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  • Energy Research
  • 15. Life on land
  • 1. No poverty
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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
    Authors: Mubasher Iqbal; Rukhsana Kalim; Shajara Ul-Durar; Arup Varma;

    Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

    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 Journal of Global Re...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
    Journal of Global Responsibility
    Article . 2023 . Peer-reviewed
    License: Emerald Insight Site Policies
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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 Journal of Global Re...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
      Journal of Global Responsibility
      Article . 2023 . Peer-reviewed
      License: Emerald Insight Site Policies
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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/
    Authors: Frédéric Chevallier; Pierre Regnier; Julia Pongratz; Atul K. Jain; +30 Authors

    Abstract. Regional land carbon budgets provide insights on the spatial distribution of the land uptake of atmospheric carbon dioxide, and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions, due to different definitions and component fluxes reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers, that connect CO2 uptake in one area with its release in another also requires better definition and protocols to reach harmonized regional budgets that can be summed up to the globe and compared with the atmospheric CO2 growth rate and inversion results. In this study, for the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims as an update of regional carbon budgets over the last two decades based on observations, for 10 regions covering the globe, with a better harmonization that the precursor project, we provide recommendations for using atmospheric inversions results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes and land use fluxes.

    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/ Université de Versai...arrow_drop_down
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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/
    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/
    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/
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    https://doi.org/10.5194/gmd-20...
    Article . 2020 . Peer-reviewed
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    Geoscientific Model Development (GMD)
    Article . 2022 . Peer-reviewed
    License: CC BY
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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/
    Geoscientific Model Development (GMD)
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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/
    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/
    Geoscientific Model Development
    Article . 2022
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    MPG.PuRe
    Article . 2020
    License: CC BY
    Data sources: MPG.PuRe
    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/
    Wageningen Staff Publications
    Article . 2022
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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/ Université de Versai...arrow_drop_down
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      https://doi.org/10.5194/gmd-20...
      Article . 2020 . Peer-reviewed
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      Data sources: Crossref
      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/
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      Geoscientific Model Development (GMD)
      Article . 2022 . Peer-reviewed
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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/
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      MPG.PuRe
      Article . 2020
      License: CC BY
      Data sources: MPG.PuRe
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      Wageningen Staff Publications
      Article . 2022
      License: CC BY
      https://dx.doi.org/10.60692/vq...
      Other literature type . 2020
      Data sources: Datacite
      https://dx.doi.org/10.60692/am...
      Other literature type . 2020
      Data sources: Datacite
      https://dx.doi.org/10.60692/bz...
      Other literature type . 2022
      Data sources: Datacite
      https://dx.doi.org/10.60692/zf...
      Other literature type . 2022
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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/
    Authors: French, Charles; Hunt, Chris O; Grima, Reuben; McLaughlin, Rowan; +2 Authors

    The ERC-funded FRAGSUS Project (Fragility and sustainability in small island environments: adaptation, cultural change and collapse in prehistory, 2013–18), led by Caroline Malone (Queens University Belfast) has explored issues of environmental fragility and Neolithic social resilience and sustainability during the Holocene period in the Maltese Islands. This, the first volume of three, presents the palaeo-environmental story of early Maltese landscapes. The project employed a programme of high-resolution chronological and stratigraphic investigations of the valley systems on Malta and Gozo. Buried deposits extracted through coring and geoarchaeological study yielded rich and chronologically controlled data that allow an important new understanding of environmental change in the islands. The study combined AMS radiocarbon and OSL chronologies with detailed palynological, molluscan and geoarchaeological analyses. These enable environmental reconstruction of prehistoric landscapes and the changing resources exploited by the islanders between the seventh and second millennia bc. The interdisciplinary studies combined with excavated economic and environmental materials from archaeological sites allows Temple landscapes to examine the dramatic and damaging impacts made by the first farming communities on the islands’ soil and resources. The project reveals the remarkable resilience of the soil-vegetational system of the island landscapes, as well as the adaptations made by Neolithic communities to harness their productivity, in the face of climatic change and inexorable soil erosion. Neolithic people evidently understood how to maintain soil fertility and cope with the inherently unstable changing landscapes of Malta. In contrast, second millennium bc Bronze Age societies failed to adapt effectively to the long-term aridifying trend so clearly highlighted in the soil and vegetation record. This failure led to severe and irreversible erosion and very different and short-lived socio-economic systems across the Maltese islands.

    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/ COREarrow_drop_down
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    Apollo
    Book . 2020
    License: CC BY NC ND
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      Apollo
      Book . 2020
      License: CC BY NC ND
      Data sources: Datacite
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    Authors: Katris, Antonios; Figus, Gioele; Greig, Alastair;

    This dataset currently consists of a single excel file which contains the Scottish Social Accounting Matrix for 2013, with households being disaggregated into quintiles based on their weekly income. The dataset has been used to study the impact of Energy Efficient Scotland programme and associated work that explored how the anticipated impacts may change due to Brexit

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    University of Strathclyde KnowledgeBase Datasets
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      University of Strathclyde KnowledgeBase Datasets
      Dataset . 2019
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  • Authors: Greenfield, L.M.; Graf, M.; Rengaraj, S.; Bargiela, R.; +4 Authors

    Data was either measured in situ in the field (N2O flux, soil moisture, rainfall and air temperature) or samples were taken, processed, and analysed in the laboratory (soil pH, electrical conductivity (EC), ammonium, nitrate, microbial community composition and crop yield). N2O flux data was measured on a mobile gas chromatograph (GC) system and integrated to obtain peak areas on Peak490Win10Canabis programme. The times, peak areas and sample ID were then exported into a .CHR file and imported into Flux.NET.3.3 which calculated N2O flux as an output in Excel which was exported as .csv file for deposit in EIDC. N2O flux was used to calculate cumulative N2O flux using trapezoidal integration in Excel and saved in a separate .csv file for deposit in EIDC. Soil moisture was measured on Accilmas with data stored as a .csv on a DataSnap that was downloaded and sorted by treatment and saved as a .csv file. Rainfall and air temperature were downloaded from the weather station as .csv file. Soil pH and EC were recorded manually into a notebook and input into an Excel spreadsheet and exported as a .csv file. Soil ammonium and nitrate content was measured using the microplate method using a programme called Gen5. Date was exported into an Excel spreadsheet and absorbance units used to calculate ammonium/nitrate content in milligrams per kilogram using a calibration curve from a set of standards in an Excel spreadsheet. This was exported as a .csv file. Crop growth data was recorded in the field in a notebook and input into an Excel spreadsheet and exported as a .csv file. Crop yield was recorded in a notebook and input into an Excel spreadsheet and exported as a .csv file. Microbial community composition was measured using 16S gene sequencing on an Illumina MiSeq. This generated raw sequencing reads which were processed using Python and filtered using QIIME v1.3.1. creating asv.count.table.csv of counts of each Amplicon Sequence Variants (ASVs) per sample and taxa.table.csv of the taxonomic lineage for each ASVs. This dataset contains field data on nitrous oxide (N2O) emissions, microbial community composition, crop yield and growth and soil biochemical properties. The field trial consisted of three different treatments of control, conventional microplastic addition and biodegradable microplastic addition where winter barley was grown. The data presented are from field and laboratory measurements. Data was collected by the data authors. The field trial was carried out from September 2020 to July 2021 at Henfaes Field Centre, UK. Research was funded through NERC Grant NE/V005871/1. Do agricultural microplastics undermine food security and sustainable development in developing countries?

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    Authors: Hermann Behling; John Carson; Bronwen S. Whitney; William D. Gosling; +12 Authors

    Abstract. An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation–climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

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    Authors: Leonardo S. Miranda; Vera L. Imperatriz-Fonseca; Tereza C. Giannini;

    Although the impacts of climate change on biodiversity are increasing worldwide, few studies have attempted to forecast these impacts on Amazon Tropical Forest. In this study, we estimated the impact of climate change on Amazonian avian assemblages considering range shifts, species loss, vulnerability of ecosystem functioning, future effectiveness of current protected areas and potential climatically stable areas for conservation actions. Species distribution modelling based on two algorithms and three different scenarios of climate change was used to forecast 501 avian species, organized on main ecosystem functions (frugivores, insectivores and nectarivores) for years 2050 and 2070. Considering the entire study area, we estimated that between 4 and 19% of the species will find no suitable habitat. Inside the currently established protected areas, species loss could be over 70%. Our results suggest that frugivores are the most sensitive guild, which could bring consequences on seed dispersal functions and on natural regeneration. Moreover, we identified the western and northern parts of the study area as climatically stable. Climate change will potentially affect avian assemblages in southeastern Amazonia with detrimental consequences to their ecosystem functions. Information provided here is essential to conservation practitioners and decision makers to help on planning their actions.

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  • Authors: Boulton, C.A.; Ritchie, P.D.L.;

    This dataset contains modelled vegetation carbon output from the land surface model JULES, along with the temperature and rainfall outputs (which were originally inputted) at a monthly, 1.5km resolution. There are four different JULES simulations, using two different climate projections (global climate sensitivity of 3.5K and highest global climate sensitivity of 7.1K) under a constant, present day atmospheric CO2 and a CO2 pathway that follows the SRES (Special Report on Emissions Scenarios) A1B scenario. JULES is a community developed land surface model, led by the UK Met Office and Centre for Ecology and Hydrology and is available for use after registering on the JULES repository (https://code.metoffice.gov.uk/trac/jules). The data produced using JULES was model version vn4.9 and the model configuration can be found on the Rose suite u-ao645 under the branch ‘transient_25km_drive’, available from https://code.metoffice.gov.uk/trac/roses-u (registration required).

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  • Authors: Grime, Philip; Fridley, Jason;

    The Buxton Climate Change Impacts study was established in 1992 on a steep daleside of calcareous grassland outside Buxton, Derbyshire, UK. In five replicate blocks of 3 x 3 m plots, the vegetation has been subjected to climate treatments of winter heating (3C above ambient, Nov-April), summer drought (no rain, July-Aug), summer augmented rainfaill (20% above the long-term average, June-Sept), and two interaction treatments (heating-drought, heating-watered) in addition to replicated controls. The grassland is maintained in a short turf to simulate sheep and cattle grazing each autumn (Oct). In addition to annual point quadrat touches conducted at the whole-plot (9 m2) scale, permanent microsite quadrats were established within each plot in 2008 at the 100 cm2 scale. Species cover and environmental parameters have been monitored in microsites annually (2009-2011 controls only). This data package contains microsite soil depth and pH data; another package contains species cover data.

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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/

    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.HighResMIP.MOHC.HadGEM3-GC31-MM.control-1950' 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 HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

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    World Data Center for Climate
    Dataset . 2023
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    Dataset . 2023
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    World Data Center for Climate
    Dataset . 2023
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      Dataset . 2023
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      World Data Center for Climate
      Dataset . 2023
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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
    Authors: Mubasher Iqbal; Rukhsana Kalim; Shajara Ul-Durar; Arup Varma;

    Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

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    Journal of Global Responsibility
    Article . 2023 . Peer-reviewed
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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 Journal of Global Re...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
      Journal of Global Responsibility
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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/
    Authors: Frédéric Chevallier; Pierre Regnier; Julia Pongratz; Atul K. Jain; +30 Authors

    Abstract. Regional land carbon budgets provide insights on the spatial distribution of the land uptake of atmospheric carbon dioxide, and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions, due to different definitions and component fluxes reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers, that connect CO2 uptake in one area with its release in another also requires better definition and protocols to reach harmonized regional budgets that can be summed up to the globe and compared with the atmospheric CO2 growth rate and inversion results. In this study, for the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims as an update of regional carbon budgets over the last two decades based on observations, for 10 regions covering the globe, with a better harmonization that the precursor project, we provide recommendations for using atmospheric inversions results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes and land use fluxes.

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    https://doi.org/10.5194/gmd-20...
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    Geoscientific Model Development (GMD)
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    MPG.PuRe
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    Wageningen Staff Publications
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      MPG.PuRe
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    Authors: French, Charles; Hunt, Chris O; Grima, Reuben; McLaughlin, Rowan; +2 Authors

    The ERC-funded FRAGSUS Project (Fragility and sustainability in small island environments: adaptation, cultural change and collapse in prehistory, 2013–18), led by Caroline Malone (Queens University Belfast) has explored issues of environmental fragility and Neolithic social resilience and sustainability during the Holocene period in the Maltese Islands. This, the first volume of three, presents the palaeo-environmental story of early Maltese landscapes. The project employed a programme of high-resolution chronological and stratigraphic investigations of the valley systems on Malta and Gozo. Buried deposits extracted through coring and geoarchaeological study yielded rich and chronologically controlled data that allow an important new understanding of environmental change in the islands. The study combined AMS radiocarbon and OSL chronologies with detailed palynological, molluscan and geoarchaeological analyses. These enable environmental reconstruction of prehistoric landscapes and the changing resources exploited by the islanders between the seventh and second millennia bc. The interdisciplinary studies combined with excavated economic and environmental materials from archaeological sites allows Temple landscapes to examine the dramatic and damaging impacts made by the first farming communities on the islands’ soil and resources. The project reveals the remarkable resilience of the soil-vegetational system of the island landscapes, as well as the adaptations made by Neolithic communities to harness their productivity, in the face of climatic change and inexorable soil erosion. Neolithic people evidently understood how to maintain soil fertility and cope with the inherently unstable changing landscapes of Malta. In contrast, second millennium bc Bronze Age societies failed to adapt effectively to the long-term aridifying trend so clearly highlighted in the soil and vegetation record. This failure led to severe and irreversible erosion and very different and short-lived socio-economic systems across the Maltese islands.

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    Apollo
    Book . 2020
    License: CC BY NC ND
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      Apollo
      Book . 2020
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    Authors: Katris, Antonios; Figus, Gioele; Greig, Alastair;

    This dataset currently consists of a single excel file which contains the Scottish Social Accounting Matrix for 2013, with households being disaggregated into quintiles based on their weekly income. The dataset has been used to study the impact of Energy Efficient Scotland programme and associated work that explored how the anticipated impacts may change due to Brexit

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    University of Strathclyde KnowledgeBase Datasets
    Dataset . 2019
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      University of Strathclyde KnowledgeBase Datasets
      Dataset . 2019
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  • Authors: Greenfield, L.M.; Graf, M.; Rengaraj, S.; Bargiela, R.; +4 Authors

    Data was either measured in situ in the field (N2O flux, soil moisture, rainfall and air temperature) or samples were taken, processed, and analysed in the laboratory (soil pH, electrical conductivity (EC), ammonium, nitrate, microbial community composition and crop yield). N2O flux data was measured on a mobile gas chromatograph (GC) system and integrated to obtain peak areas on Peak490Win10Canabis programme. The times, peak areas and sample ID were then exported into a .CHR file and imported into Flux.NET.3.3 which calculated N2O flux as an output in Excel which was exported as .csv file for deposit in EIDC. N2O flux was used to calculate cumulative N2O flux using trapezoidal integration in Excel and saved in a separate .csv file for deposit in EIDC. Soil moisture was measured on Accilmas with data stored as a .csv on a DataSnap that was downloaded and sorted by treatment and saved as a .csv file. Rainfall and air temperature were downloaded from the weather station as .csv file. Soil pH and EC were recorded manually into a notebook and input into an Excel spreadsheet and exported as a .csv file. Soil ammonium and nitrate content was measured using the microplate method using a programme called Gen5. Date was exported into an Excel spreadsheet and absorbance units used to calculate ammonium/nitrate content in milligrams per kilogram using a calibration curve from a set of standards in an Excel spreadsheet. This was exported as a .csv file. Crop growth data was recorded in the field in a notebook and input into an Excel spreadsheet and exported as a .csv file. Crop yield was recorded in a notebook and input into an Excel spreadsheet and exported as a .csv file. Microbial community composition was measured using 16S gene sequencing on an Illumina MiSeq. This generated raw sequencing reads which were processed using Python and filtered using QIIME v1.3.1. creating asv.count.table.csv of counts of each Amplicon Sequence Variants (ASVs) per sample and taxa.table.csv of the taxonomic lineage for each ASVs. This dataset contains field data on nitrous oxide (N2O) emissions, microbial community composition, crop yield and growth and soil biochemical properties. The field trial consisted of three different treatments of control, conventional microplastic addition and biodegradable microplastic addition where winter barley was grown. The data presented are from field and laboratory measurements. Data was collected by the data authors. The field trial was carried out from September 2020 to July 2021 at Henfaes Field Centre, UK. Research was funded through NERC Grant NE/V005871/1. Do agricultural microplastics undermine food security and sustainable development in developing countries?

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    Authors: Hermann Behling; John Carson; Bronwen S. Whitney; William D. Gosling; +12 Authors

    Abstract. An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation–climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

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    Climate of the Past (CP)
    Article . 2016 . Peer-reviewed
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    Climate of the Past
    Other literature type . 2018
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    Article . 2016
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    https://dx.doi.org/10.60692/ph...
    Other literature type . 2016
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    https://dx.doi.org/10.60692/0y...
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    Digital.CSIC
    Article . 2016 . Peer-reviewed
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      Climate of the Past
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      Article . 2016
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      https://dx.doi.org/10.60692/ph...
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      https://dx.doi.org/10.60692/0y...
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    Authors: Leonardo S. Miranda; Vera L. Imperatriz-Fonseca; Tereza C. Giannini;

    Although the impacts of climate change on biodiversity are increasing worldwide, few studies have attempted to forecast these impacts on Amazon Tropical Forest. In this study, we estimated the impact of climate change on Amazonian avian assemblages considering range shifts, species loss, vulnerability of ecosystem functioning, future effectiveness of current protected areas and potential climatically stable areas for conservation actions. Species distribution modelling based on two algorithms and three different scenarios of climate change was used to forecast 501 avian species, organized on main ecosystem functions (frugivores, insectivores and nectarivores) for years 2050 and 2070. Considering the entire study area, we estimated that between 4 and 19% of the species will find no suitable habitat. Inside the currently established protected areas, species loss could be over 70%. Our results suggest that frugivores are the most sensitive guild, which could bring consequences on seed dispersal functions and on natural regeneration. Moreover, we identified the western and northern parts of the study area as climatically stable. Climate change will potentially affect avian assemblages in southeastern Amazonia with detrimental consequences to their ecosystem functions. Information provided here is essential to conservation practitioners and decision makers to help on planning their actions.

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    Article . 2019 . Peer-reviewed
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    Article . 2020
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    Article . 2019
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  • Authors: Boulton, C.A.; Ritchie, P.D.L.;

    This dataset contains modelled vegetation carbon output from the land surface model JULES, along with the temperature and rainfall outputs (which were originally inputted) at a monthly, 1.5km resolution. There are four different JULES simulations, using two different climate projections (global climate sensitivity of 3.5K and highest global climate sensitivity of 7.1K) under a constant, present day atmospheric CO2 and a CO2 pathway that follows the SRES (Special Report on Emissions Scenarios) A1B scenario. JULES is a community developed land surface model, led by the UK Met Office and Centre for Ecology and Hydrology and is available for use after registering on the JULES repository (https://code.metoffice.gov.uk/trac/jules). The data produced using JULES was model version vn4.9 and the model configuration can be found on the Rose suite u-ao645 under the branch ‘transient_25km_drive’, available from https://code.metoffice.gov.uk/trac/roses-u (registration required).

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  • Authors: Grime, Philip; Fridley, Jason;

    The Buxton Climate Change Impacts study was established in 1992 on a steep daleside of calcareous grassland outside Buxton, Derbyshire, UK. In five replicate blocks of 3 x 3 m plots, the vegetation has been subjected to climate treatments of winter heating (3C above ambient, Nov-April), summer drought (no rain, July-Aug), summer augmented rainfaill (20% above the long-term average, June-Sept), and two interaction treatments (heating-drought, heating-watered) in addition to replicated controls. The grassland is maintained in a short turf to simulate sheep and cattle grazing each autumn (Oct). In addition to annual point quadrat touches conducted at the whole-plot (9 m2) scale, permanent microsite quadrats were established within each plot in 2008 at the 100 cm2 scale. Species cover and environmental parameters have been monitored in microsites annually (2009-2011 controls only). This data package contains microsite soil depth and pH data; another package contains species cover data.

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    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.HighResMIP.MOHC.HadGEM3-GC31-MM.control-1950' 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 HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

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    World Data Center for Climate
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    Dataset . 2023
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