Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 432

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Breaking the hard-to-abate bottleneck in China’s path to carbon neutrality with clean hydrogen

Open access
Yang, Xi, Nielsen, Chris P., Song, Shaojie, McElroy, Michael B.·2022·Nature Energy

Abstract

Countries such as China are facing a bottleneck in their paths to carbon neutrality: abating emissions in heavy industries and heavy-duty transport. There are few in-depth studies of the prospective role for clean hydrogen in these ‘hard-to-abate’ (HTA) sectors. Here we carry out an integrated dynamic least-cost modelling analysis. Results show that, first, clean hydrogen can be both a major energy carrier and feedstock that can significantly reduce carbon emissions of heavy industry. It can also fuel up to 50% of China’s heavy-duty truck and bus fleets by 2060 and significant shares of shipping. Second, a realistic clean hydrogen scenario that reaches 65.7 Mt of production in 2060 could avoid US$1.72 trillion of new investment compared with a no-hydrogen scenario. This study provides evidence of the value of clean hydrogen in HTA sectors for China and countries facing similar challenges in reducing emissions to achieve net-zero goals.

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 · 10.1038/s41560-022-01114-6

Cites

22 of 22 references verified0 citation errors · 0 not checkable

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

Cites

Show all 22 references

Cited by

See all 432

Metadata

Authors
Yang, X., Nielsen, C. P., Song, S., & McElroy, M. B.
Venue
Nature Energy
Published
2022-09-29
Volume
7
Issue
10
Pages
955-965
ISSN
2058-7546 (ISSN-L)
OpenAlex
W4297996718
Cited by
432
References
22
FWCI
14.63
Type
journal article
Language
en
Open access
hybrid

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: Breaking the hard-to-abate bottleneck in China’s path to carbon neutrality with clean hydrogen. https://app.cochat.ai/papers/10.1038/s41560-022-01114-6
The paper
Yang, X., Nielsen, C. P., Song, S., & McElroy, M. B. (2022). Breaking the hard-to-abate bottleneck in China’s path to carbon neutrality with clean hydrogen. Nature Energy. https://doi.org/10.1038/s41560-022-01114-6

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.