Investigation of the Effect of Weather Conditions on Solar Energy in Rivers State University of Science and Technology, Port Harcourt, Nigeria
| Autor: | Vivian N. Otugo, Udombakuku E. Udonam Inyang, Friday B. Sigalo, Etim D. Uko |
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| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | Journal of Atmosphere. 2:9-16 |
| ISSN: | 2414-2484 2518-2528 |
| DOI: | 10.18488/journal.94/2016.2.1/94.1.9.16 |
| Popis: | This study presents the effect of temperature, relative humidity, rainfall and evaporation on solar energy in Port Harcourt City, Nigeria. The data was recorded every 5 minutes daily and monthly, covering 2008 – 2014, in The Rivers State University of Science and Technology, Port Harcourt Meteorological Logging Unit. The MATLAB software used in the analysis of the data reveal a direct relationship between solar radiation and temperature and evaporation, and an inverse relationship with rainfall and relative humidity. The mean atmospheric temperature is 26.02oC, while solar energy varies between 47.07 mJm-2 month-1 and 113.99 mJm-2month-1 with a mean of 87.87 mJm-2month-1. During the rainy season (April – September), the mean monthly solar energy is 86.69mJm-2month-1, while in the dry season (October – March), the mean is 89.05mJm-2month-1. The amount of evaporation per temperature ranges from 2.92 mm/oC to 4.47 mm/oC with a mean annual of 3.57 mm/oC. In the rainy season, this value varies from 2.79 mm/oC to 3.79 mm/oC. In the dry season months, the variation is from 3.12 mm/oC to 4.47 mm/oC. The rainfall-to-evaporation ratio of 5.71 in rainy month demonstrates that about the amount of rainfall is recorded for the amount of water evaporated. This correlates with the fact that humidity is high. The results of this work could be used in the design and construction of solar energy technologies to provide energy. Moreover, the results could also provide input for climate risk information, local and national planning and decision-making for sustainable development in the areas of agriculture, aviation, health, and weather forecasting. |
| Databáze: | OpenAIRE |
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