Articles de revues sur le sujet « TANNERY WASTEWATER TREATMENT, ANAEROBIC DIGESTION, WASTEWATER TREATMENT MODELLING »

This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feedforward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.

Computational fluid dynamics (CFD) is a rapidly emerging field in wastewater treatment (WWT), with application to almost all unit processes. This paper provides an overview of CFD applied to a wide range of unit processes in water and WWT from hydraulic elements like flow splitting to physical, chemical and biological processes like suspended growth nutrient removal and anaerobic digestion. The paper's focus is on articulating the state of practice and research and development needs. The level of CFD's capability varies between different process units, with a high frequency of application in the areas of final sedimentation, activated sludge basin modelling and disinfection, and greater needs in primary sedimentation and anaerobic digestion. While approaches are comprehensive, generally capable of incorporating non-Newtonian fluids, multiphase systems and biokinetics, they are not broad, and further work should be done to address the diversity of process designs. Many units have not been addressed to date. Further needs are identified throughout, but common requirements include improved particle aggregation and breakup (flocculation), and improved coupling of biology and hydraulics.

This paper describes a new anaerobic digestion model for wastewater treatment systems (MantisAD). The model has been developed specifically for plant-wide wastewater treatment modelling. That is, rather than modelling nitrogen as a series of fractions of other carbonaceous state variables, this new model includes six dedicated nitrogen state variables. This structure makes this new anaerobic model easier to incorporate into plant-wide models by simplifying the aerobic/anaerobic model interfaces. The model is complete and initial success with the model has been achieved. A comprehensive description of the model including a Petersen Matrix representation of the model is included as is a case study in which the model is applied to full-scale anaerobic digesters.

Approaches to mathematical modelling of anaerobic digestion and criteria for reactor design in anaerobic wastewater treatment are based on biological degradation kinetics. Whatever type of kinetics is used, the crucial problem always is reliable parameter estimation. For Monod-type kinetics a concept based on batch and fed-batch techniques is presented, which allows accurate estimation of kinetic parameters Vmax and KS in short-time experiments. Following the method of Optimal Experimental Design, sensitivity analysis is applied to design fed-batch experiments. The paper presents the methodology and results for the anaerobic degradation of acetic acid and discusses further implications of the experimental strategy.

A wastewater-treatment flowsheet was developed to integrate uniquely designed biological processes with physical-chemical unit processes, allowing conversion of the organic carbon in the wastewater to methane, the removal and recovery of phosphorus and nitrogen from the wastewater, and the production of water suitable for reuse. In the flowsheet, energy is derived from the wastewater by first shunting a large fraction of the organic carbon in the wastewater to a solids slurry which is treated via anaerobic digestion. The anaerobic digestion system consists of focused pulsed (FP) pretreatment coupled to anaerobic membrane bioreactors (MBRs). Computer modelling and simulation results are used to optimize design of the system. Energy generation from the system is maximized and costs are reduced by using modest levels of recycle flow from the anaerobic MBRs to the FP pretreatment step.

Many unit process models are available in the field of wastewater treatment. All of these models use their own notation, causing problems for documentation, implementation and connection of different models (using different sets of state variables). The main goal of this paper is to propose a new notational framework which allows unique and systematic naming of state variables and parameters of biokinetic models in the wastewater treatment field. The symbols are based on one main letter that gives a general description of the state variable or parameter and several subscript levels that provide greater specification. Only those levels that make the name unique within the model context are needed in creating the symbol. The paper describes specific problems encountered with the currently used notation, presents the proposed framework and provides additional practical examples. The overall result is a framework that can be used in whole plant modelling, which consists of different fields such as activated sludge, anaerobic digestion, sidestream treatment, membrane bioreactors, metabolic approaches, fate of micropollutants and biofilm processes. The main objective of this consensus building paper is to establish a consistent set of rules that can be applied to existing and most importantly, future models. Applying the proposed notation should make it easier for everyone active in the wastewater treatment field to read, write and review documents describing modelling projects.

Activated Sludge Models (ASMs) assume an unbiodegradable organic particulate fraction in the activated sludge, which is derived from the decay of active microorganisms in the sludge and/or introduced from wastewater. In this study, a seasonal change of such activated sludge constituents in a municipal wastewater treatment plant was monitored for 1.5 years. The chemical oxygen demand ratio of the unbiodegradable particulates to the sludge showed a sinusoidal pattern ranging from 40 to 65% along with the change of water temperature in the plant that affected the decay rate. The biogas production in a laboratory-scale anaerobic digestion (AD) process was also affected by the unbiodegradable fraction in the activated sludge fed. Based on the results a chemical pre-treatment using H2O2 was conducted on the digestate to convert the unbiodegradable fraction to a biodegradable one. Once the pre-treated digestate was returned to the digester, the methane conversion increased up to 80% which was about 2.4 times as much as that of the conventional AD process, whilst 96% of volatile solids in the activated sludge was digested. From the experiment, the additional route of the organic conversion processes for the inert fraction at the pre-treatment stage was modelled on the ASM platform with reasonable simulation accuracy.

In order to deal with the environmental problems associated with animal production industrialization and at the same time considering energy costs increasing, a piggery wastewater treatment process consisting of combined anaerobic digestion and biological nitrogen removal by activated sludge was developed. This contribution presents a modelling framework in order to optimize this process. Modified versions of the well established ASM1 and ADM1 models have been used. The ADM1 was extended with biological denitrification. pH calculation and liquid gas-transfer were modified to take into account the effect of associated components. Finally, two interfaces (ADMtoASM and ASMtoADM) were built in order to combine both models. These interfaces set up the COD, nitrogen, alkalinity and charge fractionation between both models. However, for the mass balances between both models, some hypotheses were considered and might be evaluated.

Abstract This paper presents the design of a plant-wide CNP (carbon-nitrogen-phosphorus) simulation model of a full-scale wastewater treatment plant, which will be upgraded for tertiary treatment to achieve compliance with effluent total nitrogen (TN) and total phosphorus (TP) limit values. The plant-wide model of the existing plant was first designed and extensively validated under long-term dynamic operation. The most crucial step was a precise characterization of input wastewater that was performed by extending the plant performance indicators both to a water line and sludge line and systematically estimating identifiable wastewater characterization parameters from plant-wide performance indicators, i.e. effluent concentrations, biogas and sludge production, and sludge composition. The thus constructed simulation model with standard activated sludge model (ASM2d) and anaerobic digestion model (MantisAD) overpredicted ortho-P and ammonia-N on the sludge line, indicating a need to integrate state-of-the-art physico-chemical minerals precipitation models to simulate plant-wide interactions more precisely. The upgraded plant with multimode anaerobic/anoxic/oxic configuration shows limited denitrification potential. Therefore, additional reject water treatment was evaluated to improve effluent TN and TP performance.

A laboratory-scale anaerobic sequencing batch reactor (ASBR) was fed a synthetic wastewater containing glucose to study the effects of the antimicrobial tylosin on treatment performance. Measurements of methane, volatile fatty acids, and COD concentrations suggested that the addition of 1.67 mg/L and 167 mg/l of tylosin to the synthetic wastewater inhibited propionate oxidizing syntrophic bacteria and aceticlastic methanogens. The latter is presumed to be an indirect effect. A modified version of the IWA Anaerobic Digestion Model No. 1 (ADM1) with extensions for microbial storage and hydrolysis of reserve carbohydrates, and tylosin liquid–solid mass transfer and inhibition adequately described the dynamic profiles observed in the ASBR.

Anaerobic digestion is state-of-the-art technology to treat sludge and effluents from various industries. Modelling and optimisation of digestion operations can be advantageously performed using the anaerobic digestion model (ADM1) from the International Water Association. The ADM1, however, lacks a proper physico-chemical framework, which makes it difficult to consider wastewater of complex ionic composition and supersaturation phenomena. In this work, we present a direct implementation of the ADM1 within the PHREEQC chemistry engine. This makes it possible to handle ionic strength effects and ion-pairing. Thus, multiple mineral precipitation phenomena can be handled while resolving the ADM1. All these features can be accessed with very little programming effort, while retaining the full power and flexibility of PHREEQC. The distributed PHREEQC code can be easily interfaced with process simulation software for future plant-wide simulation of both wastewater and sludge treatment.

Anaerobic digestion plants are highly efficient wastewater treatment processes with inherent energy production. Despite these advantages, many industries are still reluctant to use them because of their instability confronted with changes in operating conditions. There is therefore great potential for application of instrumentation, control and automation (ICA) in the field of anaerobic digestion. This paper will discuss the requirements (in terms of on-line sensors needed, modelling efforts and mathematical complexity) but also the advantages and drawbacks of different control strategies that have been applied to AD high rate processes over the last 15 years.

This paper presents results of a novel application of coupling the Activated Sludge Model No. 3 (ASM3) and the Anaerobic Digestion Model No.1 (ADM1) to assess a tropical wastewater treatment plant in a developing country (Surat, India). In general, the coupled model was very capable of predicting current plant operation. The model proved to be a useful tool in investigating various scenarios for optimising treatment performance under present conditions and examination of upgrade options to meet stricter and upcoming effluent discharge criteria regarding N removal. It appears that use of plant-wide modelling of wastewater treatment plants is a promising approach towards addressing often complex interactions within the plant itself. It can also create an enabling environment for the implementations of the novel side processes for treatment of nutrient-rich, side-streams (reject water) from sludge treatment.

A (non-exhaustive) survey of new and existing technologies for the monitoring of wastewater treatment plants is presented. Emphasis is given to the way these sensors can provide insight in the ongoing (bio-) processes. Three different uses for sensors can be found: for monitoring (operator support), in automatic control systems and as tools for plant auditing/optimization/modelling by consultants. From this, sensors have been classified in two basic types: (i) reliable, simple and low maintenance sensors for day-to-day monitoring and control and (ii) advanced, higher maintenance sensors that are used in auditing, model calibration and optimisation. The paper is organized according to the typical unit processes of biological wastewater treatment systems: anaerobic digestion, activated sludge, nutrient removal and sedimentation. Attention is drawn to a number of practical problems associated with the use of sophisticated sensors in the harsh (dirty) conditions of wastewater treatment processes. The use of autocalibration and built-in sensor checks, cleaning systems and reliable sample preparation units is illustrated. The paper ends with a discussion of the applicability of the different sensors.

The observed acclimatisation to biodegradable toxicants in anaerobic cassava wastewater treatment is explained by modelling anaerobic cyanide degradation. A complete degradation pathway is proposed for cyanide. Cyanide degradation is modelled as enzymatic hydrolysis to formate and ammonia. Ammonia is added to the inorganic nitrogen content of the digester while formate is degraded by the hydrogenotrophic methanogens. Cyanide irreversible enzyme inhibition is modelled as an inhibition factor to acetate uptake processes. Cyanide irreversible toxicity is modelled as a decay factor to the acetate degraders. Cyanide as well as added phosphorus buffer solution were considered in the chemical equilibrium calculations of pH. The observed reversible effect after acclimatisation of sludge is modelled by a population shift between two aceticlastic methanogens that have different tolerance to cyanide toxicity. The proposed pathway is added to the IWA Anaerobic Digestion Model no.1 (ADM1). The ADM1 model with the designed extension is validated by an experiment using three lab-scale upflow anaerobic sludge bed reactors which were exposed to different cyanide loadings.

Wastewater treatment plants (WWTPs) are known to be one of the most energy-intensive industrial sectors. In this work, demand response was applied to the biological phase of wastewater treatment to reduce plant electricity cost, considering that the daily peak in flowrate typically coincides with the maximum electricity price. Compressed air storage system, composed of a compressor and an air storage tank, was proposed to allow energy cost reduction. A multi-objective modelling approach was applied by analyzing different scenarios (with and without anaerobic digestion, AD), considering both plant characteristics (in terms of treated flowrate and influent chemical oxygen demand, COD, concentration) and storage system properties (volume, air pressure), together with the current Italian market economic conditions. The results highlight that air tank volume has a strong positive influence on the obtainable economic savings, with a less significant impact held by air pressure, COD concentration and flowrate. In addition, biogas exploitation from AD led to an improvement in economic indices. The developed model is highly flexible and can be applied to different WWTPs and market conditions.

Abstract To date, mixing design practice in anaerobic digestion has focussed on biogas production, but no adequate consideration has been given to energy efficiency. A coherent, comprehensive and generalized strategy based on computational fluid dynamics (CFD) modelling is proposed to improve mixing efficiency of a full-scale, unconfined gas-mixed digester for wastewater treatment. The model consists of an Euler–Lagrange (EL) model where biogas bubbles are modelled as the Eulerian dispersed phase, and non-Newtonian sludge as the Lagrangian continuous phase. Robustness tests show that mixing predictions are independent of bubble size. The CFD strategy comprises the assessment of different mixing geometries and a range of input gas flow rates. Quantitative results show that simple retrofitting measures are able to achieve a significant improvement in the degree of mixing with reduced mixing times, and consequently recommendations for best mixing geometry and gas flow rate are given. A generalization to a generic digester is discussed in a form that is readily usable by professionals and consultants.

Recent research has demonstrated that hybrid linear flow channel reactors (HLFCRs) can desulfurize tannery effluent via sulfate reduction and concurrent oxidation of sulfide to elemental sulfur. The reactors can be used to pre-treat tannery effluent to improve the efficiency of downstream anaerobic digestion and recover sulfur. This study was conducted to gain insight into the bacterial communities in HLFCRs operated in series and identify structure-function relationships. This was accomplished by interpreting the results obtained from amplicon sequencing of the 16S rRNA gene and quantification of the dissimilatory sulfite reducing (dsrB) gene. In an effort to provide a suitable inoculum, microbial consortia were harvested from saline estuaries and enriched. However, it was found that bioaugmentation was not necessary because native communities from tannery wastewater were selected over exogenous communities from the enriched consortia. Overall, Dethiosulfovibrio sp. and Petrimonas sp. were strongly selected (maximum relative abundances of 29% and 26%, respectively), while Desulfobacterium autotrophicum (57%), and Desulfobacter halotolerans (27%) dominated the sulfate reducing bacteria. The presence of elemental sulfur reducing genera such as Dethiosulfovibrio and Petrimonas is not desirable in HLFCRs, and strategies to counter their selection need to be considered to ensure efficiency of these systems for pre-treatment of tannery effluent.

The objective of this study was to determine the effectiveness of anaerobic digestion in the treatment of polyphenols (PP) present in olive mill wastewater (OMW) and wine distillery wastewater (WDW). Anaerobic Toxicity Assay (ATA) was conducted to assess the impact of the most representative phenolic compounds present in OMW and WDW: catechol, tannins and p-Coumaric acid, on biogas production. The results from this study show that tannins do not present any inhibitory effect on methanogenesis at a concentration level of 1,664 ppm, whereas catechol has an inhibitory effect at 1,664 ppm. In addition, p-Coumaric acid was strongly inhibitory at 50 ppm. The co-digestion of OMW and WDW with other effluents was proposed as a solution for reducing the load of PP in the anaerobic medium. Biochemical methane potential (BMP) tests were carried out for dairy cattle manure and mixtures of five PP. A central composite design was implemented on the BMP tests to model the biogas production response and the degradation kinetics of PP. The co-digestion of WDW with cattle manure and/or whey was also investigated in BMP tests. The results show that the digestion was optimal at a ratio of 16: 64: 20 (WDW: manure: inoculum) with a maximum biogas yield of 172 mL/g of VS and 66% COD removal.

Anaerobic co-digestion in wastewater treatment plants is looking increasingly like a straightforward solution to many issues arising from the operation of mono-digestion. Process modelling is relevant to predict plant behavior and its sensitivity to operational parameters, and to assess the feasibility of simultaneously feeding a digester with different organic wastes. Still, much work has to be completed to turn anaerobic digestion modelling into a reliable and practical tool. Indeed, the complex biochemical processes described in the ADM1 model require the identification of several parameters and many analytical determinations for substrate characterization. A combined protocol including batch Biochemical Methane Potential tests and analytical determinations is proposed and applied for substrate influent characterization to simulate a pilot-scale anaerobic digester where co-digestion of waste sludge and expired yogurt was operated. An iterative procedure was also developed to improve the fit of batch tests for kinetic parameter identification. The results are encouraging: the iterative procedure significantly reduced the Theil’s Inequality Coefficient (TIC), used to evaluate the goodness of fit of the model for alkalinity, total volatile fatty acids, pH, COD, volatile solids, and ammoniacal nitrogen. Improvements in the TIC values, compared to the first iteration, ranged between 30 and 58%.

The overall performance of the Anjana wastewater treatment plant (WWTP) located in Surat, India, was assessed by coupling the Activated Sludge Model No. 3 (ASM3) and the Anaerobic Digestion Model No. 1 (ADM1). Guidelines developed by the Dutch Foundation for Applied Water Research (STOWA) were successfully applied for the determination of wastewater characteristics. Concerning the fractionation of primary and secondary sludge, the approach proved to be adequate for the application of ADM1. A satisfactory description of the performance of the plant was obtained in terms of effluent quality, biogas generation and sludge production. This was achieved through coupling ASM3 with ADM1 and adjusting four default values (the growth of autotrophic bacteria from 1 to 0.46 day−1, influent fraction of unbiodegradable particulate chemical oxygen demand (COD) to 0.14 gCOD/gCOD, and the anaerobic disintegration factors for soluble and particulate unbiodegradable COD in ADM1 to 0.01 and 0.29 gCOD/gCOD, respectively). The model was applied to optimise the plant performance and to assess the potential influence of the return of high strength reject effluents through the implementation of an ADM1-ASM3 interface. This study underlines the feasibility, advantages and benefits of mathematical modelling as a reliable tool for process optimisation, plant upgrade and resource recovery in developing countries.

A shortcut nitrogen removal process was investigated for treatment of high ammonium strength wastewater using an algal–bacterial consortium in photo-sequencing batch reactors (PSBRs). In this process, algae provide oxygen for nitritation during the light period, while denitritation takes place during the dark (anoxic) period, reducing overall energy and chemical requirements. Two PSBRs were operated at different solids retention times (SRTs) and fed with a high ammonium concentration wastewater (264 mg NH4+-N L−1), with a ‘12 hour on, 12 hour off’ light cycle, and an average surface light intensity of 84 μmol m−2 s−1. High total inorganic nitrogen removal efficiencies (∼95%) and good biomass settleability (sludge volume index 53–58 mL g−1) were observed in both PSBRs. Higher biomass density was observed at higher SRT, resulting in greater light attenuation and less oxygen production. A mathematical model was developed to describe the algal–bacterial interactions, which was based on Activated Sludge Model No. 3, modified to include algal processes. Model predictions fit the experimental data well. This research also proposes an innovative holistic approach to water and energy recovery. Wastewater can be effectively treated in an anaerobic digester, generating energy from biogas, and later post-treated using an algal–bacterial PSBR, which produces biomass for additional biogas production by co-digestion.

Anaerobic lagoons are natural wastewater treatment systems suitable for swine farms in small communities due to its low operational and building costs, as well as for the environmental sustainability that these technologies enable. The local weather is one of the factors which greatly influences the efficiency of the organic matter degradation within anaerobic lagoons, since microbial growth is closely related to temperature. In this manuscript, we propose a mathematical model which involves the two-dimensional Stokes, advection–diffusion-reaction and heat transfer equations for an unstirred fluid flow. Furthermore, the Anaerobic Digestion Model No1 (ADM1), developed by the International Water Association (IWA), has been implemented in the model. The partial differential equations resulting from the model, which involve a large number of state variables that change according to the position and the time, are solved through the use of the Finite Element Method. The results of the simulations indicated that the methodology is capable of predicting reasonably well the steady-state of the concentrations for all processes that take place in the anaerobic digestion and for each one of the variables considered; cells, organic matter, nutrients, etc. In view of the results, it can be concluded that the model has significant potential for the design and the study of anaerobic cells’ behaviour within free flow systems.

Anaerobic co-digestion allows for under-utilised digesters to increase biomethane production. The organic fraction of municipal solid waste (OFMSW), i.e., food waste, is an abundant substrate with high degradability and gas potential. This paper investigates the co-digestion of mixed sludge from wastewater treatment plants and OFMSW, through batch and continuous lab-scale experiments, modelling, and microbial population analysis. The results show a rapid adaptation of the process, and an increase of the biomethane production by 20% to 40%, when co-digesting mixed sludge with OFMSW at a ratio of 1:1, based on the volatile solids (VS) content. The introduction of OFMSW also has an impact on the microbial community. With 50% co-substrate and constant loading conditions (1 kg VS/m3/d) the methanogenic activity increases and adapts towards acetate degradation, while the community in the reference reactor, without a co-substrate, remains unaffected. An elevated load (2 kg VS/m3/d) increases the methanogenic activity in both reactors, but the composition of the methanogenic population remains constant for the reference reactor. The modelling shows that ammonium inhibition increases at elevated organic loads, and that intermittent feeding causes fluctuations in the digester performance, due to varying inhibition. The paper demonstrates how modelling can be used for designing feed strategies and experimental set-ups for anaerobic co-digestion.

Biogas production considered the most encouraging sources of renewable energy in Sudan. Anaerobic process of digestion is considered as efficient techniques of producing biogas. The process also a trustworthy method for treatment of municipal wastes, and the digested discharge could be utilized as soil conditioner to improve the productivity. This research work states at the option of using domestic sludge of the wastewater treatment plant in Soba municipal station (south of Khartoum-Sudan) to produce biological gas (biogas). A laboratory investigation was carried out using five-liter bioreactor to generate biogas for 30 days. The total volume of gas made was 270.25 Nml with a yield of 20 Nml of biogas/mg of COD removed. Chemical oxygen demand, Biological oxygen demand, & total solids drop produced were 89, 91 & 88.23% respectively. Microbial activity was declined from 1.8x107 (before starting the process of digestion) to 1.1x105 germs/mL (after completion of 30 days of digestion). This study offered a significant energetic opportunity by estimated the power production to 35 KWh.Key word: Sludge, municipal plant, organic material, anaerobic process, breakdown, biological gas potentialNTRODUCTIONIncreasing of urban industries style in the world has given rise to the production of effluents in huge amounts with abundant organic materials, which if handled properly, be able to end in a substantial source of energy. Although of a fact that there is an undesirable environmental effect related with industrialization, the influence can be diminished and energy can be tapped by means of anaerobic digestion of the wastewater (Deshpande et al., 2012). Biological wastewater treatment plant (WWTP) is a station for removal of mainly organic pollution from wastewaters. Organic materials are partly transformed into sludge that, with the use of up-to-date technologies, represents an important energy source. Chemical biological, and physical technology applied throughout handling of wastewater produce sludge as a by-product. Recent day-to-day totals, dry solids range from 60–90 g per population equivalent, i.e. EU produces per year 10 million tons of dry sludge (Bodík et al., 2011). Sludge disposal (fertilizers use, incineration, and landfills) is often explored since of increasingly limiting environmental legislation (Fytili and Zabaniotou, 2008). The energy present in sludge is obviously consumed in anaerobic digestion. Anaerobic Process is considering the most appropriate choice for the handling of organic effluents of strong content. This process upgraded in the last few years significantly with the applications of differently configured high rate treatment processes, particularly for the dealing of industrial releases (Bolzonella et al., 2005). Anaerobic process leads to the creation of biological gas with high content of methane, which can be recovered, and used as an energy source, making it a great energy saver. The produced gas volume during the breakdown process can oscillate over a wide range varying from 0.5 – 0.9 m3 kg–1 VS degraded (for waste activated sludge) (Bolzonella et al., 2005). This range rest on the concentration of volatile solids in the sludge nourish and the biological action in the anaerobic breakdown process. The residue after digestion process is stable, odorless, and free from the main portion of the pathogenic microorganism and finally be able to use as an organic nourishment for different application in agriculture. Sludge significant coming out from breakdown which allows to yield a renewable energy, that was cheap, obtainable, & no polluting. Sustainable development considered the production of biogas as environmentally friendly and an economic key (Poh and Chong, 2009).OBJECTIVES Sudan have huge tones of sewage sludge from domestic sewage water is accumulated daily in lagoon of soba sewage treatment plant, so this work, we were carried for energy production and treatment of sludge, which constitutes a plentiful waste which ever know any sort of handling after few years from establishing the station.MATERIALS AND METHODSExperimental apparatus: Anaerobic breakdown was done in five liters fermenter. The fermenter was maintained at 35oC in a thermostatic bath and stirred regularly. U shaped glass tube was connected to the fermenter, allowing the measurement of produced biogas volume and pressure. Water displacement technique was used for determination of the volume of produced biological gas (biogas) at the beginning of each sampling. Testing of the biogas combustibility was determined by connecting one of ends of the tube to a gas collection and storage device (balloon), the other end to a Bunsen burner. In the process of reduction of carbon dioxide (CO2) to maximum dissolution in the tube the liquid must be a salty saturated acid solution (5% citric acid, 20% NaCl, pH ¼ 2) (Connaughton et al., 2006).Substrate: About 5L sludge containing culture medium were taken from the lowest part of the first settling tank in Soba station. The moisture content of initial substrate was 35%. The collected sample was preserved at 4oC prior to loading the biological reactor (Tomei et al., 2008). Table 1 showed the sludge features in the reactor with a loading rate of 16 g TS/L, (Connaughton et al., 2006; Tomei et al., 2008).Analytical Methods: The pH was controlled by using HANNA HI 8314 model as pH meter device. Assay was used for determination of Alkanility & Volatile fatty acids (Kalloum et al., 2011). The standard method of analysis was used for recognized the Chemical Oxygen Demand (COD) (Raposo et al., 2009). Titrimetric method was used for analyzing Volatile fatty acids (VFA). Alkalinity assay was used for determination of Total Alkalinity (TA). Oxitop assay was used for measuring the biological oxygen demand. Ignition method was used for measuring Volatile Solids (VS) by losing weight in dry sample at 550oC in the furnace, & Total solids were done to constant weight at 104oC (Monou et al., 2009). A method of water displacement was used for determination of the total volume of Biological gas produced (Moletta, 2005). Microbial species & analyses were determined by microbial standard assay. Sample analysis was done by explore of three replicates and the outcomes were the middling of these replicates. Startup of experiments continues until a bubble of gas was detected.RESULTS AND DISCUSSIONMeasurement of pH: Figure 2 exhibited pH trends during 30 days with a drop pattern from 7.0 to 6.0 during the first five days; this was mainly because of the breakdown of organic materials and the development of (VFA). Then later, an increasing pattern in pH was noticed to 6.98, for the next week, then Steadying around this pH level was continued till the completion of the breakdown period which taken 30 days. Those out comes were also reported by other researchers (Raposo et al., 2008)Measurement of VFA: Development of VFA throughout 30 days was depicted in figure 3, an increase in volatile fatty acids up to 1400 mill equivalents per liter (meq/L) in the first ten days. This criterion of making of volatile fatty acid is typical to the researcher’s report of identification of hydrolysis in acidogenesis stage (Parawira et al., 2006). The decline in volatile fatty acids after the tenth day was owing to intake by bacteria which would relate to the stage of acetogenesis.Total alkalinity (TA): During the ten days, we observed rise in volatile fatty acids content followed by a drop in a pH in the same time (figures 4 and 5). Encountered to these alterations, an increase in the total alkalinity in the medium for reestablishing situations of alkalinity to the outbreak of methanogens stage (figure 4). Through all the digestion period the ratio of VFA/TA which was equal and lower than 0.6±0.1 were described in figure 6. These ratios designated the achievability of the procedure despite the essential production of volatile fatty acid (Chen and Huang, 2006; Nordberg et al., 2007). The anaerobic digestion process may be hinder by the production of volatile fatty acid.Biogas production: Pressure measurement and biogas volume were used for controlling biogas production. Figure 7 explained the changing in biogas pressure throughout the digestion period. quality of Biogas was obtained with minimum methane of 40% (Bougrier et al., 2005; Lefebvre et al., 2006). Total volume of biological gas production was 270.25 Nml. The yield of biological gas was 20.25 Nml/mg COD removed, which is in range of the others researcher report (Tomei et al., 2008). Biogas production can be calculated from the following formula (Álvarez et al., 2006): Biogas production= (Total quantity of biogas produced)/(Total solid).The COD and BOD removal: Chemical oxygen Demand (COD) and Biological Oxygen Demand (BOD) showed a significant reduction of 89% and 91% respectively (figures 8 and 9). Consequently these reduction in contaminants proved that anaerobic process of digestion was an operational technique for removal of organic pollution. Some researchers reported the same results (Bolzonella et al., 2005; Álvarez et al., 2006; Wang et al., 2006). Another criterion for proving the removal of organic pollutants was reduction of total solids (TS), where the drop approached 88.23% (figure 10). Some researcher’s reports approached the same drop (Hutnan et al., 2006; Linke, 2006; Raposo et al., 2009). Therefore it was possible to conclude that anaerobic digestion necessary showed decrease or reduction of organic pollutants rates because of the transformation of organic substances into biogas and accordingly led to the drop of chemical oxygen demand (COD). This could be explained in figure 11 by the comparison of the two techniques during the anaerobic digestion process. That means the chemical oxygen demand (COD) drop should be tailed essentially by Total solids drop (TS).Microbial activity: Figure 11 showed the microbial variation during anaerobic digestion. The total micro flora (total germs) declined from 1.8x107 (before starting the process of digestion) to1.1x105 germs/mL (after completion of 30 days of digestion). Moreover figure 12 obviously explained what was running during the process of digestion in the reactor, microbial species vanishing after the 30 days such as streptococci and Escherichia coli. Some researchers reports explained that there was some sort of relationship between physicochemical and the biological parameters of micro flora with total solid (TS). figure 13 described obviously this relationship of the drop of micro flora which go along with total solids reduction. This intended that consumption and a declining in the mass residue of organic materials created at the termination of digestion was the outcome of the transformation of organic materials into biological gas and also the sum of microorganism reduction. This attained result proved that the process of anaerobic digestion was a good process for decontamination (Deng et al., 2006; Perez et al., 2006; Davidsson et al., 2007).CONCLUSIONSoba sludge’s municipal station carried in this research paper demonstrated operative for biological gas production (biogas). During the first five days, breakdown of organic materials and the formation of volatile acids were started. Volatile fatty acids increased up to 1400 mill equivalents per liter (meq/L) in the first ten days, then started to decline in after the tenth day this owing to intake by bacteria which would resemble to acetogenesis stage. The biogas production lasted until the 21th day then starting decreasing till the last day (30 day) this due to instability of the culture medium of fermentation which became completely poor. COD and BOD showed a significant reduction of 89% and 91% respectively. Another criteria for proving of removal rate of organic pollutants was reduction of total solids (TS), where the reduction rate approached 88.23%. Total volume of biological gas production was 270.25 Nml. The yield of biological gas was 20.25 Nml/mg COD removed, which is in range of the others researcher report. The total micro flora (total germs) declined from 1.8x107 (before starting the process of digestion) to 1.1x105 germs/mL (after completion of 30 days of digestion). Study proved that process of anaerobic digestion was a good process for decontamination. Industries and will be usefulness for bioremediation in marine environment and petroleum industry.ACKNOWLEDGMENTSThe authors wish to express their appreciation to Soba treatment plant, for their financial support of this research.CONFLICT OF INTERESTThe authors wish to express their appreciation to Soba treatment plant, for their financial support of this research.REFERENCES Álvarez, J., I. Ruiz, M. Gómez, J. Presas and M. 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The biological kinetic processes for anaerobic digestion (AD) are integrated into a two phase subset of a three phase mixed weak acid/base chemistry kinetic model. The approach of characterising sewage sludge into carbohydrates, lipids and proteins, as is done in the International Water Association (IWA) AD model No 1 (ADM1), requires measurements that are not routinely available on sewage sludges. Instead, the sewage sludge is characterised with the COD, carbon, hydrogen, oxygen and nitrogen (CHON) composition and is formulated in mole units, based on conservation of C, N, O, H and COD. The model is calibrated and validated with data from laboratory mesophilic anaerobic digesters operating from 7 to 20 d sludge age and fed a sewage primary and humus sludge mixture. These digesters yielded COD mass balances between 107–109% and N mass balances between 91–99%, and hence the experimental data is accepted as reasonable. The sewage sludge COD is found to be 32–36% unbiodegradable (depending on the kinetic formulation selected for the hydrolysis process) and to have a C3.5H7O2N0.196 composition. For the selected hydrolysis kinetics of surface mediated reaction (Contois), with a single set of kinetic and stoichiometric constants, for all retention times good correlation is obtained between predicted and measured results for: (i) COD; (ii) free and saline ammonia (FSA); (iii) short chain fatty acids (SCFA); (iv) H2CO3* alkalinity; (v) pH of the effluent stream; (vi) CO2; and (vii) CH4 gases in the gas stream. The measured composition of primary sludge from two local wastewater treatment plants ranged between C3.38H7O1.91N0.21 and C3.91H7O2.04N0.16. The predicted composition based on mass balances is therefore within 5% of the average measured composition providing persuasive validation of the model.

For plant wide modelling of wastewater treatment, it is necessary to develop a suitable state variables interface for integrating state of the art models of ASM and ADM1. ADM1 currently describes such an interface, however, its suitability needs to be experimentally evaluated. In this study, we characterised activated sludge under aerobic and anaerobic conditions to obtain representative state variables for both models. ASM state variables of XS, XH and XI (as obtained from aerobic tests) and ADM1 state variables of XC and XI (as obtained from anaerobic tests) were then correlated to assess the suitability of current interface. Based on the seven datasets of this study and seven datasets from literatures, it was found that in general ASM state variables were well correlated to the state variables of ADM1. The ADM1 state variable of XC could be correlated to the sum of state variables of XS and XH, while XI in both the models showed direct correspondence. It was also observed that the degradation kinetics of XC under anaerobic condition could be better described by individual degradation kinetics of XS and XH. Therefore, to establish a one to one correspondence between ASM and ADM1 state variables and better description of degradation kinetics in ADM1, replacing the composite variable of XC by the state variables of XS and XH is recommended.

Over a decade ago, the concept of objectively evaluating the performance of control strategies by simulating them using a standard model implementation was introduced for activated sludge wastewater treatment plants. The resulting Benchmark Simulation Model No 1 (BSM1) has been the basis for a significant new development that is reported on here: Rather than only evaluating control strategies at the level of the activated sludge unit (bioreactors and secondary clarifier) the new BSM2 now allows the evaluation of control strategies at the level of the whole plant, including primary clarifier and sludge treatment with anaerobic sludge digestion. In this contribution, the decisions that have been made over the past three years regarding the models used within the BSM2 are presented and argued, with particular emphasis on the ADM1 description of the digester, the interfaces between activated sludge and digester models, the included temperature dependencies and the reject water storage. BSM2-implementations are now available in a wide range of simulation platforms and a ring test has verified their proper implementation, consistent with the BSM2 definition. This guarantees that users can focus on the control strategy evaluation rather than on modelling issues. Finally, for illustration, twelve simple operational strategies have been implemented in BSM2 and their performance evaluated. Results show that it is an interesting control engineering challenge to further improve the performance of the BSM2 plant (which is the whole idea behind benchmarking) and that integrated control (i.e. acting at different places in the whole plant) is certainly worthwhile to achieve overall improvement.

The aim of the present paper is to develop neuro-fuzzy prediction models in MATLAB environment of the anaerobic organic digestion process in wastewater treatment from laboratory and simulated experiments accounting for the variable organic load, ambient influence and microorganisms state. The main contributions are determination of significant model parameters via graphical sensitivity analysis, simulation experimentation, design and study of two “black-box” models for the biogas production rate, based on classical feedforward backpropagation and Sugeno fuzzy logic neural networks respectively. The models application is demonstrated in process predictive control

Bioprocesses interact with the aqueous environment in which they take place. Currently integrated bioprocess and three-phase (aqueous–gas–solid) multiple strong and weak acid/base system models are being developed for a range of wastewater treatment applications, including anaerobic digestion, biological sulphate reduction, autotrophic denitrification, biological desulphurization and plant-wide wastewater treatment systems. In order to model, measure and control such integrated systems, a thorough understanding of the interaction between the bioprocesses and aqueous-phase multiple strong and weak acid/bases is required. This first in a series of five papers sets out a conceptual framework and methodology for deriving bioprocess stoichiometric equations. It also introduces the relationship between alkalinity changes in bioprocesses and the underlying reaction stoichiometry, which is a key theme of the series. The second paper develops the stoichiometric equations for the main biological transformations that are important in wastewater treatment. The link between the modelling and measurement frameworks, which uses summary measures such as chemical oxygen demand (COD) and alkalinity, is described in the third and fourth papers. The fifth paper describes an equilibrium aquatic speciation algorithm which can be combined with bioprocess stoichiometry to provide integrated models of wastewater treatment processes.

Achievement of good effluent quality is always the main goal for wastewater treatment plant (WWTP) systems. However, these WWTPs have developed further objectives that include efficient design and strategic control options, with the prospect of their conversion into waste resource recovery facilities (WRRFs) that operate on reduced energy costs. With all these aspects becoming an intrinsic part of waste treatment, mathematical models that simulate WWTP unit processes are becoming of increasing relevance for the achievement of WRRF goals (including good effluent quality, low energy costs and nutrient recovery). It is expected that these mathematical models will benefit potential future applications of automation process control, which have also been developing rapidly with the availability of more reliable and affordable sensors. However, simulated automation control strategies require a thorough evaluation protocol to ensure their viability prior to being adopted as efficient operation control measures. This study considers the comparison of different control strategies implemented on a standard WWTP layout, for plant optimization. The initial task was to define performance indices, effluent quality index (EQI) and operation cost index (OCI), based on a previous investigation by the International Water Association (IWA) benchmark simulation modelling (BSM) task group. These performance indices were then used to evaluate the following strategies: (i) adding a fermentation tank, (ii) dosing flocculant and (iii) implementing a balancing tank. A control strategy was only assumed to be effective with improvement or maintenance of effluent quality. Overall, the evaluation exercise proved to be useful for providing expert advice on efficiency of proposed waste treatment system layouts, towards determination of the best configuration of future WRRFs. For instance, it was notable that significant organic strength is needed for removal of nutrients recycled back from the anaerobic digestion (AD) system into the activated sludge (AS) – hence alternate methods to put the nutrient-rich outflow from the AD system to good use are required.

Wastewater treatment plant (WWTP) mathematical models are based on the behavioural patterns of microorganisms involved in the treatment process. These microorganisms are assumed incapable of thinking or planning but simply act according to the capabilities afforded to them by their surrounding conditions – hence different microorganisms pre-dominate different WWTP zones according to how well the conditions suit them. When waste activated sludge (WAS) from biological nutrient removal (BNR) activated sludge (AS) systems, containing phosphorus-accumulating organisms (PAOs), is fed to an anaerobic digester, there is a release of high quantities of metals, phosphorus (P) and nitrogen (N). The manner in which we model the release of these metals and nutrients significantly affects the accuracy of predicted anaerobic digestion (AD) outcomes. Previous studies of PAOs show that in the anaerobic zone of the AS system, they can form energy-rich poly3-hydroxybutyrate (PHB) at the expense of their aerobically generated polyphosphate (PP). Thus, it is expected that the PAOs containing PP sent into an anaerobic digester with volatile fatty acids (VFAs) present, would utilize their PP reserves as they would in the anaerobic zone of an AS process ending up with formation and storage of some PHB. Ultimately, all the stored products of the PAO get released, since there is no alternating aerobic environment to cater for their growth. Since it has been established that the PP release in the AD occurs much faster than the PAO biomass hydrolysis rate, it is modelled as a separate process. Steps are presented in the development of this PP release mass-balanced stoichiometries that occur with AD of PAOs. By comparing outcomes from these proposed stoichiometries against measured experimental data, it is noticed that better predictions are obtained with acetate uptake for PHB formation than when modelling the AD PP release to occur with PAO death and hydrolysis.

AbstractUnderstanding the hydrodynamics within the anaerobic digester tank of a wastewater treatment plant is of high importance to ensure sufficient mixing and subsequently a homogeneous distribution of the substrates. In this paper, we demonstrate a two-dimensional computational fluid dynamics simulation of a real-world case study focusing on both, the methodology and the operation of mixing. For this work, DualSPHysics, a Lagrangian solver, has been explored as an alternative to the more commonly used Eulerian solvers in studying the slow-moving dynamics inside a digester tank. This choice of a Lagrangian solver is primarily due to the inherent accounting for advection within the formulation, thus allowing for subsequent modelling of anaerobic digestion processes. A comparison has been made between the simulations from the two methods (Eulerian and Lagrangian), highlighting the benefits and the shortcomings of using smoothed particle hydrodynamics. Concerning operational mixing, the case relies on a draft tube, the effect of which on the velocity profiles has been studied based on the presence of low-velocity zones and Lagrangian coherent structures. Removing the draft tube results in an increase in low-velocity zones by 21.38% while the amount of dead volume increases from 0.52 to 1.2%.

Bioprocesses interact with the aqueous environment in which they take place. Integrated bioprocess and three-phase (aqueous−gas−solid) multiple strong and weak acid/base system models are currently being developed for a range of wastewater treatment applications including anaerobic digestion, biological sulphate reduction, autotrophic denitrification, biological desulphurization and plant-wide water and resource recovery facilities. In order to model, measure and control such integrated systems, a thorough understanding of the interactions between the bioprocesses and aqueous phase multiple strong and weak acid/bases are required. In the first of this series of five papers, the generalized procedure for deriving bioprocess stoichiometric equations was explained. This second paper presents the stoichiometric equations for the major biological processes and shows how their structure can be analysed to provide insight into how bioprocesses interact with the aqueous environment. Such insight is essential for confident, effective and reliable use of model development protocols and algorithms. It shows that the composite parameters, total oxygen demand (TOD, electron donating capacity) and alkalinity (proton accepting capacity), are conserved in bioprocess stoichiometry and their changes in the aqueous phase can be calculated from the bioprocess components. In the third paper, the measurement of the organics composition is presented. The link between the modelling and measurement frameworks of the aqueous phase, which uses the composite parameter alkalinity, is described in the fourth paper. Aqueous ionic speciation modelling is described in detail in the fifth.