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This paper investigates the meaning of systemic risk in energy markets and proposes a methodology to measure it. Energy Systemic Risk is defined by the risk of an energy crisis raising the prices of all energy commodities with negative consequences for the real economy. Measures of the total cost (EnSysRISK) and the net impact (ΔMES) of an energy crisis on the rest of the economy are proposed. The measures are derived from the Marginal Expected Shortfall (MES) capturing the tail dependence between the asset and the energy market factor. The adapted MES accounts for causality and dynamic exposure to common latent factors. The methodology is applied to the European Energy Exchange and the DAX industrial index, where a minor decline in industrial productivity is observed from recent energy shocks.

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.

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.

The transport sector needs to go through an extended process of decarbonisation to counter the threat of climate change. Unfortunately, the International Energy Agency forecasts an enormous growth in the number of cars and greenhouse gas emissions by 2050. Two issues can thus be identified: (1) the need for a new methodology that could evaluate the policy performances ex-ante and (2) the need for more effective policies. To help address these issues, we developed an Agent-Based Model called Mobility USA aimed at: (1) testing whether this could be an effective approach in analysing ex-ante policy implementation in the transport sector; and (2) evaluating the effects of alternative policy scenarios on commuting behaviours in the USA. Particularly, we tested the effects of two sets of policies, namely market-based and preference-change ones. The model results suggest that this type of agent-based approach will provide a useful tool for testing policy interventions and their effectiveness.

This paper illustrates the main results of an expert elicitation survey on advanced (second and third generation) biofuel technologies. The survey focuses on eliciting probabilistic information on the future costs of advanced biofuels and on the potential role of Research, Development and Demonstration (RD&D) efforts in reducing these costs and in supporting the deployment of biofuels in Organisation for Economic Co-operation and Development (OECD) and non-OECD countries. Fifteen leading experts from different EU member states provide insights on the future potential of advanced biofuel technologies both in terms of costs and diffusion. This information results in a number of policy recommendations with respect to public RD&D strategies and is an important contribution to the integrated assessment modelling community.

Résumé Les transports génèrent de nombreuses externalités, dont celles liées à la pollution atmosphérique. Cet article analyse deux d’entre elles, les gaz à effet de serre et la pollution locale, qui, en général, sont étudiées séparément dans les travaux sur les politiques optimales de transport. Ici, ces externalités sont analysées conjointement grâce à un modèle de prise de décision séquentielle. Celui-ci permet de tenir compte de l’irréversibilité des politiques menées ainsi que de la possibilité d’une diminution progressive des incertitudes grâce à l’arrivée d’informations supplémentaires. Nous trouvons que des mesures structurelles qui permettent de limiter le recours aux transports privés sont économiquement plus avantageuses que des dispositifs techniques qui réduisent les émissions de substances polluantes. L’utilité de cette analyse conjointe des externalités est illustrée à travers deux cas : les dispositifs fiscaux qui grèvent l’automobile et la politique du logement. Classification JEL : C6; D62; D81; R48.

This paper estimates a US frontier residential aggregate energy demand function using panel data for 48 ‘states’ over the period 1995 to 2007 using stochastic frontier analysis (SFA). Utilizing an econometric energy demand model, the (in)efficiency of each state is modeled and it is argued that this represents a measure of the inefficient use of residential energy in each state (i.e. ‘waste energy’). This underlying efficiency for the US is therefore observed for each state as well as the relative efficiency across the states. Moreover, the analysis suggests that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controlling for a range of economic and other factors, the measure of energy efficiency obtained via this approach is. This is a novel approach to model residential energy demand and efficiency and it is arguably particularly relevant given current US energy policy discussions related to energy efficiency.