This study was designed to investigate the awareness regarding global warming among the College of Science students at University of Bahrain. A total of 143 science students were examined using a questionnaire that covered three aspects of global warming including causes, impacts, and solutions. The study included 51, 28, 40 and 24 students from the departments of biology, chemistry, mathematics, and physics respectively. The results have shown that 55 ± 10.18% of all students examined answered the questions correctly of which 51 ± 10.28% were in the first year, while 60 ± 7.4% were in their fourth year indicating a direct positive impact of university education. A significant dependence (p 6 0.05) was recorded between first and fourth year students' answers. The results have shown that fourth year biology students were the most knowledgeable, a fact that can be attributed to their academic curriculum. Therefore, the study has recommended integrating environmental concepts into the university curriculum for all students irrespective of their academic specialization in order to increase the environmental awareness.

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A modern renewable energy forecasting system blends physical models with artificial intelligence to aid in system operation and grid integration. This paper describes such a system being developed for the Shagaya Renewable Energy Park, which is being developed by the State of Kuwait. The park contains wind turbines, photovoltaic panels, and concentrated solar renewable energy technologies with storage capabilities. The fully operational Kuwait Renewable Energy Prediction System (KREPS) employs artificial intelligence (AI) in multiple portions of the forecasting structure and processes, both for short-range forecasting (i.e., the next six hours) as well as for forecasts several days out. These AI methods work synergistically with the dynamical/physical models employed. This paper briefly describes the methodology used for each of the AI methods, how they are blended, and provides a preliminary assessment of their relative value to the prediction system. Each operational AI component adds value to the system. KREPS is an example of a fully integrated state-of-the-science forecasting system for renewable energy.

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