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Within design of information and communication technology (ICT) we need to first shape and then follow a vision to take responsibility for the futures that design materializes. Although research and literature on both sustainable technology and sustainable interaction design grow significantly, both fields with their (im)material character, are less often thought together and seen as mutually shaping. Hence, this paper examines the state-of-the-art in modularity as one sustainable design principle for the mobile phone and related ICT, utilizing a review of design (concept) cases in form of their multimedia representations. Matching the findings from the concrete exemplars with generic scientific research results within modular designing informs a discussion on value preservation (promotion of reuse over recycling and the like), portraying nowadays insufficiencies on the one hand and desirable, meaningful futures on the other. It describes both the employment of and the confidence in modularity for accomplishing sustainability, digital materiality or the soft matter, and the demandingness of modularly upgradable architectures. Supposedly by help of the critical design practice in an academic context - which translates to fundamental creativity-based research driven by envisioning new possibilities - further research shall build on the insights gained here. Our vision may thus be called sustainable technology and interaction design, which as an acronym gives STaID.

This dataset holds information on data and methods for the Melvin et al., 2016 publication entitled Climate change damages to Alaska public infrastructure and the economics of proactive adaptation. The abstract for this paper is as follows: Climate change in the circumpolar region is causing dramatic environmental change that is increasing the vulnerability of infrastructure. We quantified the economic impacts of climate change on Alaska public infrastructure under relatively high and low climate forcing scenarios [representative concentration pathway 8.5 (RCP8.5) and RCP4.5] using an infrastructure model modified to account for unique climate impacts at northern latitudes, including near-surface permafrost thaw. Additionally, we evaluated how proactive adaptation influenced economic impacts on select infrastructure types and developed first-order estimates of potential land losses associated with coastal erosion and lengthening of the coastal ice-free season for 12 communities. Cumulative estimated expenses from climate-related damage to infrastructure without adaptation measures (hereafter damages) from 2015 to 2099 totaled $5.5 billion (2015 dollars, 3% discount) for RCP8.5 and $4.2 billion for RCP4.5, suggesting that reducing greenhouse gas emissions could lessen damages by $1.3 billion this century. The distribution of damages varied across the state, with the largest damages projected for the interior and southcentral Alaska. The largest source of damages was road flooding caused by increased precipitation followed by damages to buildings associated with near-surface permafrost thaw. Smaller damages were observed for airports, railroads, and pipelines. Proactive adaptation reduced total projected cumulative expenditures to $2.9 billion for RCP8.5 and $2.3 billion for RCP4.5. For road flooding, adaptation provided an annual savings of 80–100% across four study eras. For nearly all infrastructure types and time periods evaluated, damages and adaptation costs were larger for RCP8.5 than RCP4.5. Estimated coastal erosion losses were also larger for RCP8.5.

The country’s unique philosophy is expressed by Bhutan’s Gross National Happiness (GNH) as the guiding principle of development. Bhutan is at a crossroads: It can maintain the current pattern of development—with rising inequality—or develop a vibrant private sector to generate jobs and diversify the economy, building resilience to future external shocks. The overarching priority of this Country Partnership Framework (CPF) is job creation. This CPF presents an integrated framework of WBG support to help Bhutan achieve inclusive and sustainable development through private sector–led job creation.

Supplementary material for the publication " Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using material substance and energy flow analysis" Burg, V., b, Rolli, C., Schnorf, V., Scharfy, D., Anspach, V., Bowman, G. Today's agro-food system is typically based on linear fluxes (e.g. mineral fertilizers importation), when a circular approach should be privileged. The production of biogas as a renewable energy source and digestate, used as an organic fertilizer, is essential for the circular economy in the agricultural sector. This study investigates the current utilization of wet biomass in agricultural anaerobic digestion plants in Switzerland in terms of mass, nutrients, and energy flows, to see how biomass use contributes to circular economy and climate change mitigation through the substitution effect of mineral fertilizers and fossil fuels. We quantify the system and its benefits in details and examine future developments of agricultural biogas plants using different scenarios. Our results demonstrate that agricultural anaerobic digestion could be largely increased, as it could provide ten times more biogas by 2050, while saving significant amounts of mineral fertilizer and GHG emissions.

We analyze past and anticipated future trends in crop yields, per capita consumption, and population to estimate agricultural land requirements globally by 2050 and 2100. Assuming “business as usual,” higher-income countries are expected to show little or no net growth in cropland by the end of the century, even in the face of moderate climate change. In contrast, in lower-income countries, we project that land requirements will grow dramatically, and climate change will likely double this expansion. Although economic growth is often considered to work in opposition to conservation, accelerating economic development in lower-income countries, which would help alleviate poverty and increase standards of living, would also greatly reduce potential cropland expansion in lower-income countries, even with climate change, owing to slower population growth and improved crop yields that more than offset increased per capita consumption. Combining economic development in low-income countries with reduced consumption in high-income countries could dramatically shrink global cropland requirements by the year 2100 even with moderate climate change. Such a remarkable reduction in cropland area would have enormous benefits for both biodiversity and global climate change.  All of the data files are analyzed using R.

Study PopulationThe target population of the study were women aged 18 years to 69 years from households in Mwea East sub County that have experienced climate change events. As shown in table 3.1 below, the total population of female in Mwea East sub County in this age category was estimated at 38,734 (Kenya National Bureau of Statistics (KNBS)Volume III, table 2.5, (2019).Sample SizeA sample size of 449 respondents was determined as adequate for statistical analysis for the study using an online sample size calculator (calculator.net, 2021). 95% confidence level and 4.6% margin of error was used to calculate the sample size of 449 respondents determining the level of accuracy of the sample from the total estimated population of 38,734 women aged 18-69 years in Mwea East sub County.Data CollectionThe administration of the questionnaire was done by the Principal Investigator (PI) along with the KIIs, which were conducted after the questionnaire had been administered. The questionnaires were administered by 11 data collection assistants who were trained by the researcher. One of the 11 data collectors was the team leader. The researcher collected data in 5 of the households to demonstrate and practice the data collection process. Data AnalysisQuantitative and qualitative data were analyzed and triangulated to validate the findings. The quantitative data was analyzed using a combination of the IBM SPSS techniques including frequencies, cross-tabulations, bivariate statistics, means, correlations and descriptive ratio statistics. Qualitative data from both respondents and key informants’ interviews were documented using filed notes and thematically analyzed. The analysis from both sets of data was then merged to present the results. Study PopulationThe target population of the study were women aged 18 years to 69 years from households in Mwea East sub County that have experienced climate change events. As shown in table 3.1 below, the total population of female in Mwea East sub County in this age category was estimated at 38,734 (Kenya National Bureau of Statistics (KNBS)Volume III, table 2.5, (2019).Sample SizeA sample size of 449 respondents was determined as adequate for statistical analysis for the study using an online sample size calculator (calculator.net, 2021). 95% confidence level and 4.6% margin of error was used to calculate the sample size of 449 respondents determining the level of accuracy of the sample from the total estimated population of 38,734 women aged 18-69 years in Mwea East sub County.Data CollectionThe administration of the questionnaire was done by the Principal Investigator (PI) along with the KIIs, which were conducted after the questionnaire had been administered. The questionnaires were administered by 11 data collection assistants who were trained by the researcher. One of the 11 data collectors was the team leader. The researcher collected data in 5 of the households to demonstrate and practice the data collection process. Data AnalysisQuantitative and qualitative data were analyzed and triangulated to validate the findings. The quantitative data was analyzed using a combination of the IBM SPSS techniques including frequencies, cross-tabulations, bivariate statistics, means, correlations and descriptive ratio statistics. Qualitative data from both respondents and key informants’ interviews were documented using filed notes and thematically analyzed. The analysis from both sets of data was then merged to present the results.

List of Ameriflux, AON and FLUXNET sites contained in this dataset and their corresponding siteid's and doi's: CA-SCB (https://doi.org/10.17190/AMF/1498754), FI-Lom (https://doi.org/10.18140/FLX/1440228), GL-NuF (https://doi.org/10.18140/FLX/1440222), GL-ZaF (https://doi.org/10.18140/FLX/1440223), GL-ZaH (https://doi.org/10.18140/FLX/1440224), RU-Che (https://doi.org/10.18140/FLX/1440181), RU-Cok (https://doi.org/10.18140/FLX/1440182), RU-Sam (https://doi.org/10.18140/FLX/1440185), RU-Tks (https://doi.org/10.18140/FLX/1440244), RU-Vrk (https://doi.org/10.18140/FLX/1440245), SE-St1 (https://doi.org/10.18140/FLX/1440187), SJ-Adv (https://doi.org/10.18140/FLX/1440241), SJ-Blv (https://doi.org/10.18140/FLX/1440242), US-A03 (https://doi.org/10.17190/AMF/1498752), US-A10 (https://doi.org/10.17190/AMF/1498753), US-An1 (https://doi.org/10.17190/AMF/1246142), US-An2 (https://doi.org/10.17190/AMF/1246143), US-An3 (https://doi.org/10.17190/AMF/1246144), US-Atq (https://doi.org/10.17190/AMF/1246029), US-Brw (https://doi.org/10.17190/AMF/1246041), US-EML (https://doi.org/10.17190/AMF/1418678), US-HVa (https://doi.org/10.17190/AMF/1246064), US-ICh (https://doi.org/10.17190/AMF/1246133), US-ICs (https://doi.org/10.17190/AMF/1246130), US-ICt (https://doi.org/10.17190/AMF/1246131), US-Ivo (https://doi.org/10.17190/AMF/1246067), US-NGB (https://doi.org/10.17190/AMF/1436326), US-Upa (https://doi.org/10.17190/AMF/1246108), US-xHE (https://doi.org/10.17190/AMF/1617729), US-xTL (https://doi.org/10.17190/AMF/1617739). Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models.This dataset comprises harmonized, standardized and aggregated in-situ observations of surface energy budget components measured at 64 sites on vegetated and glaciated sites north of 60° latitude, in the time period from 1994 till 2021. The surface energy budget components include net radiation, sensible heat flux, latent heat flux, ground heat flux, net shortwave radiation, net longwave radiation, surface temperature and albedo, which were aggregated to daily mean, minimum and maximum values from hourly and half-hourly measurements. Data were retrieved from the monitoring networks FLUXNET, AmeriFlux, AON, GC-Net and PROMICE.

{"references": ["Hannah Ritchie, Max Roser, Edouard Mathieu, Bobbie Macdonald and Pablo Rosado - Data on CO2 and Greenhouse Gas Emissions by Our World in Data https://github.com/owid/co2-data#data-on-co2-and-greenhouse-gas-emissions-by-our-world-in-data", "Our World in Data, Cumulative CO2 emissions, 2020 https://ourworldindata.org/grapher/cumulative-co-emissions", "GDP, PPP (constant 2017 international $) - World Bank, International Comparison Program, World Bank | World Development Indicators database, World Bank | Eurostat-OECD PPP Programme", "Cumulative CO2 Emissions of International Transport \u2013 Joseph Nowarski, DOI:10.5281/zenodo.7114110", "Dataset Cumulative CO2 Emissions of International Transport \u2013 Joseph Nowarski, DOI:10.5281/zenodo.7114087", "Dataset Global Warming Forecast using Acceleration Factors - Joseph Nowarski, DOI:10.5281/zenodo.7151890", "CO2 Emission per GDP Forecast 2020-2100 - Joseph Nowarski, DOI:10.5281/zenodo.7264413"]} The dataset includes Business as Usual (BAU) forecast of world global CO2 emissions per GDP (Cp$) for 2020-2100. The CO2 emission forecast is from the publication “Dataset Global Warming Forecast using Acceleration Factors” [6]. According to this publication, the CO2 emissions without international transport will change from 33,803 MtCO2/y in 2020 to 70,191 MtCO2/y in 2100, a 108% increase. The GDP forecast applies a parabolic trendline of the last 30 years. According to this calculation, the world GDP will change from 126.3 MM$/y in 2020 to 728.1 MM$/y in 2100, a 476% increase. CO2 emissions per GDP (Cp$) are calculated by dividing the CO2 emissions per year by the GDP in the same year. The world 0.000268 tCO2/$GDP Cp$ in 2020 will decrease by 64% in 2100 to 0.000096 tCO2/$GDP.

Die Verbesserung des Zugangs zu moderneren Energieformen erfordert Lieferketten, die weiter in die ländlichen Gebiete hineinreichen. Das RWI führte eine Wirkungsevaluierung der Beschäftigungs- und Einkommenseffekte einer Energiezugangsmaßnahme in Kenia durch, bei der es sich um ein groß angelegtes Programm handelt, das die Verbreitung von verbesserten Kochherden und kleinen Solarprodukten unterstützt. Die zugrunde liegenden Daten wurden Mitte 2015 unter 648 Unternehmern erhoben. Die Unternehmerstichprobe besteht aus zuvor geschulten Unternehmern und Unternehmerinnen, die im Durchschnitt drei Jahre in ihrem Geschäft tätig sind, und aus Personen, die zum Zeitpunkt ihrer Schulung befragt wurden. Eineinhalb Jahre später wurden bei den befragten Schulungsteilnehmern Folgedaten erhoben, um diejenigen Personen zu ermitteln, die ihr Geschäft weiterführten. Improving access to more modern forms of energy requires supply chains that reach further into rural areas. RWI conducted an impact evaluation of the employment and income effects of an energy access intervention in Kenya, which is a large-scale program that supports the diffusion of improved cookstoves and small solar products. The underlying data was collected among 648 entrepreneurs in mid-2015. The sample of entrepreneurs comprises previously trained entrepreneurs who are active in their business for on average three years and people interviewed at the time of their training. Follow-up data was collected one and a half years later among the later training participants to identify those individuals who continue with the business. Kleinunternehmerinnen und -unternehmer aus den Sparten verbesserte Kochherde und Kleinstsolarsysteme, die von einem Energiezugangsprojekt in Kenia im Jahr 2015 unterstützt wurden. microentrepreneurs active in the sectors of improved cookstoves and pico-solar products supported by an energy access program in Kenya in 2015. siehe Kapitel 3 von Bensch, Kluve, Stöterau (2021) Field observation RWI-MICRO RWI-MICRO