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Estimating economic damage from climate change in the United States

Overview of attention for article published in Science, June 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
249 news outlets
blogs
50 blogs
policy
8 policy sources
twitter
1357 tweeters
facebook
22 Facebook pages
wikipedia
5 Wikipedia pages
googleplus
13 Google+ users
reddit
2 Redditors

Citations

dimensions_citation
347 Dimensions

Readers on

mendeley
1014 Mendeley
citeulike
1 CiteULike
Title
Estimating economic damage from climate change in the United States
Published in
Science, June 2017
DOI 10.1126/science.aal4369
Pubmed ID
Authors

Solomon Hsiang, Robert Kopp, Amir Jina, James Rising, Michael Delgado, Shashank Mohan, D. J. Rasmussen, Robert Muir-Wood, Paul Wilson, Michael Oppenheimer, Kate Larsen, Trevor Houser

Abstract

Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors-agriculture, crime, coastal storms, energy, human mortality, and labor-increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).

Twitter Demographics

The data shown below were collected from the profiles of 1,357 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,014 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Italy 1 <1%
Germany 1 <1%
South Africa 1 <1%
Unknown 1010 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 234 23%
Researcher 173 17%
Student > Master 152 15%
Student > Bachelor 64 6%
Student > Doctoral Student 58 6%
Other 175 17%
Unknown 158 16%
Readers by discipline Count As %
Environmental Science 173 17%
Economics, Econometrics and Finance 119 12%
Earth and Planetary Sciences 96 9%
Agricultural and Biological Sciences 87 9%
Social Sciences 74 7%
Other 253 25%
Unknown 212 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 3335. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 July 2021.
All research outputs
#951
of 18,449,552 outputs
Outputs from Science
#63
of 72,444 outputs
Outputs of similar age
#13
of 277,025 outputs
Outputs of similar age from Science
#1
of 999 outputs
Altmetric has tracked 18,449,552 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 72,444 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 56.8. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 277,025 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 999 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.