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13 results for “national contributions”
National contributions to climate change due to historical emissions of carbon dioxide, methane and nitrous oxide
<p>A complete description of the dataset is given by <a href="http://doi.org/10.1038/s41597-023-02041-1">Jones et al. (2023)</a>. Key information is provided below.</p> <p><strong>Background</strong></p> <p>A dataset describing the global warming response to national emissions CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O from fossil and land use sources during 1851-2021.</p> <p>National CO<sub>2 </sub>emissions data are collated from the Global Carbon Project (Andrew and Peters, 2024; Friedlingstein et al., 2024). </p> <p>National CH<sub>4</sub> and N<sub>2</sub>O emissions data are collated from PRIMAP-hist (HISTTP) (Gütschow et al., 2024).</p> <p>We construct a time series of cumulative CO2-equivalent emissions for each country, gas, and emissions source (fossil or land use). Emissions of CH<sub>4</sub> and N<sub>2</sub>O emissions are related to cumulative CO2-equivalent emissions using the Global Warming Potential (GWP*) approach, with best-estimates of the coefficients taken from the IPCC AR6 (Forster et al., 2021).</p> <p>Warming in response to cumulative CO2-equivalent emissions is estimated using the transient climate response to cumulative carbon emissions (TCRE) approach, with best-estimate value of TCRE taken from the IPCC AR6 (Forster et al., 2021, Canadell et al., 2021). 'Warming' is specifically the change in global mean surface temperature (GMST).</p> <p>The data files provide emissions, cumulative emissions and the GMST response by country, gas (CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O or 3-GHG total) and source (fossil emissions, land use emissions or the total).</p> <p><strong>Data records: overview</strong></p> <p>The data records include three comma separated values (.csv) files as described below.</p> <p>All files are in ‘long’ format with one value provided in the <em>Data</em> column for each combination of the categorical variables <em>Year, Country Name, Country ISO3 code, Gas, and Component</em> columns.</p> <p><em>Component</em> specifies fossil emissions, LULUCF emissions or total emissions of the gas.</p> <p><em>Gas</em> specifies CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O or the three-gas total (labelled 3-GHG).</p> <p><em>Country ISO3 codes</em> are specifically the unique ISO 3166-1 alpha-3 codes of each country.</p> <p><strong>Data records: specifics</strong></p> <p>Data are provided relative to 2 reference years (denoted <em>ref_year </em>below): 1850 and 1991. 1850 is a mutual first year of data spanning all input datasets. 1991 is relevant because the United Nations Framework Convention on Climate Change was operationalised in 1992.</p> <p><em>EMISSIONS_ANNUAL_{ref_year-20}-2023.csv:</em> <em>Data </em>includes annual emissions of CO<sub>2</sub> (Pg CO<sub>2</sub> year<sup>-1</sup>), CH<sub>4</sub> (Tg CH<sub>4</sub> year<sup>-1</sup>) and N<sub>2</sub>O (Tg N<sub>2</sub>O year<sup>-1</sup>) during the period <em>ref_year-20 </em>to 2023. The <em>Data</em> column provides values for every combination of the categorical variables. Data are provided from <em>ref_year-20</em> because these data are required to calculate GWP* for CH<sub>4</sub>.</p> <p><em>EMISSIONS_CUMULATIVE_CO2e100_{ref_year+1}-2023.csv: Data </em>includes the cumulative CO<sub>2</sub> equivalent emissions in units Pg CO<sub>2</sub>-e<sub>100</sub> during the period <em>ref_year+1</em> to 2023 (i.e. since the reference year). The <em>Data</em> column provides values for every combination of the categorical variables. </p> <p><em>GMST_response_{ref_year+1}-2023.csv:</em> <em>Data</em> includes the change in global mean surface temperature (GMST) due to emissions of the three gases in units °C during the period <em>ref_year+1</em> to 2023 (i.e. since the reference year). The <em>Data</em> column provides values for every combination of the categorical variables. </p> <p><strong>Accompanying Code</strong></p> <p>Code is available at: <a href="https://github.com/jonesmattw/National_Warming_Contributions">https://github.com/jonesmattw/National_Warming_Contributions</a> .</p> <p>The code requires Input.zip to run (see README at the GitHub link).</p> <p><strong>Further info: Country Groupings</strong></p> <p>We also provide estimates of the contributions of various country groupings as defined by the UNFCCC:</p> <ul> <li>Annex I countries (number of countries, n = 42)</li> <li>Annex II countries (n = 23)</li> <li>economies in transition (EITs; n = 15)</li> <li>the least developed countries (LDCs; n = 47)</li> <li>the like-minded developing countries (LMDC; n = 24).</li> </ul> <p>And other country groupings:</p> <ul> <li>the organisation for economic co-operation and development (OECD; n = 38)</li> <li>the European Union (EU27 post-Brexit)</li> <li>the Brazil, South Africa, India and China (BASIC) group.</li> </ul> <p>See COUNTRY_GROUPINGS.xlsx for the lists of countries in each group.</p>
Data of Survey on National Contributions to EOSC 2022
<p>This is the data set of the annual survey on National Contributions to EOSC 2022 for the EOSC Steering Board</p><p>The annual survey on National Contributions to EOSC was developed by the EOSC Future project and EOSC Steering Board to monitor policies, practices, and impacts related to EOSC and Open Science at national and institutional levels in Europe</p><p>The annual survey for 2022 was published in the EOSC Observatory on 19 January 2023 and ran until 09 June 2023 whereby 32 member states and associated countries in Europe responded to the survey</p><p>The data of the annual survey for 2022 is now available and exploitable in the online dashboard of the EOSC Observatory developed by Technopolis Group and OpenAIRE: [<a href="https://eoscobservatory.eosc-portal.eu">https://eoscobservatory.eosc-portal.eu</a>]</p><p>Disclaimer: The annual survey on National Contributions to EOSC is in an initial stage of implementation and will be improved in future iterations whereby the data should for now be taken as a best-effort attempt by participating countries</p>
Data of Survey on National Contributions to EOSC and Open Science 2023
<p>This is the data set of the annual survey on National Contributions to EOSC and Open Science 2023 for the EOSC Steering Board</p> <p>The annual survey on National Contributions to EOSC and Open Science was developed by the EOSC Future project and EOSC Steering Board to monitor policies, practices, and impacts related to EOSC and Open Science at national and institutional levels in Europe</p> <p>The annual survey for 2023 was published in the EOSC Open Science Observatory on 17 January 2024 and ran until 01 July 2024 whereby 32 European member states, associated countries, and other countries responded to the survey</p> <p>The data of the annual survey for 2023 is available and exploitable in the online dashboard of the EOSC Open Science Observatory developed by Technopolis Group and OpenAIRE in the EOSC Future project and continued in the EOSC Track project: [<a href="https://eoscobservatory.eosc-portal.eu">https://eoscobservatory.eosc-portal.eu</a>]</p> <p>Disclaimer 1: The annual survey on National Contributions to EOSC and Open Science is in an initial stage of implementation and will be improved in future iterations whereby the data should for now be taken as a best-effort attempt by participating countries</p> <p>Disclaimer 2: V1 of the data set included an error in the data set and has thus been restricted and replaced by an updated V2 of the data set</p>
Data of Survey on National Contributions to EOSC 2021
<p>This is the data set from the EOSC Steering Board pilot survey on National Contributions to EOSC 2021</p> <p>The annual survey on National Contributions to EOSC monitors policies, practices, and impacts related to EOSC and Open Science at national and institutional levels in Europe</p> <p>The pilot survey for 2021 was published and the data was collected and is now available in the online dashboard of the EOSC Observatory: [<a href="https://eoscobservatory.eosc-portal.eu">https://eoscobservatory.eosc-portal.eu</a>]</p> <p>This data set has removed confidential information on financial estimations in questions 4-14 and also descriptions of use cases in question 19 which will be presented in an EOSC Catalogue of Best Practices</p>
Nationally Determined Contributions (Latest submissions)
<p>Links to the latest (up to October 2021) national climate action plans under the Paris Agreement</p>
Figures 2-3 in Contributions to the Zerconidae (Acari: Mesostigmata) fauna of Dilek Peninsula-Büyük Menderes Delta National Park, Türkiye
Figures 2-3. Dorsal views of deutonymph specimens 2. Zercon andrei, 3. Zercon plumatopilus. Scale bar 100.
Figures 8-9 in Contributions to the Zerconidae (Acari: Mesostigmata) fauna of Dilek Peninsula-Büyük Menderes Delta National Park, Türkiye
Figures 8-9. Dorsal views of immature stages of Zercon dilekensis sp. nov. 8. Deutonymph, 9. Protonymph. Scale bar 100.
Material Efficiency Policy and Nationally Determined Contributions
<p>This is a table containing the data used to create Table 4, Number of G20 countries that include energy or material efficiency commitments in 2nd round of National Determined Contributions in the paper, Policy for material efficiency: Enabling new climate change mitigation strategies by Lifset et al.</p>
Data from: Do failures in non-technical skills contribute to fatal medical accidents in Japan? A review of the 2010–2013 national accident reports
Objectives: We sought to clarify how large a proportion of fatal medical accidents can be considered to be caused by poor Non-Technical Skills, and to support development of a policy to reduce numbers of such accidents by making recommendations about possible training requirements. Design: Summaries of reports of fatal medical accidents, published by the Japan Medical Safety Research Organization, were reviewed individually. Three experienced clinicians and one patient safety expert conducted the reviews to determine the cause of death. Views of the patient safety expert were given additional weight in the overall determination. Setting: A total of 73 summary reports of fatal medical accidents were reviewed. These reports had been submitted by healthcare organisations across Japan to the Japan Medical Safety Research Organization between April 2010 and March 2013. Primary and secondary outcome measures: The cause of death in fatal medical accidents, categorised into technical skills, non-technical skills, and inevitable progress of disease were evaluated. Non-technical skills were further sub-divided into situation awareness, decision-making, communication, team working, leadership, managing stress, and coping with fatigue. Results: Overall, the cause of death was identified as non-technical skills in 34 cases (46.6%), disease progression in 33 cases (45.2%), and technical skills in two cases (5.5%). In two cases, no consensual determination could be achieved. Further categorisation of cases of non-technical skills were identified 14 cases (41.2%) of problems with situation awareness, eight (23.5%) with team-working, and three (8.8%) with decision-making. These three sub-categories, or combinations of them, were identified as the cause of death in 33 cases (97.1%). Conclusions: Poor non-technical skills were considered to be a significant cause of adverse events in nearly half of the fatal medical accidents examined. Improving non-technical skills may be effective for reducing accidents, and training in particular sub-categories of non-technical skills may be especially relevant.
Figures 4-7 in Contributions to the Zerconidae (Acari: Mesostigmata) fauna of Dilek Peninsula-Büyük Menderes Delta National Park, Türkiye
Figures 4-7. Zercon dilekensis sp. nov. 4. Dorsal view of female, 5. Ventral view of female, 6. Dorsal view of male, 7. Ventral view of male. Scale bar 100.
Figure 1 in Contributions to the Zerconidae (Acari: Mesostigmata) fauna of Dilek Peninsula-Büyük Menderes Delta National Park, Türkiye
Figure 1. Location of Dilek Peninsula-Büyük Menderes Delta National Park in Türkiye and sampling sites for zerconid mites in the study area (sampling sites were shown with yellow dots).
Data from: Do failures in non-technical skills contribute to fatal medical accidents in Japan? A review of the 2010–2013 national accident reports
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Occupational and Environmental Origins of ANCA Vasculitis: Contribution of Data From the National Network for Vigilance and Prevention of Occupational Pathologies (RNV3P)
ClinicalTrials.gov study NCT05416723. IPD Sharing: YES. Countries: 1. Publications: 0.
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