• Energy Research
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Abstract In this paper, we analyze the rationale for an energy policy mix when the European Emissions Trading Scheme (ETS) is considered from a public choice perspective. That is, we argue that the economic textbook model of the ETS implausibly assumes (1) efficient policy design and (2) climate protection as the single objective of policy intervention. Contrary to these assumptions, we propose that the ETS originates from a political bargaining game within a context of multiple policy objectives. In particular, the emissions cap is negotiated between regulators and emitters with the emitters' abatement costs as crucial bargaining variable. This public choice view yields striking implications for an optimal policy mix comprising RES supporting policies. Whereas the textbook model implies that the ETS alone provides sufficient climate protection, our analysis suggests that support for renewable energies (1) contributes to a more effective ETS-design and (2) may even increase the overall efficiency of climate and energy policy if other externalities and policy objectives besides climate protection are considered. Thus, our analysis also shows that a public choice view not necessarily entails negative evaluations concerning efficiency and effectiveness of a policy mix.

The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.

Direct Numerical Simulations (DNS) have been conducted to study the response of initially laminar spherical premixed methane–air flame kernels to successively higher turbulence intensities at five different equivalence ratios. The numerical experiments include a 16-species/25-step skeletal mechanism for methane oxidation and a multicomponent molecular transport model. Highly turbulent conditions (with integral Reynolds numbers up to 4513) have been accessed. The effect of turbulence on the physical properties of the flame, in particular its consumption speed Sc, which is an interesting measure of the turbulent flame speed ST has been investigated. Local quenching events are increasingly observed for highly turbulent conditions, particularly for lean mixtures. The obtained results qualitatively confirm the expected trend regarding correlations between u′/SL and the consumption speed: Sc first increases, roughly linearly, with u′/SL (low turbulence zone), then levels off (bending zone) before decreasing again (quenching limit) for too intense turbulence. For a fixed value of u′/SL, Sc/SL varies with the mixture equivalence ratio, showing that additional parameters should probably enter phenomenological expressions relating these two quantities.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

This paper provides an initial analysis of the EU ETS based on the installation-level data for verified emissions and allowance allocations in the first trading year. Those data, released on May 15, 2006, and subsequent updates revealed that CO2 emissions were about 4% lower than the allocated allowances. The main objective of the paper is to shed light on the extent to which over-allocation and abatement have taken place in 2005. We propose a measure by which over-allocation can be judged and provide estimates of abatement based on emissions data and indicators of economic activity as well as trends in energy and carbon intensity. Finally, we discuss the insights and implications that emerge from this tentative assessment.

So far, various studies assessed global biomass potentials and came up with widely varying results. Existing potential estimates range from 0 EJ/a up to more than 1,550 EJ/a which corresponds to about three times the current global primary energy consumption. This paper provides an overview of the available research on bioenergy potentials and reviews the different assessments qualitative way with the objective to interpret previous research in an integrated way. In the context of this paper we understand bioenergy as energy from biomass sources including energy crops, residues, byproducts and wastes from agriculture, forestry, food production and waste management. In this review special attention was paid to the difference between residue and energy potentials, land availability estimates, and the geographical resolution of existing potential estimates. The majority of studies concentrate on energy crop potentials retrieved from surplus agricultural land and only few publications assess global potentials separated by different world regions. It results that land allocated to the exclusive production of energy crops varies from 0 to 7,000 ha, depending on land category and scenario assumptions. Only a small number of available potential assessments consider residue potentials as well as energy crop potentials from degraded land. Future energy crop potentials are assumed to vary in the mean from 200 to 600 EJ/yr. In contrast residue potentials are expected to contribute between 62 and 325 EJ/yr. The highest potentials are assigned to Asia, Africa and South America while Europe, North America and the Pacific region contribute minor parts to the global potential.