{"type": "FeatureCollection", "features": [{"id": "10.1029/2019gb006393", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:18:11Z", "type": "Journal Article", "created": "2020-02-07", "title": "Sources of Uncertainty in Regional and Global Terrestrial CO 2 Exchange Estimates", "description": "<p>The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO  growth rate, fossil fuel emissions, and modeled (bottom\uffe2\uff80\uff90up) land and ocean fluxes cannot be fully closed, leading to a \uffe2\uff80\uff9cbudget imbalance,\uffe2\uff80\uff9d highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom\uffe2\uff80\uff90up and top\uffe2\uff80\uff90down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO  growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El\uffc2\uffa0Ni\uffc3\uffb1o\uffe2\uff80\uff93Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high\uffe2\uff80\uff90resolution remote\uffe2\uff80\uff90sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.</p>", "keywords": ["[SDE] Environmental Sciences", "FLUXES", "550", "BURNED AREA PRODUCT", "atmospheric inversions", "01 natural sciences", "Environnement et pollution", "DATA ASSIMILATION", "Ph\u00e9nom\u00e8nes atmosph\u00e9riques", "PLANT FUNCTIONAL TYPES", "global carbon budget", "carbon cycle", "ATMOSPHERIC CO2", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "FOSSIL-FUEL", "VEGETATION MODEL ORCHIDEE", "15. Life on land", "ddc:910", "CARBON-DIOXIDE EMISSIONS", "13. Climate action", "[SDE]Environmental Sciences", "dynamic global vegetation models", "contr\u00f4le de la pollution", "Technologie de l'environnement", "INCORPORATING SPITFIRE"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019GB006393"}, {"href": "https://doi.org/10.1029/2019gb006393"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2019gb006393", "name": "item", "description": "10.1029/2019gb006393", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2019gb006393"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-02-01T00:00:00Z"}}, {"id": "10.5194/essd-10-405-2018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:22:46Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere \u2013 the global carbon budget \u2013 is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as \u00b11\u03c3. For the last decade available (2007\u20132016), EFF was 9.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, ELUC 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM 4.7\u202f\u00b1\u202f0.1\u202fGtC\u202fyr\u22121, SOCEAN 2.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND 3.0\u202f\u00b1\u202f0.8\u202fGtC\u202fyr\u22121, with a budget imbalance BIM of 0.6\u202fGtC\u202fyr\u22121 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121. Also for 2016, ELUC was 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM was 6.1\u202f\u00b1\u202f0.2\u202fGtC\u202fyr\u22121, SOCEAN was 2.6\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND was 2.7\u202f\u00b1\u202f1.0\u202fGtC\u202fyr\u22121, with a small BIM of \u22120.3\u202fGtC. GATM continued to be higher in 2016 compared to the past decade (2007\u20132016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ni\u00f1o conditions. The global atmospheric CO2 concentration reached 402.8\u202f\u00b1\u202f0.1\u202fppm averaged over 2016. For 2017, preliminary data for the first 6\u20139\u00a0months indicate a renewed growth in EFF of +2.0\u202f% (range of 0.8 to 3.0\u202f%) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Qu\u00e9r\u00e9 et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).                     </p></article>", "keywords": ["ENVIRONMENT SIMULATOR JULES", "550", "530 Physics", "[PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]", "MIXED-LAYER SCHEME", "INTERNATIONAL-TRADE", "7. Clean energy", "01 natural sciences", "333", "12. Responsible consumption", "FOSSIL-FUEL COMBUSTION", "ANTHROPOGENIC CO2 UPTAKE", "11. Sustainability", "SDG 13 - Climate Action", "Life Science", "GE1-350", "SDG 14 - Life Below Water", "ATMOSPHERIC CO2", "DIOXIDE EMISSIONS", "SDG 15 - Life on Land", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "QE1-996.5", "info:eu-repo/classification/ddc/550", "EARTH SYSTEM MODEL", "ddc:550", "VEGETATION MODEL", "Geology", "15. Life on land", "Environmental sciences", "Earth sciences", "13. Climate action", "8. Economic growth", "General Earth and Planetary Sciences"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/66578/1/Published_manuscript.pdf"}, {"href": "http://oceanrep.geomar.de/42391/1/essd-10-405-2018.pdf"}, {"href": "https://boris.unibe.ch/116576/1/lequere18essd.pdf"}, {"href": "https://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://essd.copernicus.org/articles/10/405/2018/essd-10-405-2018.pdf"}, {"href": "https://doi.org/10.5194/essd-10-405-2018"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-10-405-2018", "name": "item", "description": "10.5194/essd-10-405-2018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-10-405-2018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-12T00:00:00Z"}}, {"id": "1912/10214", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:26:27Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere \u2013 the global carbon budget \u2013 is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as \u00b11\u03c3. For the last decade available (2007\u20132016), EFF was 9.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, ELUC 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM 4.7\u202f\u00b1\u202f0.1\u202fGtC\u202fyr\u22121, SOCEAN 2.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND 3.0\u202f\u00b1\u202f0.8\u202fGtC\u202fyr\u22121, with a budget imbalance BIM of 0.6\u202fGtC\u202fyr\u22121 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121. Also for 2016, ELUC was 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM was 6.1\u202f\u00b1\u202f0.2\u202fGtC\u202fyr\u22121, SOCEAN was 2.6\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND was 2.7\u202f\u00b1\u202f1.0\u202fGtC\u202fyr\u22121, with a small BIM of \u22120.3\u202fGtC. GATM continued to be higher in 2016 compared to the past decade (2007\u20132016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ni\u00f1o conditions. The global atmospheric CO2 concentration reached 402.8\u202f\u00b1\u202f0.1\u202fppm averaged over 2016. For 2017, preliminary data for the first 6\u20139\u00a0months indicate a renewed growth in EFF of +2.0\u202f% (range of 0.8 to 3.0\u202f%) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Qu\u00e9r\u00e9 et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).</p></article>", "keywords": ["ENVIRONMENT SIMULATOR JULES", "550", "530 Physics", "[PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]", "MIXED-LAYER SCHEME", "INTERNATIONAL-TRADE", "7. Clean energy", "01 natural sciences", "333", "12. Responsible consumption", "FOSSIL-FUEL COMBUSTION", "ANTHROPOGENIC CO2 UPTAKE", "11. Sustainability", "SDG 13 - Climate Action", "Life Science", "GE1-350", "SDG 14 - Life Below Water", "ATMOSPHERIC CO2", "DIOXIDE EMISSIONS", "SDG 15 - Life on Land", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "QE1-996.5", "info:eu-repo/classification/ddc/550", "EARTH SYSTEM MODEL", "ddc:550", "VEGETATION MODEL", "Geology", "15. Life on land", "Environmental sciences", "Earth sciences", "13. Climate action", "8. Economic growth", "General Earth and Planetary Sciences"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/66578/1/Published_manuscript.pdf"}, {"href": "http://oceanrep.geomar.de/42391/1/essd-10-405-2018.pdf"}, {"href": "https://boris.unibe.ch/116576/1/lequere18essd.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://essd.copernicus.org/articles/10/405/2018/essd-10-405-2018.pdf"}, {"href": "https://doi.org/1912/10214"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1912/10214", "name": "item", "description": "1912/10214", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1912/10214"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-12T00:00:00Z"}}, {"id": "4b970e59-fbb7-4f9b-8155-ceebabd2d971", "type": "Feature", "geometry": null, "properties": {"updated": "2024-09-24T14:39:18", "type": "Dataset", "language": "en", "title": "Landslide susceptibility Classification 1:50,000 Ireland (ROI) ITM", "description": "A landslide is the movement of material down a Slope. This includes rock, earth, mud and Peat. Landslides in Ireland mainly occur on steep mountain slopes.  A landslide susceptibility map shows areas where a landslide could occur, how likely it will occur and what Causes them. The likelihood is measured from low to high.  The map is created using a method called the Unique Condition Unit (UCU).  A unique condition unit is an area with a set of ground types. It tells us what the soil type is, what the Slope is (angle of the ground) and where water flows.  When many landslides occur in a unit, the map will show high landslide susceptibility.  The landslide susceptibility classification map is to the scale 1:50,000 (1\u00a0cm on the map relates to a distance of 500\u00a0m) It is a vector Dataset. Vector data portray the world using points, lines, and polygons. A polygon represents the area.  The landslide susceptibility data is shown from polygons. Each polygon gives information on the unit, its soil type, the Slope of the ground, its description and the description of landslide susceptibility.", "formats": [{"name": "DATA VIEWER"}], "keywords": ["earth-science", "environment", "fossil-fuel", "geology", "geomorphic-process", "geoscientificinformation", "ie", "ireland", "landslide", "lithosphere", "peat", "pedosphere", "science", "soil", "soil-degradation"], "contacts": [{"organization": "Geological Survey of Ireland", "roles": ["creator"]}, {"organization": "https://data.gov.ie/organization/geological-survey-of-ireland", "roles": ["publisher"]}]}, "links": [{"href": "https://dcenr.maps.arcgis.com/apps/webappviewer/index.html?id=b68cf1e4a9044a5981f950e9b9c5625c"}, {"href": "https://gsi.geodata.gov.ie/downloads/Geohazards/Data/IE_GSI_Landslide_Data_IE32_ITM.zip"}, {"href": "https://gsi.geodata.gov.ie/downloads/Geohazards/Reports/IE_GSI_Landslide_Susceptibility_Mapping_Summary.pdf"}, {"href": "https://gsi.geodata.gov.ie/server/rest/services/Geohazards/IE_GSI_Landslide_Susceptibility_Classification_50K_IE26_ITM/MapServer"}, {"href": "https://gsi.geodata.gov.ie/server/rest/services/Geohazards/IE_GSI_Landslide_Susceptibility_Classification_50K_IE26_ITM/MapServer?f=pjson"}, {"href": "https://gsi.geodata.gov.ie/server/services/Geohazards/IE_GSI_Landslide_Susceptibility_Classification_50K_IE26_ITM/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"href": "http://data.europa.eu/88u/dataset/4b970e59-fbb7-4f9b-8155-ceebabd2d971"}, {"rel": "self", "type": "application/geo+json", "title": "4b970e59-fbb7-4f9b-8155-ceebabd2d971", "name": "item", "description": "4b970e59-fbb7-4f9b-8155-ceebabd2d971", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/4b970e59-fbb7-4f9b-8155-ceebabd2d971"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=fossil-fuel&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=fossil-fuel&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=fossil-fuel&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=fossil-fuel&offset=4", "hreflang": "en-US"}], "numberMatched": 4, "numberReturned": 4, "distributedFeatures": [], "timeStamp": "2026-05-30T23:16:10.392387Z"}