Potential of biological sulphur recovery from thiosulphate by haloalkaliphilic Thioalkalivibrio denitrificans.

The aim of this study was to investigate the potential for elemental sulphur recovery from sulphurous solutions under aerobic and anoxic conditions by haloalkalophilic Thioalkalivibrio denitrificans at 0.8-19.6 g S2O32--S L-1 and 0.2-0.58 g NO2 L-1, respectively. The experiments were conducted as batch assays with haloalkaline (pH 10 and ≥ 14 g Na+ L-1) thiosulphate solution. Aerobically, the highest biotransformation rate of thiosulphate obtained was 0.03 h-1 at 8.5 g L S2O32--S. Based on Monod model, the maximum substrate utilisation rate (qm) was 0.024 h-1 with half saturation constant (Ks) 0.42 g S2O32--S L-1 at initial [S2O32--S] of 14 g L-1. S0 accumulated at [S2O32--S] ≥ 1.5 g L-1 (10% yield at initial 9.5 g S2O32--S L-1) and the highest S0 yield estimated with the model was 61% with initial [S2O32--S] of 16.5 g L-1. Anoxically, the maximum nitrite removal rate based on Monod modelling was 0.011 h-1 with Ks = 0.84 g NO2- L-1. Aerobically and anoxically the maximum specific growth rates (µm) were 0.046 and 0.022 h-1, respectively. In summary, high-rate aerobic biotransformation kinetics of thiosulphate were demonstrated, whereas the rates were slower and no S0 accumulated under anoxic conditions. Thus, future developments of biotechnical applications for the recovery of S0 from haloalkaline streams from the process industry should focus on aerobic treatment.HighlightsHaloalkaline S2O32- biotransformations kinetics by Thioalkalivibrio denitrificansAerobic thiosulphate-S bioconversion up to 0.024 h-1 with Ks = 0.42 g S2O32--S L-110% S0 yield with initial 9.5 g S2O32--S L-1 in aerobic conditionAnoxic NO2 removal up to 0.01 h-1 with Ks = 0.84 g NO2- L-1.

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 Istanbul, 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.

Arsenic removal from acidic solutions with biogenic ferric precipitates.

Treatment of acidic solution containing 5g/L of Fe(II) and 10mg/L of As(III) was studied in a system consisting of a biological fluidized-bed reactor (FBR) for iron oxidation, and a gravity settler for iron precipitation and separation of the ferric precipitates. At pH 3.0 and FBR retention time of 5.7h, 96-98% of the added Fe(II) precipitated (99.1% of which was jarosite). The highest iron oxidation and precipitation rates were 1070 and 28mg/L/h, respectively, and were achieved at pH 3.0. Subsequently, the effect of pH on arsenic removal through sorption and/or co-precipitation was examined by gradually decreasing solution pH from 3.0 to 1.6 (feed pH). At pH 3.0, 2.4 and 1.6, the highest arsenic removal efficiencies obtained were 99.5%, 80.1% and 7.1%, respectively. As the system had ferric precipitates in excess, decreased arsenic removal was likely due to reduced co-precipitation at pH<2.4. As(III) was partially oxidized to As(V) in the system. In shake flask experiments, As(V) sorbed onto jarosite better than As(III). Moreover, the sorption capacity of biogenic jarosite was significantly higher than that of synthetic jarosite. The developed bioprocess simultaneously and efficiently removes iron and arsenic from acidic solutions, indicating potential for mining wastewater treatment.

Kinetics of aerobic and anaerobic biomineralization of atrazine in surface and subsurface agricultural soils in Ohio.

The purpose of this study was to assess atrazine mineralization in surface and subsurface samples retrieved from vertical cores of agricultural soils from two farm sites in Ohio. The Defiance site (NW-Ohio) was on soybean-corn rotation and Piketon (S-Ohio) was on continuous corn cultivation. Both sites had a history of atrazine application for at least a couple of decades. The clay fraction increased at the Defiance site and the organic matter and total N content decreased with depth at both sites. Mineralization of atrazine was assessed by measurement of (14)CO2 during incubation of soil samples with [U-ring-(14)C]-atrazine. Abiotic mineralization was negligible in all soil samples. Aerobic mineralization rate constants declined and the corresponding half-lives increased with depth at the Defiance site. Anaerobic mineralization (supplemented with nitrate) was mostly below the detection at the Defiance site. In Piketon samples, the kinetic parameters of aerobic and anaerobic biomineralization of atrazine displayed considerable scatter among replicate cores and duplicate biometers. In general, this study concludes that data especially for anaerobic biomineralization of atrazine can be more variable as compared to aerobic conditions and cannot be extrapolated from one agricultural site to another.

Combination of a novel electrode material and artificial mediators to enhance power generation in an MFC.

This study focuses on two main aspects: developing a novel cost-effective electrode material and power production from domestic wastewater using three different mediators. Methylene blue (MB), neutral red (NR) and 2-hydroxy-1,4-naphthoquinone (HNQ) were selected as electrode mediators with different concentrations. A tin-coated copper mesh electrode was tested as anode electrode. Maximum power density of the microbial fuel cell (MFC) with 300 µM MB was 636 mW/m². Optimal mediator concentrations with respect to the achieved maximum power output for MB, NR and HNQ were 300 µM, 200 µM and 50 µM, respectively. The results demonstrate that tin-coated copper mesh showed a higher biocompatibility and electrical conductivity.

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.

Bio-reduction of tetrachloroethen using a H2-based membrane biofilm reactor and community fingerprinting.

Chlorinated ethenes in drinking water could be reductively dechlorinated to non-toxic ethene by using a hydrogen based membrane biofilm reactor (H2-MBfR) under denitrifying conditions as it provides an appropriate environment for dechlorinating bacteria in biofilm communities. This study evaluates the reductive dechlorination of perchloroethene (PCE) to non-toxic ethene (ETH) and comparative community analysis of the biofilm grown on the gas permeable membrane fibers. For these purposes, three H2-MBfRs receiving three different chlorinated ethenes (PCE, TCE and DCE) were operated under different hydraulic retention times (HRTs) and H2 pressures. Among these reactors, the H2-MBfR fed with PCE (H2-MBfR 1) accomplished a complete dechlorination, whereas cis-DCE accumulated in the TCE receiving H2-MBfR 2 and no dechlorination was detected in the DCE receiving H2-MBfR 3. The results showed that 95% of PCE dechlorinated to ETH together with over 99.8% dechlorination efficiency. Nitrate was the preferred electron acceptor as the most of electrons generated from H2 oxidation used for denitrification and dechlorination started under nitrate deficient conditions at increased H2 pressures. PCR-DGGE analysis showed that Dehalococcoides were present in autotrophic biofilm community dechlorinating PCE to ethene, and RDase genes analysis revealed that pceA, tceA, bvcA and vcrA, responsible for complete dechlorination step, were available in Dehalococcoides strains.

Bioelectricity generation in continuously-fed microbial fuel cell: effects of anode electrode material and hydraulic retention time.

The main aim of this study is to investigate the bioelectricity production in continuously-fed dual chambered microbial fuel cell (MFC). Initially, MFC was operated with different anode electrode material at constant hydraulic retention time (HRT) of 2d to evaluate the effect of electrode material on electricity production. Pt electrode yielded about 642 mW/m(2) power density, which was 4 times higher than that of the MFC with the mixed metal oxide titanium (Ti-TiO2). Further, MFC equipped with Pt electrode was operated at varying HRT (2-0.5d). The power density generation increased with decreasing HRT, corresponding to 1313 mW/m(2) which was maximum value obtained during this study. Additionally, decreasing HRT from 2 to 0.5d resulted in increasing effluent dissolved organic carbon (DOC) concentration from 1.92 g/L to 2.23 g/L, corresponding to DOC removal efficiencies of 46% and 38%, respectively.

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.

Electricity generation from young landfill leachate in a microbial fuel cell with a new electrode material.

This study aims at evaluating the performance of a two-chambered continuously fed microbial fuel cell with new Ti-TiO2 electrodes for bioelectricity generation from young landfill leachate at varying strength of wastewater (1-50 COD g/L) and hydraulic retention time (HRT, 0.25-2 days). The COD removal efficiency in the MFC increased with time and reached 45 % at full-strength leachate (50 g/L COD) feeding. The current generation increased with increasing leachate strength and decreasing HRT up to organic loading rate of 100 g COD/L/day. The maximum current density throughout the study was 11 A/m² at HRT of 0.5 day and organic loading rate of 67 g COD/L/day. Coulombic efficiency (CE) decreased from 57 % at feed COD concentration of 1 g/L to less than 1 % when feed COD concentration was 50 g/L. Increase in OLR resulted in increase in power output but decrease in CE.

Bioelectricity production using a new electrode in a microbial fuel cell.

Electrode materials play a key role in enhancing the electricity generation in the microbial fuel cell (MFC). In this study, a new material (Ti-TiO(2)) was used as an anode electrode and compared with a graphite electrode for electricity generation. Current densities were 476.6 and 31 mA/m(2) for Ti-TiO(2) and graphite electrodes, respectively. The PCR-DGGE analysis of enriched microbial communities from estuary revealed that MFC reactors were dominated by Shewanella haliotis, Enterococcus sp., and Enterobacter sp. Bioelectrochemical kinetic works in the MFC with Ti-TiO(2) electrode revealed that the parameters by non-linear curve fitting with the confidence bounds of 95% gave good fit with the kinetic constants of η (difference between the anode potential and anode potential giving one-half of the maximum current density) = 0.35 V, K (s) (Half-saturation constant) = 2.93 mM and J (max) = 0.39 A/m(2) for T = 298 K and F = 96.485 C/mol-e(-). From the results observed, it is clear that Ti-TiO(2) electrode is a promising candidate for electricity generation in MFC.

Predictive modelling of Fe(III) precipitation in iron removal process for bioleaching circuits.

In this study, the applicability of three modelling approaches was determined in an effort to describe complex relationships between process parameters and to predict the performance of an integrated process, which consisted of a fluidized bed bioreactor for Fe(3+) regeneration and a gravity settler for precipitative iron removal. Self-organizing maps were used to visually evaluate the associations between variables prior to the comparison of two different modelling methods, the multiple regression modelling and artificial neural network (ANN) modelling, for predicting Fe(III) precipitation. With the ANN model, an excellent match between the predicted and measured data was obtained (R (2) = 0.97). The best-fitting regression model also gave a good fit (R (2) = 0.87). This study demonstrates that ANNs and regression models are robust tools for predicting iron precipitation in the integrated process and can thus be used in the management of such systems.

COD fractions of leachate from aerobic and anaerobic pilot scale landfill reactors.

One of the most important problems with designing and maintaining a landfill is managing leachate that generated when water passes through the waste. In this study, leachate samples taken from aerobic and anaerobic landfill reactors operated with and without leachate recirculation are investigated in terms of biodegradable and non-biodegradable fractions of COD. The operation time is 600 days for anaerobic reactors and 250 days for aerobic reactors. Results of this study show that while the values of soluble inert COD to total COD in the leachate of aerobic landfill with leachate recirculation and aerobic dry reactors are determined around 40%, this rate was found around 30% in the leachate of anaerobic landfill with leachate recirculation and traditional landfill reactors. The reason for this difference is that the aerobic reactors generated much more microbial products. Because of this condition, it can be concluded that total inert COD/total COD ratios of the aerobic reactors were 60%, whereas those of anaerobic reactors were 50%. This study is important for modeling, design, and operation of landfill leachate treatment systems and determination of discharge limits.

Biologically Fe2+ oxidizing fluidized bed reactor performance and controlling of Fe3+ recycle during heap bioleaching: an artificial neural network-based model.

The performance of a biological Fe(2+) oxidizing fluidized bed reactor (FBR) was modeled by a popular neural network-back-propagation algorithm over a period of 220 days at 37 degrees C under different operational conditions. A method is proposed for modeling Fe(3+) production in FBR and thereby managing the regeneration of Fe(3+) for heap leaching application, based on an artificial neural network-back-propagation algorithm. Depending on output value, relevant control strategies and actions are activated, and Fe(3+) production in FBR was considered as a critical output parameter. The modeling of effluent Fe(3+) concentration was very successful, and an excellent match was obtained between the measured and the predicted concentrations.

Sulfidogenic fluidized-bed treatment of metal-containing wastewater at 8 and 65 degrees C temperatures is limited by acetate oxidation.

Acetate utilization in sulfidogenic fluidized-bed reactors (FBRs) was investigated for the treatment of iron containing wastewater at low (8 degrees C) and high (65 degrees C) temperatures. The FBRs operated at low and high temperatures were inoculated with cultures of sulfate-reducing bacteria (SRB) originally enriched from arctic and hot mining environments, respectively. Acetate was not utilized as a carbon and electron source for SRB at 8 degrees C. With ethanol, hydrogen sulfide was produced from ethanol to acetate oxidation, which precipitated the iron. Then, several attempts were made to obtain acetate oxidation at 8 degrees C. Inoculation of two different low temperature enrichments and operating the FBR for a long period of time (321 days) did not result in enrichment of acetate oxidizing SRB. Due to the absence of acetate oxidation at 8 degrees C, external alkalinity addition was required to keep the pH neutral. At 65 degrees C, average acetate and sulfate removals were 52+/-12% and 24+/-8% at 670 mg/Ld acetate and 1500 mg/Ld sulfate loadings, respectively. The produced alkalinity from acetate oxidation increased the pH from 6.4 to around 7.5 and electron flow to sulfate reduction averaged 65%. Denaturing gradient gel electrophoresis (DGGE) analysis of 16S rRNA genes showed quite stable SRB community at 8 degrees C, whereas, at 65 degrees C SRB community was dynamic. In the FBRs, Desulfomicrobium apsheronum and Desulfosporosinus sp. at 8 degrees C and Desulfotomaculum sp. at 65 degrees C were detected.

Mineral and iron oxidation at low temperatures by pure and mixed cultures of acidophilic microorganisms.

An enrichment culture from a boreal sulfide mine environment containing a low-grade polymetallic ore was tested in column bioreactors for simulation of low temperature heap leaching. PCR-denaturing gradient gel electrophoresis and 16S rRNA gene sequencing revealed the enrichment culture contained an Acidithiobacillus ferrooxidans strain with high 16S rRNA gene similarity to the psychrotolerant strain SS3 and a mesophilic Leptospirillum ferrooxidans strain. As the mixed culture contained a strain that was within a clade with SS3, we used the SS3 pure culture to compare leaching rates with the At. ferrooxidans type strain in stirred tank reactors for mineral sulfide dissolution at various temperatures. The psychrotolerant strain SS3 catalyzed pyrite, pyrite/arsenopyrite, and chalcopyrite concentrate leaching. The rates were lower at 5 degrees C than at 30 degrees C, despite that all the available iron was in the oxidized form in the presence of At. ferrooxidans SS3. This suggests that although efficient At. ferrooxidans SS3 mediated biological oxidation of ferrous iron occurred, chemical oxidation of the sulfide minerals by ferric iron was rate limiting. In the column reactors, the leaching rates were much less affected by low temperatures than in the stirred tank reactors. A factor for the relatively high rates of mineral oxidation at 7 degrees C is that ferric iron remained in the soluble phase whereas, at 21 degrees C the ferric iron precipitated. Temperature gradient analysis of ferrous iron oxidation by this enrichment culture demonstrated two temperature optima for ferrous iron oxidation and that the mixed culture was capable of ferrous iron oxidation at 5 degrees C.

Kinetics of iron oxidation by Leptospirillum ferriphilum dominated culture at pH below one.

The kinetics of ferrous iron oxidation by Leptospirillum ferriphilum (L. ferriphilum) dominated culture was studied in the concentration range of 0.1-20 g Fe(2+)/L and the effect of ferric iron (0-60 g Fe(3+)/L) on Fe(2+) oxidation was investigated at pH below one. Denaturing gradient gel electrophoresis of PCR amplified 16S rRNA genes followed by partial sequencing confirmed that the bacterial community was dominated by L. ferriphilum. In batch assays, Fe(2+) oxidation started without lag phase and the oxidation was completed within 1 to 60 h depending on the initial Fe(2+) concentration. The specific Fe(2+) oxidation rates increased up to around 4 g/L and started to decrease at above 4 g/L. This implies substrate inhibition of Fe(2+) oxidation at higher concentrations. Haldane equation fitted the experimental data reasonably well (R(2) = 0.90). The maximum specific oxidation rate (q(m)) was 2.4 mg/mg VS . h, and the values of the half saturation (K(s)) and self inhibition constants (K(i)) were 413 and 8,650 mg/L, respectively. Fe(2+) oxidation was competitively inhibited by Fe(3+) and the competitive inhibition constant (K(ii)) was 830 mg/L. The time required to reach threshold Fe(2+) concentration was around 1 day and 2.3 days with initial Fe(3+) concentration of 5 and 60 g/L, respectively. The threshold Fe(2+) concentration, below which no further Fe(2+) oxidation occurred, linearly increased with increasing initial Fe(2+) and Fe(3+) concentrations. Fe(2+) oxidation proceeds by L. ferriphilum dominated culture at pH below 1 even in the presence of 60 g Fe(3+)/L. This indicates potential of using and biologically regenerating concentrated Fe(3+) sulfate solutions required, for example, in indirect tank leaching of ore concentrates.

Influence of leachate recirculation on aerobic and anaerobic decomposition of solid wastes.

In this study, the effect of leachate recirculation on aerobic and anaerobic degradation of municipal solid wastes is determined by four laboratory-scale landfill reactors. The options studied and compared with the traditional anaerobic landfill are: leachate recirculation, landfill aeration, and aeration with leachate recirculation. Leachate quality is regularly monitored by the means of pH, alkalinity, total dissolved solids, conductivity, oxidation-reduction potential, chloride, chemical oxygen demand, ammonia, and total Kjeldahl nitrogen, in addition to generated leachate quantity. Aerobic leachate recirculated landfill appears to be the most effective option in the removal of organic matter and ammonia. The main difference between aerobic recirculated and non-recirculated landfill options is determined at leachate quantity. Recirculation is more effective on anaerobic degradation of solid waste than aerobic degradation. Further studies are going on to determine the optimum operational conditions for aeration and leachate recirculation rates, also with the operational costs of aeration and recirculation.

Sulfidogenic fluidized-bed treatment of metal-containing wastewater at low and high temperatures.

The applicability of a fluidized-bed reactor (FBR)-based sulfate reducing bioprocess was investigated for the treatment of iron-containing (40-90 mg/L) acidic wastewater at low (8 degrees C) and high (65 degrees C) temperatures. The FBRs operated at low and high temperatures were inoculated with cultures of sulfate-reducing bacteria (SRB) originally enriched from arctic and hot mining environments, respectively. Ethanol was supplemented as carbon and electron source for SRB. At 8 degrees C, ethanol oxidation and sulfate reduction rates increased steadily and reached 320 and 265 mg/L.day, respectively, after 1 month of operation. After this point, the rates did not change significantly during 130 days of operation. Despite the complete ethanol oxidation and iron precipitation, the average sulfate reduction efficiency was 35 +/- 4% between days 30 and 130 due to the accumulation of acetate. At 65 degrees C, a rapid startup was observed as 99.9, 46, and 29% ethanol, sulfate, acetate removals, in respective order, were observed after 6 days. The feed pH was decreased gradually from its initial value of 6 to around 3.7 during 100 days of operation. The wastewater pH of 4.3-4.4 was neutralized by the alkalinity produced in acetate oxidation and the average effluent pH was 7.8 +/- 0.8. As in the low temperature FBR, acetate accumulated. Hence, the oxidation of acetate is the rate-limiting step in the sulfidogenic ethanol oxidation by thermophilic and psychrotrophic SRB. The sulfate reduction rate is three times and acetate oxidation rate is four times higher at 65 degrees C than at 8 degrees C.

Neural network prediction of thermophilic (65 degrees C) sulfidogenic fluidized-bed reactor performance for the treatment of metal-containing wastewater.

The performance of a fluidized-bed reactor (FBR) based sulfate reducing bioprocess was predicted using artificial neural network (ANN). The FBR was operated at high (65 degrees C) temperature and it was fed with iron (40-90 mg/L) and sulfate (1,000-1,500 mg/L) containing acidic (pH = 3.5-6) synthetic wastewater. Ethanol was supplemented as carbon and electron source for sulfate reducing bacteria (SRB). The wastewater pH of 4.3-4.4 was neutralized by the alkalinity produced in acetate oxidation and the average effluent pH was 7.8 +/- 0.8. The oxidation of acetate is the rate-limiting step in the sulfidogenic ethanol oxidation by thermophilic SRB, which resulted in acetate accumulation. Sulfate reduction and acetate oxidation rates showed variation depending on the operational conditions with the maximum rates of 1 g/L/d (0.2 g/g volatile solids (VS)/d) and 0.3 g/L/d (0.06 g/g VS/d), respectively. This study presents an ANN model predicting the performance of the reactor and determining the optimal architecture of this model; such as best back-propagation (BP) algorithm and neuron numbers. The Levenberg-Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 20. The developed ANN model predicted acetate (R=0.91), sulfate (R=0.95), sulfide (R=0.97), and alkalinity (R=0.94) in the FBR effluent. Hence, the ANN based model can be used to predict the FBR performance, to control the operational conditions for improved process performance.