{"type": "FeatureCollection", "features": [{"id": "10.1021/es3024435", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:17:14Z", "type": "Journal Article", "created": "2012-11-05", "title": "Bioenergy Production From Perennial Energy Crops: A Consequential Lca Of 12 Bioenergy Scenarios Including Land Use Changes", "description": "In the endeavor of optimizing the sustainability of bioenergy production in Denmark, this consequential life cycle assessment (LCA) evaluated the environmental impacts associated with the production of heat and electricity from one hectare of Danish arable land cultivated with three perennial crops: ryegrass (Lolium perenne), willow (Salix viminalis) and Miscanthus giganteus. For each, four conversion pathways were assessed against a fossil fuel reference: (I) anaerobic co-digestion with manure, (II) gasification, (III) combustion in small-to-medium scale biomass combined heat and power (CHP) plants and IV) co-firing in large scale coal-fired CHP plants. Soil carbon changes, direct and indirect land use changes as well as uncertainty analysis (sensitivity, MonteCarlo) were included in the LCA. Results showed that global warming was the bottleneck impact, where only two scenarios, namely willow and Miscanthus co-firing, allowed for an improvement as compared with the reference (-82 and -45 t CO\u2082-eq. ha\u207b\u00b9, respectively). The indirect land use changes impact was quantified as 310 \u00b1 170 t CO\u2082-eq. ha\u207b\u00b9, representing a paramount average of 41% of the induced greenhouse gas emissions. The uncertainty analysis confirmed the results robustness and highlighted the indirect land use changes uncertainty as the only uncertainty that can significantly change the outcome of the LCA results.", "keywords": ["Crops", " Agricultural", "Manures", "Nitrogen", "Life cycle", "Coal gasification plants", "Sus scrofa", "0211 other engineering and technologies", "Crops", "02 engineering and technology", "/dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_production; name=SDG 12 - Responsible Consumption and Production", "Global Warming", "7. Clean energy", "Environmental impact", "/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy", "Anaerobic digestion", "11. Sustainability", "0202 electrical engineering", " electronic engineering", " information engineering", "Animals", "Anaerobiosis", "Gas emissions", "2. Zero hunger", "Fossil fuels", "Global warming", "/dk/atira/pure/sustainabledevelopmentgoals/life_on_land; name=SDG 15 - Life on Land", "Agriculture", "Carbon Dioxide", "15. Life on land", "Carbon", "Coal combustion", "Manure", "Greenhouse gases", "Carbon dioxide", "13. Climate action", "Biofuels", "Land use", "Uncertainty analysis", "Cogeneration plants", "Power generation"]}, "links": [{"href": "https://doi.org/10.1021/es3024435"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1021/es3024435", "name": "item", "description": "10.1021/es3024435", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1021/es3024435"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-11-30T00:00:00Z"}}, {"id": "10.5061/dryad.2f70818", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:21:20Z", "type": "Dataset", "title": "Data from: Differences in carbon stocks along an elevational gradient in tropical mountain forests of Colombia", "description": "unspecifiedTropical mountain forests provide an exceptional opportunity to evaluate  the patterns of variation of carbon stocks along elevational gradients  that correspond to well-defined temperature gradients. We predicted that  carbon stored in live aboveground biomass, aboveground necromass, and soil  components of forests on the eastern flank of the Colombian Andes would  change with elevation along this gradient extending from 750 to 2800 m  above sea level. The rationale was that the corresponding change in  temperature (14\u00b0C to 26\u00b0C) would influence tree growth and decomposition  of organic matter. To address this hypothesis, we examined the carbon  stored in these three components using data from 20 0.25-ha plots located  along this elevational gradient. The mean total carbon stock found in the  study region was 241.3\u00b137.5 Mg C/ha. Aboveground carbon stocks decreased  with elevation (p =0.001), as did necromass carbon stocks (p =0.016).  Although soil organic carbon stocks did not differ significantly along the  gradient (p =0.153), they contributed proportionately more at higher than  at lower elevations, counterbalancing the opposite trends in aboveground  carbon and necromass carbon stocks. As such, total carbon stocks did not  vary significantly along the elevational gradient (p =0.576).", "keywords": ["carbon stocks", "soil organic carbon", "live aboveground biomass", "aboveground necromass", "15. Life on land", "Colombian Andes", "uncertainty analysis"], "contacts": [{"organization": "Phillips, Juan, Ramirez, Sebastian, Wayson, Craig, Duque, Alvaro,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.2f70818"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.2f70818", "name": "item", "description": "10.5061/dryad.2f70818", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.2f70818"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-06-19T00:00:00Z"}}, {"id": "10.5061/dryad.rn8pk0pm8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:21:31Z", "type": "Dataset", "created": "2024-06-28", "title": "Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass-based biofuel production", "description": "unspecifiedThis study investigates uncertainties in greenhouse gas (GHG) emission  factors related to switchgrass-based biofuel production in Michigan. Using  three life cycle assessment (LCA) databases\u2014 US lifecycle inventory  database (USLCI), GREET, and Ecoinvent\u2014each with multiple versions, we  recalculated the global warming intensity (GWI) and GHG mitigation  potential in a static calculation. Employing Monte Carlo simulations along  with local and global sensitivity analyses, we assess uncertainties and  pinpoint key parameters influencing GWI. The convergence of results across  our previous study, static calculations, and Monte Carlo simulations  enhances the credibility of estimated GWI values. Static calculations,  validated by Monte Carlo simulations, offer reasonable central tendencies,  providing a robust foundation for policy considerations. However, the  wider range observed in Monte Carlo simulations underscores the importance  of potential variations and uncertainties in real-world applications.  Sensitivity analyses identify biofuel yield, GHG emissions of electricity,  and soil organic carbon (SOC) change as pivotal parameters influencing  GWI. Decreasing uncertainties in GWI may be achieved by making greater  efforts to acquire more precise data on these parameters. Our study  emphasizes the significance of considering diverse GHG factors and  databases in GWI assessments and stresses the need for accurate  electricity fuel mixes, crucial information for refining GWI assessments  and informing strategies for sustainable biofuel production.", "keywords": ["Sensitivity Analysis", "Switchgrass", "FOS: Environmental engineering", "Cellulosic biofuel", "Global warming intensity", "Greenhouse gas emission factor", "LCA database", "uncertainty analysis"], "contacts": [{"organization": "Kim, Seungdo, Dale, Bruce, Basso, Bruno,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.rn8pk0pm8"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.rn8pk0pm8", "name": "item", "description": "10.5061/dryad.rn8pk0pm8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.rn8pk0pm8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-16T00:00:00Z"}}, {"id": "2164/6134", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:25:37Z", "type": "Journal Article", "created": "2016-05-13", "title": "Modeling Soil Processes: Review, Key Challenges, and New Perspectives", "description": "Core Ideas                     <p>                                                                           <p>A community effort is needed to move soil modeling forward.</p>                                                                             <p>Establishing an international soil modeling consortium is key in this respect.</p>                                                                             <p>There is a need to better integrate existing knowledge in soil models.</p>                                                                             <p>Integration of data and models is a key challenge in soil modeling.</p>                                                                     </p>                     <p>The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate\uffe2\uff80\uff90change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.</p>", "keywords": ["organic-matter dynamics", "550", "Sciences de l\u2019environnement & \u00e9cologie", "QH301 Biology", "Knowledge management", "0208 environmental biotechnology", "ECOSYSTEM SERVICES", "02 engineering and technology", "soil processes", "01 natural sciences", "Physical Geography and Environmental Geoscience", "Sciences de la Terre", "Biological process", "ANZSRC::3707 Hydrology", "DROUGHT SEVERITY INDEX", "SYNTHETIC-APERTURE RADAR", "ANZSRC::4106 Soil sciences", "SDG 13 - Climate Action", "Climate change", "0503 Soil Sciences", "GROUND-PENETRATING RADAR", "Integration of knowledge", "Life sciences", "ANZSRC::050399 Soil Sciences not elsewhere classified", "synthetic-aperture radar", "Physical Sciences", "Water Resources", "Knowledge and experience", "MULTIPLE ECOSYSTEM SERVICES", "knowledge integration", "570", "DIFFUSE-REFLECTANCE SPECTROSCOPY", "Environmental Engineering", "Physique", " chimie", " math\u00e9matiques & sciences de la terre", "Scientific discipline", "0703 Crop and Pasture Production", "0207 environmental engineering", "Soil Science", "soil science", "ORGANIC-MATTER DYNAMICS", "DATA ASSIMILATION", "Physical", " chemical", " mathematical & earth Sciences", "ANZSRC::0503 Soil Sciences", "Science disciplines", "PEDOTRANSFER FUNCTIONS", "Feedback mechanisms", "mod\u00e9lisation", "ground-penetrating radar", "Science & Technology", "ANZSRC::080110 Simulation and Modelling", "15. Life on land", "Sciences de la terre & g\u00e9ographie physique", "multiple ecosystem services", "root water-uptake", "Observation and measurement", "DIGITAL ELEVATION MODEL", "Quality of predictions", "SATURATED-UNSATURATED FLOW", "ARBUSCULAR MYCORRHIZAL FUNGI", "sciences du sol", "HYDRAULIC-PROPERTIES", "2. Zero hunger", "Agriculture", "diffuse-reflectance spectroscopy", "4106 Soil sciences", "ORGANIC-MATTER", "digital elevation model", "SDG 13 \u2013 Ma\u00dfnahmen zum Klimaschutz", "Sciences du vivant", "Uncertainty analysis", "0406 Physical Geography and Environmental Geoscience", "Life Sciences & Biomedicine", "Crop and Pasture Production", "101028 Mathematical modelling", "international soil modeling consortium", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Environmental Sciences & Ecology", "arbuscular mycorrhizal fungi", "Ecosystems", "Climate models", "QH301", "Environmental sciences & ecology", "Life Science", "SEDIMENT TRANSPORT MODELS", "data integration", "sediment transport models", "approche ecosyst\u00e9mique", "0105 earth and related environmental sciences", "info:eu-repo/classification/ddc/550", "3707 Hydrology", "soil modeling", "ROOT WATER-UPTAKE", "SOLUTE TRANSPORT", "13. Climate action", "Earth and Environmental Sciences", "Soil Sciences", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "Earth Sciences", "Earth sciences & physical geography", "Soils", "101028 Mathematische Modellierung", "saturated-unsaturated flow", "Environmental Sciences", "root water-uptake", " sediment transport models", " diffuse-reflectance spectroscopy", " arbuscular mycorrhizal fungi", " multiple ecosystem services", " saturated-unsaturated flow", " ground-penetrating radar", " synthetic-aperture radar", " digital elevation model", " organic-matter dynamics."]}, "links": [{"href": "https://orbi.uliege.be/bitstream/2268/263634/1/Vereecken%20VZJ%202016.pdf"}, {"href": "http://onlinelibrary.wiley.com/wol1/doi/10.2136/vzj2015.09.0131/fullpdf"}, {"href": "https://escholarship.org/content/qt6976n34c/qt6976n34c.pdf"}, {"href": "https://doi.org/2164/6134"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Vadose%20Zone%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2164/6134", "name": "item", "description": "2164/6134", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2164/6134"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-05-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Uncertainty+analysis&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=Uncertainty+analysis&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=Uncertainty+analysis&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Uncertainty+analysis&offset=4", "hreflang": "en-US"}], "numberMatched": 4, "numberReturned": 4, "distributedFeatures": [], "timeStamp": "2026-07-27T05:14:35.613361Z"}