Global carbon dioxide emissions from fossil fuels and industry totaled 37.01 billion metric tons (GtCO₂) in 2023. Emissions are projected to have risen 1.08 percent in 2024 to reach a record high of 37.41 GtCO₂. Since 1990, global CO₂ emissions have increased by more than 60 percent. Who are the biggest emitters? The biggest contributor to global GHG emissions is China, followed by the United States. China wasn't always the world's biggest emitter, but rapid economic growth and industrialization in recent decades have seen emissions there soar. Since 1990, CO₂ emissions in China have increased by almost 450 percent. By comparison, U.S. CO₂ emissions have fallen by 6.1 percent. Nevertheless, the North American country remains the biggest carbon polluter in history. Global events cause emissions to drop The outbreak of COVID-19 caused global CO₂ emissions to plummet some 5.5 percent in 2020 as a result of lockdowns and other restrictions. However, this wasn't the only time in recent history when a major global event caused emissions reductions. For example, the global recession resulted in CO₂ levels to fall by almost two percent in 2009, while the recession in the early 1980s also had a notable impact on emissions. On a percentage basis, the largest annual reduction was at the end of the Second World War in 1945, when emissions decreased by 17 percent.

Consumption-based accounting (CBA) of emissions (also called carbon footprints calculated using MRIO methods) accounts for emissions associated with imported and exported goods. CBA reports the total emissions associated with final demand in each country.

Emissions physically occurring in a country are its territorial emissions. This is sometimes called production-based accounting (PBA). This is the standard reporting of GHG emissions as reported by CDIAC, IEA, the JRC EDGAR database, UNFCCC, and others.

CBA can be calculated using a global multi-region input-output (MRIO) model which traces global supply chains. This dataset uses the Eora MRIO model to calculate the CBA emissions for each country.

Emissions from fossil fuel combustion and cement production are reattributed to the countries where final demand induced the production associated with those emissions. Emissions from aviation and marine bunker fuels are not included in the CBA inventory, as no method has yet been developed to allocate emissions from bunker fuels to countries other than where the fuel is bunkered.

In this dataset, territorial emissions are taken from the PRIMAP emissions database using the HISTCR scenario. Population and GDP data are from the World Bank. CBA results are from the Eora MRIO model (https://worldmrio.com) v199.82, years 1990-2018, by Daniel Moran, Keiichiro Kanemoto, and Arne Geschke.

This dataset represents the annual greenhouse gas emissions produced by the City of Boston from 2005 to 2021. The annual inventory is based on a combination of direct data and estimates for data that cannot be obtained directly. Data sources vary, and include City records, utility company reports, and information from state and federal agencies. Reporting is separated into community-wide and local government operations inventories. Because the data for these inventories is collected using separate protocols on separate timescales, the Local Government Operations Inventory should be considered to be overlapping, but not completely contained within the Citywide Inventory.

You can view the inventory report on the City's main website.

Note: We reviewed our community methodology and updated emissions data across the 2005-2021 period accordingly. Please contact environment@boston.gov if you would like to access past datasets or discuss the methodology.

Energy consumption in the United States produced 4.8 billion metric tons of carbon dioxide (GtCO₂) in 2024 - a decrease of 0.4 percent from the previous year. U.S. CO₂ emissions from energy consumption have fallen by approximately 20 percent since 2005. Sources of emissions in the U.S. The main source of CO₂ emissions in the U.S. is the transportation sector. For many years, the power sector was the country’s biggest contributor to CO₂ emissions, but the transition towards cleaner energy sources and a shift away from coal-fired power generation – the most carbon intensive fossil fuel – have slashed emissions from this sector. Meanwhile, transportation emissions have continued to rise, except for an unprecedented drop in 2020 due to the outbreak of COVID-19. U.S. transportation emissions The U.S. is the biggest contributor to global transportation emissions by far. The states with the largest transportation-related emissions in the U.S. are Texas and California, which combined account for almost one quarter of total U.S. transportation emissions.

Sources: OECD (2021), OECD Inter-Country Input-Output Database, https://oe.cd/icio; International Monetary Fund (IMF), Statistics Department Questionnaire; IMF staff calculations.Category: Climate FinanceData series:Carbon Footprint of Bank Loans (Based on emission intensities)Carbon Footprint of Bank Loans (Based on emission intensities - normalized)Carbon Footprint of Bank Loans (Based on emission multipliers)Carbon Footprint of Bank Loans (Based on emission multipliers - normalized)Metadata:For relevant literature see Guan, Rong, Haitao Zheng, Jie Hu, Qi Fang, and Ruoen Ren. 2017. “The Higher Carbon Intensity of Loans, the Higher Non-Performing Loan Ratio: The Case of China.” Sustainability 9 (4) (April 22): 667. https://dx.doi.org/10.3390/su9040667.Methodology:The IMF has developed the Carbon Footprint of Bank Loans (CFBL) indicator for selected countries. CFBL indicator requires (i) deposit takers’ domestic loans by industry data, and (ii) the estimation of carbon emission factors (CEFs) by industry.The IMF has conducted a data collection exercise to obtain deposit takers’ domestic loans by industry data. The CEFs are calculated based on (i) direct metric tons of carbon emissions from fuel consumption per million $US of output by country and industry (CO2 emission intensities), and (ii) direct and indirect carbon emissions from fuel consumption per million $US of output by country (CO2 emission multipliers). The output multipliers and carbon emission intensities for 66 countries and 45 industries are sourced from the OECD Input-Output Database. Direct and indirect carbon emission factors are calculated by multiplying the Leontief inverse (also known as input-output multipliers) from the OECD World Input-Output Table by the carbon emissions from fuel consumption intensities.CFBL indicator is obtained by multiplying domestic loans to a specific industry by their corresponding carbon emission factors, summing over all industries and dividing the final result by total domestic loans. For a limited number of countries, updated CFBL information until 2018 will be posted in due course. CFBL is an experimental indicator. The index requires a nuanced reading. For instance, a sharp increase in the share of a brown industry in the deposit takers’ loans portfolio may create a negative impact on this indicator in the short term, but longer term results could diverge significantly if these loans were allocated for transition to low carbon environment or for continuing unsustainable brown activities. The emission coefficients applied to loans related to the emissions of the industry and not the emissions resulting from the consumption of the goods the industry produces. Also, the estimation methodology has a number of limitations. First, class level ISIC data could be more appropriate for the CFBL estimation, as it offers more detailed information to evaluate carbon footprint by industry. However, carbon emission factors are not available at this granularity. Also, the ISIC structure is not fully aligned with the needs of climate finance.Second, the granularity of the deposit takers’ domestic loans by industry data availability is not fully consistent across jurisdictions. It is not possible to obtain the loans by industry data at the same level of granularity from all participating countries. Third, the country coverage is limited as carbon intensity factors are available for only 66 countries. Fourth, input-output multipliers have limiting assumptions. Input-output multipliers are static (i.e., assume that there is a fixed input structure and fixed ratios for production for each industry) and do not take into account supply-side constraints or budget constraints. Please see additional information in this link.

This dataset contains IoT-based data designed to track and analyze the carbon footprint of individuals, based on various factors such as energy consumption, transportation activity, and environmental conditions. The dataset includes 10,000 entries, each representing an individual, with the following features:

Person_ID: A unique identifier for each individual (from 1 to 10,000). Energy_Usage_kWh: The total daily energy consumption in kilowatt-hours, tracked via smart meters. Values range from 2 to 50 kWh. Transportation_Distance_km: The total daily distance traveled by the individual in kilometers, tracked via GPS. Values range from 0 to 100 km. Vehicle_Type: The mode of transportation used by the individual, with possible values: "Car", "Bus", "Walking", and "Electric Vehicle." (Note: "Bike" has been excluded). Smart_Appliance_Usage_hours: The daily usage (in hours) of smart appliances within the home, ranging from 1 to 12 hours. Renewable_Energy_Usage_percent: The percentage of energy usage that comes from renewable sources, ranging from 0% to 100%. Building_Type: The type of building where the individual resides, with possible values: "Residential" and "Commercial." Temperature_C: The ambient temperature in Celsius, tracked by smart thermostats or weather stations, ranging from -10°C to 40°C. Humidity_percent: The percentage of humidity, tracked by IoT humidity sensors, with values ranging from 20% to 90%. Carbon_Emission_kgCO2: The estimated carbon emissions (in kilograms of CO₂) resulting from the individual's energy usage and transportation activities

Greenhouse gas inventory for City of Austin municipal operations reflected as the number of metric tons of carbon dioxide-equivalent emissions. The data comes from various sources of activity data (gallons of fuel, ccf of natural gas) used in city operations. It can be used to assess how city operations affect climate change. Date of Last Description Update: 3/13/2020

The average American was responsible for emitting 13.8 metric tons of carbon dioxide (tCO₂) in 2023. U.S. per capita fossil CO₂ emissions have fallen by more than 30 percent since 1990. Global per capita emission comparisons Despite per capita emissions in the U.S. falling notably in recent decades, they remain roughly three times above global average per capita CO₂ emissions. In fact, the average American emits more CO₂ in one day than the average Somalian does throughout the entire year. Additionally, while China is now the world’s biggest emitter, the average Chinese citizen’s annual carbon footprint is roughly half the average American’s. Which U.S. state has the largest carbon footprint? Per capita energy-related CO₂ emissions in the U.S. vary greatly by state. Wyoming was the biggest CO₂ emitter per capita in 2022, with 97 tCO₂ per person. The least-populated state’s high per capita emissions are mainly due to its heavily polluting coal industry. In contrast, New Yorkers had the one of the smallest carbon footprints in 2022, at less than nine tCO₂ per person.

Graph and download economic data for Total Carbon Dioxide Emissions From All Sectors, All Fuels for Florida (EMISSCO2TOTVTTTOFLA) from 1970 to 2021 about carbon dioxide emissions, fuels, sector, FL, and USA.

The emissions of carbon dioxide, methane, nitrous oxide, hydro-fluorocarbons, perfluorocarbons, sulphur hexafluoride, nitrogen trifluoride and total greenhouse gas emissions, by industry (SIC 2007 group – around 130 categories), UK, 1990 to 2023.

Stabilizing greenhouse gas (GHG) emissions from croplands as agricultural demand grows is a critical component of climate change mitigation. Emissions intensity metrics—including carbon dioxide equivalent emissions per kilocalorie produced ('production intensity') -- can highlight regions, management practices, and crops as potential foci for mitigation. Yet the spatial and crop-wise distribution of emissions intensity has been uncertain. Here, we develop global crop-specific circa 2000 estimates of GHG emissions and GHG intensity in high spatial detail, reporting the effects of rice paddy management, peatland draining, and nitrogen (N) fertilizer on CH4, CO2 and N2O emissions. Global mean production intensity is 0.16 Mg CO2e M kcal-1, yet certain cropping practices contribute disproportionately to emissions. Peatland drainage (3.7 Mg CO2e M kcal-1) -- concentrated in Europe and Indonesia—accounts for 32% of these cropland emissions despite peatlands producing just 1.1% of total crop kilocalories. Methane emissions from rice (0.58 Mg CO2e M kcal-1), a crucial food staple supplying 15% of total crop kilocalories, contribute 48% of cropland emissions, with outsized production intensity in Vietnam. In contrast, N2O emissions from N fertilizer application (0.033 Mg CO2e M kcal-1) generate only 20% of cropland emissions. We find that current total GHG emissions are largely unrelated to production intensity across crops and countries. Climate mitigation policies should therefore be directed to locations where crops have both high emissions and high intensities. This download provides three datasets aggregated from the original output of the 172 crops; total emissions from croplands, per kilocalorie emissions from croplands and per food kilocalorie emissions from cropland. Downloads are available in Geotiff (.tif), NetCDF (.nc), or Google Earth (.kmz) formats. Funded by USDA Agriculture and Food Research Initiative fellowship 2016-67012-25208 and NIFA Hatch project HAW01136-H. Resources in this dataset:Resource Title: EarthStat Data Download. File Name: Web Page, url: http://www.earthstat.org/data-download/ This download provides three datasets aggregated from the original output of the 172 crops; total emissions from croplands, per kilocalorie emissions from croplands and per food kilocalorie emissions from cropland. Downloads are available in Geotiff (.tif), NetCDF (.nc), or Google Earth (.kmz) formats.

This offer includes high-precision, carbon emission-focused LCA datasets covering a wide range of industry materials, including alloys, minerals, polymers, composites, construction materials, and sinters. These datasets provide detailed CO₂ emission factors for material extraction, processing, and lifecycle emissions, allowing companies to accurately calculate Product Carbon Footprints (PCF) and optimize material selection.

The data is region-specific, ensuring that businesses can assess the environmental impact of materials based on country-specific energy mixes and industrial practices. This level of granularity is essential for companies seeking to compare materials across different suppliers and minimize their carbon footprint while maintaining cost efficiency.

Updated bi-annually, these datasets align with ISO 14067, GHG Protocol standards and Catena-X requirements, ensuring regulatory compliance for Scope 3 emissions tracking and sustainability reporting.

Customers can access the data via API, CSV files, or the sustamize Data Platform, allowing seamless integration into LCA tools, PLM systems, and procurement workflows. By leveraging these comprehensive datasets, companies can enhance supply chain transparency, make informed sourcing decisions, and ensure compliance with global sustainability regulations.

Please refer to: https://docs.sustamizer.com/knowledge-hub/database-overview/materials for more info.

This CO2 and Greenhouse Gas Emissions dataset is a collection of key metrics maintained by Our World in Data. It is updated regularly and includes data on CO2 emissions (annual, per capita, cumulative and consumption-based), other greenhouse gases, energy mix, and other relevant metrics.

For further details, please refer to https://github.com/owid/co2-data

Greenhouse gas emissions (carbon dioxide equivalents), by industries and households. Industry aggregation is at the L-level of the input-output accounts of Statistics Canada.

The primary greenhouse gas (GHG) sources for agriculture are nitrous oxide (N2O) emissions from cropped and grazed soils, methane (CH4) emissions from ruminant livestock production and rice cultivation, and CH4 and N2O emissions from managed livestock waste. The management of cropped, grazed, and forestland has helped offset GHG emissions by promoting the biological uptake of carbon dioxide (CO2) through the incorporation of carbon into biomass, wood products, and soils, yielding a U.S. net emissions of 5,903 MMT CO2 eq (million metric tonnes of carbon dioxide equivalents) in 2018. Net emissions equate to total greenhouse gas emissions minus CO2 sequestration in growing forests, wood products, and soils. The report 'U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018' serves to estimate U.S. GHG emissions for the agricultural sector, to quantify uncertainty in emission estimates, and to estimate the potential of agriculture to mitigate U.S. GHG emissions. This dataset contains zipped, tabulated data from the figures and tables, and maps of the entire report. Data are presented for Cropland Soils (N2O), Enteric Fermentation (CH4), Managed Livestock Waste (CH4 + N2O), Grazed Lands (CH4 + N2O), Rice Cultivation + Residue Burning (CH4 + N2O), Energy Use, Forests, Harvested Wood, Urban Trees, and Agricultural Soils. Please refer to the report for full descriptions of and notes on the data. Resources in this dataset:Resource Title: Chapter 2 Data. File Name: Chapter 2 Data.zipResource Description: This zip file contains data from all figures, maps, tables, and appendices from Chapter 2 (livestock and grazing) for the U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018. Resource Title: Chapter 4 Data. File Name: Chapter 4 data.zipResource Description: This zip file contains data from all figures, tables, and appendices from Chapter 4 (forests) for the U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018.Resource Title: Chapter 3 Data. File Name: Chapter 3 Data.zipResource Description: This zip file contains data from all figures, maps, tables, and appendices from Chapter 3 (cropland) for the U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018.Resource Title: Chapter 5 Data. File Name: Chapter 5 data.zipResource Description: This zip file contains data from all figures and tables from Chapter 5 (energy) for the U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018.Resource Title: Chapter 1 Data. File Name: Chapter 1 Data.zipResource Description: This zip file contains data from all figures and tables from Chapter 1 for the U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018.

Graph and download economic data for Total Carbon Dioxide Emissions From All Sectors, All Fuels for California (EMISSCO2TOTVTTTOCAA) from 1970 to 2021 about carbon dioxide emissions, fuels, sector, CA, and USA.