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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.

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.

The zinc acetato and triflato complexes of 2,2’-bipyridine and 1,10-phenanthroline were prepared and completely characterised. The whole series (including the already described dichlorido complexes and the ligands themselves) were screened for their catalytic activity in the solvent free ring-opening polymerisation of D,L-lactide. The acetato and triflato complexes were found to be active initiators and polylactides could be obtained in almost quantitative yields or with high molecular weights, up to 145,000 g/mol.

Economists have confined the concept of 'sustainability' to intertemporal distributional equity. We propose a broader definition, combining dynamic efficiency and intergenerational equity, and relate it to two concepts from neoclassical economics: potential Pareto-improvements and inter-personal compensation.