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Data

Global warming potential of greenhouse gases relative to CO₂

See all data and research on:
CO2 & Greenhouse Gas EmissionsClimate Change

What you should know about this indicator

  • Global warming potential (GWP) values are used to convert greenhouse gases into a carbon dioxide equivalent metric by multiplying emissions in mass terms by their respective GWP factors.
  • For example, a GWP value of 25 for a certain gas means that one tonne of that gas has 25 times the warming impact of one tonne of carbon dioxide.
Global warming potential of greenhouse gases relative to CO₂
measures the relative warming impact of one unit mass of a greenhouse gas relative to carbon dioxide.
Source
IPCC (2021) – with minor processing by Our World in Data
Last updated
November 6, 2023
Next expected update
May 2026
Date range
2021–2021

Related research and writing

Thumbnail

Greenhouse gas emissions

Hannah Ritchie, Pablo Rosado, and Max Roser

Sources and processing

This data is based on the following sources

IPCC – IPCC 6th Assessment Report, Working Group I, Chapter 7 Supplementary Material

Global warming potential for a 100-year time horizon (GWP-100) for a selection of greenhouse gases.

Retrieved on
November 6, 2023
Retrieved from
https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-7/
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.
Working Group I (WGI) Contribution to the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC), Chapter 7: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity.
Data extracted from the Supplementary Materials, Table 7.SM.7: Greenhouse gas lifetimes, radiative efficiencies, global warming potentials (GWPs), global temperature potentials (GTPs) and cumulative global temperature potentials (CGTPs).
Forster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 923-1054, doi: 10.1017/9781009157896.009.

Global warming potential for a 100-year time horizon (GWP-100) for a selection of greenhouse gases.

Retrieved on
November 6, 2023
Retrieved from
https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-7/
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.
Working Group I (WGI) Contribution to the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC), Chapter 7: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity.
Data extracted from the Supplementary Materials, Table 7.SM.7: Greenhouse gas lifetimes, radiative efficiencies, global warming potentials (GWPs), global temperature potentials (GTPs) and cumulative global temperature potentials (CGTPs).
Forster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 923-1054, doi: 10.1017/9781009157896.009.

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: Global warming potential of greenhouse gases relative to CO₂”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Max Roser (2023) - “CO₂ and Greenhouse Gas Emissions”. Data adapted from IPCC. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.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:

IPCC (2021) – with minor processing by Our World in Data

Full citation

IPCC (2021) – with minor processing by Our World in Data. “Global warming potential of greenhouse gases relative to CO₂” [dataset]. IPCC, “IPCC 6th Assessment Report, Working Group I, Chapter 7 Supplementary Material” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.html (archived on March 4, 2026).

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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/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.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/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.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/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.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/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/global-warming-potential-of-greenhouse-gases-over-100-year-timescale-gwp.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear