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CarbonMonitor-Power near-real-time monitoring of global power generation on hourly to daily scales

Overview of attention for article published in Scientific Data, April 2023
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Article details
Title
CarbonMonitor-Power near-real-time monitoring of global power generation on hourly to daily scales
Published in
Scientific Data, April 2023
DOI 10.1038/s41597-023-02094-2
Pubmed ID
Authors
Abstract

We constructed a frequently updated, near-real-time global power generation dataset: CarbonMonitor-Power since January, 2016 at national levels with near-global coverage and hourly-to-daily time resolution. The data presented here are collected from 37 countries across all continents for eight source groups, including three types of fossil sources (coal, gas, and oil), nuclear energy and four groups of renewable energy sources (solar energy, wind energy, hydro energy and other renewables including biomass, geothermal, etc.). The global near-real-time power dataset shows the dynamics of the global power system, including its hourly, daily, weekly and seasonal patterns as influenced by daily periodical activities, weekends, seasonal cycles, regular and irregular events (i.e., holidays) and extreme events (i.e., the COVID-19 pandemic). The CarbonMonitor-Power dataset reveals that the COVID-19 pandemic caused strong disruptions in some countries (i.e., China and India), leading to a temporary or long-lasting shift to low carbon intensity, while it had only little impact in some other countries (i.e., Australia). This dataset offers a large range of opportunities for power-related scientific research and policy-making.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 3 9%
Researcher 3 9%
Lecturer 1 3%
Student > Doctoral Student 1 3%
Professor 1 3%
Other 3 9%
Unknown 22 65%
Readers by discipline
Readers by discipline Count As %
Engineering 3 9%
Earth and Planetary Sciences 2 6%
Energy 2 6%
Arts and Humanities 1 3%
Chemical Engineering 1 3%
Other 2 6%
Unknown 23 68%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 July 2023.
All research outputs
#22,234,349
of 28,149,311 outputs
Outputs from Scientific Data
#3,627
of 4,284 outputs
Outputs of similar age
#306,240
of 428,711 outputs
Outputs of similar age from Scientific Data
#151
of 187 outputs
Altmetric has tracked 28,149,311 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,284 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.1. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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 428,711 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.