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Journal articles on the topic 'WASTEWATER TREATMENT MODELLING'

Author: Grafiati

Published: 10 March 2023

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1

Parashar, Varsha, Ashok K. Sharma, Sarita Sharma, and Sanjay Verma. "Mathematical Modelling of Uasb Reactor for Dairy Wastewater Treatment." International Journal of Scientific Research 3, no. 8 (June 1, 2012): 151–53. http://dx.doi.org/10.15373/22778179/august2014/43.

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2

Vanhooren, Henk, Jurgen Meirlaen, Youri Amerlinck, Filip Claeys, Hans Vangheluwe, and Peter A. Vanrolleghem. "WEST: modelling biological wastewater treatment." Journal of Hydroinformatics 5, no. 1 (January 1, 2003): 27–50. http://dx.doi.org/10.2166/hydro.2003.0003.

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Modelling is considered to be an inherent part of the design and operation of a wastewater treatment system. The models used in practice range from conceptual models and physical design models (laboratory-scale or pilot-scale reactors) to empirical or mechanistic mathematical models. These mathematical models can be used during the design, operation and optimisation of a wastewater treatment system. To do so, a good software tool is indispensable. WEST is a general modelling and simulation environment and can, together with a model base, be used for this task. The model base presented here is specific for biological wastewater treatment and is written in MSL-USER. In this high-level object-oriented language, the dynamics of systems can be represented along with symbolic information. In WEST's graphical modelling environment, the physical layout of the plant can be rebuilt, and each building block can be linked to a specific model from the model base. The graphical information is then combined with the information in the model base to produce MSL-EXEC code, which can be compiled with a C++ compiler. In the experimentation environment, the user can design different experiments, such as simulations and optimisations of, for instance, designs, controllers and model fits to data (calibration).

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3

Solon, Kimberly, Eveline I. P. Volcke, Mathieu Spérandio, and Mark C. M. van Loosdrecht. "Resource recovery and wastewater treatment modelling." Environmental Science: Water Research & Technology 5, no. 4 (2019): 631–42. http://dx.doi.org/10.1039/c8ew00765a.

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This paper discusses the extent to which new unit processes applied for resource recovery can be modelled with conventional ASMs, the additional modelling challenges being faced, while providing recommendations on how to address current modelling research gaps.

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4

Merayo, Noemi, Ana Balea, Javier Tejera, Amalio Garrido-Escudero, Carlos Negro, and Angeles Blanco. "Modelling the Mineralization of Formaldehyde by Treatment with Nitric Acid." Water 12, no. 6 (May 30, 2020): 1567. http://dx.doi.org/10.3390/w12061567.

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Formaldehyde is a recalcitrant pollutant, which is difficult to remove from wastewater using conventional and advanced treatments. The objective of this research was to remove the organic matter from formaldehyde from an industrial wastewater, achieving its total mineralization and allowing the reuse of the water. The treatment was based on the reaction of formaldehyde with nitric acid, which was first studied and modelled with synthetic waters. Results show that it was possible to almost completely mineralize the formaldehyde (>95% TOC removal) at the best conditions studied (1.72 M of nitric acid and 85 °C of temperature). The addition of NaNO2 accelerated this reaction; however, after 2 h of reaction time, its effect was negligible at the maximum concentration of HNO3 studied. The results obtained with industrial wastewater fit well with the model. It is concluded that formaldehyde in actual wastewaters can be successfully removed through direct mineralization with nitric acid, under selected conditions.

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Belia, E., Y. Amerlinck, L. Benedetti, B. Johnson, G. Sin, P. A. Vanrolleghem, K. V. Gernaey, et al. "Wastewater treatment modelling: dealing with uncertainties." Water Science and Technology 60, no. 8 (October 1, 2009): 1929–41. http://dx.doi.org/10.2166/wst.2009.225.

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This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation of a wastewater treatment system. It briefly references the methods currently used to evaluate prediction accuracy and uncertainty and discusses the relevance of uncertainty evaluations in model applications. The paper aims to raise awareness and initiate a comprehensive discussion among professionals on model prediction accuracy and uncertainty issues. It also aims to identify future research needs. Ultimately the goal of such a discussion would be to generate transparent and objective methods of explicitly evaluating the reliability of model results, before they are implemented in an engineering decision-making context.

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Hernandez-Sancho, F., M. Molinos-Senante, and R. Sala-Garrido. "Cost modelling for wastewater treatment processes." Desalination 268, no. 1-3 (March 2011): 1–5. http://dx.doi.org/10.1016/j.desal.2010.09.042.

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7

Daigger, G. T. "A practitioner’s perspective on the uses and future developments for wastewater treatment modelling." Water Science and Technology 63, no. 3 (February 1, 2011): 516–26. http://dx.doi.org/10.2166/wst.2011.252.

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The modern age of wastewater treatment modelling began with publication of the International Water Association (IWA) Activated Sludge Model (ASM) No.1 and has advanced significantly since. Models are schematic representations of systems that are useful for analysis to support decision-making. The most appropriate model for a particular application often incorporates only those components essential for the particular analyses to be performed (i.e. the simplest model possible). Characteristics of effective models are presented, along with how wastewater modelling is integrated into the wastewater project life cycle. The desirable characteristics of wastewater treatment modelling platforms are then reviewed. Current developments of note in wastewater treatment modelling practice include estimates of greenhouse gas emissions, incorporating uncertainty into wastewater modelling and design practice, more fundamental modelling of process chemistry, and improved understanding of the degradability of wastewater constituents in different environments. Areas requiring greater emphasis include increased use of metabolic modelling, characterisation of the hydrodynamics of suspended and biofilm biological treatment processes, and the integration of biofilm and suspended growth process modelling. Wastewater treatment models must also interface with water and wastewater management software packages. While wastewater treatment modelling will continue to advance and make important contributions to practice, it must be remembered that these are complex systems which exhibit counter-intuitive behaviour (results differ from initial expectations) and multiple dynamic steady-states which can abruptly transition from one to another.

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8

Clouzot, Ludiwine, Jean-Marc Choubert, Frédéric Cloutier, Rajeev Goel, Nancy G. Love, Henryk Melcer, Christoph Ort, et al. "Perspectives on modelling micropollutants in wastewater treatment plants." Water Science and Technology 68, no. 2 (July 1, 2013): 448–61. http://dx.doi.org/10.2166/wst.2013.272.

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Models for predicting the fate of micropollutants (MPs) in wastewater treatment plants (WWTPs) have been developed to provide engineers and decision-makers with tools that they can use to improve their understanding of, and evaluate how to optimize, the removal of MPs and determine their impact on the receiving waters. This paper provides an overview of such models, and discusses the impact of regulation, engineering practice and research on model development. A review of the current status of MP models reveals that a single model cannot represent the wide range of MPs that are present in wastewaters today, and that it is important to start considering classes of MPs based on their chemical structure or ecotoxicological effect, rather than the individual molecules. This paper identifies potential future research areas that comprise (i) considering transformation products in MP removal analysis, (ii) addressing advancements in WWTP treatment technologies, (iii) making use of common approaches to data acquisition for model calibration and (iv) integrating ecotoxicological effects of MPs in receiving waters.

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Kamara, A., O. Bernard, A. Genovesi, D. Dochain, A. Benhammou, and J. P. Steyer. "Hybrid modelling of anaerobic wastewater treatment processes." Water Science and Technology 43, no. 1 (January 1, 2001): 43–50. http://dx.doi.org/10.2166/wst.2001.0011.

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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.

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10

Henze, M., M. C. M. van Loosdrecht, G. A. Ekama, and D. Brdjanovic. "Biological Wastewater Treatment: Principles, Modelling and Design." Water Intelligence Online 7 (December 30, 2015): 9781780401867. http://dx.doi.org/10.2166/9781780401867.

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Olsson, G., and B. Newell. "Wastewater Treatment Systems: Modelling, Diagnosis and Control." Water Intelligence Online 4 (December 30, 2015): 9781780402864. http://dx.doi.org/10.2166/9781780402864.

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12

Dmitrović, Lovorka Gotal, Mario Lešina, and Hrvoje Selec. "Appliance of Simulation Modelling in Wastewater Treatment." International Journal of Environmental Science and Development 10, no. 12 (2019): 435–39. http://dx.doi.org/10.18178/ijesd.2019.10.12.1212.

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13

Mann, A. T., and T. Stephenson. "Modelling biological aerated filters for wastewater treatment." Water Research 31, no. 10 (October 1997): 2443–48. http://dx.doi.org/10.1016/s0043-1354(97)00095-x.

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14

Meister, Michael, and Wolfgang Rauch. "Wastewater treatment modelling with smoothed particle hydrodynamics." Environmental Modelling & Software 75 (January 2016): 206–11. http://dx.doi.org/10.1016/j.envsoft.2015.10.010.

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15

Sin, Gürkan, David Kaelin, Marlies J. Kampschreur, Imre Takács, Bernhard Wett, Krist V. Gernaey, Leiv Rieger, Hansruedi Siegrist, and Mark C. M. van Loosdrecht. "Modelling nitrite in wastewater treatment systems: a discussion of different modelling concepts." Water Science and Technology 58, no. 6 (October 1, 2008): 1155–71. http://dx.doi.org/10.2166/wst.2008.485.

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Originally presented at the 1st IWA/WEF Wastewater Treatment Modelling Seminar (WWTmod 2008), this contribution has been updated to also include the valuable feedback that was received during the Modelling Seminar. This paper addresses a number of basic issues concerning the modelling of nitrite in key processes involved in biological wastewater water treatment. To this end, we review different model concepts (together with model structures and corresponding parameter sets) proposed for processes such as two-step nitrification/denitrification, anaerobic ammonium oxidation and phosphorus uptake processes. After critically discussing these models with respect to their assumptions and parameter sets, common points of agreement as well as disagreement were elucidated. From this discussion a general picture of the state-of-the-art in the modelling of nitrite is provided. Taking this into account, a number of recommendations are provided to focus further research and development on nitrite modelling in biological wastewater treatment.

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16

Muhammad, Nurul Nadiah, Dennis Ling Chuan Ching, and Amir Syafiq Syamin Syah Amir Hamzah. "Mathematical Modelling of Wastewater Treatment in Oxidation Pond." Journal of Computational and Theoretical Nanoscience 16, no. 11 (November 1, 2019): 4455–60. http://dx.doi.org/10.1166/jctn.2019.8618.

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Oxidation pond also known as shallow ponds designed to treat wastewater through the interaction of sunlight, bacteria and algae. In this research, wastewater treatment model was developed to study the effect of pH towards, COD, DO and PSB. Using the process rate of breakdown of organic and inorganic substance, mass transfer and oxygen and the growth of bacteria as conditions, the advection-diffusion-reaction equations are solved using Crank Nicolson method. Comparisons were with existing data to verify the model and the similarity of dynamical behaviour.

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17

Wicklein, Edward, Damien J. Batstone, Joel Ducoste, Julien Laurent, Alonso Griborio, Jim Wicks, Stephen Saunders, Randal Samstag, Olivier Potier, and Ingmar Nopens. "Good modelling practice in applying computational fluid dynamics for WWTP modelling." Water Science and Technology 73, no. 5 (November 9, 2015): 969–82. http://dx.doi.org/10.2166/wst.2015.565.

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Computational fluid dynamics (CFD) modelling in the wastewater treatment (WWT) field is continuing to grow and be used to solve increasingly complex problems. However, the future of CFD models and their value to the wastewater field are a function of their proper application and knowledge of their limits. As has been established for other types of wastewater modelling (i.e. biokinetic models), it is timely to define a good modelling practice (GMP) for wastewater CFD applications. An International Water Association (IWA) working group has been formed to investigate a variety of issues and challenges related to CFD modelling in water and WWT. This paper summarizes the recommendations for GMP of the IWA working group on CFD. The paper provides an overview of GMP and, though it is written for the wastewater application, is based on general CFD procedures. A forthcoming companion paper to provide specific details on modelling of individual wastewater components forms the next step of the working group.

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18

Gaya, Muhammad Sani, Norhaliza Abdul Wahab, Yahya M. Sam, Azna N. Anuar, and Sharatul Izah Samsuddin. "ANFIS Modelling of Carbon Removal in Domestic Wastewater Treatment Plant." Applied Mechanics and Materials 372 (August 2013): 597–601. http://dx.doi.org/10.4028/www.scientific.net/amm.372.597.

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Modelling of an ill-defined system such as the wastewater treatment plant is quite tedious and difficult. However, successful and optimal operation of the system relied upon a suitable model. Most of the available developed models were applied to industrial wastewater treatment plants. This paper presents adaptive neuro fuzzy inference system (ANFIS) model for carbon removal in the Bunu domestic wastewater treatment plant in Kuala Lumpur, Malaysia. For comparison feed-forward neural network (FFNN) was used. Simulation results revealed that ANFIS model is slightly better than the FFNN model, thus proving that the model is a reliable and valuable tool for the wastewater treatment plant.

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19

Rieger, L., I. Takács, A. Shaw, S. Winkler, T. Ohtsuki, G. Langergraber, and S. Gillot. "Editorial: Status and future of wastewater treatment modelling." Water Science and Technology 61, no. 4 (February 1, 2010): 821–23. http://dx.doi.org/10.2166/wst.2010.003.

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20

Makisha, Nikolay. "Specific cost modelling for secondary treatment of wastewater." E3S Web of Conferences 263 (2021): 04065. http://dx.doi.org/10.1051/e3sconf/202126304065.

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The article is devoted to the study of model cost indicators of wastewater treatment facilities as one of the factors for ensuring sustainable development. It is noted that the greatest contribution in terms of cost formation is provided by the stage of biological wastewater treatment. As part of the study, a techno-economic simulation was conducted to compare two technological treatment schemes: conventional activated sludge scheme in aeration reactor and secondary settling tank, and treatment by means of membrane bioreactors. In the course of technological modeling, the concentrations of pollutants after treatment were obtained and compared for each of the schemes, as well as the values of possible harm to water bodies were calculated. Within the framework of cost modeling, capital and operating costs were obtained for the two variants, and key differences in their formation were analyzed. It is noted that the classical cleaning scheme requires the construction of a larger volume of structures, while for schemes with a membrane bioreactor, a significant cost item is the purchase of the actual membrane modules, but as the system performance increases, the share of these costs decreases.

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21

Stuetz, R., and F. B. Frechen. "Odours in Wastewater Treatment - Measurement, Modelling and Control." Water Intelligence Online 4 (December 30, 2015): 9781780402932. http://dx.doi.org/10.2166/9781780402932.

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22

Dochain, D., and P. Vanrolleghem. "Dynamical Modelling & Estimation in Wastewater Treatment Processes." Water Intelligence Online 4 (December 30, 2015): 9781780403045. http://dx.doi.org/10.2166/9781780403045.

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23

Westergreen, S., C. J. Brouckaert, and K. M. Foxon. "Modelling of ionic interactions with wastewater treatment biomass." Water Science and Technology 65, no. 6 (March 1, 2012): 1014–20. http://dx.doi.org/10.2166/wst.2012.922.

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Titration data for samples of mixed salts with glycine, baker's yeast cell mass and anaerobic digester sludge were obtained and compared to a speciation model of weak acid–base interaction in aqueous solutions. The effect of glycine on the buffer intensity of the solution could be precisely described by the speciation model but did not represent the proton exchange characteristics of either baker's yeast or anaerobic sludge well. A model component, UKZiNe, consisting of carboxylic acids, phosphate and amine groups described the baker's yeast well, and a combination of UKZiNe and carbonate-yielding inorganic solids described anaerobic digester sludge. The effect of biomass on buffer intensity in the pH range 6.5 to 8 was small for the concentration ranges tested.

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Rieger, L., J. Alex, W. Gujer, and H. Siegrist. "Modelling of aeration systems at wastewater treatment plants." Water Science and Technology 53, no. 4-5 (February 1, 2006): 439–47. http://dx.doi.org/10.2166/wst.2006.100.

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A model for the response time of aeration systems at WWTPs is proposed. It includes the delays caused by the air supply system (consisting of blowers, throttles and pipes), the rise time of the air bubbles and all control loops except the master DO controller. Beside a description of the required step-change experiments, different approaches for model calibration are given depending on the available data. Moreover, the parameters for the oxygen transfer and the response time of the aeration system model are not clearly identifiable. The model can be used for simulation studies which compare different types of controllers under changing loading and process conditions. The results from full-scale experiments at three different plants show that the response times of the aeration systems are in the range of 4–5 min. Taking all processes and time constants into account, some 30 min are needed to reach a new steady state after a step change of the airflow rate.

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Pinzón Pardo, A. L., D. Brdjanovic, M. S. Moussa, C. M. López-Vázquez, S. C. F. Meijer, H. H. A. Van Straten, A. J. H. Janssen, G. Amy, and M. C. M. Van Loosdrecht. "Modelling of an Oil Refinery Wastewater Treatment Plant." Environmental Technology 28, no. 11 (November 2007): 1273–84. http://dx.doi.org/10.1080/09593332808618889.

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26

Kordes, Bernd. "Modelling the energy balance of wastewater treatment plants." Environmental Technology Letters 6, no. 12 (December 1985): 566–75. http://dx.doi.org/10.1080/09593338509384377.

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27

Slesarenko, Viacheslav V. "Modelling of RO installations for wastewater treatment plants." Pacific Science Review 16, no. 1 (June 2014): 40–44. http://dx.doi.org/10.1016/j.pscr.2014.08.008.

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28

Capodaglio, Andrea G., Vladimir Novotny, and Luigi Fortina. "Modelling wastewater treatment plants through time series analysis." Environmetrics 3, no. 1 (1992): 99–120. http://dx.doi.org/10.1002/env.3170030107.

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29

Philips, N., S. Heyvaerts, K. Lammens, and J. F. Van Impe. "Mathematical modelling of small wastewater treatment plants: power and limitations." Water Science and Technology 51, no. 10 (May 1, 2005): 47–54. http://dx.doi.org/10.2166/wst.2005.0350.

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Although mathematical modelling of biological wastewater treatment processes has proved to be valuable for large-scale WWTPs (wastewater treatment plants) little experience has been acquired in the mathematical modelling of small wastewater treatment plants. This paper seeks to evaluate the applicability of mathematical modelling on small systems, which are characterized by high fluctuations in organic and hydraulic loads and little possibility for control. In order to achieve this, the paper examines the different steps in a general modelling protocol. One important bottleneck for the general use of mathematical modelling of small systems that emerges is the frequent sampling and many analyses needed for characterization of the flows while its applicability is limited. On the other hand, the determination of the model structure of a small WWTP can be quite valuable. Experiments show that tracer tests should include tests with a highly varying influent flow rate to spot independent small internal flows as these can have a significant impact on the behaviour of peak concentrations throughout the system. In addition, the model structure determination can provide useful information on dead zones, short-circuiting and mixing behaviour in the plant.

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30

Rahimi, Narges, and Ursula Eicker. "Renewable Electricity and Hydrogen Production via Decentralized Wastewater Treatment Systems." Energies 15, no. 23 (November 22, 2022): 8787. http://dx.doi.org/10.3390/en15238787.

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Urban wastewater could be converted into energy if microbial electrochemical technologies (METs) like microbial dual-chamber electrolysis cells (MDEC) or microbial fuel cells (MFC) are applied as a treatment method. Mathematical modelling of MFC and MDEC for wastewater treatment and energy recovery has been developed in this study. The Radaue method has been used to solve ordinary differential equations (ODEs), and the model outputs were successfully validated with previous experimental and modelling data. A case study in Montreal, Canada, has also been considered for testing the application of METs on an urban scale with a total daily wastewater flow of 75,000 L/day. The results show that from 1 m3 of wastewater, MDEC and MFC can generate 0.077 kg H2 and 0.033 kWh, respectively.

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Langeveld, J. G., F. H. L. R. Clemens, and J. H. J. M. van der Graaf. "Interactions within the wastewater system: requirements for sewer processes modelling." Water Science and Technology 47, no. 4 (February 1, 2003): 101–8. http://dx.doi.org/10.2166/wst.2003.0231.

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Today's focus on wastewater system optimisation necessitates the development of knowledge on the interactions between sewer systems and wastewater treatment, since these interactions have often been neglected in the past. In this paper the question is discussed to what extent it is favourable and possible to include dynamic changes of wastewater quality in wastewater system optimisation studies. The sensitivity of the wastewater treatment works to influent fluctuations proved to be the key issue in determining which sewer processes are involved in the dynamic interactions between sewer systems and treatment works. The preliminary results show the importance of a good description of the transport processes involving the soluble and suspended fractions.

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De Gussem, Kris, Alessio Fenu, Tom Wambecq, and Marjoleine Weemaes. "Energy saving on wastewater treatment plants through improved online control: case study wastewater treatment plant Antwerp-South." Water Science and Technology 69, no. 5 (January 17, 2014): 1074–79. http://dx.doi.org/10.2166/wst.2014.015.

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This work provides a case study on how activated sludge modelling and computational fluid dynamics (CFD) can help to optimize the energy consumption of a treatment plant that is already equipped with an advanced control based on online nutrient measurements. Currently, aeration basins on wastewater treatment plant Antwerp-South are operated sequentially while flow direction and point of inflow and outflow vary as a function of time. Activated sludge modelling shows that switching from the existing alternating flow based control to a simultaneous parallel feeding of all aeration tanks saves 1.3% energy. CFD calculations also illustrate that the water velocity is still sufficient if some impellers in the aeration basins are shutdown. The simulations of the Activated Sludge Model No. 2d indicate that the coupling of the aeration control with the impeller control, and automatically switching off some impellers when the aeration is inactive, can save 2.2 to 3.3% of energy without affecting the nutrient removal efficiency. On the other hand, all impellers are needed when the aeration is active to distribute the oxygen.

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Capodaglio, Andrea G. "EVALUATION OF MODELLING TECHNIQUES FOR WASTEWATER TREATMENT PLANT AUTOMATION." Water Science and Technology 30, no. 2 (July 1, 1994): 149–56. http://dx.doi.org/10.2166/wst.1994.0038.

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Wastewater treatment plant automation and real-time control have become important topics of research and development. Real-time control is nowadays considered a desirable goal for medium- to large-sized utilities for attaining better treatment efficiencies and improved compliance with discharge permit limitations. For an efficient implementation, real-time control must be supported by adequate modelling methodologies that take into full account the dynamic properties of the treatment system. This paper evaluates the requirements of such applications and the properties of available modelling approaches. Some applications examples are discussed.

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Protsenko, Serhii, Mykola Kizyeyev, and Olha Novytska. "Choice of the efficient flow diagram of biological wastewater treatment at municipal wastewater treatment plants." Environmental Problems 6, no. 4 (2021): 244–50. http://dx.doi.org/10.23939/ep2021.04.244.

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The possibility of increasing the efficiency of municipal wastewater treatment plant (WWTP) operation by changing the flow diagram of biological wastewater treatment in aeration tanks at minimum expenses for their reconstruction is shown in the paper on the example of one of the regional centres of Ukraine. The technology of nitri-denitrification of wastewater according to the flow diagram of the two-stage modified Ludzak-Ettinger process is offered for the considered conditions. The distribution of wastewater flows and internal nitrate recycling between the individual stages of this flow diagram has been optimized in order to minimize the residual content of total nitrogen in the treated effluents. Computer dynamic modelling of biochemical processes has proved the high efficiency and reliability of the flow diagram proposed by the authors.

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Corominas, Ll, L. Rieger, I. Takács, G. Ekama, H. Hauduc, P. A. Vanrolleghem, A. Oehmen, K. V. Gernaey, M. C. M. van Loosdrecht, and Y. Comeau. "New framework for standardized notation in wastewater treatment modelling." Water Science and Technology 61, no. 4 (February 1, 2010): 841–57. http://dx.doi.org/10.2166/wst.2010.912.

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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.

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Schopf, Kerstin, Johannes Judex, Bernhard Schmid, and Thomas Kienberger. "Modelling the bioenergy potential of municipal wastewater treatment plants." Water Science and Technology 77, no. 11 (May 14, 2018): 2613–23. http://dx.doi.org/10.2166/wst.2018.222.

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Abstract A municipal wastewater treatment plant accounts for a large portion of the total energy consumption of a municipality. Besides their high energy demand, the plants also display a significant bioenergy potential. This is due to the utilisation of the energy content of digester gas and sewage sludge if there exist suitable units. To maximise the energy recovery efficiency of wastewater treatment systems (WWTS), it is important to analyse the amount of digester gas and sludge produced in different types of plants. Therefore, the present paper deals with designing a tool to answer the following research questions: Which bioenergy potentials occur in different plant types? Which mass and energy flows are related to the specific potentials? Which utilisation processes for the potentials can lead to a high energy recovery efficiency of WWTS? Preliminary analyses with the designed tool were focused on estimating the level of electric and thermal energy self-sufficiency of different plant configuration scenarios including or excluding digester gas and/or sludge utilisation units. First results based on the level of self-sufficiency and associated energy and disposal costs show that a digester gas and sewage sludge utilisation should be considered when designing future WWTS.

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37

Corominas, Lluís, Leiv Rieger, Imre Takács, George Ekama, Hélène Hauduc, Peter A. Vanrolleghem, Adrian Oehmen, Krist V. Gernaey, Mark C. M. van Loosdrecht, and Yves Comeau. "New Framework for Standardized Notation in Wastewater Treatment Modelling." Proceedings of the Water Environment Federation 2010, no. 16 (January 1, 2010): 1099–100. http://dx.doi.org/10.2175/193864710798158580.

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Spagni, Alessandro, Marco Ferraris, and Stefania Casu. "Modelling wastewater treatment in a submerged anaerobic membrane bioreactor." Journal of Environmental Science and Health, Part A 50, no. 3 (January 16, 2015): 325–31. http://dx.doi.org/10.1080/10934529.2015.981123.

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39

Levy, J. Q. "Mathematical Modelling Applied to Control of Wastewater Treatment Stations." IFAC Proceedings Volumes 21, no. 17 (October 1988): 109–14. http://dx.doi.org/10.1016/s1474-6670(17)54563-2.

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Cosenza, Alida, Giorgio Mannina, Peter A. Vanrolleghem, and Marc B. Neumann. "Variance-based sensitivity analysis for wastewater treatment plant modelling." Science of The Total Environment 470-471 (February 2014): 1068–77. http://dx.doi.org/10.1016/j.scitotenv.2013.10.069.

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41

Marsili-Libelli, Stefano. "Modelling and automation of water and wastewater treatment processes." Environmental Modelling & Software 25, no. 5 (May 2010): 613–15. http://dx.doi.org/10.1016/j.envsoft.2009.11.002.

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42

Dziubek, Andrzej M., and Apolinary L. Kowal. "Modelling of the Coagulation–Adsorption Process in Treatment Systems." Water Science and Technology 17, no. 6-7 (June 1, 1985): 1113–20. http://dx.doi.org/10.2166/wst.1985.0206.

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Removal of organics in water or wastewater treatment systems is often described mathematically in the form of Langmuir and Freundlich adsorption isotherms. Using these equations, it is convenient to model, e.g., the removal of organic matter in the adsorption process on an activated carbon bed. In chemical treatment processes, organic substances are frequently removed from the water or wastewater under treatment via an adsorption on the precipitation products. In this paper presented is a generalized model of the equation of a multilayer adsorption isotherm, which describes TOC removal from a solution during chemical treatment in an alkaline medium. The model also includes the nonremovable concentration of organics.

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Heusch, S., B. Kamradt, and M. Ostrowski. "Simulation of wastewater treatment plant within integrated urban wastewater models." Water Science and Technology 61, no. 10 (May 1, 2010): 2645–52. http://dx.doi.org/10.2166/wst.2010.191.

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In the federal state of Hesse in Germany the application of an integrated software modelling framework is becoming part of the planning process to attain legal approval for the operation of combined sewer systems. The software allows for parallel simulation of flow and water quality routing in the sewer system and in receiving rivers. It combines existing pollution load model approaches with a simplified version of the River Water Quality Model No. 1 (RWQM1). Comprehensive simulation of the wastewater treatment plant (WWTP) is not considered yet. The paper analyses alternatives for the implementation of a WWTP module to model activated sludge plants. For both primary and secondary clarifiers as well as for the activated sludge process concepts for the integration into the existing software framework were developed. The activated sludge concept which uses a linearized version of the well known ASM1 model is presented in detail.

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Peys, Kurt, Ludo Diels, Roger Leysen, and Carlo Vandecasteele. "Development of a membrane biofilm reactor for the degradation of chlorinated aromatics." Water Science and Technology 36, no. 1 (July 1, 1997): 205–14. http://dx.doi.org/10.2166/wst.1997.0048.

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Many wastewaters generated by industry contain a limited amount of very toxic and recalcitrant pollutants which can upset biological treatment systems. A new membrane biofilm reactor concept is studied to treat these wastewaters. A biofilm is grown on an ultrafiltration membrane supporting layer that separates wastewater from an additional nutrient stream. The biofilm bacteria are in close contact with the wastewater which allows an efficient degradation of organic pollutants. Meanwhile, the diffusion of specific nutrient compounds keeps the bacteria active. The study is focused on modelling and optimization of the reactor operation considering both mass transfer and degradation kinetics. The biofilm structure and characteristics are very important in this optimization study.

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Rodriguez-Perez, Santiago, Alvaro Cabeza Sanchez, and María Lopez-Abelairas. "Modelling and mathematical optimisation of wastewater treatment in food industries." Open Research Europe 2 (May 19, 2022): 62. http://dx.doi.org/10.12688/openreseurope.14737.1.

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The current paper describes the work carried out in the Horizon 2020 AFTERLIFE project – "Advanced Filtration TEchnologies for the Recovery and Later conversIon of relevant Fractions from wastEwater" – (Grant Agreement no. 745737) which focuses on bioprocess modelling and optimisation using computational tools. The project addresses the development of a flexible, cost- and resource-efficient process framed in the zero-waste and circular economy approach for the recovery and valorisation of the relevant fractions from wastewater. The first step of such a process is an initial step consisting of a cascade of membrane filtration units to separate the total solids in sewage. Then, the concentrates recovered in each unit will be treated to obtain high-pure extracts and metabolites or to be converted into value-added biopolymers (polyhydroxyalkanoates). Moreover, the outflow of the process is an ultra-pure water stream that can be directly reused. Following a holistic approach, the design and optimisation of the AFTERLIFE process will improve performance and reduce the costs associated with wastewater treatment by maximising the value recovery. The paper focuses on the work done developing and implementing computational tools to model and optimise the design of the process. A framework for modelling-based optimisation has been developed. The applied optimisation approach is not computationally demanding and can be systematically applied to different processes. Finally, a use case establishing a scenario for testing the developed framework is described. The defined process model and optimisation methodology were applied to simulate the treatment of wastewater from the fish processing industry. The performance of the optimisation tool is analysed considering the simulation results.

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Pöyry, Lauri, Petri Ukkonen, Michela Mulas, and Anna Mikola. "Modelling solution for estimating aeration energy of wastewater treatment plants." Water Science and Technology 84, no. 12 (November 3, 2021): 3941–51. http://dx.doi.org/10.2166/wst.2021.481.

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Abstract Energy costs in the wastewater industry are increasing due to increasing trends in electricity rates and more stringent requirements for effluent quality. Wastewater aeration process is typically the largest energy consumer of the treatment plant and the optimization of the aeration process can offer significant savings for the wastewater treatment plants (WWTPs). Utilization of dynamic models can offer optimization solutions for improving the energy efficiency and process performance. In this work a simplified modelling approach emphasizing the control valves and the blowers is tested by developing aeration system models for two Finnish WWTPs. The developed model requires calibration of only a single parameter and the results from the simulations showed that reasonable estimations of the aeration systems energy demand could be made with a limited knowledge on the details of the physical system. The promising results highlight the strong influence of the control valve positioning to the whole system and indicate that airflow distribution along the system could be estimated simply from the positioning of the valves. The presented modelling approach allows the comparison between different blower and control valve alternatives during operation and for the process upgrades and offers prospect for improving the aeration operation control strategies.

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Pollard, P. C., E. v. Münch, P. A. Lant, and P. F. Greenfield. "The impact of microbiological tools on mathematical modelling of biological wastewater treatment." Water Science and Technology 36, no. 10 (November 1, 1997): 97–108. http://dx.doi.org/10.2166/wst.1997.0368.

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Biological systems are being used to treat an increasing range of complex wastes; domestic and industrial wastewaters containing nutrients and refractory organic compounds, soil sites and groundwater contaminated by organics, and organic solid residues. These treatment processes rely on micro-organisms and, more than ever before, must deliver higher quality outcomes at higher levels of reliability to protect the environment. At the same time, pressures to deliver cost-effective treatment have increased. The challenge for these biological treatment technologies and the associated engineering is to achieve the environmental and economic goals simultaneously. Mathematical modelling is an essential component in developing a detailed understanding of such processes, as well as design guidelines and suitable operating and control strategies. This paper provides a brief summary of the development of mathematical models for biological waste treatment systems, why they have become increasingly complex and how certain microbiological tools can provide the experimental means to validate more complex segregated and structured models of biological behaviour. With a number of specific modelling examples in the field of wastewater treatment, we illustrate the potential of these modern microbiological tools and their implications for gaining an improved understanding of biological waste treatment.

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Guillaud, J. F., M. Pommepuy, E. Dupray, J. C. Salomon, and B. Thouvenin. "Urban Wastewater Discharge and Bacteriological Quality of Receiving Coastal Waters: Processes and Modelling." Water Science and Technology 27, no. 12 (June 1, 1993): 223–26. http://dx.doi.org/10.2166/wst.1993.0306.

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The aim of this paper is to present some results of bacterial studies which were developed by IFREMER in coastal discharge areas of urban wastewaters; they are focused on the determination of bacterial inputs by wastewater treatment plants, the role of environmental factors on the enteric bacteria survival in the coastal zone, and the modelling of bacteria transport and disappearance in order to provide useful management information for minimizing faecal pollution in the coastal zone.

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Akuma, Desalegn Abdissa, and Ketema Beyecha Hundie. "Textile Wastewater Treatment Modelling and Design Using Stoat Graph and Summary Statistic Model." Pakistan Journal of Analytical & Environmental Chemistry 23, no. 1 (June 29, 2022): 32–40. http://dx.doi.org/10.21743/pjaec/2022.01.03.

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Without properly treated wastewater released from the textile industry contains organic and inorganic pollutants that cause environmental problems like water body contamination, which causes marine life disappearance, soil contamination, and air pollution. Treatment of textile industry wastewater is difficult due to pollutant types existing like BOD, COD, toxic heavy metals, organic particle matter, inorganic particle matter, color, etc. The multi-component wastewater pollutant needs proper designs to remove such pollutants. Dire Dawa textile wastewater treatment plant (design) and simulation was the objective of this study. The method of this study was experimental and software modelling. STOAT model software is the best capable of simulation treatments plants, and the time to complete the simulation was 3 days. The STOAT graphic and statically data analysis model efficiently removed the multi-components of pollutants effluent from Dire Dawa textile industry. Some pollutant parameter measures before design model are SS 350 mg/L, DS 2000 mg/L, ammonia 55 mg/L, BOD 350 mg/L, nitrate 0 mg/L and DO 12 mg/L. The effluent of wastewater treatment plant model simulation results are 2 mg/L SS, ammonia 8.82 mg/L, BOD 2.5 mg/L, and nitrate increases from 0 to 58 mg/L by ammonia oxidation. Totally 98.7% SS, 99% BOD, and 84% ammonia were removed in the design model. In the sludge outlet, nitrate contents increase due to nitrification being processed rather than denitrification.

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Tóth, András József, Ágnes Szanyi, Enikő Haaz, and Péter Mizsey. "Separation of Process Wastewater with Extractive Heterogeneous-Azeotropic Distillation." Hungarian Journal of Industry and Chemistry 44, no. 1 (October 1, 2016): 29–32. http://dx.doi.org/10.1515/hjic-2016-0003.

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Abstract The application of vapour-liquid equilibria-based separation alternatives can be extraordinarily complicated for the treatment of process wastewaters containing heterogeneous-azeotropic. Despite dissimilar successfully tested methods for separation, there is possibility to get better distillation method by enabling the separation of more and more specific process wastewater. Extractive heterogeneous-azeotropic distillation (EHAD) is a new advance in treatment of fine chemical wastewater showing special features to cope with the treatment of highly non-ideal mixtures. This method combines the worth of heterogeneous-azeotropic and extractive distillations in one apparatus without addition of any extra materials. The study of the separations of ternary component process wastewater from the fine chemical industry shows both in the modelled and experimental results that EHAD can be successfully applied. The measured and modelled compositions at extreme purities, that is, close to 0% or 100%, can be different because of the inaccuracies of the modelling. This highlights the paramount importance of the experiments if special extra-fine chemicals with almost no impurities, e.g. of pharmacopoeial quality are to be produced by special distillation technique. This study expands the application of EHAD technique, this new field is the separation of process wastewaters.

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