Application of artificial intelligence tools in wastewater and waste gas treatment systems: Recent advances and prospects.

The non-linear complex relationships among the process variables in wastewater and waste gas treatment systems possess a significant challenge for real-time systems modelling. Data driven artificial intelligence (AI) tools are increasingly being adopted to predict the process performance, cost-effective process monitoring, and the control of different waste treatment systems, including those involving resource recovery. This review presents an in-depth analysis of the applications of emerging AI tools in physico-chemical and biological processes for the treatment of air pollutants, water and wastewater, and resource recovery processes. Additionally, the successful implementation of AI-controlled wastewater and waste gas treatment systems, along with real-time monitoring at the industrial scale are discussed.

Neuro-fuzzy modelling of a continuous stirred tank bioreactor with ceramic membrane technology for treating petroleum refinery effluent: a case study from Assam, India.

A continuous stirred tank bioreactor (CSTB) with cell recycling combined with ceramic membrane technology and inoculated with Rhodococcus opacus PD630 was employed to treat petroleum refinery wastewater for simultaneous chemical oxygen demand (COD) removal and lipid production from the retentate obtained during wastewater treatment. In the present study, the COD removal efficiency (CODRE) (%) and lipid concentration (g/L) were predicted using two artificial intelligence models, i.e., an artificial neural network (ANN) and a neuro-fuzzy neural network (NF-NN) with a network topology of 6-25-2 being the best for NF-NN. The results revealed the superiority of NF-NN over ANN in terms of determination coefficient (R2), root mean square error (RMSE), and mean absolute percentage error (MAPE). Three learning algorithms were tested with NF-NN; among them, the Bayesian regularization backpropagation (BR-BP) outperformed others. The sensitivity analysis revealed that, if solid retention time and biomass concentrations were maintained between 35 and 75 h and 3.0 g/L and 3.5 g/L, respectively, high CODRE (93%) and lipid concentration (2.8 g/L) could be obtained consistently.

Optimization of low-grade coal and refuse-derived fuel blends for improved co-combustion behavior in coal-fired power plants.

This study is aimed at utilizing three waste materials, i.e., solid refuse fuel (SRF), tire derived fuel (TDF), and sludge derived fuel (SDF), as eco-friendly alternatives to coal-only combustion in co-firing power plants. The contribution of waste materials is limited to ≤5% in the composition of the mixed fuel (coal + waste materials). Statistical experimental design and response surface methodology are employed to investigate the effect of mixed fuel composition (SRF, TDF, and SDF) on gross calorific value (GCV) and ash fusion temperature (AFT). A quadratic model is developed and statistically verified to apprehend mixed fuel constituents' individual and combined effects on GCV and AFT. Constrained optimization of fuel blend, i.e., GCV >1,250 kcal/kg and AFT >1,200 °C, using the polynomial models projected the fuel-blend containing 95% coal with 3.84% SRF, 0.35% TDF, and 0.81% SDF. The observed GCV of 5,307 kcal/kg and AFT of 1225 °C for the optimized blend were within 1% of the model predicted values, thereby establishing the robustness of the models. The findings from this study can foster sustainable economic development and zero CO2 emission objectives by optimizing the utilization of waste materials without compromising the GCV and AFT of the mixed fuels in coal-fired power plants.

Predictive modelling and optimization of an airlift bioreactor for selenite removal from wastewater using artificial neural networks and particle swarm optimization.

Selenite (Se4+) is the most toxic of all the oxyanion forms of selenium. In this study, a feed forward back propagation (BP) based artificial neural network (ANN) model was developed for a fungal pelleted airlift bioreactor (ALR) system treating selenite-laden wastewater. The performance of the bioreactor, i.e., selenite removal efficiency (REselenite) (%) was predicted through two input parameters, namely, the influent selenite concentration (ICselenite) (10 mg/L - 60 mg/L) and hydraulic retention time (HRT) (24 h - 72 h). After training and testing with 96 sets of data points using the Levenberg-Marquardt algorithm, a multi-layer perceptron model (2-10-1) was established. High values of the correlation coefficient (0.96 ≤ R ≤ 0.98), along with low root mean square error (1.72 ≤ RMSE ≤ 2.81) and mean absolute percentage error (1.67 ≤ MAPE ≤ 2.67), clearly demonstrate the accuracy of the ANN model (> 96%) when compared to the experimental data. To ensure an efficient and economically feasible operation of the ALR, the process parameters were optimized using the particle swarm optimization (PSO) algorithm coupled with the neural model. The REselenite was maximized while minimizing the HRT for a preferably higher range of ICselenite. Thus, the most favourable optimum conditions were suggested as: ICselenite - 50.45 mg/L and HRT - 24 h, resulting in REselenite of 69.4%. Overall, it can be inferred that ANN models can successfully substitute knowledge-based models to predict the REselenite in an ALR, and the process parameters can be effectively optimized using PSO.

Immobilization of microorganisms in activated zeolite beads and alkaline pretreated straws for ammonium-nitrogen removal from urban river water.

The non-treated wastewater from residential areas contains high concentrations of ammonium-nitrogen (NH4+-N). When discharged into the drainage water system, it deteriorates the water quality in urban rivers. This study used two types of materials to form eco-bags, using activated zeolite bead (AZB) and alkaline pretreated straw (APS), in geotextile bags for easy recovery and reuse. The AZB and APS provided the breeding habitat for the microorganisms that promoted biofilm formation on their surface. The immobilization of engineered denitrification microorganisms facilitated the removal of NH4+-N from the urban river water. The NH4+-N removal in the AZB and APS bags were in the range of 64-73%, and 56-61%, respectively, while the chemical oxygen demand (COD) removal in the AZB and APS bags ranged from 33-36%, and 30-31%, respectively. In addition, as evident from DNA and microbial community analysis, the microorganisms demonstrated a greater proclivity to grow and proliferate on the surface of AZB and APS and improved the water quality of urban rivers.

Characterization of refuse derived fuel samples prepared from municipal solid waste in Vellore, India.

The objective of this work was to explore an alternative way to manage the non-biodegradable and non-recyclable fraction of municipal solid waste (MSW) in Vellore city, India. Refuse-derived fuel (RDF) samples with different proportions of plastic, thermocol, foam and jute straw were formulated. The RDF samples were characterized in the form of heating values (proximate and ultimate analysis), surface properties through X-ray diffraction (XRD) and thermal stability through thermogravimetric analysis (TGA). The measured higher heating values (HHV) of four RDF samples varying between 6032 and 6168 kcal/kg were effectively modelled using various empirical models for the prediction of HHV based on their elemental analysis. Higher absolute weight loss in TGA was evident in samples with jute straw while the highest rate of weight loss was noted in samples with a higher proportion of thermocol. Results from this preliminary investigation of RDF samples prepared from non-biodegradable and non-recyclable fractions of MSW warrants an exhaustive analysis of a larger pool of samples to project appropriate RDF composition for better energy recovery.

Process optimization, metabolic engineering interventions and commercialization of microbial polyhydroxyalkanoates production - A state-of-the art review.

BACKGROUND: Microbial polyhydroxyalkanoates (PHAs) produced using renewable resources could be the best alternative for conventional plastics. Despite their incredible potential, commercial production of PHAs remains very low. Nevertheless, sincere attempts have been made by researchers to improve the yield and economic viability of PHA production by utilizing low-cost agricultural or industrial wastes. In this context, the use of efficient microbial culture or consortia, adoption of experimental design to trace ideal growth conditions, nutritional requirements, and intervention of metabolic engineering tools have gained significant attention. PURPOSE AND SCOPE: This review has been structured to highlight the important microbial sources for PHA production, use of conventional and non-conventional substrates, product optimization using experimental design, metabolic engineering strategies, and global players in the commercialization of PHA in the past two decades. The challenges about PHA recovery and analysis have also been discussed which possess indirect hurdle while expanding the horizon of PHA-based bioplastics. SUMMARY: Selection of appropriate microorganism and substrate plays a vital role in improving the productivity and characteristics of PHAs. Experimental design-based bioprocess, use of metabolic engineering tools, and optimal product recovery techniques are invaluable in this dimension. CONCLUSION: Optimization strategies, which are being explored in isolation, need to be logically integrated for the successful commercialization of microbial PHAs.

Activated red mud as a permeable reactive barrier material for fluoride removal from groundwater: parameter optimisation and physico-chemical characterisation.

The main aim of this work is to test the performance of red mud as a permeable reactive barrier (PRB) material for fluoride removal from water. Batch experiments were carried out to optimise the fluoride removal efficiency (RE) of activated red mud (ARM) based on four selected parameters, namely, the initial fluoride concentration (3-40 mg/L), adsorbent dose (0.5-5 g/L), pH (3.0-11.0) and ionic strength (0.001-0.5 M). Statistical analysis of the results revealed the optimum conditions as initial fluoride concentration -21.46 mg/L, adsorbent dose -2.77 g/L, pH 7.01 and ionic strength -0.24 M, respectively. Under the optimum conditions, fluoride RE of 87.3% was achieved. The individual effects due to initial fluoride concentration, adsorbent dose and ionic strength on fluoride removal were highly significant (F = 59.69; P < 0.005); whereas adsorbent dose, pH and ionic strength showed the greatest squared effects (F = 26.05; P < 0.001). The interaction effect due to initial fluoride concentration and adsorbent dose was also found to be significant (F = 12.52; P = 0.002) for fluoride removal. Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) analyses were performed to identify the change in functional group and surface topography following red mud activation.

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach.

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box-Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand-metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model-genetic algorithm (RSM-GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47µg/g) is facilitated at 30.22mg C/L of EtOH with initial As(III) concentration of 196.77µg/L at pH5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.

Occurrence and removal of antibiotics, hormones and several other pharmaceuticals in wastewater treatment plants of the largest industrial city of Korea.

Occurrence and removal efficiencies of 20 pharmaceuticals and personal care products (PPCPs) including antibiotics, hormones, and several other miscellaneous pharmaceuticals (analgesics, antiepileptics, antilipidemics, antihypertensives, antiseptics, and stimulants) were investigated in five wastewater treatment plants (WWTPs) of Ulsan, the largest industrial city of Korea. The compounds were extracted from wastewater samples by solid-phase extraction (SPE) and analyzed by High-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). The results showed that acetaminophen, atenolol and lincomycin were the main individual pollutants usually found in concentrations over 10 µg/L in the sewage influent. In the WWTPs, the concentrations of analgesic acetaminophen, stimulant caffeine, hormones estriol and estradiol decreased by over 99%. On the contrary, the antibiotic sulfamethazine, the antihypertensive metoprolol, and the antiepileptic carbamazepine exhibited removal efficiencies below 30%. Particularly, removal of antibiotics was observed to vary between -11.2 and 69%. In the primary treatment (physico-chemical processes), the removal of pharmaceuticals was insignificant (up to 28%) and removal of majority of the pharmaceuticals occurred during the secondary treatment (biological processes). The compounds lincomycin, carbamazepine, atenolol, metoprolol, and triclosan showed better removal in WWTPs employing modified activated sludge process with co-existence of anoxic-oxic condition. Further investigation into the design and operational aspects of the biological processes is warranted for the efficient removal of PPCPs, particularly antibiotics, to secure healthy water resource in the receiving downstream, thereby ensuring a sustainable water cycle management.

Enhanced methane recovery by food waste leachate injection into a landfill in Korea.

The current food waste leachate (FWL) disposal practice in Korea warrants urgent attention and necessary action to develop an innovative and sustainable disposal strategy, which is both environmentally friendly and economically beneficial. In this study, methane production by FWL injection into a municipal solid waste landfill with landfill gas (LFG) recovery facility was evaluated for a period of more than 4 months. With the target of recovering LFG with methane content ~50%, optimum LFG extraction rate was decided by a trial and error approach during the field investigation in five different phases. The results showed that, upon FWL injection, LFG extraction rate of ~20 m(3)/h was reasonable to recover LFG with methane content ~58%. Considering the estimated methane production potential of 31.7 m(3) CH(4) per ton of FWL, methane recovery from the landfill was enhanced by 14%. The scientific findings of this short-term investigation indicates that FWL can be injected into the existing sanitary landfills to tackle the present issue and such landfills with efficient liner and gas collection facility can be utilized as absolute and sustainable environmental infrastructures.

Sorption of triclosan onto activated carbon, kaolinite and montmorillonite: effects of pH, ionic strength, and humic acid.

Sorption of triclosan on three sorbents, viz., activated carbon, kaolinite and montmorillonite was studied as a function of pH, ionic strength and humic acid (HA) concentration through controlled batch experiments. Triclosan sorption was found to be higher in the acidic pH range, as varying pH showed significant influence on the surface charge of the sorbents and degree of ionization of the sorbate. Sorption capacity of the sorbents increased with an increase in the ionic strength of solution. At low pH (pH 3), the overall increase in triclosan sorption was 1.2, approximately 4 and 3.5 times, respectively for activated carbon, kaolinite and montmorillonite when ionic strength was increased from 1x10(-3) to 5x10(-1) M. Triclosan sorption onto activated carbon decreased from 31.4 to 10.6 mg g(-1) by increasing the HA concentration to 200 mg C L(-1). However, during sorption onto kaolinite and montmorillonite, the effect of HA was very complex probably due to (i) hydrophobicity (log K(ow)=4.76) of triclosan; and (ii) complexation of HA with triclosan. Though triclosan sorption onto activated carbon is higher, the potential of kaolinite and montmorillonite in controlling the transport of triclosan in subsurface environment can still be appreciable.

Methane production from food waste leachate in laboratory-scale simulated landfill.

Due to the prohibition of food waste landfilling in Korea from 2005 and the subsequent ban on the marine disposal of organic sludge, including leachate generated from food waste recycling facilities from 2012, it is urgent to develop an innovative and sustainable disposal strategy that is eco-friendly, yet economically beneficial. In this study, methane production from food waste leachate (FWL) in landfill sites with landfill gas recovery facilities was evaluated in simulated landfill reactors (lysimeters) for a period of 90 d with four different inoculum-substrate ratios (ISRs) on volatile solid (VS) basis. Simultaneous biochemical methane potential batch experiments were also conducted at the same ISRs for 30 d to compare CH(4) yield obtained from lysimeter studies. Under the experimental conditions, a maximum CH(4) yield of 0.272 and 0.294 L/g VS was obtained in the batch and lysimeter studies, respectively, at ISR of 1:1. The biodegradability of FWL in batch and lysimeter experiments at ISR of 1:1 was 64% and 69%, respectively. The calculated data using the modified Gompertz equation for the cumulative CH(4) production showed good agreement with the experimental result obtained from lysimeter study. Based on the results obtained from this study, field-scale pilot test is required to re-evaluate the existing sanitary landfills with efficient leachate collection and gas recovery facilities as engineered bioreactors to treat non-hazardous liquid organic wastes for energy recovery with optimum utilization of facilities.

Methane production potential of leachate generated from Korean food waste recycling facilities: a lab-scale study.

This paper examines the applicability of food waste leachate (FWL) in bioreactor landfills or anaerobic digesters to produce methane as a sustainable solution to the persisting leachate management problem in Korea. Taking into account the climatic conditions in Korea and FWL characteristics, the effect of key parameters, viz., temperature, alkalinity and salinity on methane yield was investigated. The monthly average moisture content and the ratio of volatile solids to total solids of the FWL were found to be 84% and 91%, respectively. The biochemical methane potential experiment under standard digestion conditions showed the methane yield of FWL to be 358 and 478 ml/g VS after 10 and 28 days of digestion, respectively, with an average methane content of 70%. Elemental analysis showed the chemical composition of FWL to be C(13.02)H(23.01)O(5.93)N(1). The highest methane yield of 403 ml/g VS was obtained at 35 degrees C due to the adaptation of seed microorganisms to mesophilic atmosphere, while methane yields at 25, 45 and 55 degrees C were 370, 351 and 275 ml/g VS, respectively, at the end of 20 days. Addition of alkalinity had a favorable effect on the methane yield. Dilution of FWL with salinity of 2g/l NaCl resulted in 561 ml CH(4)/g VS at the end of 30 days. Considering its high biodegradability (82.6%) and methane production potential, anaerobic digestion of FWL in bioreactor landfills or anaerobic digesters with a preferred control of alkalinity and salinity can be considered as a sustainable solution to the present emergent problem.

A unified model of ammonium oxidation rate at various initial ammonium strength and active ammonium oxidizer concentrations.

This paper attempts to provide insight into the biological ammonium oxidation process applied to high-strength ammonium wastewater treatment. The ammonium oxidation process has been investigated at various ammonium and biomass concentrations. Using the oxygen uptake rate (OUR) method, a proportion of both active ammonium oxidizers (AAO) and nitrite oxidizers to the total suspended solids were separately estimated, and then tested to normalize the ammonium oxidation rate at various ammonium strengths and AAO concentrations. High-ammonium strength showed no significant inhibition to ammonium oxidation due to high-AAO concentration. It was demonstrated that the key factor deciding the specific ammonium oxidation rate was the ratio of ammonium concentration to the active nitrifiers (AN) concentration, but not the sole-variable such as initial ammonium concentration and AN concentration. Contois model was screened to suitably fit the ammonium oxidation kinetics under the high-ammonium loading condition, resulting in a half-saturation constant of 0.028 mg N mg(-1) AAO and a maximum specific ammonium oxidation rate of 3.56 g N g(-1)AAO d(-1).

Adsorption equilibrium and kinetics of polyvinyl alcohol from aqueous solution on powdered activated carbon.

In this study, powdered activated carbon (PAC) was used to remove polyvinyl alcohol (PVA) from the aqueous PVA solution. The adsorption kinetics has been studied pertaining to various initial PVA concentration and PAC dosage. The rates of adsorption were found to conform to the second-order kinetics with good correlation. Boyd plot confirmed that external mass transfer was the rate-limiting step in the sorption process. The adsorption isotherm obtained resembled with H-type of isotherm, which indicated a high affinity of the solute for the sorption sites. The Freundlich model appeared to fit the isotherm data better than the Langmuir model. The thermodynamic parameters such as Delta H degrees , Delta S degrees and Delta G degrees were evaluated from the slope and intercept of linear plot of log Kc against (1/T) x 1000. The change in entropy (DeltaS degrees ) and heat of adsorption (Delta H degrees ) of PAC was estimated as 1.45 kJ mol(-1)K(-1) and 365 kJ mol(-1), respectively. The free energy of the adsorption at all temperatures was negative indicating a spontaneous process. The maximum PVA removal of 92% was obtained at a pH of 6.3 and contact time of 30 min for an adsorbent dose of 5 g/L.