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 $25-31^{\circ}C$ for a retention time of 51 days. 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 $CH_4$, $CO_2$ and $H_2$. 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.

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.

In the present study research air quality analyses for $PM_{10}$, 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 $PM_{10}$ occurs generally in the night while the least concentration was found at the afternoon. Monthly concentrations of $PM_{10}$ 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.

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.

Green Leaf Volatiles (GLVs) is a class of biogenically emitted oxygenated hydrocarbons that have been identified as a potential source of Secondary Organic Aerosols (SOA) via aqueous oxidation. The physico-chemical properties of GLVs are vital to understanding their fate and transport in the atmosphere via fog processing, but few experimental data are available. We studied the aqueous solubility, 1-octanol/water partition coefficient, and Henry's law constant ($K_H$) of five GLVs at $25^{\circ}C$: methyl jasmonate, methyl salicylate, 2-methyl-3-buten-2-ol, cis-3-hexen-1-ol, and cis-3-hexenyl acetate. Henry's law constant was also measured at temperatures and ionic strengths typical of fog. Experimental values are compared to scarcely-available literature values, as well as estimations using group and bond contribution methods, property-specific correlations and molecular dynamics simulations. From these values, the partition coefficients to the air-water interface were also calculated. The large Henry's law constant of methyl jasmonate ($8091{\pm}1121M{\cdot}atm^{-1}$) made it the most significant GLV for aqueous phase photochemistry. The HENRYWIN program's bond contribution method from the Estimation Programs Interface Suite (EPI Suite) produced the best estimate of the Henry's constant for GLVs. Estimations of 1-octanol/water partition coefficient and solubility are best when correlating an experimental value of one to find the other. Finally, the scavenging efficiency was calculated for each GLV indicating aqueous phase processing will be most important for methyl jasmonate.