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15 results for “Fossil CO2”

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zenodo52/100

CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil and biofuel CO2 emission inventories

<p>CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories of anthropogenic CO2 emissions developed in the framework of the CoCO2 project (<a href="https://coco2-project.eu/">https://coco2-project.eu/</a>). CoCO2-MOSAIC 1.0 provides gridded (0.1˚&times;0.1˚) monthly emissions fluxes of CO2 fossil fuel (CO2ff, long cycle) and CO2 biofuel (CO2bf, short cycle) for the years 2015 to 2018 disaggregated in seven sectors: energy_s (super-emitting sources above 7.9e-6 kg/m2/s), energy_a (average emitters), manufacturing, settlements, transport, aviation land/take-off (LTO) and other. The regional inventories included are CAMS-GHG-REG 5.1 (Europe), DACCIWA 2.0 (Africa), GEAA-AEI 3.0 (Argentina), INEMA 1.0 (Chile), REAS 3.2.1 (South-East Asia) and VULCAN 3.0 (USA). EDGAR 6.0 and CAMS-GLOB-SHIP 3.1 are used for gap-filling missing sectors and regions. CAMS-GLOB-TEMPO 3.1 is used for temporal disaggregation of inventories providing annual emissions. Aviation emissions from climb, descent, and cruise are not covered by regional inventories and are provided as a separate file. Note that 2015 is the only year when all regional inventories are simultaneously available. &nbsp;</p> <p>Compared to global inventories, CoCO2-MOSAIC 1.0 includes all the regional information available without the limitation of providing spatially consistent emissions. Therefore, CoCO2-MOSAIC 1.0 can be used as a global baseline inventory due to the higher level of detail, higher spatial resolution, and country-specific information included by regional inventories.&nbsp;</p> <p>For further details see Urraca et al. 2023 (ESSD submitted). The paper (i) describes the CoCO2-MOSAIC methodology and (ii) uses the mosaic to inter-compare the most widely used global inventories: CAMS-GLOB-ANT 5.3, EDGAR 6.0/7.0, ODIAC v2020b, and CEDS v2020_04_24.</p>

opencc-by-4.0Apr 2023View details →
zenodo48/100

Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories

<p><strong>Data Access Notice</strong></p> <p>Please note that, at present, the data for a sample of years are provided in this data record due to Zenodo's 50GB data limit. Data for all years 1959-2023 can be accessed via the following link:</p> <p><a href="http://opendap.uea.ac.uk/opendap/hyrax/greenocean/GridFED/GridFEDv2024.0/contents.html">http://opendap.uea.ac.uk/opendap/hyrax/greenocean/GridFED/GridFEDv2024.0/contents.html</a></p> <p><strong>Product Description</strong></p> <p>See Jones et al. (2021) for a detailed description of this dataset and the core methods used to produce it. Key details are provided below.</p> <p>GCP-GridFED (version 2024.0) is a gridded fossil emissions dataset that is consistent with the national CO<sub>2</sub> emissions reported by the Global Carbon Project (GCP; <a href="https://www.globalcarbonproject.org/">https://www.globalcarbonproject.org/</a>) in the annual editions of its Global Carbon Budget (Friedlingstein et al., 2023).</p> <p>GCP-GridFEDv2024.0 provides monthly fossil CO<sub>2 </sub>emissions for the period 1959-2023 at a spatial resolution of 0.1&deg; &times; 0.1&deg;. The gridded emissions estimates are provided separately for fossil CO<sub>2</sub> emitted by the oxidation of oil, coal and natural gas, international bunkers, and the calcination of limestone during cement production. The dataset also includes&nbsp;the cement carbonation sink of CO<sub>2</sub>.&nbsp;Note that&nbsp;positive values in GridFED signify&nbsp;a surface-to-atmosphere&nbsp;CO<sub>2 </sub>flux (emissions). Negative values signify an atmosphere-to-surface flux and apply only to the cement carbonation sink.</p> <p>GCP-GridFED also includes gridded uncertainties in CO<sub>2 </sub>emission, incorporating differences in uncertainty across emissions sectors and countries, and gridded estimates of corresponding O<sub>2</sub> uptake based on oxidative ratios for oil, coal and natural gas (see Jones et al., 2021).</p> <p><strong>Core Methodology in Brief</strong></p> <p>GCP-GridFEDv2024.0 was produced by scaling monthly gridded emissions for the year 2010, from the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2; Janssens-Maenhout et al., 2019), to the national annual emissions estimates compiled as part of the 2024 global carbon budget (GCP-NAE) for the years 1959-2023 (Friedlingstein et al., 2024).&nbsp;</p> <p>GCP-GridFEDv2024.0 uses a preliminary release of GCP-NAE covering the years 1959-2023 (timestamp 1st August 2024; an update from Andrew and Peters [2023]). The GCP-NAE estimates for year 2023 are based on data available at the timestamp and the estimates are thus expected to differ somewhat from those that will be presented by Friedlingstein et al. (2024), which will adopt updates to GCP-NAE since the timestamp.</p> <p>For full details of the core methodology, see&nbsp;Jones et al. (2021).</p> <p><strong>Changes to the Seasonality of Emissions&nbsp;in GCP-GridFEDv2022.2 onwards</strong></p> <p>The seasonality of emissions (monthly distribution of annual emissions) for the following countries/sources is now based on the seasonality observed in the&nbsp;Carbon Monitor dataset (Liu et al., 2020;&nbsp;Dou et al., 2022):&nbsp;</p> <ul> <li>Austria, Belgium, Brazil, Bulgaria, China, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, India, Ireland, Italy, Japan, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, Spain, Sweden, United Kingdom, United States.</li> <li>State or province-level data is used for Brazil, China, Russia, and the United States.</li> <li>This also applies for the Bunker Aviation and Bunker Shipping sectors.</li> </ul> <p>Seasonality is determined in the following ways for those countries/sources:</p> <ul> <li>The seasonality of emissions in 2019-2023 is taken from Carbon Monitor.</li> <li>The seasonality of emissions in all years prior to 2019 is assigned as the average of the seasonality from Carbon Monitor in all years excluding 2020 (due to the impact of COVID-19 on the seasonality of emissions in 2020).</li> </ul> <p>For all countries not listed above and all years 1959-2023, GCP-GridFED adopts the seasonality from EDGAR v4.3.2 (year 2010; Janssens-Maenhout et al., 2019) and applies a small correction based on heating/cooling degree days to account for inter-annual climate variability which effects emissions in some sectors (see Jones et al., 2021).</p> <p><strong>Other New Features of GCP-GridFEDv2024.0</strong></p> <ul> <li>There have been no changes to the functionality of the GridFED code in this update versus the previous update (v2023.1).</li> </ul> <p>&nbsp;</p>

opencc-by-4.0Sep 2022View details →
zenodo48/100

The Global Carbon Project's fossil CO2 emissions dataset

<p>The <a href="https://www.globalcarbonproject.org/">Global Carbon Project</a> (GCP) has been publishing estimates of global and national fossil CO2 emissions since 2001. In the first instance these were simple re-publications of data from another source, but over subsequent years refinements have been made in response to feedback and identification of inaccuracies. In this article (PDF document) we describe the history of this process leading up to the methodology used in the 2025 release of the GCP's fossil CO2 dataset.</p> <p>The fossil CO2 emissions dataset is included in both its standard, absolute form, and per capita, with associated metadata files in JSON format. A file indicating the source(s) of each data point is also provided.</p> <p>This is the initial release of the 2025 dataset.</p>

opencc-by-4.0Dec 2020View details →
zenodo48/100

Hybridization of Fossil- and CO2-Based Routes for Ethylene Production using Renewable Energy

<p>Dataset associated with the publication &quot;Hybridization of Fossil- and CO<sub>2</sub>-Based Routes for Ethylene Production using Renewable Energy&quot; by Iasonas Ioannou, Sebastiano C. D&#39;Angelo,&nbsp;Antonio J. Mart&iacute;n, Javier P&eacute;rez-Ram&iacute;rez, and Gonzalo Guill&eacute;n-Gos&aacute;lbez,&nbsp;available at&nbsp;<a href="https://doi.org/10.1002/cssc.202001312">https://doi.org/10.1002/cssc.202001312</a>. The dataset includes the numeric&nbsp;data associated with most of the scenarios described in the main manuscript and in the Supporting&nbsp;Information (SI), as well as the tables presented in the main manuscript and in the&nbsp;SI converted in a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>MS-Results</strong>: numerical values associated with the economic and environmental results included in both the main manuscript and the SI, for all the considered scenarios. The results include the total price for the assessed scenarios, with and without externalities, with uncertainty ranges, as well as the environmental results for human health, ecosystems, resources, and global warming potential (GWP).</li> <li><strong>MS-Tables</strong>: table reported in the main manuscript associated with the price and breakeven point of four assessed scenarios dependent on different CO<sub>2</sub> source assumptions.</li> <li><strong>SI-Tables-Economics</strong>: tables reported in the SI associated with the economic assessment of all the scenarios.</li> <li><strong>SI-Tables-LCI</strong>: tables reported in the SI associated with the environmental assessment of all the scenarios.</li> <li><strong>SI-Tables-AdditionalResults</strong>: tables reported in the SI associated with additional results presented in the work.</li> </ul>

opencc-by-4.0Jul 2020View details →
zenodo40/100

Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories 1959-2018

<p>GCP-GridFED (version 2019.1) is a gridded fossil emissions dataset that is consistent with the national CO<sub>2</sub> emissions reported by the Global Carbon Project (GCP). GCP-GridFEDv2019.1 provides monthly fossil CO<sub>2 </sub>emissions for the period 1959-2018 at a spatial resolution of 0.1&deg; &times; 0.1&deg;. The gridded emissions estimates are provided separately for fossil CO<sub>2</sub> emitted by the oxidation of oil, coal and natural gas, with mixed international bunker fuels considered separately, as well as for the calcination of limestone during cement production. GCP-GridFED also includes gridded uncertainties in CO<sub>2 </sub>emission, incorporating differences in uncertainty across emissions sectors and countries, and gridded estimates of corresponding O<sub>2</sub> uptake based on oxidative ratios for oil, coal and natural gas.</p> <p>GCP-GridFED was produced by scaling monthly gridded emissions for the year 2010, from the Emissions Database for Global Atmospheric Research (EDGAR; version 4.3.2; Janssens-Maenhout et al., 2019), to the national annual emissions estimates compiled as part of the 2019 global carbon budget (GCB-NAE) for the years 1959-2018 (Friedlingstein et al., 2019).</p> <p>The data description article&nbsp;is under review.</p>

opencc-by-4.0Jul 2020View details →
zenodo40/100

China's fossil fuel CO2 emissions estimated using surface observations of co-emitted NO2

<p>We employed an EnKF-based Regional Multi-Air Pollutant Assimilation System (RAPAS) to assimilate <em>in-situ</em> NO<sub>2</sub> observations, allowing us to combine observation-constrained NO<em><sub>x</sub></em> emissions co-emitted with FFCO<sub>2</sub> and grid-specific CO<sub>2</sub>-to-NO<em><sub>x</sub></em> emission ratios for inferring daily <strong>FFCO<sub>2</sub> emissions</strong> over China.</p> <p><strong>cnemc_obs.nc </strong>includes assimilated and verified observations.</p> <p><strong>emission.tar.gz</strong> includes inferred daily posterior NO<em><sub>x</sub></em> and FFCO<sub>2</sub> emissions for the year 2016.</p>

opencc-by-4.0Jul 2023View details →
zenodo36/100

Collected data on early estimates of global fossil CO2 emissions

<p>This dataset collects together a number of early estimates made of global emissions of fossil CO2, starting with Arvid H&ouml;gbom in 1894. Microsoft Excel files for original data sources where these are time series, including images of the tables from the original sources, in addition to one CSV file of CO2 emissions from all sources. Sources that only reported emissions for a short period are not included in the Excel collection, but are included in the CSV file. In addition the original United Nations energy data used by several sources is included as UN1956.xlsx.</p>

opencc-by-4.0May 2020View details →
zenodo36/100

Global, Regional, and National Fossil-Fuel CO2 Emissions: 1751-2017

<p>This data product is a time series of Carbon Dioxide (CO2) emissions from fossil fuel combustion and cement manufacture. Estimates of CO2 emissions are included for the globe and by nation back to 1751, and include emissions from solid fuel consumption, liquid fuel consumption, gas fuel consumption, cement production, and gas flaring. Per capita CO2 emissions and emissions from international trade (bunker fuels) are included as well; bunker fuels are not included in country totals, but are assigned to the country in which loading took place. Estimates are generated using the United Nations Energy Statistics database and the United States Geologic Survey&rsquo;s cement statistics. Datasets produced from this group at Appalachian State University are located at https://data.ess-dive.lbl.gov/view/doi:10.15485/1712447, and are also located at https://energy.appstate.edu/research/work-areas/cdiac-appstate. Historic CDIAC data from Oak Ridge National Laboratory are located here: https://data.ess-dive.lbl.gov/view/doi:10.3334/CDIAC/00001_V2017. This dataset is the foundational dataset for the annual global carbon budget and other carbon cycle analyses that need relevant fossil fuel CO2 data. Within this data package are spreadsheets (.csv) of global and national estimates of CO2 emissions as well as text files of the ranking of each country&rsquo;s total CO2 emissions and per capita for that year</p>

opencc-by-4.0Dec 2019View details →
zenodo36/100

Data set for fossil Co2 emission in Nigeria

<p>Here is a dataset that captures fossil Co2 emission in Nigeria.&nbsp;</p>

opencc-by-4.0Sep 2023View details →
dryad36/100

Reductions in California's urban fossil fuel CO2 emissions during the COVID-19 pandemic

Open the record for dataset details and reuse information.

publicMay 2022View details →
zenodo32/100

Data included in "Radiocarbon Measurements Reveal Underestimated Fossil CH4 and CO2 Emissions in London"

<p>CO2 and CH4 concentrations measured at Imperial College, radiocarbon measurements of sample collected, radiocarbon simulations using the Met Office NAME model coupled with EDGAR emission inventories.&nbsp;</p>

opencc-by-4.0Mar 2023View details →
nasa28/100

CMS: CO2 Signals Estimated for Fossil Fuel Emissions and Biosphere Flux, California

This data set provides estimated CO2 emission signals for 16 regions (air quality basins) in California, USA, during the individual months of November 2010 and May 2011. The CO2 signals were predicted from simulated atmospheric CO2 observations and modeled fossil fuel emissions and biosphere CO2 fluxes. Data is also provided for the land surface in the larger modeling domain outside California. CO2 signals refer to the local enhancement or depletion in atmospheric CO2 concentration caused by fossil fuel emissions or biospheric exchange occurring within the region.

restrictednotspecifiedApr 2025View details →
nasa28/100

CMS: Atmospheric CO2 and C Isotopes, Fossil Fuel Contributions, California, 2014-2015

This dataset provides measurements of atmospheric CO2 concentrations, carbon isotopes d13C and D14C, and fossil fuel CO2 (ffCO2) estimates from nine observation sites in California over three month-long campaigns in separate seasons of 2014-2015. ffCO2 was quantified based on the CO2 concentration and D14C. Simulations of ffCO2 at the sites and times of the observations were conducted with the Vulcan v2.2 fossil fuel emissions estimate for 2002 and the Weather Research and Forecasting - Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) atmospheric model. The observed and simulated ffCO2 were incorporated into Bayesian inverse estimates of ffCO2 to calculate California's ffCO2 emissions during the campaign period.

restrictednotspecifiedApr 2025View details →
nasa28/100

Vulcan: High-Resolution Hourly Fossil Fuel CO2 Emissions in USA, 2010-2015, Version 3

The Vulcan version 3.0 hourly dataset quantifies hourly emissions at a 1-km resolution for the 2010-2015 time period. Estimates are provided of hourly carbon dioxide (CO2) emissions from the combustion of fossil fuels (FF) and CO2 emissions from cement production for the conterminous United States and the state of Alaska. Referred to as FFCO2, the emissions from Vulcan are categorized into 10 source sectors including; residential, commercial, industrial, electricity production, onroad, nonroad, commercial marine vessel, airport, rail, and cement. Files for hourly total emissions are also available. Data are represented in space on a 1 km x 1 km grid as hourly totals for 2010-2015. This dataset provides the first bottom-up U.S.-wide FFCO2 emissions data product at 1 km2/hourly for multiple years and is designed to be used as emission estimates in atmospheric transport modeling, policy, mapping, and other data analyses and applications.

restrictednotspecifiedApr 2025View details →
nasa28/100

Vulcan: High-Resolution Annual Fossil Fuel CO2 Emissions in USA, 2010-2015, Version 3

The Vulcan version 3.0 annual dataset provides estimates of annual carbon dioxide (CO2) emissions from the combustion of fossil fuels (FF) and CO2 emissions from cement production for the conterminous United States and the State of Alaska. Referred to as FFCO2, the emissions from Vulcan are categorized into 10 source sectors including; residential, commercial, industrial, electricity production, onroad, nonroad, commercial marine vessel, airport, rail, and cement. Data are gridded annually on a 1-km grid for the years 2010 to 2015. These data are annual sums of hourly estimates. Also provided are estimates of the upper 95% confidence interval and the lower 95% confidence interval boundaries for each emission estimate. For each uncertainty level, there are 10 individual sector files and one total file. These data are designed to be used as emission estimates in atmospheric transport modeling, policy, mapping, and other data analyses and applications.

restrictednotspecifiedApr 2025View details →

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dandi-nwb
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International Brain Laboratory public data

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Last verified 2026-04-29Open record