Duo-molecularly imprinted polymer-coated magnetic particles for class-selective removal of endocrine-disrupting compounds from aqueous environment

The removal of steroid and phenolic endocrine-disrupting compounds (EDCs) from an aqueous environment was investigated using magnetic particles encapsulated by a duo-molecularly imprinted polymer (duo-MIP). The effect of environmental variables on the binding efficiency was studied. Experimental results showed that the amount of EDCs adsorbed was neither affected by up to 10.0 mM NaCl nor significantly interfered by up to 10.0 mg/L humic acid. Negligible influence was observed from pH 3.3 to pH 6.8, but a decrease started at pH 9. Freundlich isotherm parameters indicated binding capacities in the order of DES?>?E2?～?E1?>?BPA. The applicability of class-selective removal was verified using river water samples spiked with these EDCs at 10 μg/L; the binding efficiencies were 90, 90, 88, and 98 % for estrone (E1), 17β-estradiol (E2), bisphenol A (BPA), and diethylstilbestrol (DES), respectively. A reuse investigation verified constant binding capacities exhibiting <2 % reduction after seven cycles of regeneration.     

Seasonal variation of some heavy metal pollution with environmental and microbiological parameters in sub-basin of Kocabas Stream (Biga, Canakkale, Turkey) by ICP-AES

Waste water pollution in industrial areas is one of the most important environmental problems. Heavy metal pollution, especially chromium species in waste water sources from tannery affects our lives. Kocabas Stream is located in south-west Marmara region and Biga town is positioned in the sub basin on the stream. This water source functions as the water for irrigation in agriculture, drinking water for animals and for human use. Thus, this study is of great importance. Waste water pollution can affect all ecosystems and human health by directly or indirectly as in food chain. The concentration of heavy metals (Pb, Cd, Cu, Zn and Cr) were pre-analysed by ICP-AES method in water samples taken from sub-basin of Kocabas stream. In the results of these analyses, concentrations of the metals except chromium were founded at the limit value. But the total concentration of the Cr was found at high levels of between 0.0082 +/- 0.0001 and 5.7231 +/- 0.0921 mg l(-1) over the limit value (0.05 mg l(-1); WHO, EPA, TSE 266 and inland water quality classification) at sampling points very close to tannery factories. Also physicochemical and microbiological parameters of Kocabas Stream were determined. The effects of the experimental results on environment were investigated.     

Hydrogeochemical and Geophysical Investigation of the Istanbul Tuzla–Icmeler Spring Area for Environmental and Land Use Planning Purposes

The spring waters of Tuzla–Icmeler are on the Marmara Sea coast in Tuzla town of Istanbul city. The springs discharge a natural sodium chloride mineral water that consumed for ages for therapeutic purposes attributed to their chemical properties. Development of springs commenced during the Ottoman times and a surface collection structure was built at the discharge point of the main spring. Two deep wells were drilled to tap mineral water within the past decades. The bottled water of these springs is also sold for a couple of years and its consumption as a beverage is increasing. The geochemical properties of these springs were investigated by several researchers in the past. This study comprises geochemical and geophysical measurements performed between July 2001 and July 2002 in order to construct a conceptual hydrogeological model for environmental and land use planning purposes. The seasonal evaluation of Tuzla–Icmeler (mineral spring) shows that the chemical properties fluctuate from the beginning of summer until the beginning of winter. This indicates that the overdraft of water during the summer season causes the movement and mix of normal groundwater with the mineralized groundwater. As a result, mixing of less mineralized groundwater decreases the salinity of mineralized groundwater. Using the site-specific hydrogeological, geochemical and geophysical data, zones of protection areas were delineated in order to prevent a possible pollution access to the springs and surroundings from nearby dockyards, dwellings and vehicle traffic. For this purpose, a new land use plan was proposed using the existing settlement sustainability plans.     

Comparison of hybrid machine learning methods for the prediction of short-term meteorological droughts of Sakarya Meteorological Station in Turkey

Drought is a harmful natural disaster with various negative effects on many aspects of life. In this research, short-term meteorological droughts were predicted with hybrid machine learning models using monthly precipitation data (1960–2020 period) of Sakarya Meteorological Station, located in the northwest of Turkey. Standardized precipitation index (SPI), depending only on precipitation data, was used as the drought index, and 1-, 3-, and 6-month time scales for short-term droughts were considered. In the prediction models, drought index was predicted at t?+?1 output variable by using t, t???1, t???2, and t???3 input variables. Artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), Gaussian process regression (GPR), support vector machine regression (SVMR), k-nearest neighbors (KNN) algorithms were employed as stand-alone machine learning methods. Variation mode decomposition (VMD), discrete wavelet transform (DWT), and empirical mode decomposition (EMD) were utilized as pre-processing techniques to create hybrid models. Six different performance criteria were used to assess model performance. The hybrid models used together with the pre-processing techniques were found to be more successful than the stand-alone models. Hybrid VMD-GPR model yielded the best results (NSE?=?0.9345, OI?=?0.9438, R²?=?0.9367) for 1-month time scale, hybrid VMD-GPR model (NSE?=?0.9528, OI?=?0.9559, R²?=?0.9565) for 3-month time scale, and hybrid DWT-ANN model (NSE?=?0.9398, OI?=?0.9483, R²?=?0.9450) for 6-month time scale. Considering the entire performance criteria, it was determined that the decomposition success of VMD was higher than DWT and EMD.

     

Solid waste composition and COVID-19-induced changes in an inland water ecosystem in Turkey

Environmental Science and Pollution Research - The composition and abundance of solid waste and the effect of COVID-19 measures were studied in an inland water ecosystem in Turkey. Solid waste...