The main objective of this study was to investigate two of the possible exploitation routes of anaerobic digestion (acid-phase and methane-phase) for the treatment of sugar-beet processing wastes, while producing valuable biobased products. For this purpose, four sets of laboratory experiments were carried out in a stepwise fashion: First, in the biochemical methane potential (BMP) assay (Set-up 1) wastewater and beet-pulp were efficiently digested (63.7&ndash / 87.3% COD removal and 69.6&ndash / 89.3% VS reduction) in batch anaerobic reactors. Secondly, wastewater and beet-pulp could simultaneously be converted to VFAs in acidogenic anaerobic reactors with considerable acidification degrees (43.8&ndash / 52.9%), optimizing the operational conditions (Set-up 2). Then, the produced VFAs were recovered by liquid-liquid extraction (Set-up 3), in which highest VFA recoveries (60.7&ndash / 97.6%) were observed at 20% trioctylphosphine oxide (TOPO) in kerosene with KD values ranging between 1.54 and 40.79 at pH 2.5. Finally, methane-phase anaerobic digestion was evaluated in two different reactor configurations, namely fed-batch continuously mixed reactor (FCMR) and anaerobic sequencing batch reactor (ASBR) (Set-up 4). Methane production yield of 255 &plusmn / 11 mL/g COD-added was increased to 337 &plusmn / 15 mL/g COD-added (32.2% increase in methane yield) when configuration was changed from FCMR to ASBR. In addition, tCOD removal was increased from 68.7 &plusmn / 2.2 to 79.7 &plusmn / 1.1%. Based on the result obtained in this study, it is postulated that, biorefining of sugar-beet processing wastes by anaerobic digestion can not only be a solution for environmental related problems, but also contribute to resource conservation and sustainable production via valuable bio-based product formation.

Recovery of caustic solution from mercerizing wastewaters of a denim producing textile mill was performed by using membrane technologies. A comprehensive characterization study was conducted to develop the treatment scheme. Highly alkaline and warm condition of wastewater has induced using membranes made of Polyethersulfone (PES). Conducted pretreatment applications such as microfiltration, flocculation and centrifuge have been found unsuccessful to improve further treatment capacities. Hence recovery studies which are UF, NF and pilot-system membrane applications have been implemented without any pretreatment. Effects of TMP and CFV on UF and NF processes were investigated and optimum operating conditions have been defined. UF has accomplished almost complete caustic solution recovery beside high COD and color retentions 84 % and 94 % under 4.03 bar TMP and 0.79 m/s CFV at 20&plusmn / 2 0C. Because of higher capacity of NF membranes also in acid and alkali recovery area, NF process has been studied in addition to UF. NF has also provided nearly complete NaOH recoveries with 92 % COD and 98 % color retentions under 4.03 bar TMP and 0.79 m/s CFV at 20&plusmn / 2 0C. Furthermore temperature effect was also studies by repeating the same processes at 40&plusmn / 2 0C considering the real operating conditions. Temperature has affected the system performance positively with regards to flux increases with insignificant loses in recovery and retention capacities. Lastly a pilot plant study has been conducted and it was found successful despite some operational difficulties due to high inorganic content and temperature of wastewater.

In this study, aerobic biological treatment of opium alkaloid wastewater and the effect of gamma preirradiation and fenton&amp / #8217 / s oxidation were investigated. First, the biodegradability of alkaloid wastewater was investigated by batch reactors and wastewater was found to be highly biodegradable providing 83 &amp / #8211 / 90 % COD degradation. In order to evaluate the effect of irradiation, original wastewater and irradiated wastewaters (40 &amp / 140 kGy) were compared by means of BOD5/COD values and through aerobic batch experiments. Results indicated that irradiation imparted no further enhancement in biodegradability. Sequencing batch reactor (SBR) studies revealed that the treatment operation was not possible due to sludge settleability problem observed beyond an influent COD value of 2 g/L. Possible reasons for problem were investigated, and the high molecular weight, larger size and aromatic structure of the organic matters present in wastewater was thought to contribute to poor settleability characteristics. Some operational modifications including phosphate buffer addition cured the settleability problem. Influent COD was then increased to 5,000 mg/L. Significant COD removal efficiencies (&gt / 70 %) were obtained in SBRs fed with both original and irradiated wastewaters. Preirradiated wastewater provided a better settling sludge in comparison to original wastewater. Degradation of the complex structure was followed by GC/MS analyses, particle size measurements and enhancement in filterability. Pre-irradiation enhanced the filterability of wastewater more than Fenton&amp / #8217 / s treatment and degradation by irradiation was proved by GC/MS analyses.

Xenobiotic compounds, which are exclusively man made, are produced in large quantities every year and released to the environment. Besides, anaerobic sludge digestion offers advantage in co-treatment of hazardous substances produced by the industry. The performance of the digesters can be monitored by modeling efforts. In this study, Anaerobic Digestion Model No.1 (ADM1) was calibrated, and validated for full-scale digester, lab-scale digester, and lab-scale digester seeded with totally different anaerobic biomass than that of full-scale digester. The model xenobiotic compound, a mono azo dye RO107, was co-treated with sewage sludge in an anaerobic digester. High removal efficiencies as 98% was found for azo dye at standard operating conditions of anaerobic digesters. The digester performance was not effected from azo dye or its reduction products. The dye reduction mechanism was modeled by biochemical mechanism due to unspecific enzymes and by chemical mechanism due to sulfide reduction. Some of the dye metabolites were suggested to be degraded by aerobic biotreatment. The anaerobic reduction metabolites of RO107 were identified as 2-(4-aminophenylsulfonyl) ethanol and 2,5-diamino-4-formamidobenzenesulfonic acid, and sulfanilic acid.

Ozonation is an efficient method to degrade refractory organics in textile wastewaters. In recent years, catalytic ozonation is applied to reduce ozone consumption and to increase chemical oxygen demand and total organic carbon (TOC) removal efficiencies. The ozonation of two industrial dyes, namely Acid Red-151 (AR-151) and Remazol Brilliant Blue R (RBBR) was examined separately both in a semi-batch reactor and also in a fluidized bed reactor (FBR) by conventional and catalytic ozonation with alumina and perfluorooctyl alumina (PFOA) catalysts. The conventional and catalytic ozonation reactions followed a pseudo-first order kinetics with respect to the dye concentration. The highest COD reductions were obtained in the presence of the catalysts at pH=13, with alumina for AR-151 and with PFOA for RBBR. Residence time distribution experiments were performed to understand the degree of liquid mixing in the reactor. The behaviour of the FBR was almost equivalent to the behaviour of one or two completely stirred tank reactors in series in the presence of the solid catalyst particles. The volumetric ozone-water mass transfer coefficients (kLa) were found at various gas and liquid flow rates and catalyst dosages in the FBR. A model was developed to find kLa in the reactor by comparing the dissolved O3 concentrations in the experiments with the model results. kLa increased significantly by the increase of gas flow rate. Higher catalysts dosages at the fluidization conditions yielded higher kLa values indicating higher rates of mass transfer. Dye ozonation experiments without catalyst and with alumina or PFOA catalyst were conducted at different conditions of the inlet dye concentration, gas and liquid flow rates, inlet ozone concentration in the gas, catalyst dosage, particle size and pH. The dye and TOC removal percentages were increased with the increase of gas flow rate and with the decrease of both the liquid flow rate and inlet dye concentration. The addition of the catalyst was beneficial to enhance the TOC degradation. The ozone consumed per liter of wastewater was much lower when the catalyst was present in the reactor. In terms of TOC removal and O3 consumption, the most efficienct catalyst was PFOA. According to the organic analysis, the intermediate by-products were oxalic, acetic, formic and glyoxalic acids in RBBR and AR-151 ozonation. The dye and dissolved ozone concentration profiles were predicted from a developed model and the model results were compared with the experimental results to obtain the enhanced kLa values. The presence of the chemical reaction and the catalysts in the FBR, enhanced the kLa values significantly. The enhancement factor (E) was found as between 0.97 and 1.93 for the non-catalytic ozonation and 0.96 and 1.53 for the catalytic ozonation at pH = 2.5. The dimensionless number of Hatta values were calculated between 0.04-0.103 for the sole ozonation of RBBR and AR-151 solutions. According to the calculated Ha values, the reaction occurred in the bulk liquid and in the film being called as the intermediate regime in the literature.

Ecodesign is an approach for product development, which focuses on minimizing the environmental impacts of the product during the whole life cycle while maintaining the major concerns such as function, usability, aesthetic and ergonomic qualities. This approach is regarded as a fundamental step to achieve sustainable production, consumption and development. The thesis examines the current situation of ecodesign in Turkish Industry, in relation to design and manufacturing. First, it introduces the literature on ecodesign in general, and more specifically, it presents a comparative analysis of six international studies with an aim to explore internal and external stimuli for promoting ecodesign, as well as reflections on barriers that were encountered. Then, literature review on ecodesign activities in Turkish industry is discussed. To complement these findings, the results of the interviews conducted with three stakeholder groups (i.e. government, universities and industry) are presented. Finally, the results of a study that was conducted in Turkish packaging, and electric &amp / electronics sectors to understand approaches of environmentally-conscious product development, the drivers and the barriers of ecodesign implementation into these sectors are revealed. The level of ecodesign implementation is found to be strongly related with the economic situation of Turkish context, which is the most important determining factor for the drivers and barriers found in the study. Acquiring a more stable economic situation, ecodesign will become a considerable competitive advantage through: (i) reduction of manufacturing costs in the long term, (ii) innovational approach in the manufacturing process and product development, and (iii) increasing brand awareness.

Lakes present in arid regions of Central Anatolia need further attention with regard to water quality. In most cases, mathematical modeling is a helpful tool that might be used to predict the DO concentration of a lake. Deterministic models are frequently used to describe the system behavior. However most ecological systems are so complex and unstable. In case, the deterministic models have high chance of failure due to absence of priori information. For such cases black box models might be essential. In this study DO in Eymir Lake located in Ankara was modeled by using both Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS). Phosphate, Orthophospate, pH, Chlorophyll-a, Temperature, Alkalinity, Nitrate, Total Kjeldahl Nitrogen, Wind, Precipitation, Air Temperature were the input parameters of ANN and ANFIS. The aims of these modeling studies were: to develop models with ANN to predict DO concentration in Lake Eymir with high fidelity to actual DO data, to compare the success (prediction capacity) of ANN and ANFIS on DO modeling, to determine the degree of dependence of different parameters on DO. For modeling studies &ldquo / Matlab R 2007b&rdquo / software was used. The results indicated that ANN has high prediction capacity of DO and ANFIS has low with respect to ANN. Failure of ANFIS was due to low functionality of Matlab ANFIS Graphical User Interface. For ANN Modeling effect of meteorological data on DO data on surface of the lake was successfully described and summer month super saturation DO concentrations were successfully predicted.

Sludge management is one of the most difficult and expensive problems in wastewater treatment plant operation. Consequently, &amp / #8216 / sludge minimization&amp / #8217 / concept arose to solve the excess sludge production by sludge pretreatment. Sludge pretreatment converts the waste sludge into a more bioavailable substrate for anaerobic digestion and leads to an enhanced degradation. The enhanced degradation results in more organic reduction and more biogas production. Therefore, sludge pretreatment is a means of improving sludge management in a treatment plant. Among pretreatment methods, acidic pretreatment has been subject of limited successful studies reported in the literature. On the contrary / ultrasonic pretreatment was reported as an effective pretreatment method. Main objective of this study was to investigate the effects of these two pretreatment methods and their combination in order to achieve a synergistic effect and improve the success of both pretreatment methods. Experimental investigation of pretreatment methods consists of preliminary studies for deciding the most appropriate pretreatment method. Anaerobic batch tests were conducted for optimization of the parameters of selected method. Finally, operation of semi-continuous anaerobic reactors was to investigate the effect of pretreatment on anaerobic digestion in details. Preliminary studies indicated that, more effective pretreatment method in terms of solubilization of organics is ultrasonic pretreatment. Fifteen minutes of sonication enhanced 50 mg/L initial soluble COD concentration up to a value of 2500 mg/L. Biochemical methane potential tests indicated that the increased soluble substrate improved anaerobic biodegradability concurrently. Finally, semi-continuous anaerobic reactors were used to investigate the efficiency of pretreatment under different operating conditions. Results indicate that at SRT 15 days and OLR 0.5 kg/m3d ultrasonic pretreatment improved the daily biogas production of anaerobic digester by 49% and methane percentage by 16% and 24% more volatile solids were removed after pretreatment. Moreover, even after pushing reactors into worse operating conditions such as shorter solids retention time (7.5 days) and low strength influent, pretreatment worked efficiently and improved the anaerobic digestion. Finally cost calculations were performed. Considering the gatherings from enhancement of biogas amount, higher methane percentage and smaller amounts of volatile solid disposal from a treatment plant / installation and operation costs of ultrasound were calculated. The payback period of the installation was found to be 4.7 years.

The effect of heterogeneity correlation scale (&amp / #61548 / ) of hydraulic conductivity (K), equilibrium distribution coefficient (Kd) and mass transfer rate (&amp / #61537 / ) on the design and cost of the P&amp / T remediation system for different heterogeneity levels (defined by the variance (&amp / #963 / 2lnK)) and parameter distributions under the rate-limited sorption conditions was evaluated in this study. In addition, the impacts of initial amount of contaminant mass and plume configuration on the remediation design and cost were explored. The effects of different K heterogeneity and remediation design conditions on the length of remediation period, the influence of &amp / #61548 / anisotropy of K, correlation between K and Kd, and Kd and &amp / #61537 / , and the fraction of equilibrium sorption sites (f) on the pump-and-treat (P&amp / T) design and cost were the other studied subjects. In this study, simulation-optimization approach, in which a groundwater flow and contaminant transport simulation model was linked with a genetic algorithm (GA) library, was used. Results showed that not only the amount of PCE mass initially present in the aquifer was important in terms of P&amp / T design, cost and remediation time, but also the location and size of the high and low K regions defined by &amp / #955 / lnK as well as the magnitudes of K represented by geometric mean and &amp / #963 / 2lnK were influential. It was also found that P&amp / T designs utilizing higher numbers of wells with lower pumping rates may be more robust predicting the time-to-compliance compared to a single well with higher pumping rate for aquifers heterogeneous in K. Homogenous Kd assumption might cause serious error in both the design and the cost of remediation. The magnitude of this error may change depending on the spatial distribution of K and Kd, &amp / #955 / lnKd, &amp / #963 / 2lnKd and &amp / #963 / 2lnK. The effect of heterogeneity in &amp / #61537 / on the design and cost of remediation may or may not be significant depending on K, Kd and &amp / #61537 / distributions, &amp / #61548 / ln&amp / #61537 / and &amp / #963 / 2ln&amp / #61537 / . Increased amount of kinetically sorbed mass defined by decreased f value resulted in more costly remediation.

Although deep saline aquifers are found in all sedimentary basins and provide very large storage capacities, a little is known about them because they are rarely a target for the exploration. Furthermore, nearly all the experiments and simulations made for CO2 sequestration in deep saline aquifers are related to the sandstone formations. The aim of this study is to create a predictive model to estimate the CO2 storage capacity of the deep saline carbonate aquifers since a little is known about them. To create a predictive model, the variables which affect the CO2 storage capacity and their ranges are determined from published literature data. They are rock properties (porosity, permeability, vertical to horizontal permeability ratio), fluid properties (irreducible water saturation, gas permeability end point, Corey water and gas coefficients), reaction properties (forward and backward reaction rates) and reservoir properties (depth, pressure gradient, temperature gradient, formation dip angle, salinity), diffusion coefficient and Kozeny-Carman Coefficient. Other parameters such as pore volume compressibility and density of brine are calculated from correlations found in literature. To cover all possibilities, Latin Hypercube Space Filling Design is used to construct 100 simulation cases and CMG STARS is used for simulation runs. By using least squares method, a linear correlation is found to calculate CO2 storage capacity of the deep saline carbonate aquifers with a correlation coefficient 0.81 by using variables found from literature and simulation results. Numerical dispersion effects have been considered by increasing the grid dimensions. It has been found that correlation coefficient decreased to 0.77 when the grid size was increased from 250 ft to 750 ft. The sensitivity analysis shows that the most important parameter that affects CO2 storage capacity is depth since the pressure difference between formation pressure and fracture pressure increases with depth. Also, CO2 storage mechanisms are investigated at the end of 300 years of simulation. Most of the gas (up to 90%) injected into formation dissolves into the formation water and negligible amount of CO2 reacts with carbonate. This result is consistent with sensitivity analysis results since the variables affecting the solubility of CO2 in brine have greater affect on storage capacity of aquifers. Dimensionless linear and nonlinear predictive models are constructed to estimate the CO2 storage capacity of all deep saline carbonate aquifers and it is found that the best dimensionless predictive model is linear one independent of bulk volume of the aquifer.