[From "BP Statistical Review of World Energy 2001: 2000 in review"]

 "World consumption of primary energy rebounded in 2000, rising by
 2.1%, driven by continued strong growth in the world economy and a
 return to colder winter weather patterns. There were again strong
 contrasts in the performance of different fuels. Natural gas and coal
 grew by significantly more than their 1990-2000 annual averages and
 oil and nuclear energy grew effectively in line with their 10-year
 average, while hydroelectricity grew by less."

An annual publication that provides high-quality objective and globally consistent data on world energy markets. Tables include consumption of primary energy; reserves, production, consumption, prices and trade data for oil, natural gas and coal; consumption of nuclear energy, hydroelectricity and renewable energy; electricity generation; and carbon dioxide emissions.

Website: http://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html

The BP Statistical review of World Energy provides an interactive energy charting tool, with data back to 1965, and a conversion calculator. The 2006 Review includes data through the year 2005 including: - Oil production: Global oil output rose by 900,000 barrels per day in 2005 - Natural gas production: Gas production rose by 2.5%, despite declines in some regions - Coal production: China had 80% of the growth in the world's fastest growing fuel

The energy statistics published by BP are a reference source in the sector.

Global anthropogenic CO2 emissions based on EDGARv4.3, fuel type and category specific emissions provided by Greet Janssens-Maenhout (EU-JRC), BP statistics 2016 (http://www.bp.com/content/dam/bp/excel/energy-economics/statistical-review-2016/bp-statistical-review-of-world-energy-2016-workbook.xlsx), temporal variations based on MACC-TNO (https://gmes-atmosphere.eu/documents/deliverables/d-emis/MACC_TNO_del_1_3_v2.pdf), temporal extrapolation and disaggregation described in COFFEE (Steinbach et al. 2011). Gerbig, C., Janssens-Maenhout, G., Karstens, U. (2017). Global anthropogenic CO2 emissions based on EDGARv4.3 and BP statistics 2016, 2009-08-01–2009-08-31, Miscellaneous, https://hdl.handle.net/11676/-Ds8OPhCs4jTWMyTVyH9C5Xg

Context

Data is compiled by Our World in Data based on two sources: – BP Statistical Review of World Energy: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html – Ember: https://ember-climate.org/data/

Generation in THh between 2000 and 2019

Content

World in Data rely on electricity mix data from BP as it's primary source for two key reasons: BP also provides total energy (not just electricity) consumption data, meaning energy and electricity data is consistent from the same source; and it provides a longer time-series. However, BP does not provide data for all countries, but these were removed from this datasets.

Acknowledgements

Ember compiles electricity mix data from numerous international and national sources, but relies on the Energy Information Administration (EIA) as its primary source.

Global anthropogenic CO2 emissions based on EDGARv4.3 (Janssens-Maenhout et al., 2019, https://doi.org/10.5194/essd-11-959-2019, fuel type and category specific emissions were provided by Greet Janssens-Maenhout, EU-JRC), BP statistics 2019 (https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/xlsx/energy-economics/statistical-review/bp-stats-review-2019-all-data.xlsx), temporal variations based on MACC-TNO (Denier van der Gon et al., 2011, https://atmosphere.copernicus.eu/sites/default/files/2019-07/MACC_TNO_del_1_3_v2.pdf), temporal extrapolation and disaggregation described in COFFEE (Steinbach et al. 2011, https://doi.org/10.5194/acp-11-6855-2011). Gerbig, C., Janssens-Maenhout, G., Karstens, U. (2019). Global anthropogenic CO2 emissions based on EDGARv4.3 and BP statistics 2019, 2012-06-01–2012-06-30, Miscellaneous, https://hdl.handle.net/11676/-3i7GG5XsH3jNZSpLzq53RRP

The dataset contains the following information from 12 Middle Eastern countries from 1990 to 2020 (namely Bahrain, Iran, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, the United Arab Emirates, and Yemen): • The population (according to the United Nations population statistics) • The GDPs of countries (constant 2010 US dollar) in the studied period (collected from World Bank datasets) • Energy consumption in the Middle East by fuel (collected from the International Energy Agency (IEA) Energy Outlook and British Petroleum (BP) statistical review) • The rate of carbon dioxide emissions in the Middle East by fuel (collected from the International Energy Agency (IEA) Energy Outlook and British Petroleum (BP) statistical review)

Global primary energy consumption has increased dramatically in recent years and is projected to continue to increase until 2045. Only hydropower and renewable energy consumption are expected to increase between 2045 and 2050 and reach 30 percent of the global energy consumption. Energy consumption by country The distribution of energy consumption globally is disproportionately high among some countries. China, the United States, and India were by far the largest consumers of primary energy globally. On a per capita basis, it was Qatar, Singapore, the United Arab Emirates, and Iceland to have the highest per capita energy consumption. Renewable energy consumption Over the last two decades, renewable energy consumption has increased to reach over 90 exajoules in 2023. Among all countries globally, China had the largest installed renewable energy capacity as of that year, followed by the United States.

Anthropogenic CO2 emissions for Europe based on EDGARv4.3 (Janssens-Maenhout et al., 2019, https://doi.org/10.5194/essd-11-959-2019, fuel type and category specific emissions were provided by Greet Janssens-Maenhout, EU-JRC), BP statistics 2021 (https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/xlsx/energy-economics/statistical-review/bp-stats-review-2021-all-data.xlsx), temporal variations based on MACC-TNO (Denier van der Gon et al., 2011, https://atmosphere.copernicus.eu/sites/default/files/2019-07/MACC_TNO_del_1_3_v2.pdf), temporal extrapolation and disaggregation described in COFFEE (Steinbach et al. 2011, https://doi.org/10.5194/acp-11-6855-2011) Gerbig, C., Koch, F. (2021). European anthropogenic CO2 emissions for 2019 based on EDGARv4.3 and BP statistics 2021, 2019, Miscellaneous, https://hdl.handle.net/11676/ZU0G9vak8AOz-GprC0uY-HPM

Russia is the largest natural gas supplier to the EU. The invasion of Ukraine was followed by a cut-off of gas supplies from Russia to many EU countries, and the EU is planning to ban or dramatically reduce its dependence from Russia. To quantify the magnitude of the Russian gas used for different countries and sectors and the potential solutions to the Russian gas gap, we provide two daily resolution datasets: 1) EU27&UK daily gas supply-consumption (EUGasSC), and 2) EU27&UK daily gas reduction potential (EUGasRP). EUGasSC (from 2016-2022) provides the country- and sector-specific natural gas supply-storage-consumption (including Russian Supply Share) in the EU27&UK at a daily resolution, which is aimed to quantify the shortfalls if Russian imports were to stop. EUGasRP (for 2021) shows the maximal daily gas conservation potentials estimated by reducing demand for heating and/or increasing power generation from other sources, i.e., coal, nuclear, and biomass. They can be used as either input or reference datasets for further research in various fields, such as gas/energy modeling, carbon emission, climate change, geopolitical policy discussions, and the international gas/energy market. The units of the two datasets are KWh.

Preprint of our paper: https://essd.copernicus.org/preprints/essd-2022-246/

Website of our datasets: https://eugas.herokuapp.com/

Github of our work: https://github.com/chuanlongZhou/russia_gas_essd.git

The EUGasSC dataset was developed with a gas network flow simulation based on flow mass balance by combining data from multiple datasets including ENTSO-G, ENTSO-E, and Eurostat energy balance (annual and monthly). The EUGasSC dataset was validated with BP Statistical Review of World Energy and multiple Eurostat datasets. The EUGasSC shows the share of gas supplied by Russia in each country to analyze the ‘gap’ that would result from a stop of all Russian exports to Europe.

The EUGasRP is developed for the potential solutions to fill the Russian gap in the EU27&UK. We analyze gas reductions for reducing demand for heating and increasing power generation from other sources, i.e., coal, nuclear, and biomass, that can substitute the gas.

For the heating sector, we analyze reduction scenarios for weekdays and weekends of household and public buildings. The reduction estimations are based on empirical temperature-gas-consumption (TGC) curves based on population-weighted air temperatures using the Eurostat population dataset and ERA5 daily 2-meters air temperature data. The values provided in EUGasRP assume the following reduction scenarios: 1) households on weekdays adopt a 2 °C lower critical temperature and follow the lower 20th percentile of TGC curves to define the slope, 2) households on weekends adopt a 2 °C lower critical temperature and the lower 40th percentile of TGC curves, and 3) public buildings adopt a 4 °C lower critical temperature and the lower 20th percentile of the TGS curve.

For the power sector, we assume that the electricity generated with gas can be substituted by boosting the hourly electricity generated with coal, nuclear, and biomass to certain observed higher levels. We estimate the observed higher levels by95% (as maximal gas reduction) of the maximum observed diurnal hourly capacities for coal, nuclear, and biomass for each country based on observed ENTSO-E electricity production data from 2019 to 2021.

We also provide further discussions in our paper for 1) uncertainties of the two datasets, 2) the moderate scenarios for gas reductions, 3) transferring gas savings from countries with surplus to those with deficits, and 4) increasing imports from other countries like Norway, the US, and Australia from either pipelines or LNG. Based on our analysis, we argue that with plausible demand reductions, shifts in power generation towards nuclear and coal, and intra-EU and international coordination, particularly with the UK, the US, Australia, and Norway, it should be possible for the EU to make up for the sudden loss of Russian gas.

China's daily biofuel production reached 78 thousand barrels of oil equivalent in 2023, an increase by eight thousand barrels of oil equivalent per day in comparison to the year prior. Between 2002 and 2023, production of biofuels in the East Asian country experienced a growth of 75 thousand barrels of oil equivalent per day. As of 2022, China's production corresponded to 3.5 percent of the global biofuel production.

China is the largest consumer of primary energy in the world, having used some 176.35 exajoules in 2024. This is a lot more than what the United States consumed, which comes in second place. The majority of primary energy fuels worldwide are still derived from fossil fuels, such as oil and coal. China's energy mix China’s primary energy mix has shifted from a dominant use of coal to an increase in natural gas and renewable sources. Since 2013, the renewables share in total energy consumption has grown by around eight percentage points. Overall, global primary energy consumption has increased over the last decade, and it is expected to experience the largest growth in emerging economies like the BRIC countries - Brazil, Russia, India, and China. What is primary energy? Primary energy is the energy inherent in natural resources such as crude oil, coal, and wind before further transformation. For example, crude oil can be refined into secondary fuels, such as gasoline or diesel, while wind is harnessed for electricity - itself a secondary energy source. A country’s total primary energy supply is a measure of the country’s primary energy sources. Meanwhile, end use energy is the energy directly consumed by the user and includes primary fuels such as natural gas, as well as secondary sources, like electricity and gasoline.

This is an updated version of Gütschow et al. (2019, http://doi.org/10.5880/pik.2019.001). Please use this version which incorporates updates to input data as well as correction of errors in the original dataset and its previous updates. For a detailed description of the changes please consult the CHANGELOG included in the data description document. The PRIMAP-hist dataset combines several published datasets to create a comprehensive set of greenhouse gas emission pathways for every country and Kyoto gas covering the years 1850 to 2017, and all UNFCCC (United Nations Framework Convention on Climate Change) member states, as well as most non-UNFCCC territories. The data resolves the main IPCC (Intergovernmental Panel on Climate Change) 2006 categories. For CO2, CH4, and N2O subsector data for Energy, Industrial Processes and Agriculture is available. Version 2.1 of the PRIMAP-hist dataset does not include emissions from Land use, land use change and forestry (LULUCF). List of datasets included in this data publication:(1) PRIMAP-hist_v2.1_09-Nov-2019.csv: With numerical extrapolation of all time series to 2017. (only in .zip folder)(2) PRIMAP-hist_no_extrapolation_v2.1_09-Nov-2019.csv: Without numerical extrapolation of missing values. (only in .zip folder)(3) PRIMAP-hist_v2.1_data-format-description: including CHANGELOG(4) PRIMAP-hist_v2.1_updated_figures: updated figures of those published in Gütschow et al. (2016)(all files are also included in the .zip folder) When using this dataset or one of its updates, please also cite the data description article (Gütschow et al., 2016, http://doi.org/10.5194/essd-8-571-2016) to which this data are supplement to. Please consider also citing the relevant original sources. SOURCES:- Global CO2 emissions from cement production v4: Andrew (2019)- BP Statistical Review of World Energy: BP (2019)- CDIAC: Boden et al. (2017)- EDGAR version 4.3.2: JRC and PBL (2017), Janssens-Maenhout et al. (2017)- EDGAR versions 4.2 and 4.2 FT2010: JRC and PBL (2011), Olivier and Janssens-Maenhout (2012)- EDGAR-HYDE 1.4: Van Aardenne et al. (2001), Olivier and Berdowski (2001)- FAOSTAT database: Food and Agriculture Organization of the United Nations (2019)- RCP historical data: Meinshausen et al. (2011)- UNFCCC National Communications and National Inventory Reports for developing countries: UNFCCC (2019)- UNFCCC Biennal Update Reports: UNFCCC (2019)- UNFCCC Common Reporting Format (CRF): UNFCCC (2018), UNFCCC (2019), Jeffery et al. (2018) Full references are available in the data description document.

This dataset contains information about coal total proved reserves from 2004. Data from BP.Follow datasource.kapsarc.org for timely data to advance energy economics research.Please note that due to process improvements for the Statistical Review these reserves tables have not been updated this year.Source: statistics are taken from national statistical agencies, international organizations, and other proprietary sources. Includes data from Federal Institute for Geosciences and Natural Resources (BGR) Energy Study 2021. * More than 500 years.♦ Less than 0.05%.Notes: Total proved reserves of coal- Generally taken to be those quantities that geological and engineering information indicates with reasonable certainty can be recovered in the future from known reservoirs under existing economic and operating conditions. The data series for total proved coal reserves does not necessarily meet the definitions, guidelines and practices used for determining proved reserves at company level, for instance as published by the US Securities and Exchange Commission, nor does it necessarily represent BP’s view of proved reserves by country. Reserves-to-production (R/P) ratio - If the reserves remaining at the end of any year are divided by the production in that year, the result is the length of timethat those remaining reserves would last if production were to continue at that rate.Reserves-to-production (R/P) ratios are calculated excluding other solid fuels in reserves and production.Shares of total and R/P ratios are calculated using million tonnes figures.

Recommended citation

Gütschow, J.; Günther, A.; Jeffery, L.; Gieseke, R. (2021): The PRIMAP-hist national historical emissions time series v2.2 (1850-2018). zenodo. doi:10.5281/zenodo.4479172.

Gütschow, J.; Jeffery, L.; Gieseke, R.; Gebel, R.; Stevens, D.; Krapp, M.; Rocha, M. (2016): The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571-603, doi:10.5194/essd-8-571-2016

Content

• Use of the dataset and full description
• Abstract
• Support
• Sources
• Files included in the dataset
• Notes
• Data format description (columns)
• Changelog
• References

Use of the dataset and full description

Before using the dataset, please read this document and the article describing the methodology, especially the section on uncertainties and the section on limitations of the method and use of the dataset.

Gütschow, J.; Jeffery, L.; Gieseke, R.; Gebel, R.; Stevens, D.; Krapp, M.; Rocha, M. (2016): The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571-603, doi:10.5194/essd-8-571-2016

Please notify us (johannes.guetschow@pik-potsdam.de) if you use the dataset so that we can keep track of how it is used and take that into consideration when updating and improving the dataset.

When using this dataset or one of its updates, please cite the DOI of the precise version of the dataset used and also the data description article which this dataset is supplement to (see above). Please consider also citing the relevant original sources when using the PRIMAP-hist dataset. See the full citations in the References section further below.

Support

If you encounter possible errors or other things that should be noted, please check our issue tracker at github.com/JGuetschow/PRIMAP-hist and report your findings there.

If you need support in using the dataset or have any other questions regarding the dataset, please contact johannes.guetschow@pik-potsdam.de.

Abstract

The PRIMAP-hist dataset combines several published datasets to create a comprehensive set of greenhouse gas emission pathways for every country and Kyoto gas, covering the years 1850 to 2018, and all UNFCCC (United Nations Framework Convention on Climate Change) member states as well as most non-UNFCCC territories. The data resolves the main IPCC (Intergovernmental Panel on Climate Change) 2006 categories. For CO₂, CH₄, and N₂O subsector data for Energy, Industrial Processes and Product Use (IPPU), and Agriculture is available. Due to data availability and methodological issues, version 2.2 of the PRIMAP-hist dataset does not include emissions from Land Use, Land-Use Change, and Forestry (LULUCF).

The PRIMAP-hist v2.2 dataset is an updated version of

Gütschow, J.; Jeffery, L.; Gieseke, R.; Günther, A. (2019): The PRIMAP-hist national historical emissions time series v2.1 (1850-2017). GFZ Data Services. doi:10.5880/pik.2019.018.

The Changelog indicates the most important changes. You can also check the issue tracker on github.com/JGuetschow/PRIMAP-hist for additional information on issues found after the release of the dataset.

Sources

• Global CO₂ emissions from cement production v4 (Andrew 2019) data, paper Andrew (2019a), Andrew (2019b)
• BP Statistical Review of World Energy website: British Petroleum (2020)
• CDIAC data: Boden et al. (2017)
• EDGAR versions 4.2 and 4.2 FT2010: EDGAR v4.2, EDGAR v4.2 FT2010: JRC and PBL (2011), Olivier and Janssens-Maenhout (2012)
• EDGAR version 5.0: data, paper: JRC and PBL (2017), Crippa et al. (2019)
• EDGAR-HYDE 1.4 data: Van Aardenne et al. (2001), Olivier and Berdowski (2001)
• FAOSTAT database data: Food and Agriculture Organization of the United Nations (2020)
• RCP historical data data, paper: Meinshausen et al. (2011)
• UNFCCC National Communications and National Inventory Reports for developing countries website, data: UNFCCC (2020b), Gieseke and Gütschow (2020)
• UNFCCC Biennial Update Reports website: UNFCCC (2020a)
• UNFCCC Common Reporting Format (CRF) website, paper, data: Gütschow et al. (2020b) UNFCCC (2019a) (processed as described in Jeffery et al. (2018a). PRIMAP-hist contains updated CRF data for Hungary, compared to the published PRIMAP-crf dataset)

Files included in the dataset

• PRIMAP-hist_v2.2_19-Jan-2021.csv: With numerical extrapolation of all time series to 2018.
• PRIMAP-hist_no_extrapolation_v2.2_19-Jan-2021.csv: Without numerical extrapolation of missing values and not including the country groups mentioned in section country.
• PRIMAP-hist_v2.2_data-description.pdf: Data description including changelog.
• PRIMAP-hist_v2.2_updated_figures.pdf: Updated figures from the PRIMAP-hist paper published in ESSD.

Notes

• Emissions from international aviation and shipping are not included in the dataset.
• Emissions from Land Use, Land-Use Change, and Forestry (LULUCF) are not included in this dataset.

Data format description (columns)

“scenario”

• HISTCR: In this scenario country-reported data (CRF, BUR, UNFCCC) is prioritized over third-party data (CDIAC, FAO, Andrew, EDGAR, BP).
• HISTTP: In this scenario third-party data (CDIAC, FAO, Andrew, EDGAR, BP) is prioritized over country-reported data (CRF, BUR, UNFCCC)

“country”

ISO 3166 three-letter country codes or custom codes for groups:

Code    Region description
----    -------
EARTH   Aggregated emissions for all countries.
ANNEXI   Annex I Parties to the Convention
NONANNEXI Non-Annex I Parties to the Convention
AOSIS   Alliance of Small Island States
BASIC   BASIC countries (Brazil, South Africa, India and China)
EU28    European Union
LDC    Least Developed Countries
UMBRELLA  Umbrella Group

Table: Additional “country” codes.

“category”

IPCC (Intergovernmental Panel on Climate Change) 2006 categories for emissions. Some aggregate sectors have been added to the hierarchy. These begin with the prefix IPCM instead of IPC.

-----------------------------------------------------------------------
Category code Description




IPCM0EL    National Total excluding LULUCF
IPC1     Energy
IPC1A     Fuel Combustion Activities
IPC1B     Fugitive Emissions from Fuels
IPC1B1    Solid Fuels
IPC1B2    Oil and Natural Gas
IPC1B3    Other Emissions from Energy Production
IPC1C     Carbon Dioxide Transport and Storage
       (currently no data available)
IPC2     Industrial Processes and Product Use (IPPU)
IPC2A     Mineral Industry
IPC2B     Chemical Industry
IPC2C     Metal Industry
IPC2D     Non-Energy Products from Fuels and Solvent Use
IPC2E     Electronics Industry
       (no data available as the category is only used for
       fluorinated gases which are only resolved at the level
       of category IPC2)
IPC2F     Product uses as Substitutes for Ozone Depleting Substances
       (no data available as the category is only used for
       fluorinated gases which are only resolved at the level
       of category IPC2)
IPC2G     Other Product Manufacture and Use
IPC2H     Other
IPCMAG    Agriculture, sum of IPC3A and IPCMAGELV
IPC3A    

O Anuário Estatístico Brasileiro do Petróleo, Gás Natural e Biocombustíveis 2022 consolida os dados referentes ao desempenho da indústria do petróleo, gás natural e biocombustíveis e do sistema de abastecimento nacionais no período 2012-2021. Estão disponíveis para consulta e download as tabelas integrantes do Anuário 2022 representadas em metadados e no formato CSV. A ANP não divulgará os dados de reservas internacionais provadas de petróleo e gás natural de 2021, porque o BP Statistical Review of World Energy 2022, nossa fonte de dados internacionais, ainda não publicou esses dados. Portanto serão repetidos os dados do Anuário de 2021.

Please use the updated version of this dataset which incorporates updates to input data as well as correction of errors in the original dataset. For a detailed description of the changes please consult the CHANGELOG included in the data description document of the new version. This dataset combines several published datasets to create a comprehensive set of greenhouse gas emission pathways for every country and Kyoto gas covering the years 1850 to 2014 and all UNFCCC (United Nations Framework Convention on Climate Change) member states as well as most non-UNFCCC territories. The data resolves the main IPCC (Intergovernmental Panel on Climate Change) 1996 categories. For CO₂ from energy and industry time series for subsectors are available. List of datasets included in this data publication:PRIMAP-hist_v1.0_14-Apr-2016.csv: With numerical extrapolation of all time series to 2014. PRIMAP-hist_no_extrapolation_v1.0_14-Apr-2016.csv: Without numerical extrapolation of missing values. When using this dataset or one of its updates, please cite the precise version of the dataset used. Please consider also citing the relevant original sources.

Sources: UNFCCC National Communications and National Inventory Reports for developing countries: UNFCCC (2015) UNFCCC Biennal Update Reports: UNFCCC (2016) UNFCCC Common Reporting Format (CRF): UNFCCC (2013), UNFCCC (2014) BP Statistical Review of World Energy: BP (2014) CDIAC: Boden et al. (2015) EDGAR versions 4.2 and 4.2 FT2010: JRC and PBL (2011), Olivier and Janssens-Maenhout (2012) FAOSTAT database: Food and Agriculture Organization of the United Nations (2015b) Houghton land use CO2: Houghton (2008); RCP historical data: Meinshausen et al. (2011) EDGAR-HYDE 1.4: Van Aardenne et al. (2001), Olivier and Berdowski (2001), HYDE land cover data: Klein Goldewijk et al. (2010), Klein Goldewijk et al. (2011) SAGE Global Potential Vegetation Dataset: Ramankutty and Foley (1999) FAO Country Boundaries: Food and Agriculture Organization of the United Nations (2015a)

Die Statistik zeigt die größten nachgewiesenen Kohlereserven nach Ländern weltweit im Jahr 2020. Zu den nachgewiesenen Kohlereserven zählen laut Quelle im Allgemeinen Mengen, die nach geologischen und ingenieurtechnischen Informationen aller Wahrscheinlichkeit nach aus den heute bekannten Vorkommen und unter den derzeitigen wirtschaftlichen und technischen Bedingungen künftig gefördert werden können. Indonesien verfügte in diesem Jahr über Kohlereserven von rund 35 Milliarden Tonnen.Der BP Statistical Review of World Energy erschien erstmalig 1951. Er enthält Zahlen, Daten und Fakten über die weltweite Produktion und den Verbrauch von Öl, Gas, Kohle, Kern- und Wasserkraft und erneuerbaren Energien.

Die Statistik zeigt die Menge der weltweit nachgewiesenen Erdölreserven in den Jahren 1990 bis 2020 in Milliarden Tonnen. Zu den nachgewiesenen Erdölreserven zählen laut Quelle im Allgemeinen Mengen, die nach geologischen und ingenieurtechnischen Informationen aller Wahrscheinlichkeit nach aus den heute bekannten Vorkommen und unter den derzeitigen wirtschaftlichen und technischen Bedingungen künftig gefördert werden können. Die weltweiten Erdölreserven beliefen sich im Jahr 2020 auf rund 244,4 Milliarden Tonnen.Der BP Statistical Review of World Energy erschien erstmalig 1951. Er enthält Zahlen, Daten und Fakten über die weltweite Produktion und den Verbrauch von Öl, Gas, Kohle, Kern- und Wasserkraft und erneuerbaren Energien.