish maintenance programs

Cited by 6 publications

References 10 publications

Application of life cycle thinking in multidisciplinary multistakeholder contexts for cross‐sectoral planning and implementation of sustainable development projects

Application of life cycle thinking in multidisciplinary multistakeholder contexts for cross‐sectoral planning and implementation of sustainable development projects

Stochastic and epistemic uncertainty propagation in LCA

Using Eco-Indicator 99 to Evaluate Building Technologies under Life Cycle Assessment Uncertainties

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