Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 490

The DOI matches its Crossref record.

Options for Achieving a 50% Cut in Industrial Carbon Emissions by 2050

Allwood, Julian M., Cullen, Jonathan M., Milford, Rachel L.·2010·Environmental Science & Technology

Abstract

Carbon emissions from industry are dominated by production of goods in steel, cement plastic, paper, and aluminum. Demand for these materials is anticipated to double at least by 2050, by which time global carbon emissions must be reduced by at least 50%. To evaluate the challenge of meeting this target the global flows of these materials and their associated emissions are projected to 2050 under five technical scenarios. A reference scenario includes all existing and emerging efficiency measures but cannot provide sufficient reduction. The application of carbon sequestration to primary production proves to be sufficient only for cement The emissions target can always be met by reducing demand, for instance through product life extension, material substitution, or "light-weighting". Reusing components shows significant potential particularly within construction. Radical process innovation may also be possible. The results show that the first two strategies, based on increasing primary production, cannot achieve the required emissions reductions, so should be balanced by the vigorous pursuit of material efficiency to allow provision of increased material services with reduced primary production.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/es902909k

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 490

Metadata

Authors
Allwood, J. M., Cullen, J. M., & Milford, R. L.
Venue
Environmental Science & Technology
Published
2010-02-02
Volume
44
Issue
6
Pages
1888-1894
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2033198823
Cited by
490
References
0
FWCI
42.59
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Options for Achieving a 50% Cut in Industrial Carbon Emissions by 2050. https://app.cochat.ai/papers/10.1021/es902909k
The paper
Allwood, J. M., Cullen, J. M., & Milford, R. L. (2010). Options for Achieving a 50% Cut in Industrial Carbon Emissions by 2050. Environmental Science & Technology. https://doi.org/10.1021/es902909k

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.