Microplastics and heavy metals represent two pollutant classes which have adverse impacts on aquatic ecosystems. This study has investigated the adsorption of two heavy metals [Lead (Pb)II and Aluminum (Al)III] on three different types of microplastics [polyethylene terephthalate (PET), polyamide (PA), ethylene vinyl acetate (EVA)]. The Scanning Electron Microscope (SEM) analysis has shown that microplastics have different surface characteristics. The effects of parameters such as the pH of solution, duration of contact, initial concentration and temperature on adsorption capacity have been examined. Experimental results have been applied to the adsorption isotherm models of Langmuir and Freundlich and it has been seen that the Freundlich model has been seen as more suitable than the Langmuir model. Moreover, the pseudo-second kinetic has been found to be more appropriate than the pseudo-first kinetic model. Adsorption percentages have changed according to the type of microplastic and working conditions. Finally, the study has investigated the potential of microplastics to act as an instrument of transport for heavy metals to the food chain and for their bioaccumulation.

The Riva River is a water basin located within the borders of Istanbul in the Marmara Region (Turkey) in the south-north direction. Water samples were taken for the 35 km drainage area of the Riva River Basin before the river flows into the Black Sea at 4 stations on the Riva River every month and analyses were carried out. Changes were observed in the quality of water from upstream to downstream. For this purpose, the spatial and temporal variations of water quality were investigated using 13 water quality variables with the ANOVA test. It was observed that COD, DO, S and BOD were important in determining the spatial variation. On the other hand, it was found out that all the variables were effective in determining the temporal variation. Moreover, the correlation analysis which was carried out in order to assess the relations between water quality variables showed that the variables of BOD-COD, BOD-EC, COD-EC, BOD-T and COD-T were correlated and the regression analysis showed that COD, TKN and NH4-N explained BOD and BOD, NH4-N, T and TSS explained COD by approximately 80 %. Consequently, the Artificial Neural Network (ANN), Decision Tree and Logistic Regression models were developed using the data of training set in order to predict the water quality classes of the variables of COD, BOD and NH4-N. Quality classes were predicted for the variables by inputting the data of testing set into the developed models. According to these results, it was seen that the ANN was the best prediction model for COD, the Decision Tree for BOD and the ANN and Decision Tree for NH4-N.

Heavy metal removal by using porous mineral adsorbents bears a great potential to decontaminate sludge compost, and natural zeolite (NZ), artificial zeolite (AZ), and expanded perlite (EP) seem to be possible candidates for this purpose. A composting experiment was conducted to compare the efficiency of those adsorbents for removal of iron (Fe), manganese (Mn), chromium (Cr), copper (Cu), zinc (Zn), nickel (Ni), and lead (Pb) from sewage sludge compost with no adsorbent amendment. For this purpose, 10 g of NZ and AZ and 5 g of EP was filled in a small bag made from non-biodegradable synthetic textile and was separately mixed in composting piles. The bags were separated from compost samples at the end of the experiment. AZ and NZ exhibited different reduction potentials depending on the type of heavy metal. AZ significantly reduced Cr (43.7%), Mn (35.8%), and Fe (29.9%), while NZ more efficiently reduced Cu (24.5%), Ni (22.2%), Zn (22.1%), and Pb (21.2%). The removal efficiency of EP was smaller than both AZ and NZ. The results of this simultaneous composting and metal removing study suggest that AZ and NZ can efficiently bind metal during composting process.

A high pH, low solubility of bound plant nutrients, and negative impacts on microbial communities are common drawbacks of biomass ash (BA) vermicomposting. In this study, nutrient-rich BA mixed with cow manure was tested at three different application rates to obtain final nitrogen (N), phosphorus (P), and potassium (K) contents of 3.5%, 7.0%, and 10.0% for bio-based fertilizers via vermicomposting. The results showed that all BA blends made with cow manure increased fermentation temperatures and allowed successful worm activity during the subsequent vermicomposting phase. The order of indicator enzyme activities in all vermicomposting samples was urease (220 μg NH4 g−1 h−1) > β-glucosidase (95 μg PNP g−1 h−1) > alkaline phosphatase (91 μg PNP g−1 h−1) > arylsulfatase (83 μg PNP g−1 h−1) > acid phosphatase (60 μg PNP g−1 h−1). As an indicator of nutrient bioavailability, high correlations were observed between enzyme activities and microbial diversity in vermicompost samples. Determination coefficients (R2) obtained from multiple linear regressions between enzyme activities and bacterial population for T0, T1, T2, and T3 were determined as 0.90, 0.65, 0.73, and 0.90, respectively. According to a novel metagenome-based approach proposed within the scope of the present study, the stimulatory effects of Flavobacteriales, Burkholderiales, Saccharimonadales, and Pseudomonadales on enzyme activities for the nutrient solubility were found to be significant and positive. The findings of this study demonstrated that worm composting could be a sustainable bio-based technology for the production of slow-release fertilizer from nutrient-rich waste material.

Domestic wastewaters causing pollution contain inorganic and/or organic materials. When the domestic wastewater outflows to the receiving waters, it causes physical, chemical, and biological pollution in them, and deteriorates the ecological balance of those waters. In the treatment of wastewater, various treatment methods are available depending on the pollution strength of the wastewater. Besides mechanical and biological methods, wastewater treatment with physicochemical methods is still one of the most effective and economical options. Particularly in wastewater with a high concentration of suspended solids, this method is very successful, and obtaining high suspended solids removal efficiencies is very possible. In this study, the effects of the use of coagulant and coagulant aid to be used in a treatment plant where domestic wastewater treatment is carried out are determined to increase the treatment efficiency of a biological treatment that comes later in the stages of the treatment. The effluent of the pre-settling tank may contain a lot of suspended solids. This presence of excess suspended solids decreases the efficiency at other levels of treatment and causes energy loss. In the experiments, the standard jar and inhibition tests are done as a method. As a result of the conducted studies, it is determined that the FeCl3, Synthetic coagulant LP 526, FeClSO4, and the combination of anionic polyelectrolyte yield the best results in the removal of the parameters of chemical oxygen demand (COD), total suspended solids (TSS), and volatile suspended solids (VSS). While FeCl3, APE 65, APE 85, Synthetic coagulant LP 526, and FeClSO4 did not show any inhibition effect in the sludge, APE 67, CPE 84, and (Al2(SO4)3 are found to cause inhibition in the sludge.