Volume 19 - 2017

Snow depletion curves (SDCs) are important in hydrological studies for predicting snowmelt generated runoff in high mountain catchments. The present study deals with the derivation of the average snow depletion pattern in the Mago basin of Arunachal Pradesh, which falls in the eastern Himalayan region and the generation of climate affected SDCs in future years (2020, 2030, 2040, and 2050) under different projected climatic scenarios. The MODIS daily snow cover product at 500m resolution from both the Aqua and Terra satellites was used to obtain daily snow cover maps. MOD10A1 and MYD10A1 images were compared to select cloud free or minimum cloud image to obtain the temporal distribution of snow cover area (SCA). Snow accumulation and depletion patterns were obtained by analysing SCA at different days. For most of the years, two peaks were observed in the SCA analysis. The conventional depletion curve (CDC) representing present climate was derived by determining and interpolating the SCA from cloud-free (cloud<5%) images for the selected hydrological year 2007. The investigation shows that the SCA was highest in February and lowest in May. Ten years meteorological data were used to normalize the temperature and precipitation data of the selected hydrological year (2007) to eliminate the impact of their yearly fluctuations on the snow cover depletion. The temperature and precipitation changes under four different projected climatic scenarios (A1B, A2, B1, and IPCC Commitment) were analysed for future years. Changes in the cumulative snowmelt depth with respect to the present climate for different future years were studied by a degree-day approach and were found to be highest under A1B, followed by A2, B1, and IPCC Commitment scenarios. It was observed that the A1B climatic scenario affected the depletion pattern most, making the depletion of snow to start and complete faster than under different scenarios. Advancing of depletion curve for different future years was found to be highest under A1B and lowest under IPCC Commitment scenarios with A2 and B1 in-between them.

Application of nano particle in the treatment of municipal solid waste leachate is of recent interest. In this paper, the effectiveness of silica nano particles synthesized from blast furnace slag and iron nano particle synthesized from chemicals was studied for the removal of organic pollutants and color. The synthesized nano particles were characterized using SEM, TEM, EDX and FTIR analysis. Batch experiments were conducted to remove the BOD, COD and color from Aged landfill leachate (ALL) and leachate from the composting yard (CYL).Influencing parameters like pH, contact time, nano particle dosage and Hydrogen peroxide concentration were studied. The maximum removal was achieved at the pH of 6 for both the nano particle, contact time 90 minutes for silica nano particle and 120 minutes for iron nano particle, silica nano particle dose as 0.4g/50 ml, iron nano particle dose as 0.3g/50ml and hydrogen peroxide concentration was found to be 3M and 4M for silica and iron nano particles respectively. The removal efficiency in CYL and ALL using silica nano particle was obtained as 87.15%, 72.72%, 83.15% and 82.5%, 62.5%, 77.34% for color, BOD and COD respectively. Similarly for iron nano particle, the removal efficiency was found to be 60.3%, 65%, 67.43% and 57.06%, 57.27%, 67% for the removal of color, BOD and COD in CYL and ALL, respectively.

The decomposition of sodium dodecylbenzene sulfonate (SDBS), which is a dangerous and anionic surfactant, was investigated by the electro/Fe2+/persulfate process from aqueous solutions. The activation of persulfate anion and production of active radicals were performed by means of heat, UV and iron ions (released from iron electrodes). The finding illustrated that the pH value of the solution, initial concentration of persulfate anion, the amount of input voltage and iron dosage were entirely effective in SDBS removal. Nearly 100% of SDBS was removed under the optimum conditions: pH 3, voltage 10 V, anion persulfate concentration 25 mM/L, iron ion dosage 0.25 g/L and reaction time 25 min. Furthermore, the application of the persulfate anion process in concert with the electrochemical process, in order to generate electrical iron and persulfate activation, had a better performance compared to separate methods.

In this study, an analytical methods for determination of antidepressants including (diazepam (DZP), lorazepam (LZP), carbamazepine (CBZ), fluoxetine (FLU)) was developed. The concentration of antidepressants was monitored in Konya Urban Wastewater Treatment Plant influent and effluent samples for one years.  Environmental risk assessment was performed with detected concentration with treatment plant effluent wastewater by hazard quotient (HQ) methods. Oasis HLB cartridges with SPE system was used for extraction of wastewater samples. The effect of sample volume and pH, different analyte concentration, pretreatment and matrix on efficiency of cartridges were optimized. Quantitative analyses of the target compounds were performed by LC/MS-MS system. Recoveries of antidepressant compounds from fortified wastewater were over 87% for three different fortification levels. The limits of detection were determined between 0.006 and 0.118 ng l-1. CBZ, FLU and LZP concentration in influent varied from 6.3 to 135.6 ng l-1, <dl to 2.6 ng l-1, <dl to 4.8 ng l-1, respectively, while DZP was not detected. CBZ, DZP, FLU and LZP concentrations in the effluent was determined as <dl-245.1 ng l-1, <dl-0.21 ng l-1, <dl-2.7 ng l-1, <dl-2.2 ng l-1, respectively. Antidepressants were generally removed in January, February, and August. The high removal was determined for CBZ compounds as %100 at January. The low removal was determined for FLU compounds as %2.4 at January.

While the HQ values for DZP, LZP, CBZ were determined below 0.1 which means insignificant risk to aquatic organisms, HQ values for FLU determined above 0.1 which means low risk to aquatic organism