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Uncertainty in Prospective Sustainability Assessment

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (15 December 2020) | Viewed by 6888

Special Issue Editor

Department of Planning, Aalborg University, Rendsburggade 14, 9000 Aalborg, Denmark
Interests: Industrial Ecology and Sustainability Science; Decision support tools for quantitative sustainability assessment: Life Cycle assessment (LCA), Network Analysis, Valuation of externalities, Environmentally-Extended Input-Output Analysis; Quantitative, quantitative, and mixed research methods and interdisciplinary inquiries for sustainability assessment; Green technologies and green innovation, scenario analysis and futures thinking; Programming for big data analysis and statistics

Special Issue Information

Dear Colleagues,

In facing current climate and ecological crises, technological as well as behavioral change are urgently needed, and so is the assessment of new sustainable technologies and consumption patterns. However, the future is unpredictable, constantly changing, and intrinsically uncertain. We therefore need appropriate tools and approaches to address such uncertainty in prospective studies of sustainability assessment. This Special Issue will comprise a selection of papers offering insights, approaches, and tools for the particular challenges related to dealing with uncertainty in prospective sustainability assessment. We expect papers from several disciplines as well as interdisciplinary contributions.

The issue welcomes contributions on the use of both quantitative and qualitative approaches to tackle, reduce, and make explicit the uncertainty of prospective sustainability assessment studies. Topics covered might vary from, for example, stochastic- or system dynamics-based approaches in the modeling and anticipation of future technological systems and the adoption of emerging technologies at scale, to participatory scenario analysis and the use of expert and stakeholder-based surveys to identify industrial learning mechanisms and anticipate systemic changes. Studies focusing on existing challenges in prospective life cycle assessment (LCA) are especially welcome.

Papers selected for this Special Issue are subject to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications.

Assoc. Prof. Massimo Pizzol
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Technology assessment and forecasting
  • Prospective life cycle assessment
  • Green innovation and green technology upscaling
  • Scenarios and participatory scenario development
  • Decision support on emerging technologies
  • Uncertainty and sensitivity analysis in sustainability assessment models
  • System dynamics and agent-based modelling for sustainability
  • Stakeholders involvement and expert surveying

Published Papers (1 paper)

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24 pages, 1064 KiB  
The Future of Ex-Ante LCA? Lessons Learned and Practical Recommendations
Sustainability 2019, 11(19), 5456; - 01 Oct 2019
Cited by 69 | Viewed by 6382
Every decision-oriented life cycle assessment (LCAs) entails, at least to some extent, a future-oriented feature. However, apart from the ex-ante LCAs, the majority of LCA studies are retrospective in nature and do not explicitly account for possible future effects. In this review a [...] Read more.
Every decision-oriented life cycle assessment (LCAs) entails, at least to some extent, a future-oriented feature. However, apart from the ex-ante LCAs, the majority of LCA studies are retrospective in nature and do not explicitly account for possible future effects. In this review a generic theoretical framework is proposed as a guideline for ex-ante LCA. This framework includes the entire technology life cycle, from the early design phase up to continuous improvements of mature technologies, including their market penetration. The compatibility with commonly applied system models yields an additional aspect of the framework. Practical methods and procedures are categorised, based on how they incorporate future-oriented features in LCA. The results indicate that most of the ex-ante LCAs focus on emerging technologies that have already gone through some research cycles within narrowly defined system boundaries. There is a lack of attention given to technologies that are at a very early development stage, when all options are still open and can be explored at a low cost. It is also acknowledged that technological learning impacts the financial and environmental performance of mature production systems. Once technologies are entering the market, shifts in market composition can lead to substantial changes in environmental performance. Full article
(This article belongs to the Special Issue Uncertainty in Prospective Sustainability Assessment)
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