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Monthly CO2 emissions projections from 2015-2025: modified SSP2-4.5 to account for COVID-19 impacts on sector activity

Authors: Lamboll, Robin; Forster, Piers; Rogelj, Joeri;

Monthly CO2 emissions projections from 2015-2025: modified SSP2-4.5 to account for COVID-19 impacts on sector activity

Abstract

Monthly CO2 emissions projections 2015-2025, modified by country-specific impacts of COVID-19 lockdown in 2020-2023, with 4 different projections for the period 2024-2025. This repository holds the netcdf files for CO2 emissions from ground-level and aviation sources from the MESSAGE_GLOBIOM scenario SSP2-4.5, from the Scenario4MIPs database (https://esgf-node.llnl.gov/search/input4mips/), modified by the country and sector activity levels associated with lockdown for 2020. Sector activity level in 2020 is based on data up until June, and a fixed estimate is used thereafter. This is the monthly equivalent of https://zenodo.org/record/3951601#.XxYBsihKhPY for this time period. Funding was provided by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement nos. 820829 (CONSTRAIN) http://constrain-eu.org/ see https://github.com/Priestley-Centre/COVID19_emissions for more details.

Note that the data and normalisation process used in the aviation data is subtly updated since the version 4 found in related databases, hence that is referred to as v4.5. It still does not cover the whole month of July, due to publication date. The whole dataset is now considered version 4.5.1 as it features more variables and differently cropped timeframes, however is still consistent with version 4.5 in terms of the input data.

Country
United Kingdom
Related Organizations
Keywords

COVID-19, C02 emissions, CO2 emissions

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
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