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The Wuppertal Institute conducted an impact analysis of the NRW Sustainability Bond #4 of 2018 on behalf of the State Government of North Rhine-Westphalia (NRW). The most recent bond has a volume of EUR 2.025bn, a term of 10 years and consists of 52 eligible projects from the State's 2017 general budget (sustainable value-added was confirmed in a second party opinion by oekom research1). This report analyses the contribution of the bond to climate mitigation, sustainable land use and social impacts. It also includes information on the impacts of the previous three bonds (NRW Sustainability Bond #1 to #3).
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.
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.
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.
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.
To contribute to a better understanding of consumer food leftovers and to facilitate their reduction in out-of-home settings, our study analyzes the effects of two common intervention strategies for reducing leftovers in a holistic behavioral model. Based on a quasi-experimental baseline-intervention design, we analyzed how the display of information posters and the reduction of portion sizes take an effect on personal, social and environmental determinants in a structural equation model. Applying data from online surveys and observations among 880 guests (503 baseline, 377 intervention) during two weeks in a university canteen, the suggested model allows to assign effects from the two interventions on plate leftovers to specific changes in behavioral determinants. Portion size reductions for target dishes are found to relate to lower levels of plate waste based on conscious perception, represented in smaller portion size ratings. Effects from seeing information posters are found to base on changed personal attitudes, subjective norms and perceived behavioral control. However, depending on how an individual reacts to the information (by only making an effort to finish all food or by making an effort and additionally choosing a different dish in the canteen) there are opposite effects on these determinants and consequently also on plate leftovers. Overall, the differentiated results on intervention effects strongly support the benefits of more holistic and in-depth analyses of interventions to reduce plate leftovers and therefore to contribute to more sustainable food consumption in out-of-home settings.
Das Deutsche Zentrum für Luft- und Raumfahrt (DLR) hat gemeinsam mit dem Wuppertal Institut für Klima, Umwelt, Energie in der Studie "STROMbegleitung" Technologien, Perspektiven und Ökobilanzen elektrifizierter PKW untersucht. Die Studie gibt einen umfassenden Einblick in den aktuellen Stand der Technik, identifiziert Trends und analysiert die Ökobilanz unterschiedlicher Fahrzeugkonzepte. Gleichzeitig ordnet sie die deutschen Aktivitäten im Bereich Elektromobilität in einen globalen Kontext ein.
Wie werden Handys hergestellt? Woraus bestehen sie? Was bedeutet es für die Umwelt, wenn immer die neusten Modelle angeschafft werden? Und was passiert mit den Geräten, wenn wir sie nicht mehr brauchen und zurückgeben?
Das Buch nimmt den Leser/die Leserin mit auf eine spannende Reise durch das Rohstoffleben eines Handys und zeigt, wie Alltagstechnik bewusster und umweltverträglicher genutzt werden kann. Durch seine fachdidaktische Einordnung und seine wissenschaftlich fundierten Inhalte ist das Buch ideal als Grundlage für Kurse an Schulen und Hochschulen geeignet.
