Evidence map›Paper›PMID 42017192›Full record

ArticleJournal of industrial ecology2025

A framework for guiding safe and sustainable-by-design innovation.

Carlos Felipe Blanco, Paul Behrens, Martina Vijver, Willie Peijnenburg, Joris Quik, Stefano Cucurachi

Abstract read
In one paragraph

Article in Journal of industrial ecology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Carlos Felipe BlancoInstitute of Environmental Sciences (CML), Leiden University, P.O. Box 9518, Leiden, 2300 RA The Netherlands.ORCID https://orcid.org/0000-0001-8199-8420
Paul BehrensInstitute of Environmental Sciences (CML), Leiden University, P.O. Box 9518, Leiden, 2300 RA The Netherlands.
Martina VijverInstitute of Environmental Sciences (CML), Leiden University, P.O. Box 9518, Leiden, 2300 RA The Netherlands.
Willie PeijnenburgInstitute of Environmental Sciences (CML), Leiden University, P.O. Box 9518, Leiden, 2300 RA The Netherlands.
Joris QuikCentre for Sustainability, Health and Environment, National Institute of Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
Stefano CucurachiInstitute of Environmental Sciences (CML), Leiden University, P.O. Box 9518, Leiden, 2300 RA The Netherlands.ORCID https://orcid.org/0000-0001-9763-2669

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessing the safety and sustainability of novel technologies while they are still in the early research and development stages is the most effective way to avoid undesired outcomes. However, the journey from idea to market is highly uncertain and involves intensive trial and error as technology developers attempt to optimize material choices and product configurations. Designs evolve quickly, and assessing their risks and impacts while numerous factors remain undetermined is challenging. The standard practice is to evaluate a limited subset of scenarios that can guide design choices. However, selecting scenarios from hundreds of undetermined factors without a systematic sensitivity screening may leave out important improvement opportunities. To provide well-informed guidance, the evaluated scenarios should be selected based on factors that are most influential to the safety and sustainability impacts of the technology. We propose an approach that accomplishes this by incorporating a wide spectrum of undetermined factors, both intrinsic and extrinsic to the technology design. The assessment models are then screened for highly-sensitive factors using global sensitivity analysis. Strategies to reduce uncertainty on highly influential factors are proposed for subsequent iterations, and the residual factors for which uncertainty cannot be further reduced yet remain influential are selected as a basis for proposed "sensitive scenarios" and improvement roadmaps. We demonstrate the framework with an emerging photovoltaics case study. Over a hundred uncertain factors are reduced to less than five which, if optimized, would substantially improve the future safety and sustainability performance of the technology as well as reduce the uncertainty around it. Supplementary Information: The online version of this article (doi:10.1111/jiec.13609) contains supplementary material, which is available to authorized users.

Indexed as

emerging technologiesinnovationprospective life cycle assessmentrisk assessmentSSbDuncertainty

Identifiers

PMID42017192
PMCPMC13092547

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.