Qatar had the highest per capita carbon dioxide emissions worldwide in 2023, at 42.6 metric tons per person. Per capita emissions in Qatar have remained relatively stable in recent years, but have fallen notably since the mid-2000s.In 1985, the tiny Dutch Caribbean island of Curaçao had the highest CO₂ emissions per capita in the world, at 90 metric tons, but by 2020, this figure had fallen to just 10 metric tons per person. Greenhouse gas emissions worldwide Several of the Middle East’s largest oil producing countries, including Qatar, the United Arab Emirates, and Saudi Arabia, are among the world’s largest per capita CO₂ emitters. Per capita emissions in Saudi Arabia have experienced a growth of roughly 75 percent since 1990. Canada is another major oil producing country with high CO₂ emissions per capita. Rising emissions Global greenhouse gas emissions have been on the rise since the industrial revolution began approximately 200 years ago. However, over the past 50 years CO₂ emissions have skyrocketed, and are projected to have reached a new record high in 2024.

Over the past two decades, many developing countries have experienced significant growth in per capita emissions. This is particularly the case in Asia. Fueled by rapid industrialization, per capita emissions in Vietnam have increased by almost 400 percent since 2000. Per capita emissions in China, India, and Indonesia have also increased substantially during this period. In comparison, per capita emissions in developed countries such as the United Kingdom have halved since 2000. Per capita emissions The growth in per capita emissions in China has coincided with the country becoming the world’s biggest emitter. However, despite the vast amounts of carbon dioxide China releases every year, its per capita emissions are far lower than in many other countries, at just eight metric tons per person. In comparison, the average American produces nearly 15 metric tons of carbon dioxide a year. This is three times higher than the average per capita emissions worldwide. Emissions in oil producing countries Per capita emissions are noticeably higher in oil producing countries. In the Middle East region, Qatar and Kuwait average more than 25 metric tons of CO₂ per inhabitant. People in more populous oil producing countries, such as Canada and Australia, average roughly 15 metric tons of carbon dioxide a year.

Saudi Arabia is the largest per capita emitter of fossil carbon dioxide (CO₂) among G20 countries. In 2023, emissions in the Middle Eastern country amounted to just over 17 metric tons per person (tCO₂/cap). Meanwhile, India had the lowest per capita CO₂ emissions, at around 2.1 tCO₂/cap.

Population vs emissions Despite being the most populated G20 country, India has the lowest per capita CO₂ emissions of them all. This is mainly due to India’s economy being largely agrarian. Additionally, per capita energy consumption in the South Asian country is relatively low compared to many developed nations. On the other hand, Canada, which has a small population size of roughly 38 million, had the second-largest emissions per capita in the G20. The North American country’s oil and gas industry is a key factor for this. Emissions from oil and gas production Other major oil and gas producers, such as Saudi Arabia, the U.S., and Russia, are also among the biggest per capita emitters globally. Russia alone accounted for nearly a quarter of global GHG emissions from oil and gas production in 2022, while the U.S. contributed almost 20 percent.

Qatar has the highest per capita carbon dioxide emissions worldwide, at 42.6 metric tons per person. Many countries in the Middle East had high levels emissions, especially when compared to countries in Africa. Greenhouse gas emissions worldwide Some of the Middle East’s largest oil producing countries, including Qatar, the United Arab Emirates, and Saudi Arabia are among the world’s largest carbon dioxide (CO₂) emitters per capita. Countries such as the United States, Australia and Canada also show disproportionately high levels of emission per inhabitant. Despite a relatively low population for its size, Canada’s CO₂ emissions have recently surpassed 500 million metric tons, and the country is now amongst the largest producers of CO₂ emissions worldwide. Rising emissions Global greenhouse gas emissions have been on the rise since the industrial revolution began approximately 200 years ago. Over the past half-century CO₂ emissions have skyrocketed, and climbed to a record high in recent years. Yet, emissions fell considerably in 2020 as a result of the COVID-19 pandemic, which caused disruptions to transportation and industrial activities.

The average for 2020 based on 27 countries was 5.54 metric tons. The highest value was in Luxembourg: 12.46 metric tons and the lowest value was in Malta: 3.13 metric tons. The indicator is available from 1990 to 2020. Below is a chart for all countries where data are available.

Global per capita carbon dioxide emissions averaged 4.7 metric tons in 2023. This represented a slight increase in comparison to the previous year. Qatar has the largest per capita CO₂ emissions worldwide, at more than 37 metric tons per person.

Kenya KE: CO2 Emissions: Metric Tons per Capita data was reported at 0.310 Metric Ton in 2014. This records an increase from the previous number of 0.297 Metric Ton for 2013. Kenya KE: CO2 Emissions: Metric Tons per Capita data is updated yearly, averaging 0.287 Metric Ton from Dec 1960 (Median) to 2014, with 55 observations. The data reached an all-time high of 0.386 Metric Ton in 1981 and a record low of 0.192 Metric Ton in 1985. Kenya KE: CO2 Emissions: Metric Tons per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Environment: Pollution. Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.; ; Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, Tennessee, United States.; Weighted average;

Angola AO: CO2 Emissions: Metric Tons per Capita data was reported at 0.593 Metric Ton in 2020. This records a decrease from the previous number of 0.754 Metric Ton for 2019. Angola AO: CO2 Emissions: Metric Tons per Capita data is updated yearly, averaging 0.925 Metric Ton from Dec 1990 (Median) to 2020, with 31 observations. The data reached an all-time high of 1.125 Metric Ton in 2015 and a record low of 0.544 Metric Ton in 1992. Angola AO: CO2 Emissions: Metric Tons per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Angola – Table AO.World Bank.WDI: Environmental: Gas Emissions and Air Pollution. Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.;Emissions data are sourced from Climate Watch Historical GHG Emissions (1990-2020). 2023. Washington, DC: World Resources Institute. Available online at: https://www.climatewatchdata.org/ghg-emissions;Weighted average;

PerCapita_CO2_Footprint_InDioceses_FULLBurhans, Molly A., Cheney, David M., Gerlt, R.. . “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.MethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

Libya was the largest polluter in Africa in 2021. That year, carbon dioxide (CO2) emissions in the country reached over 11 metric tons per capita. South Africa and Seychelles followed, emitting around 7.3 and 5.3 metric tons of CO2 per capita, respectively. In addition, Africa's average stood at roughly one metric ton per capita. In absolute terms, South Africa and Egypt produced the most emissions in Africa in 2021.

The aim of the Greenhouse Gas Inventory is to provide information about greenhouse gas emissions in the Basque Country with a view to keeping track of progress made in reaching the targets set in the 2050 Climate Change Strategy of the Basque Country. More information in the https://www.euskadi.eus/web01-s2ekono/es/contenidos/informacion/estatistika_ing_090205/es_def/index.shtml departmental statistical portal.

The CAIT Country GHG emissions collection applies a consistent methodology to create a six-gas, multi-sector, and internationally comparable data set for 186 countries.

CAIT enables data analysis by allowing users to quickly narrow down by year, gas, country/state, and sector. Automatic calculations for percent changes from prior year, per capita, and per GDP are also available. Users are presented with clear and customizable data visualizations that can be readily shared through unique URLs or embedded for further use online.

Data for Land-Use and Forestry indicator are provided by the Food and Agriculture Organization of the United Nations (FAO). WRI has been granted a non-exclusive, non-transferrable right to publish these data. Therefore, if users wish to republish this dataset in whole or in part, they should contact FAO directly at copyright@fao.org

Data sources: - Boden, T.A., G. Marland, and R.J. Andres. 2015. Global, Regional, and National Fossil-Fuel CO2 Emissions. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. doi 10.3334/CDIAC/00001_V2015 Available online at:http://cdiac.ornl.gov/trends/emis/overview_2011.html . - Food and Agriculture Organization of the United Nations (FAO). 2014. FAOSTAT Emissions Database. Rome, Italy: FAO. Available at: http://faostat3.fao.org/download/G1/*/E - International Energy Agency (IEA). 2014. CO2 Emissions from Fuel Combustion (2014 edition). Paris, France: OECD/IEA. Available online at:http://data.iea.org/ieastore/statslisting.asp. © OECD/IEA, [2014]. - World Bank. 2014. World Development Indicators 2014. Washington, DC. Available at: http://data.worldbank.org/ Last Accessed May 18th, 2015 - U.S. Energy Information Administration (EIA). 2014. International Energy Statistics Washington, DC: U.S. Department of Energy. Available online at:http://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=90&pid=44&aid=8 - U.S. Environmental Protection Agency (EPA). 2012. “Global Non-CO2 GHG Emissions: 1990-2030.” Washington, DC: EPA. Available at: http://www.epa.gov/climatechange/EPAactivities/economics/nonco2projections.html.

This dataset offers detailed insights into CO2 emissions by country (2022), focusing on per capita trends from 1991 to 2022 across major global economies. It highlights significant reductions in the United States, where emissions dropped from 21.28 tons per capita in 2000 to 14.93 tons by 2022, driven by increased energy efficiency, renewable energy adoption, and a transition from coal to natural gas. Canada’s stable emissions (16-18 tons) reflect its energy-intensive industries and cold climate. China's dramatic increase in CO2 emissions per capita by country (2023) stands out, with a rise from 2.23 tons in 1991 to 7.95 tons by 2022, driven by rapid industrialization. European nations, including Germany and France, exhibit declining trends due to aggressive climate policies and renewable energy advancements, visible in the CO2 emissions per capita by country (2023) graph. Japan shows stable emissions (9-10 tons), balancing energy efficiency with nuclear power challenges. The dataset also tracks low but rising emissions in India (0.69 to 1.9 tons) and Brazil (1.5 to 2.32 tons), reflecting economic growth and sustainable practices. This resource is invaluable for analyzing per capita CO2 emissions (2023) trends, supporting climate policy development, and creating visual comparisons for global emissions data.

France FR: CO2 Emissions: Metric Tons per Capita data was reported at 4.573 Metric Ton in 2014. This records a decrease from the previous number of 5.062 Metric Ton for 2013. France FR: CO2 Emissions: Metric Tons per Capita data is updated yearly, averaging 6.436 Metric Ton from Dec 1960 (Median) to 2014, with 55 observations. The data reached an all-time high of 9.667 Metric Ton in 1973 and a record low of 4.573 Metric Ton in 2014. France FR: CO2 Emissions: Metric Tons per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank: Environment: Pollution. Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.; ; Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, Tennessee, United States.; Weighted Average;

The United States has one of the highest road transportation emissions per capita worldwide. The average American emitted roughly 4,500 kilograms of CO2 from road transport in 2018, which was slightly more than in neighboring Canada. The U.S. emits the largest volume of CO2 emissions from road transportation worldwide, followed by China. However, China's emissions per capita are considerably lower than in the U.S.. Low income countries, such as those is South Asia and Africa, have far lower road transportation emissions per capita than in higher income countries. For example, per capita road transportation emissions in Eritrea averaged 63 kg CO2/capita in 2018. This was approximately 70 times less than the per capita emissions in the U.S..

CO2 emissions per capita of Maine slumped by 5.64% from 0.012 metric tones of carbon in 2016 to 0.012 metric tones of carbon in 2017. Since the 1.43% climb in 2015, CO2 emissions per capita dropped by 8.10% in 2017. A ratio of annual fossil-fuel CO2 emitted to population.

This dataset is about countries in San Marino per year, featuring 4 columns: carbon dioxide emissions (CO2), country, date, and health expenditure per capita. The preview is ordered by date (descending).

Indonesia Production Based Emissions of CO2 per Capita: Gas data was reported at 0.271 Tonne in 2021. This records a decrease from the previous number of 0.276 Tonne for 2020. Indonesia Production Based Emissions of CO2 per Capita: Gas data is updated yearly, averaging 0.030 Tonne from Dec 1889 (Median) to 2021, with 133 observations. The data reached an all-time high of 0.401 Tonne in 1997 and a record low of 0.000 Tonne in 1946. Indonesia Production Based Emissions of CO2 per Capita: Gas data remains active status in CEIC and is reported by Our World in Data. The data is categorized under Global Database’s Indonesia – Table ID.OWID.ESG: Environmental: CO2 and Greenhouse Gas Emissions: Annual.

Monaco CO2 Emissions: Tonnes of CO2 Equivalent per Capita per Year data was reported at 4.253 Tonne in 2023. This records a decrease from the previous number of 4.691 Tonne for 2022. Monaco CO2 Emissions: Tonnes of CO2 Equivalent per Capita per Year data is updated yearly, averaging 6.697 Tonne from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 10.261 Tonne in 1973 and a record low of 4.253 Tonne in 2023. Monaco CO2 Emissions: Tonnes of CO2 Equivalent per Capita per Year data remains active status in CEIC and is reported by European Commission’s Directorate-General for Joint Research Centre. The data is categorized under Global Database’s Monaco – Table MC.DG JRC.EDGAR: Environmental: Greenhouse Gas Emissions: CO2 Emissions: Annual. The data is combination of France and Monaco.

This dataset is about countries in Myanmar per year, featuring 4 columns: carbon dioxide emissions (CO2), country, date, and health expenditure per capita. The preview is ordered by date (descending).