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Data

Change in global mean surface temperature caused by greenhouse gas emissions

See all data and research on:
CO2 & Greenhouse Gas Emissions

What you should know about this indicator

  • This temperature change measures each country's contribution to global mean surface temperature (GMST) rise from its cumulative emissions of carbon dioxide, methane and nitrous oxide.
  • The warming effects of each gas are calculated based on cumulative CO₂-equivalent emissions using the Global Warming Potential (GWP*) approach.
Change in global mean surface temperature caused by greenhouse gas emissions
Measured in °C.
Source
Jones et al. (2025) – with major processing by Our World in Data
Last updated
December 4, 2025
Next expected update
December 2026
Date range
1851–2024
Unit
°C

Sources and processing

This data is based on the following sources

Jones et al. – National contributions to climate change

A dataset describing the global warming response to national emissions CO2, CH4 and N2O from fossil and land use sources during 1851-2024.

National CO2 emissions data are collated from the Global Carbon Project (Andrew and Peters, 2025; Friedlingstein et al., 2025).

National CH4 and N2O emissions data are collated from PRIMAP-hist (HISTTP) (Gütschow et al., 2024).

We construct a time series of cumulative CO2-equivalent emissions for each country, gas, and emissions source (fossil or land use). Emissions of CH4 and N2O emissions are related to cumulative CO2-equivalent emissions using the Global Warming Potential (GWP*) approach, with best-estimates of the coefficients taken from the IPCC AR6 (Forster et al., 2021).

Warming in response to cumulative CO2-equivalent emissions is estimated using the transient climate response to cumulative carbon emissions (TCRE) approach, with best-estimate value of TCRE taken from the IPCC AR6 (Forster et al., 2021, Canadell et al., 2021). 'Warming' is specifically the change in global mean surface temperature (GMST).

The data files provide emissions, cumulative emissions and the GMST response by country, gas (CO2, CH4, N2O or 3-GHG total) and source (fossil emissions, land use emissions or the total).

Retrieved on
December 4, 2025
Retrieved from
https://zenodo.org/records/7636699/latest
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Jones, Matthew W., Glen P. Peters, Thomas Gasser, Robbie M. Andrew, Clemens Schwingshackl, Johannes Gütschow, Richard A. Houghton, Pierre Friedlingstein, Julia Pongratz, and Corinne Le Quéré. “National Contributions to Climate Change Due to Historical Emissions of Carbon Dioxide, Methane and Nitrous Oxide”. Scientific Data. Zenodo, November 13, 2025. https://doi.org/10.5281/zenodo.16640595.

A dataset describing the global warming response to national emissions CO2, CH4 and N2O from fossil and land use sources during 1851-2024.

National CO2 emissions data are collated from the Global Carbon Project (Andrew and Peters, 2025; Friedlingstein et al., 2025).

National CH4 and N2O emissions data are collated from PRIMAP-hist (HISTTP) (Gütschow et al., 2024).

We construct a time series of cumulative CO2-equivalent emissions for each country, gas, and emissions source (fossil or land use). Emissions of CH4 and N2O emissions are related to cumulative CO2-equivalent emissions using the Global Warming Potential (GWP*) approach, with best-estimates of the coefficients taken from the IPCC AR6 (Forster et al., 2021).

Warming in response to cumulative CO2-equivalent emissions is estimated using the transient climate response to cumulative carbon emissions (TCRE) approach, with best-estimate value of TCRE taken from the IPCC AR6 (Forster et al., 2021, Canadell et al., 2021). 'Warming' is specifically the change in global mean surface temperature (GMST).

The data files provide emissions, cumulative emissions and the GMST response by country, gas (CO2, CH4, N2O or 3-GHG total) and source (fossil emissions, land use emissions or the total).

Retrieved on
December 4, 2025
Retrieved from
https://zenodo.org/records/7636699/latest
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Jones, Matthew W., Glen P. Peters, Thomas Gasser, Robbie M. Andrew, Clemens Schwingshackl, Johannes Gütschow, Richard A. Houghton, Pierre Friedlingstein, Julia Pongratz, and Corinne Le Quéré. “National Contributions to Climate Change Due to Historical Emissions of Carbon Dioxide, Methane and Nitrous Oxide”. Scientific Data. Zenodo, November 13, 2025. https://doi.org/10.5281/zenodo.16640595.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Change in global mean surface temperature caused by greenhouse gas emissions”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Max Roser (2023) - “CO₂ and Greenhouse Gas Emissions”. Data adapted from Jones et al.. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/contribution-temp-rise-degrees.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Jones et al. (2025) – with major processing by Our World in Data

Full citation

Jones et al. (2025) – with major processing by Our World in Data. “Change in global mean surface temperature caused by greenhouse gas emissions” [dataset]. Jones et al., “National contributions to climate change 2025.1” [original data]. Retrieved March 31, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/contribution-temp-rise-degrees.html (archived on March 4, 2026).

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/contribution-temp-rise-degrees.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/contribution-temp-rise-degrees.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/contribution-temp-rise-degrees.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/contribution-temp-rise-degrees.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/contribution-temp-rise-degrees.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/contribution-temp-rise-degrees.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/contribution-temp-rise-degrees.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/contribution-temp-rise-degrees.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear