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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: awit Diriba, Dawit;

    Household Surveys performed in four villages selected from Oromia, Amhara and Southern Nations, Nationalities, and Peoples’ Region (SNNPR) following from the ‘Ethiopian Rural Household Survey’ (ERHS) conducted in 2004.It contains detailed data on household consumption and expenditures, assets, income, agricultural activities, land allocation, demographic characteristics, and other variables. From September 2011 to January 2012 another survey of 221 households was conducted in three major regions of central and southern Ethiopia. At the time of this latest survey effort the most recent ERHS survey data available was from 2004. The selection of respondents, determination of sample size, and apportionment of the sample were based on a proportional sampling technique.In addition to addressing important questions from the ERHS survey data, the field survey was designed to generate detailed information on household biomass energy production and consumption practices; as well as farming activities; labour and land allocation; economic and demographic characteristics; and expenditures on food, non-food items, and energy. The 2011 survey effort collected detailed household biomass energy use data. The measurement of household biomass energy use was obtained in traditional units and later converted into kilograms. The conversion factors for each of the biomass were collected from the closest urban centre of each of the study areas. Information obtained on household biomass energy use was collected for a time period of one week before the survey was conducted. It was then aggregated into annual figures, although household biomass energy use may vary seasonally. Quality/Lineage: The data was collected by qualified enumerators who had participated in previous ERHS survey. In addition to myself I recruited assistant supervisor to check the accuracy and quality of data on daily basis and followup interview process closely. Before the survey commenced a pilot survey was conducted in each of the study areas to identify the different types of energy households are using and other critical variables of interest for the research. This information was used to revise and improve questionnaire. Moreover, a one day in-depth training was given to enumerators and assistant supervisor to enrich their deeper understanding of each the question in the survey and to further improve questionnaire from their earlier experiences in those villages. Purpose: Over 90% of Ethiopian rural population rely on biomass energy. However, biomass energy utilization is linked to household livelihood as in rural households produce and consume biomass energy simultaneously with other (on and off-farm)activities. With the rampant rate of deforestation that Ethiopia is facing it is important to investigate the effect of deforestation or fuelwood scarcity which is assumed affect household welfare through influence on wage and price. In light of this, the survey effort collected information on household use of biomass energy sources, expenditure and labour allocation choices and amount of labour time used for each activities.This helped me to investigate the effect of fuelwood scarcity on household welfare from three aspects: labour allocation decision, energy expenditure and fuel choice and biomass energy consumption behavior to better understand the related linkage of household production and utilization of biomass with livelihoods or food security. This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={c08e08aa-3055-4651-801b-0383610c1987}.

    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/ https://dx.doi.org/1...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/
    https://dx.doi.org/10.60507/fk...
    Dataset . 2023
    License: CC BY SA
    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/ https://dx.doi.org/1...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/
      https://dx.doi.org/10.60507/fk...
      Dataset . 2023
      License: CC BY SA
      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/
    Authors: Li, Ru; Perdana, Sigit; Vielle, Marc;

    This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 https://doi.org/10.1007/s11027-021-09960-7.

    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 . 2021
    License: CC BY
    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 . 2021
    License: CC BY
    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 . 2021
    License: CC BY
    Data sources: ZENODO
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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 . 2021
      License: CC BY
      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 . 2021
      License: CC BY
      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 . 2021
      License: CC BY
      Data sources: ZENODO
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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: Kerstin Wilde (10264166); Frans Hermans (3719845);

    In this paper, we investigate the promises that are employed within and around clusters that were formed in the evolving bioeconomy: bioclusters for short. Our paper aims to provide a conceptual clarification of the biocluster concept. To that effect, we employ the prism of sociotechnical imaginaries. We argue that both industrial clusters and the bioeconomy constitute separate, but partly overlapping sociotechnical imaginaries that shape stakeholder attitudes towards bioclusters. We applied a Q-methodology study in two bioeconomy clusters, one in Germany and one in The Netherlands, to investigate the resonance of different imaginaries in the cluster regions. Five distinct narratives, combining specific elements of cluster and bioeconomy imaginaries, are shared by different stakeholder groups. We revealed bioeconomy imaginaries at large to be far more contested than different cluster imaginaries. The latter mobilise overwhelmingly positive associations across diverse stakeholder groups. From this perspective, the popularity of biocluster promotional policies can be explained as they support some of the contested elements of bioeconomy imaginaries in gaining traction.

    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/ figsharearrow_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/
    figshare
    Dataset . 2021
    License: CC BY
    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/
    figshare
    Dataset . 2021
    License: CC BY
    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/
    Smithsonian figshare
    Dataset . 2021
    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/ figsharearrow_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/
      figshare
      Dataset . 2021
      License: CC BY
      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/
      figshare
      Dataset . 2021
      License: CC BY
      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/
      Smithsonian figshare
      Dataset . 2021
      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/
    Authors: Uckert, Götz; Hoffmann, Harry; Fasse, Anja; Gervas, Ewald Emil;

    We provide a dataset from a household survey in Mpanda region in Western Tanzania (N = 137) that was conducted in 2011. Household heads (or replacements) were interviewed. The topics addressed covered a broad range of socio-economic data and including, among others, household information (number of household members, age, sex, religion etc.), agricultural production (e.g. crops produced and livestock owned) including number and size of plots, income generation, energy access and owned assets.

    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/ https://dx.doi.org/1...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/
    https://dx.doi.org/10.4228/zal...
    Dataset . 2019
    License: CC BY
    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/ https://dx.doi.org/1...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/
      https://dx.doi.org/10.4228/zal...
      Dataset . 2019
      License: CC BY
      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/

    This is a repository of global and regional human population data collected from: the databases of scenarios assessed by the Intergovernmental Panel on Climate Change (Sixth Assessment Report, Special Report on 1.5 C; Fifth Assessment Report), multi-national databases of population projections (World Bank, International Database, United Nation population projections), and other very long-term population projections (Resources for the Future). More specifically, it contains: - in `other_pop_data` folder files from World Bank, the International Database from the US Census, and from IHME - in the `SSP` folder, the Shared Socioeconomic Pathways, as in the version 2.0 downloaded from IIASA and as in the version 3.0 downloaded from IIASA workspace - in the `UN` folder, the demographic projections from UN - `IAMstat.xlsx`, an overview file of the metadata accompanying the scenarios present in the IPCC databases - `RFF.csv`, an overview file containing the population projections obtained by Resources For the Future '- the remaining `.csv` files with names `AR6#`, `AR5#`, `IAMC15#` contain the IPCC scenarios assessed by the IPCC for preparing the IPCC assessment reports. They can be downloaded from AR5, SR 1.5, and AR6 This data in intended to be downloaded for use together with the package downloadable here. The dataset was used as a supporting material for the paper "Underestimating demographic uncertainties in the synthesis process of the IPCC" accepted on npj Climate Action (DOI : 10.1038/s44168-024-00152-y).

    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
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    ZENODO
    Dataset . 2024
    License: CC BY
    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 . 2024
    License: CC BY
    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 . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    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 . 2023
    License: CC BY
    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 . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      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 . 2024
      License: CC BY
      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 . 2024
      License: CC BY
      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 . 2023
      License: CC BY
      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 . 2023
      License: CC BY
      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 . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Boer, Lukas;

    Diese Dissertation beantwortet verschiedene politikrelevante ökonomische Fragen in den Bereichen Handelspolitik, Geldpolitik, sowie Rohstoffmärkte und Energieökonomik mit Hilfe von strukturellen Vektorautoregressionsmodellen (SVAR). SVARs stellen eine effektive Möglichkeit dar, die Beziehungen zwischen verschiedenen makroökonomischen und/oder Finanzmarkt-Variablen zu modellieren und werden verwendet, um die dynamischen kausalen Effekte von ökonomischen Schocks zu schätzen. Für jede ökonomische Fragestellung wird eine Identifikationsstrategie angewandt, die auf die betrachteten Daten und ihre statistischen Eigenschaften sowie die zugrundeliegenden Annahmen über ökonomische Mechanismen zwischen den betrachteten Zeitreihen zugeschnitten ist. Im Einzelnen besteht diese Dissertation aus vier Kapiteln. In den ersten beiden Kapiteln werden die Auswirkungen von Handelspolitik auf Finanzmärkte und auf die Makroökonomie geschätzt. Das dritte Kapitel liefert einen methodischen Beitrag zur SVAR-Literatur, der in einer Anwendung zu den Effekten von Geldpolitik dargestellt wird. Das letzte Kapitel verlässt die Felder der Handels- und Geldpolitik und wendet sich Rohstoffmärkten und der Energiewirtschaft zu, stützt sich dabei aber ebenfalls auf Zeitreihenmethoden. Es analysiert die Rolle von Metallen in der Energiewende. This dissertation answers various policy relevant economic questions in the fields of trade policy, monetary policy, and commodity markets and energy economics using structural vector autoregression (SVAR) models. SVARs constitute a parsimonious way to model the relations between different macroeconomic and/or financial variables and they are used to estimate the dynamic causal effects of economic shocks. For each economic question, this dissertation applies an identification strategy that is tailored to the relevant data and its statistical properties as well as the underlying assumptions about economic mechanisms among the regarded time series. Specifically, this dissertation consists of four chapters. The first two chapters estimate the effects of trade policy on financial markets and on the macroeconomy. The third chapter makes a methodological contribution to the SVAR literature in an application to monetary policy shocks. The final chapter moves away from trade and monetary policy to commodity markets and energy economics but also relies on time series methods. It analyzes the role of metals for the clean energy transition.

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    Authors: Xiaogang Pan; Kangli Liu; Jianhua Wang; Yutao Hu; +1 Authors

    The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

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    Sustainability
    Article . 2023 . Peer-reviewed
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    Authors: Patrizia Ghisellini; Amos Ncube; Gianni D’Ambrosio; Renato Passaro; +1 Authors

    In this study, our aim was to explore the potential energy savings obtainable from the recycling of 1 tonne of Construction and Demolition Waste (C&DW) generated in the Metropolitan City of Naples. The main fraction composing the functional unit are mixed C&DW, soil and stones, concrete, iron, steel and aluminium. The results evidence that the recycling option for the C&DW is better than landfilling as well as that the production of recycled aggregates is environmentally sustainable since the induced energy and environmental impacts are lower than the avoided energy and environmental impacts in the life cycle of recycled aggregates. This LCA study shows that the transition to the Circular Economy offers many opportunities for improving the energy and environmental performances of the construction sector in the life cycle of construction materials by means of internal recycling strategies (recycling C&DW into recycled aggregates, recycled steel, iron and aluminum) as well as external recycling by using input of other sectors (agri-food by-products) for the manufacturing of construction materials. In this way, the C&D sector also contributes to realizing the energy and bioeconomy transition by disentangling itself from fossil fuel dependence.

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    Energies
    Article . 2021 . Peer-reviewed
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    Authors: Scholl, Hans J.; Scholl, Margit C.;

    In the early 21st century, societies and their governments around the world have been meeting unprecedented challenges, many of which surpass the capacities, capabilities, and reaches of their traditional institutions and their classical processes of governing. Among these challenges are the need for an accelerated transition of the global economy from its current fossil fuel basis to renewable energies, the so-called post-carbon era also known as the third industrial revolution, the containment and reduction of government spending and debt financing, the increasing rapidity of market changes, and the expanding lag of timely interventions via traditional lawmaking and government action. While upholding the proven principles of Western democracy, democratic self-governance in 21st century market economies apparently needs to develop new institutional formats and novel mechanisms for staying abreast with the systemic dynamics of a tightly interconnected global society. We claim that actionable and omnipresent information along with its underlying technologies are substantial prerequisites and backbones for developing models of smart (democratic) governance, which foster smart, open, and agile governmental institutions as well as stakeholder participation and collaboration on all levels and in all branches of the governing process. We present and discuss an agenda for research and practice, which advances the concept of smart, open, and participatory government of the 21st century.

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    Authors: Héctor Morales-Muñoz; Arwen Bailey; Katharina Löhr; Giulia Caroli; +5 Authors

    Climate disasters affect human security and development, moreso in fragile and conflict-affected contexts where population’ capacities to cope with climate change are compromised. Responses to such crises lie at the nexus of humanitarian assistance, development, and peacebuilding. Yet, there are still too few integrated programmatic responses coordinating peacebuilding and climate actions to ensure a progressive human development. This research develops a multi-scalar model to help actors identify thematic areas to inform synergistic efforts and programs at different scales to better coordinate their actions. Findings suggest that climate action and peacebuilding sectors can coordinate actions around climate and conflict risk assessments, the management of land and water resources, ecosystem restoration, nature-based climate adaptation, climate and conflict smart agriculture, natural resources governance, and sustainable market development. These collaborative efforts have the potential to generate co-benefits, such as increased social cohesion and livelihood creation.

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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: awit Diriba, Dawit;

    Household Surveys performed in four villages selected from Oromia, Amhara and Southern Nations, Nationalities, and Peoples’ Region (SNNPR) following from the ‘Ethiopian Rural Household Survey’ (ERHS) conducted in 2004.It contains detailed data on household consumption and expenditures, assets, income, agricultural activities, land allocation, demographic characteristics, and other variables. From September 2011 to January 2012 another survey of 221 households was conducted in three major regions of central and southern Ethiopia. At the time of this latest survey effort the most recent ERHS survey data available was from 2004. The selection of respondents, determination of sample size, and apportionment of the sample were based on a proportional sampling technique.In addition to addressing important questions from the ERHS survey data, the field survey was designed to generate detailed information on household biomass energy production and consumption practices; as well as farming activities; labour and land allocation; economic and demographic characteristics; and expenditures on food, non-food items, and energy. The 2011 survey effort collected detailed household biomass energy use data. The measurement of household biomass energy use was obtained in traditional units and later converted into kilograms. The conversion factors for each of the biomass were collected from the closest urban centre of each of the study areas. Information obtained on household biomass energy use was collected for a time period of one week before the survey was conducted. It was then aggregated into annual figures, although household biomass energy use may vary seasonally. Quality/Lineage: The data was collected by qualified enumerators who had participated in previous ERHS survey. In addition to myself I recruited assistant supervisor to check the accuracy and quality of data on daily basis and followup interview process closely. Before the survey commenced a pilot survey was conducted in each of the study areas to identify the different types of energy households are using and other critical variables of interest for the research. This information was used to revise and improve questionnaire. Moreover, a one day in-depth training was given to enumerators and assistant supervisor to enrich their deeper understanding of each the question in the survey and to further improve questionnaire from their earlier experiences in those villages. Purpose: Over 90% of Ethiopian rural population rely on biomass energy. However, biomass energy utilization is linked to household livelihood as in rural households produce and consume biomass energy simultaneously with other (on and off-farm)activities. With the rampant rate of deforestation that Ethiopia is facing it is important to investigate the effect of deforestation or fuelwood scarcity which is assumed affect household welfare through influence on wage and price. In light of this, the survey effort collected information on household use of biomass energy sources, expenditure and labour allocation choices and amount of labour time used for each activities.This helped me to investigate the effect of fuelwood scarcity on household welfare from three aspects: labour allocation decision, energy expenditure and fuel choice and biomass energy consumption behavior to better understand the related linkage of household production and utilization of biomass with livelihoods or food security. This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={c08e08aa-3055-4651-801b-0383610c1987}.

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    https://dx.doi.org/10.60507/fk...
    Dataset . 2023
    License: CC BY SA
    Data sources: Datacite
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      https://dx.doi.org/10.60507/fk...
      Dataset . 2023
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    Authors: Li, Ru; Perdana, Sigit; Vielle, Marc;

    This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 https://doi.org/10.1007/s11027-021-09960-7.

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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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    Authors: Kerstin Wilde (10264166); Frans Hermans (3719845);

    In this paper, we investigate the promises that are employed within and around clusters that were formed in the evolving bioeconomy: bioclusters for short. Our paper aims to provide a conceptual clarification of the biocluster concept. To that effect, we employ the prism of sociotechnical imaginaries. We argue that both industrial clusters and the bioeconomy constitute separate, but partly overlapping sociotechnical imaginaries that shape stakeholder attitudes towards bioclusters. We applied a Q-methodology study in two bioeconomy clusters, one in Germany and one in The Netherlands, to investigate the resonance of different imaginaries in the cluster regions. Five distinct narratives, combining specific elements of cluster and bioeconomy imaginaries, are shared by different stakeholder groups. We revealed bioeconomy imaginaries at large to be far more contested than different cluster imaginaries. The latter mobilise overwhelmingly positive associations across diverse stakeholder groups. From this perspective, the popularity of biocluster promotional policies can be explained as they support some of the contested elements of bioeconomy imaginaries in gaining traction.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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    Authors: Uckert, Götz; Hoffmann, Harry; Fasse, Anja; Gervas, Ewald Emil;

    We provide a dataset from a household survey in Mpanda region in Western Tanzania (N = 137) that was conducted in 2011. Household heads (or replacements) were interviewed. The topics addressed covered a broad range of socio-economic data and including, among others, household information (number of household members, age, sex, religion etc.), agricultural production (e.g. crops produced and livestock owned) including number and size of plots, income generation, energy access and owned assets.

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    https://dx.doi.org/10.4228/zal...
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      https://dx.doi.org/10.4228/zal...
      Dataset . 2019
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    This is a repository of global and regional human population data collected from: the databases of scenarios assessed by the Intergovernmental Panel on Climate Change (Sixth Assessment Report, Special Report on 1.5 C; Fifth Assessment Report), multi-national databases of population projections (World Bank, International Database, United Nation population projections), and other very long-term population projections (Resources for the Future). More specifically, it contains: - in `other_pop_data` folder files from World Bank, the International Database from the US Census, and from IHME - in the `SSP` folder, the Shared Socioeconomic Pathways, as in the version 2.0 downloaded from IIASA and as in the version 3.0 downloaded from IIASA workspace - in the `UN` folder, the demographic projections from UN - `IAMstat.xlsx`, an overview file of the metadata accompanying the scenarios present in the IPCC databases - `RFF.csv`, an overview file containing the population projections obtained by Resources For the Future '- the remaining `.csv` files with names `AR6#`, `AR5#`, `IAMC15#` contain the IPCC scenarios assessed by the IPCC for preparing the IPCC assessment reports. They can be downloaded from AR5, SR 1.5, and AR6 This data in intended to be downloaded for use together with the package downloadable here. The dataset was used as a supporting material for the paper "Underestimating demographic uncertainties in the synthesis process of the IPCC" accepted on npj Climate Action (DOI : 10.1038/s44168-024-00152-y).

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    ZENODO
    Dataset . 2024
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    Data sources: Datacite
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    ZENODO
    Dataset . 2024
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    ZENODO
    Dataset . 2024
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    ZENODO
    Dataset . 2023
    License: CC BY
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    ZENODO
    Dataset . 2023
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    ZENODO
    Dataset . 2023
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      Dataset . 2024
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      Dataset . 2024
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      Dataset . 2024
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      ZENODO
      Dataset . 2023
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      ZENODO
      Dataset . 2023
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      Data sources: Datacite
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      ZENODO
      Dataset . 2023
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    Authors: Boer, Lukas;

    Diese Dissertation beantwortet verschiedene politikrelevante ökonomische Fragen in den Bereichen Handelspolitik, Geldpolitik, sowie Rohstoffmärkte und Energieökonomik mit Hilfe von strukturellen Vektorautoregressionsmodellen (SVAR). SVARs stellen eine effektive Möglichkeit dar, die Beziehungen zwischen verschiedenen makroökonomischen und/oder Finanzmarkt-Variablen zu modellieren und werden verwendet, um die dynamischen kausalen Effekte von ökonomischen Schocks zu schätzen. Für jede ökonomische Fragestellung wird eine Identifikationsstrategie angewandt, die auf die betrachteten Daten und ihre statistischen Eigenschaften sowie die zugrundeliegenden Annahmen über ökonomische Mechanismen zwischen den betrachteten Zeitreihen zugeschnitten ist. Im Einzelnen besteht diese Dissertation aus vier Kapiteln. In den ersten beiden Kapiteln werden die Auswirkungen von Handelspolitik auf Finanzmärkte und auf die Makroökonomie geschätzt. Das dritte Kapitel liefert einen methodischen Beitrag zur SVAR-Literatur, der in einer Anwendung zu den Effekten von Geldpolitik dargestellt wird. Das letzte Kapitel verlässt die Felder der Handels- und Geldpolitik und wendet sich Rohstoffmärkten und der Energiewirtschaft zu, stützt sich dabei aber ebenfalls auf Zeitreihenmethoden. Es analysiert die Rolle von Metallen in der Energiewende. This dissertation answers various policy relevant economic questions in the fields of trade policy, monetary policy, and commodity markets and energy economics using structural vector autoregression (SVAR) models. SVARs constitute a parsimonious way to model the relations between different macroeconomic and/or financial variables and they are used to estimate the dynamic causal effects of economic shocks. For each economic question, this dissertation applies an identification strategy that is tailored to the relevant data and its statistical properties as well as the underlying assumptions about economic mechanisms among the regarded time series. Specifically, this dissertation consists of four chapters. The first two chapters estimate the effects of trade policy on financial markets and on the macroeconomy. The third chapter makes a methodological contribution to the SVAR literature in an application to monetary policy shocks. The final chapter moves away from trade and monetary policy to commodity markets and energy economics but also relies on time series methods. It analyzes the role of metals for the clean energy transition.

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    Authors: Xiaogang Pan; Kangli Liu; Jianhua Wang; Yutao Hu; +1 Authors

    The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

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    Sustainability
    Article . 2023 . Peer-reviewed
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    Authors: Patrizia Ghisellini; Amos Ncube; Gianni D’Ambrosio; Renato Passaro; +1 Authors

    In this study, our aim was to explore the potential energy savings obtainable from the recycling of 1 tonne of Construction and Demolition Waste (C&DW) generated in the Metropolitan City of Naples. The main fraction composing the functional unit are mixed C&DW, soil and stones, concrete, iron, steel and aluminium. The results evidence that the recycling option for the C&DW is better than landfilling as well as that the production of recycled aggregates is environmentally sustainable since the induced energy and environmental impacts are lower than the avoided energy and environmental impacts in the life cycle of recycled aggregates. This LCA study shows that the transition to the Circular Economy offers many opportunities for improving the energy and environmental performances of the construction sector in the life cycle of construction materials by means of internal recycling strategies (recycling C&DW into recycled aggregates, recycled steel, iron and aluminum) as well as external recycling by using input of other sectors (agri-food by-products) for the manufacturing of construction materials. In this way, the C&D sector also contributes to realizing the energy and bioeconomy transition by disentangling itself from fossil fuel dependence.

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    Authors: Scholl, Hans J.; Scholl, Margit C.;

    In the early 21st century, societies and their governments around the world have been meeting unprecedented challenges, many of which surpass the capacities, capabilities, and reaches of their traditional institutions and their classical processes of governing. Among these challenges are the need for an accelerated transition of the global economy from its current fossil fuel basis to renewable energies, the so-called post-carbon era also known as the third industrial revolution, the containment and reduction of government spending and debt financing, the increasing rapidity of market changes, and the expanding lag of timely interventions via traditional lawmaking and government action. While upholding the proven principles of Western democracy, democratic self-governance in 21st century market economies apparently needs to develop new institutional formats and novel mechanisms for staying abreast with the systemic dynamics of a tightly interconnected global society. We claim that actionable and omnipresent information along with its underlying technologies are substantial prerequisites and backbones for developing models of smart (democratic) governance, which foster smart, open, and agile governmental institutions as well as stakeholder participation and collaboration on all levels and in all branches of the governing process. We present and discuss an agenda for research and practice, which advances the concept of smart, open, and participatory government of the 21st century.

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    Authors: Héctor Morales-Muñoz; Arwen Bailey; Katharina Löhr; Giulia Caroli; +5 Authors

    Climate disasters affect human security and development, moreso in fragile and conflict-affected contexts where population’ capacities to cope with climate change are compromised. Responses to such crises lie at the nexus of humanitarian assistance, development, and peacebuilding. Yet, there are still too few integrated programmatic responses coordinating peacebuilding and climate actions to ensure a progressive human development. This research develops a multi-scalar model to help actors identify thematic areas to inform synergistic efforts and programs at different scales to better coordinate their actions. Findings suggest that climate action and peacebuilding sectors can coordinate actions around climate and conflict risk assessments, the management of land and water resources, ecosystem restoration, nature-based climate adaptation, climate and conflict smart agriculture, natural resources governance, and sustainable market development. These collaborative efforts have the potential to generate co-benefits, such as increased social cohesion and livelihood creation.

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