Forecasts of wind power production are increasingly being used in various management tasks. So far, such forecasts and related uncertainty information have usually been generated individually for a given site of interest (either a wind farm or a group of wind farms), without properly accounting for the spatio‐temporal dependencies observed in the wind generation field. However, it is intuitively expected that, owing to the inertia of meteorological forecasting systems, a forecast error made at a given point in space and time will be related to forecast errors at other points in space in the following period. The existence of such underlying correlation patterns is demonstrated and analyzed in this paper, considering the case‐study of western Denmark. The effects of prevailing wind speed and direction on autocorrelation and cross‐correlation patterns are thoroughly described. For a flat terrain region of small size like western Denmark, significant correlation between the various zones is observed for time delays up to 5 h. Wind direction is shown to play a crucial role, while the effect of wind speed is more complex. Nonlinear models permitting capture of the interdependence structure of wind power forecast errors are proposed, and their ability to mimic this structure is discussed. The best performing model is shown to explain 54% of the variations of the forecast errors observed for the individual forecasts used today. Even though focus is on 1‐h‐ahead forecast errors and on western Denmark only, the methodology proposed may be similarly tested on the cases of further look‐ahead times, larger areas, or more complex topographies. Such generalization may not be straightforward. While the results presented here comprise a first step only, the revealed error propagation principles may be seen as a basis for future related work. Copyright © 2010 John Wiley & Sons, Ltd.

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In this paper, we introduce a new method, based on spherical principal component analysis (S-PCA), for the identification of Rayleigh and Raman scatters in fluorescence excitation-emission data. These scatters should be found and eliminated as a prestep before fitting parallel factor analysis models to the data, in order to avoid model degeneracies. The work is inspired and based on a previous research, where scatter removal was automatic (based on a robust version of PCA called ROBPCA) and required no visual data inspection but appeared to be computationally intensive. To overcome this drawback, we implement the fast S-PCA in the scatter identification routine. Moreover, an additional pattern interpolation step that complements the method, based on robust regression, will be applied. In this way, substantial time savings are gained, and the user's engagement is restricted to a minimum, which might be beneficial for certain applications. We conclude that the subsequent parallel factor analysis models fitted to excitation-emission data after scatter identification based on either ROBPCA or S-PCA are comparable; however, the modified method based on S-PCA clearly outperforms the original approach in relation to computational time. Figure 8. Parallel factor analysis resolved spectra for the North Sea data: (a) spherical principle component analysis (S-PCA) with correction and unimodality constraint, (b) S-PCA with correction and nonnegativity constraint, and (c) S-PCA with correction and unimodality and nonnegativity constraints.

Faced with the difficulties of establishing a centralized management of waste generated in the poorest neighborhoods of the Haitian capital it is necessary to develop alternative ways of collection, treatment and recycling appropriated to the precarious situation of for the vast majority of the population. In the context of the call for proposals "Flash Haiti" of ANR, INSA Lyon, University of Limoges, CEFREPADE and GRET proposed a program of operational research entitled GEDEAH "Decentralized and integrated waste and sanitation in urban and peri urban areas in Haiti" which was retained. This program aims to identify the conditions for success and sustainability of participatory management of waste across districts located in urban areas. This management requires consideration of technical, economic and social conditions of targeted populations. Due to the total lack of financial ressources of the municipality, the methods selected should be simple and the entire management chain must operate on an economic logic to ensure its financial independence in the long term. This implies an optimal management system (participative management, quality research for all products recycled, the existence of market flow, project ownership by civil society…).The program also relies on the expertise of several partners including Haitian universities like Quisqueya University (UNIQ) with the LAQUE (Laboratory for Water and Environment Quality) and FAMV (Faculty of Agronomy and Veterinary Medicine). The paper presents the first results on the characterization of target neighborhoods and analysis of waste deposits. Face aux difficultés de mise en place d'une gestion centralisée des déchets générés dans les quartiers les plus pauvres de la capitale haïtienne, il est nécessaire de développer des voies alternatives de collecte, de traitement et de valorisation adaptées à la situation de précarité dans laquelle se trouve la gronde majorité de la population. Dans le cadre de l'appel à projet « Flash Haïti » de l’ANR, l’INSA de Lyon, l'université de Limoges, le CEFREPADE et le GRET ont proposé un programme de recherche opérationnelle intitulé GEDEAH « Gestion décentralisée et intégrée des déchets et de l'assainissement en zones urbaines et périurbaines haïtiennes » qui a étéretenu. Ce programme a pour objectif de déterminer les conditions de réussite et de pérennisation de la gestion participative des déchets à l'échelle de quartiers situées dans des zones urbaines défavorisées.Cette gestion nécessite de tenir compte des conditions techniques, économiques et sociales des populations concernées. Compte tenu de l'absence totale de moyens de la commune, les procédés choisis doivent être simples et l'ensemble de la filière de gestion doit fonctionner sur une logique économique permettant d'assurer son autonomie financière sur le long terme. Cette démarche implique une gestion optimale du système (gestion participative, recherche de qualité pour tous les produits de revalorisation, existence de marchés d'écoulement, appropriation du projet par la société civile…). Le programme s'appuie aussi sur les compétences de plusieurs partenaires universitaireshaïtiens dont l'Université Quisqueya (UNIQ), notamment sur le LAQUE (Laboratoire de Qualité des Eaux et Environnement) et la FAMV (Faculté d'Agronomie et de Médecine Vétérinaire). L’article présente les premiers résultats concernant la caractérisation des quartiers cibles et l'analyse des gisements de déchets.