Constructed wetland (CW) is a low-cost alternative technology to treat wastewater. This study was conducted to co-treat landfill leachate and municipal wastewater by using a CW system. Typha domingensis was transplanted to CW, which contains two substrate layers of adsorbents, namely, ZELIAC and zeolite. Response surface methodology and central composite design have been utilized to analyze experimental data. Contact time (h) and leachate-to-wastewater mixing ratio (%; v/v) were considered as independent variables. Colour, COD, ammonia, nickel, and cadmium contents were used as dependent variables. At optimum contact time (50.2 h) and leachate-to-wastewater mixing ratio (20.0%), removal efficiencies of colour, COD, ammonia, nickel, and cadmium contents were 90.3%, 86.7%, 99.2%, 86.0%, and 87.1%, respectively. The accumulation of Ni and Cd in the roots and shoots of T. domingensis was also monitored. Translocation factor (TF) was >1 in several runs; thus, Typha is classified as a hyper-accumulator plant.
This study determined the optimum conditions for preparation and adsorptive treatment of landfill leachate from banana pseudo-stem based activated carbon. Response surface methodology (RSM) based on Box-Behnken was applied to optimize the combination effect of three important reaction variables, i.e. activation temperature (°C), activation time and impregnation ratio (IR). The reaction was performed via a single step activation with ZnCl2 in a closed activation system. A series of 17 individual experiments were conducted and the results showed that the RSM based on BBD is very applicable for adsorptive removal of pollutants from landfill leachate treatment. The optimum conditions obtained by Design of Experiments (DOE) was at 761°C activation temperature, 87min activation time and 4.5g/g impregnation ratio with product yield (27%), iodine number (1101mg/g), color removal (91.2%) and COD removal (83.0%).
In Sarawak, pig farm operators are required to treat the wastewater containing pig waste and spilt food in oxidation ponds before discharge. However, information on the impact of this industry on surface water quality is lacking. Therefore, the objective of this study is to determine the impact of pig farm effluent on the water quality of Serin River and its tributaries. Results of analysis show that the tributary that received pond effluent has significantly higher mean of total suspended solids (TSS), biochemical oxygen demand (BOD5) chemical oxygen demand (COD), ammonia-nitrogen (NH3 -N), reactive phosphorus (SRP) and Escherichia coli (E. coli) concentrations when compared to those of the tributary that did not receive pond effluent. Comparisons between the stations upstream and downstream of the discharge point indicated that BOD5 and COD were significantly higher at the downstream station that received pond effluent. Dissolved oxygen (DO) was the lowest at the tributary receiving effluent from pig farms with a mean of 2.40 mg/l. According to the Interim Water Quality Standard of the Department of Environment, water quality at the tributary that received pig farm effluent falls into Class III whereas that of the other stations falls into Class II. It is recommended that further studies be conducted on the management of waste to explore the possibility of turning the waste into a resource so that water quality of rivers can remain pristine for drinking and recreation.
Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data.
Integrated fixed-film activated sludge (IFAS) process is considered as one of the leading-edge processes that provides a sustainable solution for wastewater treatment. IFAS was introduced as an advancement of the moving bed biofilm reactor by integrating the attached and the suspended growth systems. IFAS offers advantages over the conventional activated sludge process such as reduced footprint, enhanced nutrient removal, complete nitrification, longer solids retention time and better removal of anthropogenic composites. IFAS has been recognized as an attractive option as stated from the results of many pilot and full scales studies. Generally, IFAS achieves >90% removals for combined chemical oxygen demand and ammonia, improves sludge settling properties and enhances operational stability. Recently developed IFAS reactors incorporate frameworks for either methane production, energy generation through algae, or microbial fuel cells. This review details the recent development in IFAS with the focus on the pilot and full-scale applications. The microbial community analyses of IFAS biofilm and floc are underlined along with the special emphasis on organics and nitrogen removals, as well as the future research perspectives.
Landfill leachate is a liquid generated due to rainwater percolation through the waste in a landfill or dumping site that may contain high levels of organic matter, both biodegradable and non-biodegradable, which are the major sources of water pollution. Chemical oxygen demand (COD) and Ammoniacal Nitrogen (NH3-N) contents have been relevant indicators of severity and pollution potential of landfill leachate. The reductions of COD and NH3-N were investigated in this study using different combinations of media ratios of green mussel (GM) and zeolite (ZEO). Generally, ZEO is considered as a renowned adsorbent but with a relatively high in cost. In Malaysia, mussel shell is abundantly available as a by-product from the seafood industry, is regarded as waste, and is mostly left at the dumpsite to naturally deteriorate. Its quality and availability make GMs a cost-effective material. In this research study, leachate samples were characterized and found to contain high concentrations of COD and NH3-N. The adsorption process was conducted to find out the best combination media ratio between GM and ZEO. The removing efficiency was determined at different amounts of composite media ratios. The optimal adsorbent mixture ratios between (GM: ZEO) of 1.0:3.0 and 1.5:2.5 were considered as a more efficient technique in removing COD and NH3-N compared to exploiting these adsorbents individually. The optimal extenuation removal reduction was found at an approximately 65% of COD and 78% of NH3-N. The adsorption Isotherm Langmuir model exhibited a better fit with high regression coefficient for COD (R2 = 0.9998) and NH3-N (R2 = 0.9875), respectively. This means that the combination of GM: ZEO adsorption of landfill leachate in this analysis is homogeneous with the monolayer. The mixture of GMs and ZEO was observed to provide an alternative medium for the reduction of COD and NH3-N with comparatively lower cost.Implications: The concentration of organic constituents (COD) and ammoniacal nitrogen in stabilized landfill leachate have significantly strong influences of human health and the environment. The combination of mixing media green mussel and zeolite adsorbent enhancing organic constituents (COD) and ammoniacal nitrogen reduction efficiency from leachate. This would be greatly applicable in future research as well as conventionally minimizing high cost materials like zeolite, thereby lowering the operating cost of leachate treatment.
Ozonation, combined with the Fenton process (O(3)/H(2)O(2)/Fe(2+)), was used to treat matured landfill leachate. The effectiveness of the Fenton molar ratio, Fenton concentration, pH variance, and reaction time were evaluated under optimum operational conditions. The optimum removal values of chemical oxygen demand (COD), color, and NH(3)-N were found to be 65%, 98%, and 12%, respectively, for 90 min of ozonation using a Fenton molar ratio of 1 at a Fenton concentration of 0.05 mol L(-1) (1700 mg/L) H(2)O(2) and 0.05 mol L(-1) (2800 mg/L) Fe(2+) at pH 7. The maximum removal of NH(3)-N was 19% at 150 min. The ozone consumption for COD removal was 0.63 kg O(3)/kg COD. To evaluate the effectiveness, the results obtained in the treatment of stabilized leachate were compared with those obtained from other treatment processes, such as ozone alone, Fenton reaction alone, as well as combined Fenton and ozone. The combined method (i.e., O(3)/H(2)O(2)/Fe(2+)) achieved higher removal efficiencies for COD, color, and NH(3)-N compared with other studied applications.
The removal of concentrated colour (around 5039 Pt-Co) and chemical oxygen demand (COD; around 4142 mg L-1) from matured landfill leachate through a novel combination of humic acid extraction and coagulation with natural oil palm trunk starch (OPTS) was investigated in this study. Central composite design from response surface methodology of Design Expert-10 software executed the experimental design to correlate experimental factors with desired responses. Analysis of variance developed the quadratic model for four factors (e.g. coagulant dosage, slow mixing speed and time and centrifugation duration) and two responses (% removal of colour, COD). The model confirmed the highest colour (84.96%) and COD (48.84%) removal with a desirability function of 0.836 at the optimum condition of 1.68 g L-1 coagulant dose, 19.11 rpm slow mixing speed, 16.43 minutes for mixing time and 35.75 minutes for centrifugation duration. Better results of correlation coefficient (R2 = 0.98 and 0.96) and predicted R2 (0.94 and 0.84) indicates the model significance. Electron microscopic images display the amalgamation of flocs through bridging. Fourier transforms infrared spectra confirmed the existence of selected organic groups in OPTS, which eventually signifies the applied method.
Heterogeneous combinations of organic compounds (humic acid (HA) and fulvic acid) are the prime factor for the high concentration of colour and chemical oxygen demand (COD) in semi-aerobic stabilized landfill leachate. These organics are less biodegradable and cause a severe threat to environmental elements. Microfiltration and centrifugation processes were applied in this study to investigate the HA removal from stabilized leachate samples and its corresponding interference with COD and colour. The three-stage extraction process recovered a maximum of 1412 ± 2.5 mg/L (Pulau Burung landfill site (PBLS) leachate), 1510 ± 1.5 mg/L (Alor Pongsu landfill site (APLS leachate) at pH 1.5 and 1371 ± 2.5 mg/L (PBLS) and 1451 ± 1.5 mg/L (APLS) of HA (about 42% of the total COD concentration) at pH 2.5, which eventually indicates the process efficiency. Comparative characteristics analysis of recovered HA by scanning electron microscopy, energy-dispersive X-ray, X-ray photoelectron spectroscopy, and Fourier transform infrared significantly indicate the existence of identical elements in the recovered HA compared with the previous studies. The higher reduction (around 37%) in ultraviolet (UV) absorbance values (UV254 and UV280) in the final effluent indicates the elimination of aromaticity and conjugated double-bond compounds from leachate. Moreover, 36 and 39% COD and 39 and 44% colour removal exhibit substantial interference.
In this approach, a batch reactor was employed to study the degradation of pollutants under natural sunlight using TiO2 as a photocatalyst. The effects of photocatalyst dosage, reaction time and pH were investigated by evaluating the percentage removal efficiencies of total organic carbon (TOC), chemical oxygen demand (COD), biological oxygen demand (BOD) and biodegradability (BOD/COD). Design Expert-Response Surface Methodology Box Behnken Design (BBD) and MATLAB Artificial Neural Network - Adaptive Neuro Fuzzy Inference system (ANN-ANFIS) methods were employed to perform the statistical modelling. The experimental values of maximum percentage removal efficiencies were found to be TOC = 82.4, COD = 85.9, BOD = 30.9% and biodegradability was 0.070. According to RSM-BBD and ANFIS analysis, the maximum percentage removal efficiencies were found to be TOC = 90.3, 82.4; COD = 85.4, 85.9; BOD = 28.9, 30.9% and the biodegradability = 0.074, 0.080 respectively at the pH 7.5, reaction time 300 min and photocatalyst dosage of 4 g L-1. The study reveals both models found to be well predicted as compared with experimental values. The values of R2 for RSM-BBD (0.920) and for ANFIS (0.990) models were almost close to 1. The ANFIS model was found to be marginally better than that of RSM-BBD.
Water pollution due to the discharge of untreated industrial effluents is a serious environmental and public health issue. The presence of organic pollutants such as polycyclic aromatic hydrocarbons (PAHs) causes worldwide concern because of their mutagenic and carcinogenic effects on aquatic life, human beings, and the environment. PAHs are pervasive atmospheric compounds that cause nervous system damage, mental retardation, cancer, and renal kidney diseases. This research presents the first usage of palm kernel shell biochar (PKSB) (obtained from agricultural waste) for PAH removal from industrial wastewater (oil and gas wastewater/produced water). A batch scale study was conducted for the remediation of PAHs and chemical oxygen demand (COD) from produced water. The influence of operating parameters such as biochar dosage, pH, and contact time was optimized and validated using a response surface methodology (RSM). Under optimized conditions, i.e., biochar dosage 2.99 g L-1, pH 4.0, and contact time 208.89 min, 93.16% of PAHs and 97.84% of COD were predicted. However, under optimized conditions of independent variables, 95.34% of PAH and 98.21% of COD removal was obtained in the laboratory. The experimental data were fitted to the empirical second-order model of a suitable degree for the maximum removal of PAHs and COD by the biochar. ANOVA analysis showed a high coefficient of determination value (R2 = 0.97) and a reasonable second-order regression prediction. Additionally, the study also showed a comparative analysis of PKSB with previously used agricultural waste biochar for PAH and COD removal. The PKSB showed significantly higher removal efficiency than other types of biochar. The study also provides analysis on the reusability of PKSB for up to four cycles using two different methods. The methods reflected a significantly good performance for PAH and COD removal for up to two cycles. Hence, the study demonstrated a successful application of PKSB as a potential sustainable adsorbent for the removal of micro-pollutants from produced water.
In this study, landfill leachate was treated by using the sequencing batch reactor (SBR) process. Two types of the SBR, namely non-powdered activated carbon and powdered activated carbon (PAC-SBR) were used. The influence of aeration rate and contact time on SBR and PAC-SBR performances was investigated. Removal efficiencies of chemical oxygen demand (COD), colour, ammoniacal nitrogen (NH(3)-N), total dissolved salts (TDS), and sludge volume index (SVI) were monitored throughout the experiments. Response surface methodology (RSM) was applied for experimental design, analysis and optimization. Based on the results, the PAC-SBR displayed superior performance in term of removal efficiencies when compared to SBR. At the optimum conditions of aeration rate of 1L/min and contact time of 5.5h the PAC-SBR achieved 64.1%, 71.2%, 81.4%, and 1.33% removal of COD, colour, NH(3)-N, and TDS, respectively. The SVI value of PAC-SBR was 122.2 mL/g at optimum conditions.
The objective of this study was to investigate the performance of employing Fenton's reagent in the advanced oxidation of ozone to treat stabilized landfill leachate in an ozone reactor. A central composite design (CCD) with response surface methodology (RSM) was applied to evaluate the relationships between operating variables, such as ozone and Fenton dosage, pH, and reaction time, to identify the optimum operating conditions. Quadratic models for the following four responses proved to be significant with very low probabilities (<0.0001): chemical oxygen demand (COD), color, NH-N, and ozone consumption (OC). The obtained optimum conditions included a reaction time of 90 min, 30 g/m³ ozone, 0.01 mol/L₂H₂O,0.02 mol/L Fe²⁺, and pH 5. COD, color, and NH₃-N removal rates of 79%, 100%, and 20%, respectively, and 0.18 kg O₃/kg COD OC were obtained. The predictions correspond well with experimental results (COD, color, and NH-N removal rates of 78%, 98.5%, and 19%, respectively, and 0.29 kg O₃/kg COD OC). This method reduces the treatment time and improves the treatment efficiency relative to a previously published method that used Fenton's reagent prior to ozonation.
Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40-100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008-0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities.
With inoculum sludge from a conventional activated sludge wastewater treatment plant, three sequencing batch reactors (SBRs) fed with synthetic wastewater were operated at different high temperatures (30, 40 and 50±1°C) to study the formation of aerobic granular sludge (AGS) for simultaneous organics and nutrients removal with a complete cycle time of 3h. The AGS were successfully cultivated with influent loading rate of 1.6CODg(Ld)(-1). The COD/N ratio of the influent wastewater was 8. The results revealed that granules developed at 50°C have the highest average diameter, (3.36mm) with 98.17%, 94.45% and 72.46% removal efficiency observed in the system for COD, ammonia and phosphate, respectively. This study also demonstrated the capabilities of AGS formation at high temperatures which is suitable to be applied for hot climate conditions.
The effect of temperature on the efficiency of organics and nutrients removal during the cultivation of aerobic granular sludge (AGS) in biological treatment of synthetic wastewater was studied. With this aim, three 3 L sequencing batch reactors (SBRs) with influent loading rate of 1.6 COD g (L d)(-1) were operated at different high temperatures (30, 40 and 50 °C) for simultaneous COD, phosphate and ammonia removal at a complete cycle time of 3 h. The systems were successfully started up and progressed to steady state at different cultivation periods. The statistical comparison of COD, phosphate and ammonia for effluent from the three SBRs revealed that there was a significant difference between groups of all the working temperatures of the bioreactors. The AGS cultivated at different high temperatures also positively correlated with the accumulation of elements including carbon, oxygen, phosphorus, silicon, iron, aluminium, calcium and magnesium that played important roles in the granulation process.
An air-cathode MFC-adsorption hybrid system, made from earthen pot was designed and tested for simultaneous wastewater treatment and energy recovery. Such design had demonstrated superior characteristics of low internal resistance (29.3Ω) and favor to low-cost, efficient wastewater treatment and power generation (55mW/m(3)) with average current of 2.13±0.4mA. The performance between MFC-adsorption hybrid system was compared to the standalone adsorption system and results had demonstrated great pollutants removals of the integrated system especially for chemical oxygen demand (COD), biochemical oxygen demand (BOD3), total organic carbon (TOC), total volatile solids (TVS), ammoniacal nitrogen (NH3-N) and total nitrogen (TN) because such system combines the advantages of each individual unit. Besides the typical biological and electrochemical processes that happened in an MFC system, an additional physicochemical process from the activated carbon took place simultaneously in the MFC-adsorption hybrid system which would further improved on the wastewater quality.
A microbial fuel cell (MFC) integrated with adsorption system (MFC-AHS) is tested under various operating temperatures with palm oil mill effluent as the substrate. The optimum operating temperature for such system is found to be at ∼35°C with current, power density, internal resistance (Rin), Coulombic efficiency (CE) and maximum chemical oxygen demand (COD) removal of 2.51 ± 0.2 mA, 74 ± 6 mW m-3, 25.4 Ω, 10.65 ± 0.5% and 93.57 ± 1.2%, respectively. Maximum current density increases linearly with temperature at a rate of 0.1772 mA m-2 °C-1, whereas maximum power density was in a polynomial function. The temperature coefficient (Q10) is found to be 1.20 between 15°C and 35°C. Present studies have demonstrated better CE performance when compared to other MFC-AHSs. Generally, MFC-AHS has demonstrated higher COD removals when compared to standalone MFC regardless of operating temperatures.
ABBREVIATIONS: ACFF: activated carbon fiber felt; APHA: American Public Health Association; CE: Coulombic efficiency; COD: chemical oxygen demand; ECG: electrocardiogram; GAC: granular activated carbon; GFB: graphite fiber brush; MFC: microbial fuel cell; MFC-AHS: microbial fuel cell integrated with adsorption hybrid system; MFC-GG: microbial fuel cell integrated with graphite granules; POME: palm oil mill effluent; PTFE: polytetrafluoroethylene; SEM: scanning electron microscope.
In this study, laundry wastewater filtration was studied using hydrophilic polyvinylpyrollidone (PVP) modified polyethersulfone (PES) ultrafiltration membranes. The performances of PES/PVP membranes were assessed using commercial PES membrane with 10kDa in ultrafiltration. Operating parameters The influence of transmembrane pressure (TMP) and stirring speed on laundry wastewater flux was investigated. A higher permeate flux of 55.2L/m(2)h was obtained for modified PES membrane with high concentration of PVP at TMP of 500kPa and 750rpm of stirring speed. The separation efficiencies of membranes were also studied with respect to chemical oxygen demand (COD), total dissolved solids (TDS), turbidity and conductivity. Results showed that PES membrane with 10% of PVP had higher permeate flux, flux recovery and less fouling when compared with other membranes. Higher COD and TDS rejection of 88% and 82% were also observed for modified membranes due to the improved surface property of membranes. This indicated that modified PES membranes are suitable for the treatment of surfactant, detergent and oil from laundry wastewater.
A wastewater treatment plant (WWTP) is an essential part of the urban water cycle, which reduces concentration of pollutants in the river. For monitoring and control of WWTPs, researchers develop different models and systems. This study introduces a new deep learning model for predicting effluent quality parameters (EQPs) of a WWTP. A method that couples a convolutional neural network (CNN) with a novel version of radial basis function neural network (RBFNN) is proposed to simultaneously predict and estimate uncertainty of data. The multi-kernel RBFNN (MKRBFNN) uses two activation functions to improve the efficiency of the RBFNN model. The salp swarm algorithm is utilized to set the MKRBFNN and CNN parameters. The main advantage of the CNN-MKRBFNN-salp swarm algorithm (SSA) is to automatically extract features from data points. In this study, influent parameters (if) are used as inputs. Biological oxygen demand (BODif), chemical oxygen demand (CODif), total suspended solids (TSSif), volatile suspended solids (VSSif), and sediment (SEDef) are used to predict EQPs, including CODef, BODef, and TSSef. At the testing level, the Nash-Sutcliffe efficiencies of CNN-MKRBFNN-SSA are 0.98, 0.97, and 0.98 for predicting CODef, BODef, and TSSef. Results indicate that the CNN-MKRBFNN-SSA is a robust model for simulating complex phenomena.