Data

Fossil fuel consumption per capita

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What you should know about this indicator

  • Includes commercial solid fuels only, i.e. bituminous coal and anthracite (hard coal), and lignite and brown (sub-bituminous) coal, and other commercial solid fuels. Excludes coal converted to liquid or gaseous fuels, but includes coal consumed in transformation processes. Differences between the consumption figures and the world production statistics are accounted for by stock changes, and unavoidable disparities in the definition, measurement or conversion of coal supply and demand data.
  • Includes inland demand plus international aviation and marine bunkers and refinery fuel and loss. Consumption of biogasoline (such as ethanol) and biodiesel are excluded while derivatives of coal and natural gas are included. Differences between the world consumption figures and world production statistics are accounted for by stock changes, consumption of non-petroleum additives and substitute fuels and unavoidable disparities in the definition, measurement or conversion of oil supply and demand data.
  • Excludes natural gas converted to liquid fuels but includes derivatives of coal as well as natural gas consumed in Gas-to-Liquids transformation. The difference between the world consumption figures and the world production statistics is due to variations in stocks at storage facilities and liquefaction plants, together with unavoidable disparities in the definition, measurement or conversion of gas supply and demand data.
Fossil fuel consumption per capita
Measured in per person.
Source
Energy Institute - Statistical Review of World Energy (2025); Population based on various sources (2024)with major processing by Our World in Data
Last updated
June 27, 2025
Next expected update
June 2026
Date range
1965–2024
Unit
kilowatt-hours

Sources and processing

Energy Institute – Statistical Review of World Energy

The Energy Institute Statistical Review of World Energy analyses data on world energy markets from the prior year.

Retrieved on
June 27, 2025
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.
Energy Institute - Statistical Review of World Energy (2025).

The Energy Institute Statistical Review of World Energy analyses data on world energy markets from the prior year.

Retrieved on
June 27, 2025
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.
Energy Institute - Statistical Review of World Energy (2025).

Various sources – Population

Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on various sources.

You can find more information on these sources and how our time series is constructed on this page: https://ourworldindata.org/population-sources

Retrieved on
July 11, 2024
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.
The long-run data on population is based on various sources, described on this page: https://ourworldindata.org/population-sources

Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on various sources.

You can find more information on these sources and how our time series is constructed on this page: https://ourworldindata.org/population-sources

Retrieved on
July 11, 2024
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.
The long-run data on population is based on various sources, described on this page: https://ourworldindata.org/population-sources

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
Notes on our processing step for this indicator

Per capita figures are calculated by dividing by a population dataset that is built and maintained by Our World in Data, based on different sources.

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: Fossil fuel consumption per capita”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Max Roser (2023) - “Energy”. Data adapted from Energy Institute, Various sources. Retrieved from https://archive.ourworldindata.org/20260304-142439/grapher/fossil-fuels-per-capita.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:

Energy Institute - Statistical Review of World Energy (2025); Population based on various sources (2024) – with major processing by Our World in Data

Full citation

Energy Institute - Statistical Review of World Energy (2025); Population based on various sources (2024) – with major processing by Our World in Data. “Fossil fuel consumption per capita” [dataset]. Energy Institute, “Statistical Review of World Energy”; Various sources, “Population” [original data]. Retrieved March 31, 2026 from https://archive.ourworldindata.org/20260304-142439/grapher/fossil-fuels-per-capita.html (archived on March 4, 2026).

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.

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/fossil-fuels-per-capita.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/fossil-fuels-per-capita.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/fossil-fuels-per-capita.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/fossil-fuels-per-capita.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/fossil-fuels-per-capita.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/fossil-fuels-per-capita.csv?v=1&csvType=full&useColumnShortNames=false")

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