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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Brazil is home to the largest tracts of tropical vegetation in the world, harbouring high levels of biodiversity and carbon. Several biomass maps have been produced for Brazil, using different approaches and methods, and for different purposes. These maps have been used to estimate historic, recent, and future carbon emissions from land use change (LUC). It can be difficult to determine which map to use for what purpose. The implications of using an unsuitable map can be significant, since the maps have large differences—both in terms of total carbon storage and its spatial distribution. This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare. This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare. Data är baserade på befintliga kartor och en aktuell LULC-karta (änding av markanvändning) för bildandet av ovanjordiskt kol i Brasilien. Kartan speglar nuvarande LULC, har hög noggrannhet och upplösning (50 m) och en nationell täckning. Mer information på den engelska katalogsidan: https://snd.gu.se/en/catalogue/study/ecds0244 This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Swedish National Dat...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Swedish National Data Service
    Dataset . 2017
    License: CC BY NC
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Swedish National Data Service
    Dataset . 2017
    License: CC BY NC
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Swedish National Dat...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Swedish National Data Service
      Dataset . 2017
      License: CC BY NC
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Swedish National Data Service
      Dataset . 2017
      License: CC BY NC
      Data sources: Datacite
      addClaim
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Hansen, Teis; Keaney, Monica; Bulkeley, Harriet A.; Cooper, Mark; +10 Authors

    This database includes more than 100 decarbonisation innovations in Paper, Plastic, Steel and Meat & Dairy sectors, across their value chains, as well as in Finance. For each innovation there is a description, information about its contribution to decarbonisation, actors and collaborators involved, sources of funding, drivers, (co)benefits and disadvantages. More information on the method for selecting innovations for the database is available here. The database was created as part of REINVENT – a Horizon 2020 research project funded by the European Commission (grant agreement 730053). REINVENT involves five research institutions from four countries: Lund University (Sweden), Durham University (United Kingdom), Wuppertal Institute (Germany), PBL Netherlands Environmental Assessment Agency (the Netherlands) and Utrecht University (the Netherlands). More information can be found on our website: www.reinvent-project.eu.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2018
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2018
    License: CC BY NC ND
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: Datacite
    addClaim
    1
    citations1
    popularityAverage
    influenceAverage
    impulseAverage
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2018
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2018
      License: CC BY NC ND
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: Datacite
      addClaim
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Sathre, Roger;
    Sathre, Roger
    ORCID
    Harvested from ORCID Public Data File

    Sathre, Roger in OpenAIRE
    Gustavsson, Leif;

    Heavy trucks contribute significantly to climate change, and in 2020 were responsible for 7% of total Swedish GHG emissions and 5% of total global CO2 emissions. Here we study the full lifecycle of cargo trucks powered by different energy pathways, comparing their biomass feedstock use, primary energy use, net biogenic and fossil CO2 emission, and cumulative radiative forcing. We analyse battery electric trucks with bioelectricity from standalone or combined heat and power (CHP) plants, and pathways where bioelectricity is integrated with wind and solar electricity. We analyse trucks operated on fossil diesel fuel and on dimethyl ether (DME). All energy pathways are analysed with and without carbon capture and storage (CCS). Bioelectricity and DME are produced from forest harvest residues. Forest biomass is a limited resource, so in a scenario analysis we allocate a fixed amount of biomass to power Swedish truck transport. Battery lifespan and chemistry, the technology level of energy supply, and the biomass source and transport distance are all varied to understand how sensitive the results are to these parameters. The scenario spans 100 years into the future. We find that pathways using electricity to power battery electric trucks have much lower climate impacts and primary energy use, compared to diesel and DME based pathways. The pathways using bioelectricity with CCS result in negative emissions leading to global cooling of the earth. The pathways using diesel and DME have significant and very similar climate impact, even with CCS. The robust results show that truck electrification and increased renewable electricity production is a much better strategy to reduce the climate impact of cargo transport and much more primary energy efficient than the adoption of DME trucks. This climate impact analysis includes all fossil and net biogenic CO2 emissions as well as the timing of these emissions. Considering only fossil emissions is incomplete and could be misleading. This dataset contains data on 4 metrics (primary energy use, biomass feedstock use, cumulative CO2 emissions, and cumulative radiative forcing) resulting from scenario modeling of cargo truck use in Sweden powered by different energy pathways. The energy pathways include battery electric trucks powered by bioelectricity, solar photovoltaic electricity and wind electricity, and internal combustion trucks powered by fossil diesel and dimethyl ether. The scenario spans 100 years into the future. The Excel sheet "tables" contains input data for the scenario modeling, with sources listed where applicable. The remaining sheets contains the modeled results and generated figures that are also a published in the associated article Sathre & Gustavsson (2023). Refer to the method description and reference list in the included documentation files for details. Tunga lastbilar bidrar kraftigt till klimatförändringarna och stod 2020 för 7% av de totala svenska växthusgasutsläppen och 5% av de totala globala CO2-utsläppen. Här studerar vi hela livscykeln för lastbilar som drivs av olika energivägar, jämför deras användning av biomassaråvaror, primär energianvändning, biogena och fossila CO2-utsläpp netto och kumulativ strålningstvingning. Vi analyserar batterielektriska lastbilar med bioel från fristående eller kraftvärmeverk och vägar där bioel integreras med vind- och solkraft. Vi analyserar lastbilar som drivs med fossilt dieselbränsle och med dimetyleter (DME). Alla energivägar analyseras med och utan avskiljning och lagring av koldioxid (CCS). Bioelektricitet och DME produceras av skogsavverkningsrester. Skogsbiomassa är en begränsad resurs, så i en scenarioanalys avsätter vi en fast mängd biomassa för att driva svenska lastbilstransporter. Batteriets livslängd och kemi, tekniknivån för energiförsörjning och biomassakällan och transportavståndet varierar alla för att förstå hur känsliga resultaten är för dessa parametrar. Scenariot sträcker sig 100 år in i framtiden. Vi finner att vägar som använder el för att driva batterielektriska lastbilar har mycket lägre klimatpåverkan och primär energianvändning, jämfört med diesel- och DME-baserade vägar. De vägar som använder bioelektricitet med CCS resulterar i negativa utsläpp som leder till global kylning av jorden. Vägarna med diesel och DME har betydande och mycket liknande klimatpåverkan, även med CCS. De robusta resultaten visar att elektrifiering av lastbilar och ökad förnybar elproduktion är en mycket bättre strategi för att minska godstransporternas klimatpåverkan än införandet av DME-lastbilar, och mycket mer primärenergieffektiv. Denna klimatkonsekvensanalys omfattar alla fossila och biogena CO2-utsläpp samt tidpunkten för dessa utsläpp. Att bara ta hänsyn till fossila utsläpp är ofullständigt och kan vara missvisande. Detta dataset innehåller data om 4 mätvärden (primär energianvändning, biomassaråvara, kumulativa CO2-utsläpp och kumulativ strålkraftspåverkan) som härrör från scenariomodellering av lastbilsanvändning i Sverige som drivs av olika energivägar. Energivägarna inkluderar batterielektriska lastbilar som drivs av bioelektricitet, solcellselektricitet och vindkraft samt förbränningsbilar som drivs av fossil diesel och dimetyleter. Scenariot sträcker sig 100 år in i framtiden. På arket "tables" i Excelfilen återfinns den indata som använts i modelleringen med angivna källor där detta är tillämpligt. Övriga ark innehåller resultat samt figurer som också publiceras i den samhörande artikeln Sathre & Gustavsson (2023). Se metodbeskrivning samt referenslista i tillhörande dokumentationsfiler för detaljer.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Swedish National Dat...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Swedish National Data Service
    Dataset . 2023
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Swedish National Data Service
    Dataset . 2023
    Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2023
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Swedish National Data Service
      Dataset . 2023
      Data sources: Datacite
      addClaim
  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Hedberg, Per; Sundquist, Göran;

    Oskarshamn is one of the municipalities being discussed as a possible site for disposal of nuclear waste from the Swedish nuclear power plants, and there has been inquiries made for a pilot study in the area. In view of this the local council of Oskarshamn appointed a ´Youth team´, consisting of ten young politicians from all political parties represented in the local council. The aim of the team was to inform and create debate among adolescents about how to store the radioactive waste from nuclear power plants. The purpose of this survey, addressed to young people in Oskarshamn, was to shed light on their opinion towards a pilot study and possible disposal of nuclear waste in Oskarshamn. The respondents had to answer questions about their opinion on the use of nuclear power in Sweden, if they believed nuclear power to be abolished by year 2010, and about their general interest in issues concerning energy and nuclear power. Other questions concerned risks associated with nuclear power, the influence different groups have/ought to have when it comes to disposal of nuclear waste, and if the respondent would accept a decision to dispose nuclear waste in Oskarshamn. A number of questions dealt with the suggested pilot study; if the respondent was for or against a pilot study; who should decide about the pilot study; if there had been enough information about the study; and if the respondent had attended any meeting, signed any petition, contacted any politician, contacted or participated in mass media, or tried to influence anyone´s opinion on any issue concerning the pilot study. The respondents also had to state the issues they considered to be important to study in a pilot study. Furthermore the respondents had to give their opinion about a number of risks discussed in connection with disposal of nuclear waste in Oskarshamn. Other questions concerned the influence on job opportunities and tourism. Demographic items include age, gender, marital status, children, education, occupation, and trade union membership. Oskarshamn is one of the municipalities being discussed as a possible site for disposal of nuclear waste from the Swedish nuclear power plants, and there has been inquiries made for a pilot study in the area. In view of this the local council of Oskarshamn appointed a 'Youth team', consisting of ten young politicians from all political parties represented in the local council. The aim of the team was to inform and create debate among adolescents about how to store the radioactive waste from nuclear power plants. The purpose of this survey, addressed to young people in Oskarshamn, was to shed light on their opinion towards a pilot study and possible disposal of nuclear waste in Oskarshamn. The respondents had to answer questions about their opinion on the use of nuclear power in Sweden, if they believed nuclear power to be abolished by year 2010, and about their general interest in issues concerning energy and nuclear power. Other questions concerned risks associated with nuclear power, the influence different groups have/ought to have when it comes to disposal of nuclear waste, and if the respondent would accept a decision to dispose nuclear waste in Oskarshamn. A number of questions dealt with the suggested pilot study; if the respondent was for or against a pilot study; who should decide about the pilot study; if there had been enough information about the study; and if the respondent had attended any meeting, signed any petition, contacted any politician, contacted or participated in mass media, or tried to influence anyone's opinion on any issue concerning the pilot study. The respondents also had to state the issues they considered to be important to study in a pilot study. Furthermore the respondents had to give their opinion about a number of risks discussed in connection with disposal of nuclear waste in Oskarshamn. Other questions concerned the influence on job opportunities and tourism. Demographic items include age, gender, marital status, children, education, occupation, and trade union membership.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Swedish National Dat...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Swedish National Data Service
    Dataset . 1998
    Data sources: Datacite
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Swedish National Data Service
    Dataset . 1998
    Data sources: Datacite
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Swedish National Dat...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Swedish National Data Service
      Dataset . 1998
      Data sources: Datacite
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Swedish National Data Service
      Dataset . 1998
      Data sources: Datacite
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    Authors: Prof. Claude Pichard;

    Background and Aims: This study aims at evaluating the ease of use of the new calorimeter for the measurement of energy expenditure (EE) in intensive care unit (ICU) patients. EE in ICU patients is highly variable depending on the severity of the disease and treatments. Clinicians need to measure EE by indirect calorimetry (IC) to optimize nutritional support for the better clinical outcome. However, indirect calorimeters available on the market have insufficient accuracy for clinical and research use. Difficulties of handling and interpretation of results often limit IC in ICU patients. An accurate, easy-to-use calorimeter has been developed to meet these needs. The Study Device: The new calorimeter (Quark RMR 2.0, COSMED) is capable of IC measurements in mechanically ventilated patients without warm-up and limited calibration. The disposable in-line pneumotach flow meter and direct sampling of respiratory gas from the ventilator circuit enables the accurate measurement of oxygen consumption volume (VO2) and CO2 production volume (VCO2) to derive the energy expenditure. The software interface to manage the device and the collected data provides easy-to-use, user-friendly interface. This calorimeter bears an European Commission (EC) Conformity Mark, and will be used in the way it is intended to be used as described in the instruction manual. Currently used indirect calorimeters at each study center will be used as the comparator. This study will evaluate the ease of use of the new calorimeter (Quark RMR 2.0 (COSMED, Italy)) in intensive care unit (ICU) patients compared to currently used calorimeters (i.e. Quark RMR 1.0(COSMED, Italy) or Deltatrac Metabolic Monitor (Datex, Finland)), as well as the stability and the feasibility of the measurements in various clinically relevant situations. Time needed to prepare and start indirect calorimetry (IC) measurement will be compared as the measure of the ease of use of the calorimeter.

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    OpenTrials
    Clinical Trial . 2016
    Data sources: OpenTrials
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    OpenTrials
    Clinical Trial . 2016
    Data sources: OpenTrials
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    ClinicalTrials.gov
    Clinical Trial . 2016
    Data sources: ClinicalTrials.gov
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    ClinicalTrials.gov
    Clinical Trial . 2016
    Data sources: ClinicalTrials.gov
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      Clinical Trial . 2016
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      OpenTrials
      Clinical Trial . 2016
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      Clinical Trial . 2016
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      Clinical Trial . 2016
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    Authors: orcid bw Thiery, Wim;
    Thiery, Wim
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Thiery, Wim in OpenAIRE
    Lange, Stefan; Rogelj, Joeri; Schleussner, Carl-Friedrich; +33 Authors

    This data set contains the essential files used as input for the analysis, intermediate files produced during the analysis, and the key output fields. The code of the analysis is available here: https://github.com/VUB-HYDR/2021_Thiery_etal_Science Input fields: - isimip.zip: Postprocessed ISIMIP2b simulation output. This data set is very similar to the data presented in Lange et al. (2020 Earth's Future) but includes selected additional impact models and scenarios (notably RCP8.5). This data set also includes the gridded population data. - GMT_50pc_manualoutput_4pathways.xlsx: Global mean temperature anomaly trajectories from the IPCC SR15 - wcde_data.xlsx: postprocessed cohort size data originally obtained from the Wittgenstein Centre Human Capital Data Explorer. - WPP2019_MORT_F16_1_LIFE_EXPECTANCY_BY_AGE_BOTH_SEXES.xlsx: Postprocessed life expectancy data originally obtained from the UNited Nations World Population Programme Intermediate files *only use if you're interested in reproducing the results*: - workspaces.zip: Postprocessed ISIMIP2b simulation output. These matlab workspaces contain data on land area annually exposed to extreme events which is stored in a format designed to speed up the analysis. - mw_isimip.mat: ISIMIP2 simulations metadata (e.g. model, gcm and rcp name per simulation) - mw_countries.mat: information on the countries used in the analysis (e.g. border polygon coordinates) - mw_exposure.mat: age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic.mat: pre-industrial control age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic_coldwaves.mat: pre-industrial control age-dependent exposure to coldwaves computed from the ISIMIP and population data Output of the analysis: - mw_output.mat: Matlab workspace containing all variables produced during the analysis presented in thepaper. Use this file if you wish to look up certain numbers or want to use the study results for further analysis.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Volodin, Evgeny; Mortikov, Evgeny; Gritsun, Andrey; Lykossov, Vasily; +7 Authors

    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.INM.INM-CM4-8.piControl' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The INM-CM4-8 climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM4-8 (2x1.5; 180 x 120 longitude/latitude; 21 levels; top level sigma = 0.01), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E; 360 x 318 longitude/latitude; 40 levels; sigma vertical coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Leip, Adrian; Billen, Gilles; Garnier, Josette; Lassaletta, Luis; +6 Authors

    Table S1-1 Quantification of GHG and Nr flow intensities [kg CO2eq (kg product)-1 yr-1] or [g N (kg product)-1 yr-1] with the CAPRI N-LCA model for six main livestock products (BEEF: beef, PORK: pork, EGGS: eggs, POUM: poultry meat; DAIR: milk and dairy products, SGMP: meat from sheep and goats) and six main vegetable food groups (POTA: potatoes, SUGB: sugar beet before processing, OILP: oil seeds before processing; CERR: cereals, LEGU: leguminous crops) as well as other crops (OCRP) and aggregated livestock (ANIMP) and vegetable (CROPP) food. Table S2-1 Quantification of the main N budget flows in the EU25 agriculture sector

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    ZENODO
    Dataset . 2015
    License: CC BY
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    ZENODO
    Dataset . 2015
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2015
      License: CC BY
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      ZENODO
      Dataset . 2015
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    Authors: orcid bw Pajala, Gustav;
    Pajala, Gustav
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Pajala, Gustav in OpenAIRE

    The dataset includes the data used to produce figures in the main article ”Higher apparent gas transfer velocities for CO2 compared to CH4 in small lakes” and in the supplementary information. The dataset was originally published in DiVA and moved to SND in 2024. Se engelsk beskrivning för info. Datasetet har ursprungligen publicerats i DiVA och flyttades över till SND 2024.

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    Swedish National Data Service
    Dataset . 2022
    Data sources: Datacite
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    Swedish National Data Service
    Dataset . 2022
    Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2022
      Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2022
      Data sources: Datacite
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    Authors: orcid bw Gebruk, Anna;
    Gebruk, Anna
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Gebruk, Anna in OpenAIRE
    Dgebuadze, Polina; Rogozhin, Vladimir; Ermilova, Yulia; +2 Authors

    The dataset comprises full list of species of macrozoobenthos collected from the Pechora Sea (SE Barents Sea). Grab samples were collected from 10 stations in the Pechora Bay from aboard RV Kartesh in 2020-2021. Macrobenthic invertebrates were identified with the maximum level of certainty through optical microscopy using regional taxonomic keys. All taxonomic names were standardised using the World Register of Marine Species (WoRMS). All specimens have been counted and weighted (wet biomass) on Ohaus Adventurer scales with reported accuracy to 0.01 g. Bivalve molluscs and gastropods were weighed in shells. Biomass (g. m-2) and abundance (ind m-2) are used to characterise macrozoobenthos. The sampling and identification work was carried out in collaboration with specialists from Lomonosov Moscow State University Marine Research Center and P.P. Shirshov Institute of Oceanology.

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