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Firouz Mojarrad, Amanollah Fathnia, Saeed Rajaee Najafabadi ,
Volume 17, Issue 44 (3-2017)
Abstract

The aim of this study was to provide a reliable estimate of the amount of solar radiation in Kermanshah province by using “Liu and Jordan” model in order to develop solar sites. The amount of atmospheric elimination in each month was calculated using an index called clearness index (AWT IMAGE) and the results were applied on different slopes, aspects and heights. Then, according to the obtained results, amounts of direct, diffuse and total radiation were calculated in different slopes of the region and the relevant maps were consequently drawn. The results showed that the minimum amount of atmospheric elimination and thus the maximum amount of received radiation in the province occurs in late spring and summer due to the increase of clearness index (AWT IMAGE) with a maximum of 1360 cal/cm2/day in May. the least amount of received radiation occurs in Janury equal to 386.3 cal/cm2/day. Radiation variations at the provincial level are high between lowlands and highlands in Janury and December, according to the angle of radiation and significant elevation changes in the region. However, in summer, distribution of surface radiation is almost identical because of high solar radiation, and thus standard deviation amount of received radiation is reduced. The highest amount of radiation is received in Javanrood city as much as 528.1 cal/ cm2/day due to greater heights, and the lowest amount is received in Qasr-e Shirin city as much as 443.6 cal/ cm2/day due to lower heights.


Dr Javad Sadidi, Dr Hani Rezayan, Mr Mohammad Reza Barshan,
Volume 17, Issue 47 (12-2017)
Abstract

Due to the complexity of air pollution action, artificial intelligence models specifically, neural networks are utilized to simulate air pollution. So far, numerous artificial neural network models have been used to estimate the concentration of atmospheric PMs. These models have had different accuracies that scholars are constantly exceed their efficiency using numerous parameters. The current research aims to compare Elman and Jordan recurrent networks for error distribution and validation to estimate atmospheric particular matters concentration in Ahvaz city. The used parameters are relative humidity, air pressure, and temperature and aerosol optical depth. The latter one is extracted from MODIS sensor images and air pollution monitoring stations. The results show that Jordan model with RMSE of 219.9 milligram per cubic meter has more accuracy rather than Elman model with RMSE of 228.5. The value of R2 index that shows the linear relation between the estimated from the model and observed values for Jordan is equal to 0.5 that implies 50% estimation accuracy. The value is because of MODIS spatial resolution, inadequacy in numbers as well as spatial distribution of meteorological station inside the study area. According to the results of the current research, it seems that air pollution monitoring stations have to increase in terms of numbers and suitable spatial distribution. Also, other ancillary data like volunteer geographic air pollution data entry using mobile connected cheap sensors as portable stations may be used to implement more accurate simulation for air pollution.
 


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