Characterization of the Leachate in an Urban Landfill by Physicochemical Analysis and Solid Phase Microextraction-GC/MS

The aim of this study is to evaluate extensively the characterization and identification of major pollutant parameters by paying attention to the organic chemical pollution for unregulated dumping site leachate in Eskişehir/Turkey. The study that is first and only one research has been very important data related with before new sanitary landfill site in Eskişehir city. For this purpose, in this study leachate samples were collected in-situ at monthly interval for a period of 8 months. Firstly, thirty three physicochemical parameters were monitored. Secondly, SPME technique was used for identification of organic pollutants. Meteorological data were also recorded for the same sampling period to correlate meteorological data and physicochemical parameters. Mean values are used in the correlation analysis. Correlation is shown only for the relationship between air temperature and NO₃ ⁻. No correlation has been found between rain and leachate quality parameters since the amount of rain was very low during the sampling period. However, analysis results were generally decreased in winter season when each parameter and each sampling point are examined separately. According to correlation between every parameter, especially solid content and dissolved oxygen concentration of leachate is affecting to other parameters. Also, sodium and potassium are changing proportionally with same parameters (suspended solids, fixed solids, dissolved oxygen) and high correlation between chloride and heavy metal concentration is showing. The results were statistically evaluated by use of SPSS 10.0 program. Second part of the study, the leachate was extracted by Solid Phase Microextraction (SPME) technique and then analyzed. Of the methodologies tested in this study, the best one selected was based on 100 μ m polydimethylsiloxane coated fiber (PDMS), headspace with heating (Δ HS) sampling mode and an extraction time of 15 min. at a temperature of 50 ^o C. Thirty three organic compounds in leachate were identified by GC/MS.     

Bioaccumulation of Some Heavy Metals in Different Tissues Of Dicentrarchus Labrax L, 1758, Sparus Aurata L, 1758 And Mugil Cephalus L, 1758 From the ÇamlIk Lagoon of the Eastern Cost Of Mediterranean (Turkey)

In this study, bioaccumulation of the heavy metals (Fe, Zn, Cd) in the liver, gill, gonad and muscle tissues of Dicentrarchus labrax, Mugil cephalus and Sparus aurata were investigated seasonally. Camlik is the important fisheries lagoon located in The Iskenderun Bay, Mediterranean coast of Turkey. Due to heavy industrial and agricultural activities in the region, the bay has the polluted coastal waters of Turkey. Therefore, the levels of cadmium, zinc, iron were determined in the muscle in each species because of its importance for human consumption and also the liver, gill, gonad were analysed since these organs tend to accumulate metals. Heavy metal levels were found generally higher in the liver and gill than the gonad and muscle tissues in three species; the levels of all metals in a given tissue were generally higher in Mugil cephalus than the other two species. Data collected in this study suggest that Camlik lagoon is affected by a relatively metal pollution. The concentrations of Zn concentrations in the muscle tissues exceeded the acceptable levels for a food source for human consumption and other metals in the edible parts of the investigated fish were in the permissible safety levels for human uses.     

An Approach for Recreation Suitability Analysis to Recreation Planning in Gölcük Nature Park

Gölcük Nature Park (GNP) is an area protected by law in Turkey. It is an important nature park with rich flora, fauna, geomorphologic forms, landscape features, and recreational potential in the region. However, GNP does not have a recreation management plan. The purpose of this study was to determine the actual natural, cultural, and visual resources of GNP, determine the most suitable recreational sites with multiple factors, evaluate the demands and tendencies of visitors, and suggest recreational activities and facilities for the most suitable sites of GNP. However, it was also conceived as leading to a recreational plan and design of GNP in the future and identifying the entire appropriate and current data of GNP with the creation of various maps. This study used multifactor analysis to determine the most suitable recreation sites of GNP. Used recreation factors were established including degree of slope, proximity to water resources, accessibility, elevation, vegetation, soil, climate, aspect, current cultural facilities, visual values, and some limiting factors in accordance with the characteristics of GNP. Weighting and suitability values of factors were determined by 30 local expert surveys. All obtained data were evaluated and integrated in the Geographical Information Systems base. Obtained maps were overlapped. Thus, recreational suitability zones map were created manually. However, the demands and behaviours from visitor surveys in GNP were focused on the most suitable recreation sites of the park. Finally, 10% of GNP was identified as the most suitable sites for recreational use. Various recreational facilities and activities (including picnicking, sports facilities and playgrounds, camping sites, walking paths, food and local outlets, etc.) were recommended for nine of the most suitable areas on the proposed recreational map.     

Non-Metal Polymeric Bioparticles Based on Maleic Acid/Citric Acid as a Catalyst for H2 Generation from NaBH4

Journal of Polymers and the Environment - Novel metal-free catalysts were synthesized form maleic acid (MA) and citric acid (CA) based polymers for hydrogen generation form NaBH4....     

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.

     

Application of Poly (Agar-Co-Glycerol-Co-Sweet Almond Oil) Based Organo-Hydrogels as a Drug Delivery Material

In this study, it was aimed to investigate the synthesis, characterization and drug release behaviors of organo-hydrogels containing pH-sensitive Agar (A), Glycerol (G), Sweet Almond oil (Wu et al. in J Mol Struct 882:107–115, 2008). Organo-hydrogels, which contained Agar, Glycerol and different amounts of Sweet Almond oil, were synthesized via the free-radical polymerization reaction with emulsion technique using glutaraldehyde or methylene bis acrylamide crosslinkers. Then, the degree of swelling, bond structures, blood compatibility and antioxidant properties of the synthesized organo-hydrogels were examined. In addition, Organo-hydrogels which loaded with Ceftriaxone and Oxaliplatin were synthesized with the same polymerization reaction and release kinetics were investigated. In vitro release studies were performed at media similar pH to gastric fluid (pH 2.0), skin surface (pH 5.5), blood fluid (pH 7.4) and intestinal fluid (pH 8.0), at 37 °C. The effects on release of crosslinker type and sweet almond oil amount were investigated. Kinetic parameters were determined using release results and these results were applied to zero and first-order equations and Korsmeyer-Peppas and Higuchi equations. Diffusion exponential was calculated for drug diffusion of organo-hydrogels and values consistent with release results were found.

     

Use of Coconut Oil-Based Organo-Hydrogels in Pharmaceutical Applications

Journal of Polymers and the Environment - In this study, six different organo-hydrogel containing Agar-Glycerol (AG) based Coconut Oil (CnO) were synthesized using different crosslinkers to ensure...     

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...