کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
301770 512515 2010 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparing diffuse radiation models with one predictor for partitioning incident PAR radiation into its diffuse component in the eastern Mediterranean basin
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Comparing diffuse radiation models with one predictor for partitioning incident PAR radiation into its diffuse component in the eastern Mediterranean basin
چکیده انگلیسی

In the photosynthesis process, solar radiation energy is converted to chemical energy by using atmospheric CO2. That is, almost all living species depend on energy produced through photosynthesis for their nourishing components thus making photosynthesis vital to the earth's life. Nevertheless, the knowledge of photosynthetic photon flux density QP (PAR, 400–700 nm) is important in several applications dealing with plants physiology, biomass production, natural illumination in greenhouses and agricultural research. This study aiming to explore the applicability of several diffuse radiation empirical models, hourly measurements of diffuse PAR and global PAR irradiation collected at Athens (37°N, 23°E, 250 m above MSL) from 1 January 2000 to 31 December 2002, are employed. These data were used to establish an empirical model relating the spectral diffuse fraction, kdP (ratio of the diffuse-to-global PAR) with the fractional transmission of global PAR ktP (ratio of the global PAR-to-extraterrestrial solar PAR). The performance of the proposed empirical model was further compared with those of twelve other diffuse–global correlation models available in the literature in terms of the widely used statistical indicators mbe, rmse and t-test. From the overall analysis, it can be concluded that the proposed model predicts diffuse PAR values accurately, whereas most of the candidate empirical models examined here appear to be location-independent for the diffuse PAR predictions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable Energy - Volume 35, Issue 8, August 2010, Pages 1820–1827
نویسندگان
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