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Environmental Modelling & Software 25 (2010) 613–615

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Environmental Modelling & Software

journal homepage: www.elsevier .com/locate/envsoft

Preface

Modelling and automation of water and wastewater treatment processes

1. Background to the thematic issue

The 8th International Symposium on Sanitary and Environ-mental Engineering (SIDISA 08) was held in Florence, Italy, onJune 24–28, 2008 and hosted a special session on the applicationsof modelling and automation to water and wastewater treatmentprocesses. The session, under the auspices of IWA, ISWA Italy, GEWater & Process Technologies and many other local institutions,was attended by over 150 participants and included 24 extendedoral presentations, 6 short orals and 9 posters. It is my pleasure toacknowledge the cooperation of Giuseppe d’Antonio, Professor ofEnvironmental and Sanitary Engineering at the University of Naples‘‘Federico II’’ and President of ANDIS (National Association of Sani-tary Engineers), who with great open-mindedness agreed to includethis Special Session in the SIDISA annual general meeting. I amequally grateful to the Conference Chairman Professor ClaudioLubello, Department of Civil and Environmental Engineering,University of Florence, for the opportunity of organizing and chair-ing the session.

The wide and qualified participation confirmed the growinginterest of the sanitary engineering world towards new technologieswhich can successfully complement and enhance their profession,with automation figuring prominently among the new disciplinesrequired to improve the performance of modern water processingsystems. The fusion of these disciplines was advocated in twopioneering books (Olsson and Newell, 1999; Dochain and Vanrolle-ghem, 2001), whose prophetic value was confirmed by subsequentspecialized conferences (Olsson, 2002; Olsson, 2006), a specifictechnical publication (Olsson et al., 2005) and this session. The Envi-ronmental Modelling and Software journal welcomed the opportu-nity to publish such a set of papers that convey innovative andinterdisciplinary modelling approaches to meaningful instances ofadvanced sanitary engineering.

2. Topics and the core theme

The topics presented in the session ranged from advancedkinetics modelling to the use of artificial intelligence tools, eitherneural networks or fuzzy systems, for process control to newmethods for a better model calibration. From the operational view-point, many papers considered conventional activated sludgeprocesses, to which unconventional and innovative controlstrategies were applied. But there were also other interesting contri-butions regarding respirometry, constructed wetlands, and drinkingwater purification systems. Many papers showed a considerableeffort to extend the analysis from the single plant unit to a wider

1364-8152/$ – see front matter � 2009 Elsevier Ltd. All rights reserved.doi:10.1016/j.envsoft.2009.11.002

context, in line with the current approach of plant-wide bench-marking (Olsson and Jeppsson, 2006), including sewage systemsand surrounding land use.

From the methodological viewpoint, the session was particu-larly rich showing a mature use of many cutting edge techniques,such as the systematic identifiability approach (see e.g. Marsili-Libelli and Giusti, 2008; Cunha Machado et al., 2009) or fuzzymulti-criteria analysis and uncertainty evaluation (Benettoet al., 2008). Many papers showed a robust theoretical back-ground in model calibration, artificial intelligence, neuralnetworks, and global optimization methods, showing that excel-lence in performance can be achieved only by introducing theseadvanced techniques into the water treatment process designand operation.

From the application viewpoint the largest number of contribu-tions involved conventional wastewater treatment plants (WWTP),for which several control improvements were proposed, mainlybased on very detailed models derived from the ASM family (Henzeet al., 2000) and advanced calibration techniques.

Many papers straddled more than one application area or inte-grated methodology and applications. In the first set manyadvanced modelling results were presented, based on the Bench-mark extension (Copp, 2002) of the ASM models (Henze et al.,2000). Advanced modelling was not confined to WWTP and MBR,but was also extended to constructed wetlands for which modelswere presented as complex as those normally used for moreconventional processes, such as WWTP and MBR.

The session demonstrated the potential benefits of integrationbetween sanitary engineering practice and automation tech-niques. In fact the thematic issue common to all the selectedpapers is a strong and innovative methodological backgroundcoupled to an advanced sanitary application. In this sense, artifi-cial intelligence techniques were largely applied to WWTP, pota-bilization and constructed wetlands, producing advanced modelsor innovative modelling and control solution to well-knownproblems.

3. The individual contributions

Of the session contributions, nine appear in extended form inthis Thematic Issue and one as a short communication. These tenpapers convey the theme of the session, which is the fusion ofsystem-theoretic and information technology tools on one sideand sanitary engineering concepts on the other. The main criteriafor their selection was innovative methodological content (models,

Preface / Environmental Modelling & Software 25 (2010) 613–615614

estimation algorithms, data-processing techniques) coupled to therelevance of the target application.

The contribution of Benedetti, De Baets, Nopens, and Vanrolle-ghem, entitled Multi-criteria analysis of wastewater treatment plantdesign and control scenarios under uncertainty considers thecomplex, highly non-linear nature of a wastewater treatment plant,especially when controllers are introduced, and propose a methodsimilar to Benetto et al. (2008) for scenario analysis of processdesigns based on Monte Carlo simulations and multi-criteria evalu-ation of the results. Using the Benchmark Simulation Model no. 2 torepresent the plant, with dissolved oxygen and ammonium control-lers, the paper compares differing control structure and concludethat a cascade controller, in which the ammonium controller deter-mines the dissolved oxygen set-point, performs much better thattwo simple separated controllers. In the last part, an uncertaintyanalysis of the optimal designs, confirms the improvements attain-able with the more sophisticated controller in terms of a more stableeffluent quality.

The paper Software sensors are a real alternative to true sensors byCecil and Kozlowska describes the design and use of a softwaresensor to predict the ammonium-, nitrate- and nitrite-nitrogenconcentration in real-time, based on ammonium and ORP potentialmeasurements. The predicted ammonium concentration is used tocontrol the length of the nitrification phase in a Biodenipho� acti-vated sludge unit, given better response characteristics of the soft-ware sensor with respect to the ammonium meter. The softwaresensor simplifies meter service and reduces maintenance costs, inaddition to being much less expensive.

In their paper Modelling respirometric tests for the assessment ofkinetic and stoichiometric parameters on MBBR biofilm for municipalwastewater treatment, Ferrai, Guglielmi and Andreottola presenta new respirometric test to be used in conjunction with the MovingBed Biofilm Reactor (MBBR) technology used to upgrade conven-tional WWTPs. Experimental OUR profiles of heterotrophic biomasswere obtained from biofilm and modelled with the ASM3 model inorder to assess the biokinetics of heterotrophic and autotrophicbiomass. Through this approach the fractions of used and storedsubstrate were determined and the related parameters estimated.This paper represents a valuable advance in the procedure, longadvocated by the authors, of carefully calibrating the ASM modelbefore it could be used for design.

A complex multi-phase kinetic model of a constructed wetlandsystem was described by Giraldi, de Michieli Vitturi, and Iannelliin their paper FITOVERT: A dynamic numerical model of subsurfacevertical flow constructed wetlands, specifically developed to modelvertical subsurface flow constructed wetlands, providing a practicaltool for design and optimization of discontinuous feeding-emptyingoperation. The improvement with respect to previous models is theinclusion of the porosity reduction due to bacteria growth and accu-mulation of particulate components. In this way progressive clog-ging can be described. The model performance was analyzedthrough hydrodynamic tests with differing saturation levels of themedium and the calibration aspects are also discussed.

Giusti and Marsili-Libelli have used a fuzzy approach to modelthe dynamics of the relatively new (to modellers) compostingprocess. In their paper Fuzzy modelling of the composting process.Composting is a solid waste treatment process consisting of thebiochemical degradation of organic materials to produce stabi-lized organic materials. Given the complexity of the microbialprocesses involved in composting, a fuzzy model was proposed,composed of clustered antecedents, describing the processregimes, and consequent linear models driven by the aerationcycle and in-cycle temperature evolution. This fuzzy model wasadapted to the data by cluster training and minimization ofa model/data error criterion. The calibrated model was able to

describe the temperature profile during the most significantpart of the composting batch.

A complex patter recognition strategy is illustrated in the paperby Luccarini, Bragadin, Colombini, Mancini, Mello, Montali, andSottara, entitled Formal verification of wastewater treatmentprocesses using events detected from continuous signals by means ofartificial neural networks. Case study: SBR plant. An algorithm usingneural networks is used to extract the relevant qualitative patternsfrom the operation of a Sequencing Batch Reactor (SBR) process.They are then analyzed using tools commonly applied for the Veri-fication of Business Processes. The SBR process is regarded asa suitable case study because the commonly acknowledged criteriafor monitoring the biological processes (nitrification and denitrifi-cation) can be expressed in the form or qualitative constraints,which are easily translated into formal rules with desirable charac-teristics of flexibility and abstraction.

A fundamental ten-step procedure for model building and vali-dation has now been established by a number of landmark publica-tions (see Jakeman et al. 2006; Robson et al., 2008; and Welsh, 2008)and the paper by Rietveld, van der Helm, van Schagen, and van derAa, entitled Good modelling practice in drinking water treatment,applied to the Weesperkarspel plant of Waternet applies this proce-dure to the modelling of a complex drinking water treatment plant.This study was carried out in the belief that good modelling practiceincreases the credibility, acceptance and impact of the informationand insight into the process being modelled. The authors make theirpoint by applying their methodology to a complete drinking waterplant consisting of several process units: ozonation, pellet softening,biological activated carbon filtration and slow sand filtration. Themodels developed for each unit were used for operational improve-ments by providing fresh insights into their working. Several prac-tical advantages were obtained with this approach: chemicaldosing related to pellet softening was optimized; likewise ozonationwas optimized by modelling ozone exposure, bromate formationand biologically degradable natural organic matter.

Another paper applying fuzzy methodologies is A systematicapproach for fine-tuning of fuzzy controllers applied to WWTPs byRuano, Ribes, Sin, Seco, and Ferrer. It describes a systematicapproach for fine-tuning fuzzy controllers for the aeration controlsystem in a WWTP, similar to that described in Cunha Machadoet al. (2009). One of the difficulty of designing fuzzy controllers istheir tuning, given the large number of the parameters involved.The proposed approach has the merit of representing a viable alter-native to conventional step-by-step heuristic tuning recipes. In thispaper three methods are used in sequence: a Monte Carlo procedureto find proper initial conditions, an identifiability analysis to find anidentifiable parameter subset of the fuzzy controller, and lastly theminimization algorithm proper, to fine-tune the identifiable param-eter subset of the controller. This composite methodology resultedin a dramatic reduction in the number of identified parametersand improved the performance of the control system as measuredby the integral absolute deviation between the set-point and thecontrolled variable.

The paper by Worm, van der Helm, Lapikas, van Schagen, andRietveld, entitled Integration of models, data management, interfacesand training support in a drinking water treatment plant simulator,deals again with a drinking water plant, exploring the implicationsof a centralized, full automation of the process. This paper is coordi-nated with the previous paper by Rietveld et al., as both deal withthe drinking water treatment plant at Weesperkarspel as a casestudy and are part of a larger project named ‘‘Waterspot’’. This lastpaper describes the set-up of a full simulator to be used for operatortraining. Using familiar interfaces, the simulator can be used byoperators who are normally accustomed to the SCADA ‘‘look andfeel’’, though the underlying models are much more sophisticated.

Preface / Environmental Modelling & Software 25 (2010) 613–615 615

Further the operator can delve into deeper levels of the process,each providing dynamic information on relevant process parame-ters. Therefore, the strong point in this paper is the integration ofmodels, command and data management, training and decision-support features, and a GUI. All these features sum up to providea very sophisticated simulator for a complex water treatmentprocess.

The short communication by Doglioni, Primativo, Laucelli,Monno, Soon-Thiam, and Giustolisi is entitled An integratedmodelling approach for the assessment of land use change effectson wastewater infrastructures. Though it was published separately(Doglioni et al., 2009) it is nonetheless part of this ThematicIssue. It describes a clever example of integration to obtaina comprehensive model of both the wastewater pathway and ofits implication on the surrounding territory, in terms of theimpact of urban expansion and land use. The authors point outhow the three main model components have widely differingdynamics: the land use model accounts for the urban expansionaccording to developers’ guidelines; the sewers model reflectsthe urbanization impact on wastewater production, and thewastewater treatment model describes the varying load depend-ing on the new sewage routing and human pressure. Theproposed framework is convincingly demonstrated with thecase study of a small town located in Scotland.

Editing this Special Issue was a particularly rewarding experi-ence: reviewing many interesting contributions and keeping intouch with a host of dedicated reviewers, whom I deeply thankfor their commitment to the initiative. I wish to thank all theauthors, for their readiness in revising their manuscripts accordingto the reviewers’ suggestions and for their patience in waiting forthe completion of this long editing process. I hope that they willbe satisfied by the end result. This Thematic Issue, however, wouldnot have seen the light without the enthusiastic support and theunwavering backing of the Editor-in-Chief, Professor Tony Jakeman,always ready to help with suggestions, opinions, and encourage-ment. At the end of this adventure, I wish to express my deepestgratitude to the scientist, the editor, the friend, all of the purestgrade.

References

Benetto, E., Dujet, C., Rousseaux, P., 2008. Integrating fuzzy multicriteria analysisand uncertainty evaluation in life cycle assessment. Environmental Modelling& Software 23, 1461–1467.

Copp, J.B., 2002. The COST Simulation Benchmark: Description and SimulatorManual. EC Publication Office.

Cunha Machado, V., Tapia, G., Gabriel, D., Lafuente, J., Baeza, J.A., 2009. Systematicidentifiability study based on the Fisher Information Matrix for reducing thenumber of parameters calibration of an activated sludge model. EnvironmentalModelling & Software 24, 1274–1284.

Dochain, D., Vanrolleghem, P.A., 2001. Dynamical Modelling and Estimation inWastewater Treatment Processes. IWA Publishing, London, pp. 342.

Doglioni, A., Primativo, F., Laucelli, D., Monno, V., Soon-Thiam, K., Giustolisi, O., 2009. Anintegrated modelling approach for the assessment of land use change effects onwastewater infrastructures. Environmental Modelling & Software 24, 1522–1528.

Henze, M., Gujer, W., Mino, T., van Loosdrecht, M.C.M., 2000. Activated sludgemodels ASM1, ASM2, ASM2d, and ASM3. In: IWA Scientific and Technical ReportNo. 9.

Jakeman, A.J., Letcher, R.A., Norton, J.P., 2006. Ten iterative steps in developmentand evaluation of environmental models. Environmental Modelling & Software21, 602–614.

Marsili-Libelli, S., Giusti, E., 2008. Water quality modelling for small river basins.Environmental Modelling & Software 23, 451–463.

Olsson, G., 2002. Lessons learned at ICA2001. Water Science & Technology 45 (4–5),1–8.Olsson, G., Nielsen, M.K., Yuan, Z., Lynggaard-Jensen, A., Steyer, J.Ph., 2005. Instru-

mentation, control and automation in wastewater systems. Scientific and Tech-nical Report n. 15. IWA Publ., London.

Olsson, G., Jeppsson, U., 2006. Plant-wide control: dream, necessity or reality?Water Science & Technology 53 (3), 121–129.

Olsson, G., Newell, B., 1999. Wastewater Treatment Systems – Modelling, Diagnosisand Control. IWA Publishing, London, 742 pp.

Robson, B.J., Hamilton, D.P., Webster, I.T., Chan, T., 2008. Ten steps applied to devel-opment and evaluation of process-based biogeochemical models of estuaries.Environmental Modelling & Software 23, 369–384.

Welsh, W., 2008. Water balance modelling in Bowen, Queensland, and the teniterative steps in model development and evaluation. Environmental Modelling& Software 23, 195–205.

Stefano Marsili-Libelli*

Department of Systems and Computers, University of Florence,Via S. Marta 3, I-50139 Florence, Italy

* Tel./fax: þ39 055 4796264.E-mail address: marsili@dsi.unifi.it

9 November 2009Available online 22 December 2009