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Paterna, Spain

Klemm O.,University of Munster | Schemenauer R.S.,FogQuest Sustainable Water Solutions | Lummerich A.,Alimon E.V | Cereceda P.,University of Santiago de Chile | And 12 more authors.
Ambio | Year: 2012

The collection of fog water is a simple and sustainable technology to obtain fresh water for afforestation, gardening, and as a drinking water source for human and animal consumption. In regions where fresh water is sparse and fog frequently occurs, it is feasible to set up a passive mesh system for fog water collection. The mesh is directly exposed to the atmosphere, and the foggy air is pushed through the mesh by the wind. Fog droplets are deposited on the mesh, combine to form larger droplets, and run down passing into a storage tank. Fog water collection rates vary dramatically from site to site but yearly averages from 3 to 10 l m-2 of mesh per day are typical of operational projects. The scope of this article is to review fog collection projects worldwide, to analyze factors of success, and to evaluate the prospects of this technology. © Royal Swedish Academy of Sciences 2012. Source


Niclos R.,Mixed Unit CEAM UVEG | Estrela M.J.,University of Valencia | Valiente J.A.,Mixed Unit CEAM UVEG | Barbera M.J.,Mixed Unit CEAM UVEG
IEEE Geoscience and Remote Sensing Letters | Year: 2010

A frequent and accurate determination of sea-surface temperature (SST) would permit an improvement in both the forecasting of natural hazards and the monitoring of the effects of climate change. The Meteosat Second Generation (MSG) spinning enhanced visible and infrared imager (SEVIRI) (MSG-SEVIRI) offers this possibility, since it has a temporal resolution of 15 min. Current algorithms for SST retrieval from MSG-SEVIRI data use angular-dependent coefficients, but they do not use sea-surface emissivity (SSE) as an explicit input. This letter proposes a both angular- and emissivity-dependent split-window equation, together with simple equations to estimate SSE and atmospheric water-vapor content, with the aim of determining SST from MSG1/2-SEVIRI data. The first validation results point out the soundness of this sort of expression, even for large observation angles and under any sea and atmospheric states. © 2006 IEEE. Source

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