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CONTENTS
Volume 7, Number 2, June 2018
 

Abstract
The anaerobically digestion and agricultural application of organic wastes was conducted using food wastes and cow dung. Twenty kilograms each of the feed stocks was added into two 30 liters-capacity batch digesters. The anaerobic digestion was carried out within a temperature range of 25 – 31O C for a retention time of 51days. The results showed a cumulative gas yield of 5.0 bars for food waste and no gas production for cow dung within the retention time. Bacteria such as Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Proteus vulgaris and Clostridium sp were isolated. Fungi isolated included Aspergillus niger, Aspergillus nidulan, Trichophyton rubrum and Epidermophyton flocossum. The non-dispersive infrared (NDIR) analysis of the biogas produced confirmed that the gas consisted of CH4, CO2 and H2. Statistical analysis revealed there was no significant correlation between temperature and biogas produced from the organic wastes (r= 0.177, p = 0.483).The organic wastes from the biogas production process stimulated maize growth when compared to control (soil without organic waste) and indicated maximum height. The study therefore reveals that food waste as potential substrates for biogas production has a moderate bio-fertilizer potential for improving plant growth and yield when added to soil.

Key Words
waste; biogas; digestion; methane (CH4); carbon dioxide (CO2)

Address
Leh-Togi Zobeashia S. Suanu: National Biotechnology Development Agency, Lugbe, Abuja, Nigeria

Aransiola S. Abiodun: Bioresources Development Centre, National Biotechnology Development Agency,
KM 5 Ogbomoso/Iresapa Road, Onipaanu, Ogbomoso, Nigeria

Ijah U. J. Josiah and Abioye O. Peter: Department of Microbiology, Federal University of Technology, PMB 65, Minna, Nigeria

Abstract
Water quality monitoring network needs periodic evaluations based on environmental demands and financial constraints. We used a genetic algorithm to optimize the existing water quality monitoring stations on the Sefid-Rud River, which is located in the North of Iran. Our objective was to optimize the existing stations for drinking and irrigation purposes, separately. The technique includes two stages called data preparation and the optimization. On the data preparation stage, first the basin was divided into four sections and each section was consisted of some stations. Then, the score of each station was computed using the data provided by the water Research Institute of the Ministry of energy. After that, we applied a weighting method by providing questionnaires to ask the experts to define the significance of each parameter. In the next step, according to the scores, stations were prioritized cumulatively. Finally, the genetic algorithm was applied to identify the best combination. The results indicated that out of 21 existing monitoring stations, 14 stations should remain in the network for both irrigation and drinking purposes. The results also had a good compliance with the previous studies which used dynamic programming as the optimization technique.

Key Words
genetic algorithm; network design; optimization, sampling site; water quality monitoring

Address
Gholamreza Asadollahfardi, Nima Heidarzadeh,
Atabak Mosalli and Ali Sekhavati: Civil Engineering Department, Faculty of Engineering, Kharazmi University, Tehran, Iran

Abstract
In the present study research air quality analyses for PM10, were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The averages concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of PM10 occurs generally in the night while the least concentration was found at the afternoon. Monthly concentrations of PM10 showed highest value in August, while least value was found in January. The seasonal concentrations showed the least amounts in autumn while the highest amounts in summer. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions SPSS software. RMSE test showed that among different prediction models, stepwise model is the best option.

Key Words
PM10; air pollution; meteorological parameters; regression model

Address
Masoud Masoudi, Neda Rajai Poor and Fatemeh Ordibeheshti:Department of Natural Resources and Environmental Engineering, Shiraz University, Iran

Abstract
Depending on the increased energy needs, a large number of dams have been built around the world. These dams have significant impacts on river ecology and climate change. When the climate change scenarios are examined, it is stated that the annual average temperature in Turkey will increase by 2.5-4 degrees in the future years, the south of the country will be opposed to the severe drought threat, and the northern regions will have a flood risk. In particular, it can be predicted that many dams and dam lakes built in the North of Turkey may increase the impact of climate change. In this study, the effects of the dams constructed in Çoruh basin on climate change are examined. Environmental and ecological problems of dam reservoirs have been examined. As a result of the data received from meteorological stations, it was determined that temperature and rainfall changes in the region. In this direction, solution proposal is presented.

Key Words
Coruh Valley; climate change; ecology; environmental; multiple dam

Address
Egemen Aras: Civil Engineering Department, Faculty of Technology, Karadeniz Technical University, 61830 Trabzon, Turkey



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