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Im Rahmen des Forschungsprojektes wurde auf der Ebene von privaten Haushalten untersucht, in welchem Ausmaß eine Bedürfnisbefriedigung mit materiellen Gütern innerhalb der Randbedingungen von globaler Gerechtigkeit, einer nachhaltigen Rohstoffnutzung und einer umweltverträglichen Gesellschaft möglich ist. Zur Bestimmung des Rohstoffbedarfs langlebiger Haushaltsgüter wurden das methodische Konzept der Verfügungskorridore entwickelt und empirisch fundiert sowie global tragfähige Ausstattungen für verschiedene Haushalte prototypisch dargestellt. Das im Rahmen des Projekts entwickelte Webtool veranschaulicht wesentliche Ergebnisse des Forschungsvorhabens. Vor dem Hintergrund ihrer eigenen Haushaltsausstattungen wird den Nutzer/-innen des Webtools das Forschungsthema "Rohstoffverbrauch und Nachhaltigkeit" exemplarisch veranschaulicht, wodurch eine konkrete Reflexion des eigenen Konsumverhaltens ermöglicht wird.
The transformation processes towards a sustainable development are complex. How can science contribute towards new solutions and ideas leading to change in practice? The authors of this book discuss these questions along the energy transition in the building sector.
A transformative research that leaves the neutral observer position needs appropriate concepts and methods: how can knowledge from different disciplines and from practice be integrated in order to be able to explain and understand complex circumstances and interrelations? What role do complex (agent-based) models and experiments play in this respect? Which mix of methods is required in transformative science in order to actively support the actors in transformation processes?
Theses questions are illustrated by the example of the BMBF funded project "EnerTransRuhr".
Die Transformationsprozesse hin zu einer nachhaltigen Entwicklung sind komplex.
Wie kann Wissenschaft dazu beitragen, dass neue Lösungen und Ideen in der Praxis zu Veränderung führen? Dieser Frage gehen die Autorinnen und Autoren am Beispiel der Gebäudeenergiewende nach. Eine transformative Forschung, die den neutralen Beobachterposten verlässt, braucht entsprechende Konzepte und Methoden: Wie kann Wissen aus unterschiedlichen Disziplinen und aus der Praxis integriert werden, um komplexe Sachverhalte und Zusammenhänge zu erklären und zu verstehen? Welche Rolle spielen komplexe (agentenbasierte) Modelle und Experimente dabei? Wie sieht der Methodenmix einer transformativen Wissenschaft aus, die Akteure bei Transformationsprozessen aktiv unterstützt? Illustriert werden diese Fragen am Beispiel des vom BMBF geförderten Forschungsprojektes "EnerTransRuhr".
We present the results of a regression analysis of a large-scale integrated user online application that surveys natural resource use and subjective well-being in Germany. We analyse more than 44,000 users who provided information on their natural resource consumption (material footprint) as well as their personal socio-economic and socio-psychological characteristics. We determine an average material footprint of 26 tonnes per person per year. In addition, we endeavour to determine how much environment humans need by regressing natural resource use as well as relevant socio-economic and socio-psychological features on subjective well-being. We establish a slightly negative correlation between subjective well-being and material footprints. A higher material footprint is associated with lower subjective well-being. We conclude that consumer policies seeking to promote sustainable behaviour should highlight the fact that a lower material footprint may result in greater subjective well-being.
Recent research on the natural resource use of private consumption suggests a sustainable Material Footprint of 8 tons per capita by 2050 in industrialised countries. We analyse the Material Footprint in Germany from 2015 to 2020 in order to test whether the Material Footprint decreases accordingly. We studied the Material Footprint of 113,559 users of an online footprint calculator and predicted the Material Footprint by seasonally decomposed autoregressive (STL-ARIMA) and exponential smoothing (STL-ETS) algorithms. We find a relatively stable Material Footprint for private consumption. The overall Material Footprint decreased by 0.4% per year between 2015 and 2020 on average. The predictions do not suggest that the Material Footprint of private consumption follows the reduction path of 3.3% per year that will lead to the sustainable consumption of natural resource
Footprint calculators are efficient tools to monitor the environmental impact of private consumption. We present the results of an analysis of data entered into an online Material Footprint calculator undertaken to identify the socioeconomic drivers of the Material Footprint in different areas of consumption, from housing to holidaymaking. We developed regression models to reveal (1) the impact of socioeconomic characteristics on Material Footprints of private households and (2) correlations between the components of Material Footprints for different arrays of consumption. Our results show that an increasing Material Footprint in one array of consumption comes with an increasing Material Footprint in all other arrays, with the exception of housing and holidaymaking. The socioeconomic characteristics of users have a significant impact on their Material Footprints. However, this impact varies by the array of consumption. Households only exhibit generally bigger Material Footprints as a result of higher incomes and larger dwellings. We conclude that indicators which strive to monitor resource efficiency should survey disaggregated data in order to classify the resource use to different population groups and arrays of consumption.
Measure or management? : Resource use indicators for policymakers based on microdata by households
(2018)
Sustainable Development Goal 12 (SDG 12) requires sustainable production and consumption. One indicator named in the SDG for resource use is the (national) material footprint. A method and disaggregated data basis that differentiates the material footprint for production and consumption according to, e.g., sectors, fields of consumption as well as socioeconomic criteria does not yet exist. We present two methods and its results for analyzing resource the consumption of private households based on microdata: (1) an indicator based on representative expenditure data in Germany and (2) an indicator based on survey data from a web tool. By these means, we aim to contribute to monitoring the Sustainable Development Goals, especially the sustainable management and efficient use of natural resources. Indicators based on microdata ensure that indicators can be disaggregated by socioeconomic characteristics like age, sex, income, or geographic location. Results from both methods show a right-skewed distribution of the Material Footprint in Germany and, for instance, an increasing Material Footprint with increasing household income. The methods enable researchers and policymakers to evaluate trends in resource use and to differentiate between lifestyles and along socioeconomic characteristics. This, in turn, would allow us to tailor sustainable consumption policies to household needs and restrictions.
Green Information Systems in general, and footprint calculators in particular, are promising feedback tools to assist people in adopting sustainable behaviour. Therefore, a Material Footprint model for use in an online footprint calculator was developed by identifying the most important predictors of the Material Footprint of the calculator's users. By means of statistical learning, the analysis revealed that 22 of the 95 predictors identified accounted for 74% of the variance in Material Footprints. Ten predictors out of the 95, mainly from the mobility domain, were capable of showing a prediction accuracy of 61%. The authors conclude that 22 predictors from the areas of mobility, housing and nutrition, as well as sociodemographic information, accurately predict a person's Material Footprint. The short and concise Material Footprint model may help developers and researchers to enhance their information systems with additional items while ensuring the data quality of such applications.