Mehmet Cakmakci

Molecular weight distribution of a full-scale landfill leachate treatment by membrane bioreactor and nanofiltration membrane

In this study, Molecular weight (MW) distributions of a full-scale landfill leachate treatment plant consisting of membrane bioreactor (MBR) and nanofiltration (NF) membrane were investigated. The leachate was sampled from the equalization tank, and effluents of MBR and NF membrane in the landfill leachate treatment plant. Parameters of COD, TOC, TKN, NH4(+)-N and UV(254, 280 and 320) absorbance were analyzed to evaluate both the removal performance of the plant and MW distributions. MW distribution of samples were determined by ultrafiltration (UF) (100 kDa, 10 kDa, 5 kDa, 1 kDa and 500 Da) membranes. The results indicated that organic matter of one third percent is particulate or colloidal form and almost half of the organic fraction has a lower MW than 500 Da. In addition, organic matter had hydrophilic character. Most part of TKN was>500 Da with the corresponding rate of 92%. Further, UV absorbance of raw leachate (RW) decreased 85% after 500 Da.

ARTIFICIAL INTELLIGENCE-BASED PREDICTION MODELS FOR ENVIRONMENTAL ENGINEERING

A literature survey was conducted to appraise the recent applications of artiflcal intelligence (AI)-based modeling studies in the environmental engineer- ing fleld. A number of studies on artiflcial neural networks (ANN), fuzzy logic and adaptive neuro-fuzzy systems (ANFIS) were reviewed and important aspects of these models were highlighted. The results of the extensive literature survey showed that most AI-based prediction models were implemented for the solution of water/wastewater (55.7%) and air pollution (30.8%) related environmental prob- lems compared to solid waste (13.5%) management studies. The present literature review indicated that among the many types of ANNs, the three-layer feed-forward and back-propagation (FFBP) networks were considered as one of the simplest and the most widely used network type. In general, the Levenberg-Marquardt algo- rithm (LMA) was found as the best-suited training algorithm for several complex and nonlinear real-life problems of environmental engineering. The literature sur- vey showed that for water and wastewater treatment processes, most of AI-based prediction models were introduced to estimate the performance of various biolog- ical and chemical treatment processes, and to control e†uent pollutant loads and ∞owrates from a speciflc system. In air polution related environmental problems, forecasting of ozone (O3) and nitrogen dioxide (NO2) levels, daily and/or hourly particulate matter (PM2:5 and PM10) emissions, and sulfur dioxide (SO2) and car- bon monoxide (CO) concentrations were found to be widely modeled. For solid waste management applications, reseachers conducted studies to model weight of waste generation, solid waste composition, and total rate of waste generation.

Electricity production by a microbial fuel cell fueled by brewery wastewater and the factors in its membrane deterioration

Electricity production from brewery wastewater using dual-chamb er microbial fuel cells (MFCs) with a tin-coated copper mesh in the anode was investigated by changing the hydraulic retention time (HRT). The MFCs were fed with wastewater samples from the inlet (inflow, MFC-1) and outlet (outflow, MFC-2) of an anaerobic digester of a brewery wastewater treatment plant. Both chemical oxygen demand removal and current density were improved by decreasing HRT. The best MFC performance was with an HRT of 0.5 d. The maximum power densities of 8.001 and 1.843 µW/cm2 were obtained from reactors MFC-1 and MFC-2, respectively. Microbial diversity at different conditions was studied using PCR-DGGE profiling of 16S rRNA fragments of the microorganisms from the biofilm on the anode electrode. The MFC reactor had mainly Geobacter, Shewanella, and Clostridium species, and some bacteria were easily washed out at lower HRTs. The fouling characteristics of the MFC Nafion membrane and the resulting degradation of MFC performance were examined. The ion exchange capacity, conductivity, and diffusivity of the membrane decreased significantly after fouling. The morphology of the Nafion membrane and MFC degradation were studied using scanning electron microscopy and attenuated total reflection-Fourier transform infrared spectroscopy.

Anaerobic granular reactors for the treatment of dairy wastewater: a review

Considerable research has been conducted on the treatment of dairy wastewater by anaerobic granular reactors. Upflow anaerobic sludge blanket (UASB) reactors, anaerobic sequencing batch reactors (ASBR) and static granular bed reactors (SGBR) are the conventional granular reactor types most commonly applied in dairy wastewater treatment. Hybrid systems have also been developed to increase treatment efficiency and overcome the operational problems associated with the treatment of this substrate. Effects of parameters including temperature, organic loading and operating protocols on the performance of granular reactors are summarised. Individual and hybrid granular reactors are evaluated based on organic matter removal and methane production capacity.

Electricity generating capacity and performance deterioration of a microbial fuel cell fed with beer brewery wastewater.

This study focused on using beer brewery wastewater (BBW) to evaluate membrane concentrate disposal and production of electricity in microbial fuel cells. In the membrane treatment of BBW, the membrane permeate concentration was 570 ± 30 mg/L corresponding to a chemical oxygen demand (COD) removal efficiency of 75 ± 5%, and the flux values changed between 160 and 40 L/m(2)-h for all membrane runs. For electricity production from membrane concentrate, the highest current density in the microbial fuel cell (MFC) was observed to be 1950 mA/m(2) according to electrode surface area with 36% COD removal efficiency and 2.48% CE with 60% BBW membrane concentrate. The morphologies of the cation exchange membrane and the MFC deterioration were studied using a scanning electron microscope (SEM), attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy, differential scanning calorimetry (DSC), and thermal gravimetric analysis (TGA). A decrease in the thermal stability of the sulfonate (-SO3H) groups was demonstrated and morphological changes were detected in the SEM analysis.

Case study on prediction of remaining methane potential of landfilled municipal solid waste by statistical analysis of waste composition data.

Main objective of this study was to develop a statistical model for easier and faster Biochemical Methane Potential (BMP) prediction of landfilled municipal solid waste by analyzing waste composition of excavated samples from 12 sampling points and three waste depths representing different landfilling ages of closed and active sections of a sanitary landfill site located in İstanbul, Turkey. Results of Principal Component Analysis (PCA) were used as a decision support tool to evaluation and describe the waste composition variables. Four principal component were extracted describing 76% of data set variance. The most effective components were determined as PCB, PO, T, D, W, FM, moisture and BMP for the data set. Multiple Linear Regression (MLR) models were built by original compositional data and transformed data to determine differences. It was observed that even residual plots were better for transformed data the R(2) and Adjusted R(2) values were not improved significantly. The best preliminary BMP prediction models consisted of D, W, T and FM waste fractions for both versions of regressions. Adjusted R(2) values of the raw and transformed models were determined as 0.69 and 0.57, respectively.

The production of electricity from dual-chambered microbial fuel cell fueled by old age leachate

ABSTRACT In this study, electricity production from old age landfill leachate was investigated using dual chambered microbial fuel cell with Ti-TiO2 electrodes. The effect of organic loading rate on microbial fuel cell performance was examined by changing the hydraulic retention time and leachate chemical oxygen demand (COD) concentration. Microbial diversity at different conditions was studied using PCR-DGGE profiling of 16 sRNA fragments of microorganisms in the liquid media of the anode chamber and of the biofilm on the anode electrode. Both COD removal and current density were positively affected with increasing organic loading rate. The highest microbial fuel cell performance was achieved at hydraulic retention time of 0.5 day and organic loading rate of 10 g COD/L.day. The performance of the microbial fuel cell reactor decreased when hydraulic retention time was reduced to 0.25 day. The investigation of the microbial dynamics indicated that abundance of bacterial species was considerably dependent on the operational conditions. The microbial fuel cell reactor was mainly dominated by Geobacter, Shewanella, and Clostridium species, and some bacteria were easily washed out at lower hydraulic retention times.

Anaerobic treatment of ozonated membrane concentrate

AbstractA concentrate stream is generated by the application of nanofiltration (NF) membranes in wastewater reuse. Due to the high concentrations of pollutants, disposal of NF concentrates is an important problem. In this study, ozonation and anaerobic treatment processes were performed to treat cotton dyeing textile mill wastewater NF concentrate. After ozonation, the concentration of biochemical oxygen demand (BOD5) increased while dissolved chemical oxygen demand (DCOD) decreased. Thus, biodegradability of the concentrate was increased by the ozonation process. The average removal efficiencies of DCOD, BOD5, and sulfate () in the anaerobic process were achieved about 72, 76, and 68%, respectively. These results indicated that the combination of ozonation and anaerobic treatment showed a remarkable performance for the removal of pollutants from NF concentrate.

Meteorological parameters as an important factor on the energy recovery of landfill gas in landfills

The effect of meteorological factors on the composition and the energy recovery of the landfill gas (LFG) were evaluated in this study. Landfill gas data consisting of methane, carbon dioxide, and oxygen content as well as LFG temperature were collected from April 2009 to March 2010 along with meteorological data. The data set were, first, used to visualize the similarity by using self-organizing maps and to calculate correlation factors. Then, the data was used with ANN to further analyze the impacts of meteorological factors. In both analysis, it is seen that the most important meteorological parameter effective on LFG energy content is soil temperatures. Furthermore, ANN was found to be successful in explaining variations of methane content and temperature of LFG with correlation coefficients of 0.706 and 0.984, respectively. ANN was proved itself to be a useful tool for estimating energy recovery of the landfill gas.

Harvesting microalgal biomass using crossflow membrane filtration: critical flux, filtration performance, and fouling characterization

ABSTRACT The purpose of this study was to investigate the efficient harvesting of microalgal biomass through crossflow membrane filtration. The microalgal biomass harvesting experiments were performed using one microfiltration membrane (pore size: 0.2 µm, made from polyvinylidene fluoride) and three ultrafiltration membranes (molecular weight cut-off: 150, 50, and 30 kDa, made from polyethersulfone, hydrophilic polyethersulfone, and regenerated cellulose, respectively). Initially, to minimize membrane fouling caused by microalgal cells, experiments with the objective of determining the critical flux were performed. Based on the critical flux calculations, the best performing membrane was confirmed to be the UH050 membrane, produced from hydrophilic polyethersulfone material. Furthermore, we also evaluated the effect of transmembrane pressure (TMP) and crossflow velocity (CFV) on filtration flux. It was observed that membrane fouling was affected not only by the membrane characteristics, but also by the TMP and CFV. In all the membranes, it was observed that increasing CFV was associated with increasing filtration flux, independent of the TMP.