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Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0

Overview of attention for article published in Geoscientific Model Development, April 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#10 of 2,079)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
12 news outlets
blogs
2 blogs
twitter
14 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
18 Mendeley
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Title
Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0
Published in
Geoscientific Model Development, April 2023
DOI 10.5194/gmd-16-2193-2023
Authors

Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodriguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, Oriol Jorba

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 17%
Researcher 3 17%
Student > Ph. D. Student 3 17%
Unspecified 1 6%
Librarian 1 6%
Other 2 11%
Unknown 5 28%
Readers by discipline Count As %
Environmental Science 7 39%
Chemical Engineering 1 6%
Unspecified 1 6%
Earth and Planetary Sciences 1 6%
Social Sciences 1 6%
Other 1 6%
Unknown 6 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 103. 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 03 May 2023.
All research outputs
#412,959
of 25,622,179 outputs
Outputs from Geoscientific Model Development
#10
of 2,079 outputs
Outputs of similar age
#9,428
of 414,100 outputs
Outputs of similar age from Geoscientific Model Development
#1
of 81 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,079 research outputs from this source. They receive a mean Attention Score of 4.9. 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 414,100 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 97% of its contemporaries.
We're also able to compare this research output to 81 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.