This dataset contains CO2 Emissions by sectors for 2020. Follow datasource.kapsarc.org for timely data to advance energy economics research. Notes:Note: The IEA Greenhouse gas emissions from energy product replaces the IEA CO2 emissions from fuel combustion product, with expanded content. Similarly, the Greenhuose gas emissions from energy highlights replaces the IEA CO2 emissions from fuel combustion highlights. This extract from the Greenhouse Gas Emissions from Energy 2022 database contains an extensive selection of GHG emissions data for over 190 countries and regions. Emissions data are based on the IEA World Energy Balances 2022 and on the 2006 IPCC Guidelines for Greenhouse Gas Inventories.

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.

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.

The EV-GHG Mobile Source Data asset contains measured mobile source GHG emissions summary compliance information on light-duty vehicles, by model, for certification as required by the 1990 Amendments to the Clean Air Act, and as driven by the 2010 Presidential Memorandum Regarding Fuel Efficiency and the 2005 Supreme Court ruling in Massachusetts v. EPA that supported the regulation of CO2 as a pollutant. Manufacturers submit data on an annual basis, or as needed to document vehicle model changes. This asset will be expanded to include medium and heavy duty vehicles in the future.The EPA performs targeted GHG emissions tests on approximately 15% of vehicles submitted for certification. Confirmatory data on vehicles is associated with its corresponding submission data to verify the accuracy of manufacturer submissions beyond standard business rules.Submitted data comes in XML format or as documents, with the majority of submissions sent in XML, and includes descriptive information on the vehicle itself, emissions information, and the manufacturer's testing approach. This data may contain proprietary information (CBI) such as information on estimated sales or other data elements indicated by the submitter as confidential. CBI data is not publically available; however, CBI data can accessed within EPA under the restrictions of the Office of Transportation and Air Quality (OTAQ) CBI policy [RCS Link]. Pollutants data includes CO2, CH4, N2O. Datasets are divided by vehicle/engine model and/or year with corresponding emission, test, and certification data. Data assets are stored in EPA's Verify system.Coverage began in 2011, with summary light duty data available to the public on request. Raw data is only available to select EPA employees.EV-GHG Mobile Source Data submission documents with metadata, certificate and summary decision information is stored in Verify after it has been quality assured. Where summary data appears inaccurate, OTAQ returns the entries for review to their originator.

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

Comprehensive dataset of 14000+ listed companies globally - covering developed, emerging and frontier markets and looks at GHG metrics (Scope 1, Scope 2 & Scope 3) from years 2016 - 2022

Our ESG Data is crawled from publicly available company disclosures using our cognitive search engine. The data undergoes validation by our team of expert analysts to identify, verify and document outliers. Following reprocessing and data appending, the data undergoes algorithmic assurance before final approval by team leads specializing in each area of impact. The combination of human and machine quality control delivers a high level of confidence in the accuracy of the data. Where unavailable, indicators are gap-filled using estimations based on ML models that provide outputs with higher correlation with actuals.

GIST’s GHG emissions data can be used to: - Measure carbon impacts of companies and portfolios - Benchmark companies within their sector - Benchmark a portfolio against indices - Screen companies for risk and opportunity - Integrate sustainability into portfolio decision-making

The data can also be used to augment sustainability disclosures, reporting and regulatory compliance.

GHG emissions consist of direct emissions (operations and factories - Scope 1) and indirect emissions (purchased energy - Scope 2, upstream and downstream emissions - scope 3)

The datasets comprise greenhouse gas (GHG) emission factors (Factors) for 1,016 U.S. commodities as defined by the 2017 version of the North American Industry Classification System (NAICS). The Factors are based on GHG data for 2022. Factors are given for all NAICS-defined commodities at the 6-digit level except for electricity, government, and households. Each record consists of three factor types as in the previous releases: Supply Chain Emissions without Margins (SEF), Margins of Supply Chain Emissions (MEF), and Supply Chain Emissions with Margins (SEF+MEF). One set of Factors provides kg carbon dioxide equivalents (CO2e) per 2022 U.S. dollar (USD) for all GHGs combined using 100-yr global warming potentials from IPCC 5th report (AR5) to calculate the equivalents. In this dataset there is one SEF, MEF and SEF+MEF per commodity. The other dataset of Factors provides kg of each unique GHG emitted per 2022 dollar per commodity without the CO2e calculation. The dollar in the denominator of all factors uses purchaser prices. See the supporting file 'Aboutv1.3SupplyChainGHGEmissionFactors.docx' for complete documentation of this dataset.

Annual country-level estimates for 66 countries for the three indicators are presented by industry for 45 industries, for the years 1995-2018.CO₂ emissions from fuel consumption are in millions of metric tons of CO₂.CO₂ emissions intensities are in metric tons of CO₂ emissions per $1 million USD of output.CO₂ emissions multipliers are in metric tons of CO₂ emissions per $1 million USD of output.Sources: OECD (2021), OECD Inter-Country Input-Output Database, https://oe.cd/icio; OECD (2021), Trade in embodied CO₂ (TeCO2) Database, https://www.oecd.org/sti/ind/carbondioxideemissionsembodiedininternationaltrade.htm; Organisation for Economic Co-operation and Development (OECD). 2021. Input-Output Tables (IOTs) (https://oe.cd/i-o).Category: Greenhouse Gas (GHG) EmissionsData series: CO2 emissionsCO2 emissions intensitiesCO2 emissions multipliersMetadata:Input-Output tables and Carbon Emissions for 66 Countries and 45 industries have been taken from the OECD’s compilation of indicators on “Carbon dioxide emissions embodied in international trade” (2021 ed.) which combines the Input-Output Database and Trade in embodied CO₂ (TeCO2) Database. In this release of TeCO2 sourced from OECD, emissions from fuels used for international aviation and maritime transport (i.e. aviation and marine bunkers) are also considered.The data series “CO₂ emissions, emission intensities; emission multipliers” was earlier referred to as “Carbon emissions from fuel combustion per unit of output” in the previous vintage of the Climate Change Indicator Dashboard.Methodology:CO₂ emission intensities are calculated by dividing the CO₂ emissions from fuel consumption by output from the OECD Inter-Country Input-Output (ICIO) Tables and multiplying the result by 1 million for scaling purposes. CO₂ emission multipliers are calculated by multiplying the Leontief inverse (also known as output multipliers matrix) from the OECD Inter-Country Input-Output (ICIO) Tables by the CO₂ emission intensities.Disclaimer:Users are encouraged to examine the documentation, metadata, and sources associated with the data. User feedback on the fit-for-use of this product and whether the various dimensions of the product are appropriate is welcome.Note on CO2 Emissions, Intensities, and Multipliers, June 2022Update of the CO₂ emissions by industry - April 2022

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.

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.

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.

United States US: CO2 Emissions data was reported at 5,254,279.285 kt in 2014. This records an increase from the previous number of 5,159,160.972 kt for 2013. United States US: CO2 Emissions data is updated yearly, averaging 4,823,403.118 kt from Dec 1960 (Median) to 2014, with 55 observations. The data reached an all-time high of 5,789,727.291 kt in 2005 and a record low of 2,880,505.507 kt in 1961. United States US: CO2 Emissions data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.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.; Gap-filled total;

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). 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 tabulated data from the figures and tables presented in Chapter 2, Livestock and Grazed Lands Emissions, of the report. This chapter covers carbon dioxide, methane, and nitrous oxide emissions and removals due to enteric fermentation, animal waste management, and land use for confined and grazed animals. Please refer to the report for full descriptions of and notes on the data. Resources in this dataset:Resource Title: Table 2-1. File Name: Table2_1.csvResource Description: Greenhouse Gas Emission Estimates and Uncertainty in the United States, 2018 for enteric fermentation, managed waste, grazed land, grazed land remaining grazed land, and land converted to grazed land, in MMT CO2 eq. Measured in Millions of Metric Tons, Carbon Dioxide Equivalent (MMT CO2 eq.) and also displayed in percentage units.Resource Title: Table 2-2. File Name: Table2_2.csvResource Description: Greenhouse Gas Emissions by Livestock Category and Source, 2018. For enteric fermentation, managed livestock waste, and grazed land, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent)Resource Title: Table 2-3. File Name: Table2_3.csvResource Description: Descriptions of livestock waste deposition and storage pathways.Resource Title: Table 2-4. File Name: Table2_4.csvResource Description: Methane emissions from enteric fermentation, 1990-2018, from beef cattle, dairy cattle, sheep, poultry, swine, horses, goats, American bison, and mules and asses in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent)Resource Title: Table 2-5. File Name: Table2_5.csvResource Description: Greenhouse Gas Emissions from Managed Livestock Waste in 1990, 1995, 2000, 2005, 2010-2018. In MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Table 2-6. File Name: Table2_6.csvResource Description: Greenhouse Gas Emissions from Grazed Lands in 1990, 1995, 2000, 2005, 2010-2018, for nitrous oxide and methane, presented in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Data for Figure 2-1. File Name: Figure2_1.csvResource Description: Greenhouse Gas Emissions from Livestock, 2018. MMT CO2 eq. emissions from beef cattle, dairy cattle, sheep, poultry, swine, horses, goats, bison, and mules. Measured in Millions of Metric Tons, Carbon Dioxide Equivalent (MMT CO2 eq.) and also displayed in percentage units.Resource Title: Data for Figure 2-2. File Name: Figure2_2.csvResource Description: Greenhouse Gas Emissions from Managed Livestock Waste by Livestock Type, 2018. MMT CO2 eq. emissions from beef cattle, dairy cattle, sheep, poultry, swine, horses, goats, bison, and mules. Measured in Millions of Metric Tons, Carbon Dioxide Equivalent (MMT CO2 eq.) and also displayed in percentage units.Resource Title: Data for Figure 2-3. File Name: Figure2_3.csvResource Description: Greenhouse Gas Emission from Managed Livestock Waste, 1990-2018. MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent) for N2O and CH4.Resource Title: Data for Figure 2-4. File Name: Figure2_4.csvResource Description: Estimated Reductions in Methane Emissions from Anaerobic Digesters, 2000-2018 in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Data for Map 2-1. File Name: Map2_1.csvResource Description: GHG Emission from Livestock Production in 2018, by U.S. State, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent)Resource Title: Data for Map 2-2. File Name: Map2_2.csvResource Description: Map 2-2 Methane Emissions from Enteric Fermentation in 2018, by U.S. State, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Data for Map 2-3. File Name: Map2_3.csvResource Description: GHG Emission from Managed Livestock Waste in 2018, by U.S. State, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Chapter 2 Appendix Tables. File Name: Chapter2_Appendix_Tables.xlsxResource Description: Chapter 2 includes 27 appendix tables, that include data on, inter alia, the population of animals by state, emission factors for livestock, state level GHG emissions from enteric fermentation, state level methane and nitrous oxide emissions from managed manure, and state volatile solids production rates for 2018.Resource Title: Figures, maps, tables and appendices from Chapter 2. File Name: Chapter 2 Data.zip

This offer includes high-precision, carbon emission-focused LCA datasets covering Materials, Production (Processes and Machines), and Energy, enabling companies to conduct accurate Product Carbon Footprint (PCF) calculations. The data is region-specific, updated bi-annually, and aligned with ISO 14067 and GHG Protocol standards. Customers can access the datasets via API, CSV files, or the sustamize Data Platform, ensuring seamless integration into LCA tools, PLM systems, and sustainability reporting workflows. By utilizing these comprehensive CO₂ datasets, businesses can enhance supply chain transparency, improve Scope 3 emissions tracking, and ensure compliance with global sustainability regulations. Please refer to: https://docs.sustamizer.com/knowledge-hub/database-overview/overview for more info.

The dataset provides the statistics on Greenhouse Gas Emissions and Carbon Intensity in Hong Kong.

Monthly average hourly CO2, NOx, and SO2 emission factors for each U.S. eGRID subregion. This project utilized GridViewTM, an electric grid dispatch software package, to estimate hourly emission factors for all of the eGRID subregions in the continental United States. These factors took into account electricity imports and exports across the eGRID subregion boundary, and included estimated transmission and distribution (T) losses. Emission types accounted for included carbon dioxide (CO2), nitrogen oxides (NOx), and sulfur dioxide (SO2).Data reported as part of this project include hourly average, minimum, and maximum emission factors by month; that is, the average, minimum, and maximum emission factor for the same hour of each day in a month. Please note that the data are reported in lbs/MWh, where the MWh value reported is site electricity use (the actual electricity used at the building) and the pounds of emissions reported are the emissions created at the generator to meet the building load, including transmission and distribution losses. The demand profiles used to generate the data pertain to the following years: eastern interconnect - 2005; Electricity Reliability Council of Texas (ERCOT) - 2008; Western Electricity Coordinating Council (WECC) - 2008.

In response to global climate change, strengthening control of greenhouse gas emissions has become an international trend. In order to implement various actions to promote energy conservation and reduce greenhouse gas emissions in the transportation sector, it is necessary to establish a complete database and estimation model for vehicle energy consumption rates and emission factors for road transportation. This dataset provides energy consumption/CO2 emission rates of motorcycles on different road types in our country, and users can choose the appropriate data for their own purposes.

Thailand Carbon Dioxide Emission data was reported at 247,841.660 Ton th in 2024. This records an increase from the previous number of 243,291.350 Ton th for 2023. Thailand Carbon Dioxide Emission data is updated yearly, averaging 192,904.435 Ton th from Dec 1987 (Median) to 2024, with 38 observations. The data reached an all-time high of 263,433.860 Ton th in 2018 and a record low of 49,842.330 Ton th in 1987. Thailand Carbon Dioxide Emission data remains active status in CEIC and is reported by Energy Policy and Planning Office, Ministry of Energy. The data is categorized under Global Database’s Thailand – Table TH.RB020: Carbon Dioxide Emissions Statistics.

The Ministry of the Environment, Conservation and Parks collects greenhouse gas emissions data from regulated facilities under Ontario Regulation 390/18: Greenhouse Gas Emissions: Quantification, Reporting and Verification using the quantification methods in the incorporated Guideline for Quantification, Reporting and Verification of Greenhouse Gas Emissions.

The emissions reports serve as a baseline for the ministry and interested parties to understand emissions profiles and are a valuable tool for reporters to manage and reduce their greenhouse gas emissions. For information on Ontario’s Greenhouse Gas Reporting Program please visit our program webpage.