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Cited by 344

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Communicating the deadly consequences of global warming for human heat stress

Open access
Matthews, Tom K. R., Wilby, Robert L., Murphy, Conor·2017·Proceedings of the National Academy of Sciences

Abstract

Significance: Extremely hot weather can have deadly human consequences. As the climate warms, the frequency and intensity of such conditions are expected to increase—among the most certain negative impacts expected under global warming. Concerns about dangerous climate change have encouraged the international community to commit to limiting global temperature changes to below 2 °C above preindustrial. Although lauded as a great achievement to avoid dangerous climate change, we find that, even if such aspirations are realized, large increases in the frequency of deadly heat should be expected, with more than 350 million more megacity inhabitants afflicted by midcentury. Such conclusions underline the critical role for ambitious adaptation alongside these climate change mitigation targets.

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Registry

Crossref · 10.1073/pnas.1617526114

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Metadata

Authors
Matthews, T. K. R., Wilby, R. L., & Murphy, C.
Venue
Proceedings of the National Academy of Sciences
Published
2017-03-27
Volume
114
Issue
15
Pages
3861-3866
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2600045851
Cited by
344
References
9
FWCI
10.93
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Communicating the deadly consequences of global warming for human heat stress. https://app.cochat.ai/papers/10.1073/pnas.1617526114
The paper
Matthews, T. K. R., Wilby, R. L., & Murphy, C. (2017). Communicating the deadly consequences of global warming for human heat stress. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1617526114

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.