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Multi-model comparison of the economic and energy implications for China and India in an international climate regime

Overview of attention for article published in Mitigation & Adaptation Strategies for Global Change, February 2014
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Title
Multi-model comparison of the economic and energy implications for China and India in an international climate regime
Published in
Mitigation & Adaptation Strategies for Global Change, February 2014
DOI 10.1007/s11027-014-9549-4
Pubmed ID
Authors

Daniel J. A. Johansson, Paul L. Lucas, Matthias Weitzel, Erik O. Ahlgren, A. B Bazaz, Wenying Chen, Michel G. J. den Elzen, Joydeep Ghosh, Maria Grahn, Qiao-Mei Liang, Sonja Peterson, Basanta K. Pradhan, Bas J. van Ruijven, P. R. Shukla, Detlef P. van Vuuren, Yi-Ming Wei

Abstract

This paper presents a modeling comparison on how stabilization of global climate change at about 2 °C above the pre-industrial level could affect economic and energy systems development in China and India. Seven General Equilibrium (CGE) and energy system models on either the global or national scale are soft-linked and harmonized with respect to population and economic assumptions. We simulate a climate regime, based on long-term convergence of per capita carbon dioxide (CO2) emissions, starting from the emission pledges presented in the Copenhagen Accord to the United Nations Framework Convention on Climate Change and allowing full emissions trading between countries. Under the climate regime, Indian emission allowances are allowed to grow more than the Chinese allowances, due to the per capita convergence rule and the higher population growth in India. Economic and energy implications not only differ among the two countries, but also across model types. Decreased energy intensity is the most important abatement approach in the CGE models, while decreased carbon intensity is most important in the energy system models. The reduction in carbon intensity is mostly achieved through deployment of carbon capture and storage, renewable energy sources and nuclear energy. The economic impacts are generally higher in China than in India, due to higher 2010-2050 cumulative abatement in China and the fact that India can offset more of its abatement cost though international emission trading.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
United States 1 2%
Unknown 50 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 25%
Student > Ph. D. Student 10 19%
Student > Master 8 15%
Other 5 10%
Professor 3 6%
Other 13 25%
Readers by discipline Count As %
Economics, Econometrics and Finance 12 23%
Environmental Science 12 23%
Energy 8 15%
Unspecified 5 10%
Engineering 5 10%
Other 10 19%

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 04 March 2014.
All research outputs
#9,839,946
of 12,321,253 outputs
Outputs from Mitigation & Adaptation Strategies for Global Change
#380
of 415 outputs
Outputs of similar age
#131,552
of 195,012 outputs
Outputs of similar age from Mitigation & Adaptation Strategies for Global Change
#12
of 12 outputs
Altmetric has tracked 12,321,253 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 415 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 3rd percentile – i.e., 3% 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 195,012 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.