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The deployment of onshore wind power is an important means to mitigate climate change. However, wind turbines also have negative impacts at the local scale, like disamenities to residents living nearby, changes in landscape quality, or conflicts with nature conservation. Our paper quantifies spatial trade-offs arising between these criteria. For this purpose, we propose a novel approach using Pareto frontiers and a Gini-like potential trade-off indicator. Our analysis builds on a spatial optimization model using geographical information system data for Germany. We show that spatial trade-offs between the criteria under consideration are substantial. The size of the trade-off varies substantially with the criteria under consideration, depending on the spatial heterogeneity of each criterion as well as on the spatial correlation between the criteria. Spatial trade-offs are particularly pronounced between nature conservation (measured by impacts on wind power-sensitive birds) and other criteria. [ABSTRACT FROM AUTHOR]

The present paper focuses on green defaults as demand-side policies supporting the uptake of renewable energy in Germany. It sets out to gain a better understanding of whether and for whom green electricity defaults work. The present study is one of the first to use a large-scale data set to investigate this question. We combine micro-level data from the German Socio-Economic Panel (GSOEP) covering private households (including a wealth of individual information) with macro-level information such as population density of a region and proportion of energy suppliers in a given region that use a green opt-out tariff within their basic supply. We show that in Germany, green defaults, automatically enrolling customers in renewable energy sources, tend to stick, especially but not only among those who are concerned about the problem of climate change. This finding, based on real-world rather than experimental evidence, attests to the power of automatic enrollment in addressing environmental problems in Germany and potentially beyond, including climate change, and also adds to the growing literature on the substantial effects of shifting from opt-in to opt-out strategies. [ABSTRACT FROM AUTHOR]

This paper explores the effects of framing a polluting activity in different contexts, i.e. different modes of transportation (bus versus plane) and different travel occasions (holiday versus professional training) on the individual willingness to pay (WTP) for carbon offsetting. For both types of framing, we also study additional contributions from the travel provider (i.e. matching). The empirical analyses with mixed logit and latent class logit models are based on data from discrete choice experiments with a representative sample of about 1000 individuals from Germany. The findings suggest substantial and systematic framing effects resulting from varying the mode of transportation, but not the travel occasion. Furthermore, the individual WTP is significantly higher across all four contexts when offsets are matched by the travel provider at a rate of 100%. In contrast, a lower matching rate of 33% is only relevant for one context, i.e. bus trips to a professional training. In addition, our results indicate that re-/afforestation projects are preferred to renewable energies projects or projects to improve energy efficiency. Likewise, projects carried out in a participant's region are preferred to projects implemented in European countries other than Germany or in developing countries. Finally, the WTP for offsets is found to be significantly higher for individuals with higher income, younger age, and stronger environmental and social preferences, as well as for individuals who believe that offsetting is effective in protecting the climate. [ABSTRACT FROM AUTHOR]