Evidence map›Paper›PMID 34334025›Full record

ReviewPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2021

A critical review of life cycle assessment studies of woody biomass conversion to sugars.

Niamh Ryan, Polina Yaseneva

Abstract readReview
In one paragraph

Review in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Niamh RyanDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK.
Polina YasenevaCambridge Institute for Sustainability Leadership, University of Cambridge, 1 Trumpington Street, Cambridge CB2 1QA, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Woody biomass could potentially become a viable raw material for the future sustainable chemical industry. For this, a suitable regulatory framework must exist, that would create favourable economic conditions for wood biorefineries. Such policies must be developed on the basis of scientific evidence-in this case, data supporting the environmental advantages of the bio-based feedstocks to the chemical industry. The most suitable methodology for comprehensive evaluation of environmental performance of technologies is life cycle assessment (LCA). In this review, the available LCA studies of woody biomass fractionation and conversion to bulk chemical feedstocks are critically evaluated. It has been revealed that the majority of the openly available studies do not contain transparent inventory data and, therefore, cannot be verified or re-used; studies containing inventory data are reported in this review. The lack of inventory data also prevents comparison between studies of the same processes performed with different evaluation methods or using different system boundaries. Recommendations are proposed on how to overcome issues of commercial data sensitivity by using black-box modelling when reporting environmental information. From several comparable LCA studies, it has been concluded that today the most environmentally favourable technology for wood biomass fractionation is organosolv. This article is part of the theme issue 'Bio-derived and bioinspired sustainable advanced materials for emerging technologies (part 1)'.

Indexed as

SugarsWoodAnimalsBiomassEnvironmentLife Cycle StagesSugarsbiotechnologylife cycle assessmentwoody biomass

Identifiers

PMID34334025
PMCPMC8326825

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.