Argumentation-based framework for industrial wastewater discharges management

Engineering Applications of Artificial Intelligence 25 (2012) 317–325

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Engineering Applications of Artificial Intelligence journal homepage: www.elsevier.com/locate/engappai

Argumentation-based framework for industrial wastewater discharges management M. Aulinas a,b,n, P. Tolchinsky b, C. Turon c, M. Poch a, U. Corte´s b a

Laboratory of Chemical and Environmental Engineering, Parc Cientı´fic i Tecnolo gic, Edifici Jaume Casademont, Pic de Peguera 15, 17003 Girona, Catalonia, Spain Knowledge Engineering and Machine Learning Group, Technical University of Catalonia, Campus Nord - Edifici C5, Jordi Girona 1-3, 08034 Barcelona, Spain c Consorci per a la Defensa de la Conca del Riu Beso s, Av. Sant Julia 241, Granollers, Spain b

a r t i c l e i n f o

abstract

Article history: Received 12 December 2008 Received in revised form 24 November 2010 Accepted 19 September 2011

The daily operation of wastewater treatment plants (WWTPs) in unitary sewer systems of industrialized areas is of special concern. Severe problems can occur due to the characteristics of incoming flow. In order to avoid decision that leads to hazardous situations, guidelines and regulations exist. However, there are still no golden standards by which to a priori decide whether a WWTP can cope with critical discharges. Strict adherence to regulations may not always be convenient, since special circumstances may motivate operators to accept discharges that are above established thresholds or to reject discharges that comply with guidelines. Nonetheless, such decisions must be well justified. This paper proposes an argumentation-based model by which to formulate a flexible decision-making process. An example of the model application describes how experts deliberate the safety of a discharge and adapt each decision to the particular characteristics of the industrial discharge and the WWTP. & 2011 Elsevier Ltd. All rights reserved.

Keywords: Agents Argumentation River basin management Urban wastewater system Industrial discharge management Wastewater treatment plant (WWTP)

1. Introduction In industrialized areas, where industrial discharges are connected to sewer systems and are treated, together with domestic wastewater and rainfall, by wastewater treatment plants (WWTPs), industrial discharges represent an important load contribution to urban wastewater systems (UWSs). In this context, where there is high diversification of industries (e.g., longand short-term variations), it is difficult to define typical input operating conditions at the WWTP and to account for external factors. The uncertain and often insufficient knowledge describing the interrelation between industrial discharges and the treatment performance complicate the regulation and management of industrial wastewater discharges into the UWS (Butler and ¨ Schutze, 2005; Devesa et al., 2009; Vanrolleghem et al., 2005). The characteristics of inflow wastewater and its influence on biological processes, can cause problems that may have an effect on the WWTP effluent, which in turn may produce an undesirable outcome on the receiving media where treated wastewater is discharged (e.g., the river).

n Corresponding author at: Laboratory of Chemical and Environmental Engi neering, Parc Cientı´fic i Tecnologic, Edifici Jaume Casademont, Pic de Peguera 15, 17003 Girona, Catalonia, Spain. Tel.: þ 34 972183244; fax: þ 34 972418150. E-mail address: [email protected] (M. Aulinas).

0952-1976/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.engappai.2011.09.016

Up-to-date approaches to control and prevent hazardous situations related to industrial discharges are based on the application of standards at discharge point sources. These standards use numerical limits of a set of polluting parameters, indicating a concentration and/or load (Tilche and Orhon, 2002; Gabriel and Zessner, 2006), to define the permitted quality of wastewater discharged. Strict adherence to conventional guidelines and regulations may not always be convenient for both WWTP and water quality protection, since each input operating condition is different. Special circumstances may sometimes motivate operators to either reject discharges that are under legal limits in order to prevent potential complications (e.g., the WWTP is overloaded) or accept discharges that are above legal thresholds, thereby optimizing the infrastructure, because the current state of the WWTP can deal with them. However, because these decisions are critical, they need to be well justified. This task implies successfully adapting the WWTP operation to influent variability and avoiding or mitigating operational problems in the WWTP. These decisions should be based on whether, in the current circumstances and accounting for possible complementary courses of action (e.g., adjustment of operational WWTP parameters, preventive or mitigating actions, etc.), the discharge will cause an undesirable side effect that justifies not performing it. For this reason, we propose a flexible decision-making process in which decisions can be adapted to

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each circumstance depending on the particular situation. The different stakeholders involved in wastewater management can pose arguments to justify or counter a previously made argument. In our proposal, guidelines and thresholds are taken as perspectives by which to evaluate the arguments for and against the discharge safety. Other relevant perspectives are expert opinion and empirical evidence. These perspectives make it possible to consider of accepting the discharge or not because it is below thresholds because experts claim it will not cause an undesirable side effect. This paper proposes a method, based on artificial intelligence tools, that provides a procedural framework for deciding whether or not an industrial discharge can safely be handled by the WWTP. This method defines an argumentative process for eliciting the relevant factors from the decision makers (experts in the domain). This results in a network of interacting arguments in favor or against the industrial discharge. These arguments are then evaluated, taking into account the domain’s guidelines and thresholds, the available empirical evidence and the decision makers’ opinions. The result of such an evaluation is a justification as to why the proposed industrial spill is or is not environmentally safe. Moreover, the proposed method, being of a computational nature, allows partial automation of the process. The following subsection contains the background literature on the argumentation-based method applied. In Section 3, we introduce ProCLAIM (see Corte´s and Poch, 2009 for a more detailed explanation). The rest of the paper is organized as follows. Section 2 describes the context in which the decision making process takes place, motivating a need for an alternative representation of the problem. This alternative approach will enable deliberation on the safety of an industrial discharge. Section 3 explores the different lines of reasoning relevant for deliberating the safety of a discharge beyond the existing standards, and it presents the overall framework to evaluate the arguments. Section 4 introduces a simplified but significant wastewater scenario in which a toxic substance is discharged into the system and a critical safety decision must be made. This is an example from a collection used to show the power of the tools presented and to study their feasibility and viability for deployment in a real scenario. Finally, Section 5 gives the main conclusions of the paper and planned future work. 1.1. Background Argumentation theory has recently emerged from an interdisciplinary area of research as one of the most promising paradigms for conflict resolution and as an important method of reasoning and human interaction (Bench-Capon and Dunne, 2007). The practical benefits of using argumentation in contexts as diverse as inference, decision-making and dialog has drawn increasing attention from the computational research community. As a result, in recent years formal models have emerged to establish argumentation on a rigorous computational basis and enable the development of automated computational capabilities based on argumentation (Tolchinsky et al., 2009). It is worth emphasizing that argumentation has already been proposed in safety-critical domains, particularly in medical scenarios. In Tolchinksy and Corte´s (2006) the ProCLAIM model is proposed to allow experts to efficiently deliberate on whether a proposed action is safe or not, accounting for common consented knowledge, evidence and participants’ degree of expertise. These authors report that the family of scenarios for which ProCLAIM may be useful naturally falls into safety-critical domains. For example, in environmental scenarios, in the same way as in the medical domain, the performance of wrong actions may cause catastrophic effects on the environment. In many of these

situations, decisions are made by experts with the help of various guidelines to indicate the most appropriate, commonly agreed upon solutions. Furthermore, in such contexts empirical evidence plays an important role in the decision making. Briefly, for model evaluation, two safety-critical scenarios are now being explored. One scenario is related to human organ transplants (Tolchinsky et al., 2008) while the other is related to the environmental impact of industrial wastewater discharges in river basins (Aulinas et al., 2007; Aulinas, 2009). The latter is the scenario investigated in this work.

2. Using arguments to reason about problems in municipal WWTPs The aim of the decision-making process we present is to determine whether an industrial spill can be safely discharged. The most common treatment method at municipal WWTPs is the activated sludge system, based on a dynamic multi-species microorganism population capable of oxidizing organic matter under special operating conditions (Tchobanoglous et al., 2003). The microorganisms’ metabolism and capacity to remove organic matter depend on wastewater composition as well as the capacity to adapt the management of WWTP operational parameters (e.g., returned activated sludge (RAS), dissolved oxygen (DO), waste activated sludge (WAS)) to wastewater influent variations in order to meet effluent safety standards. A scheme of the activated sludge process at a biological WWTP is shown in Fig. 1. Industrial discharges of various types, with different characteristics, can affect the growth of microorganisms in municipal WWTPs working with activated sludge systems (e.g., content of organic matter, nutrients and/or presence of pollutants), and by extension of the treatment and the final result. A spill is safe if it does not cause any undesirable side effects to the UWS. Otherwise, the spill is considered to be unsafe. Several studies have been carried out to improve and increase the knowledge of WWTP operational problems related to influent characteristics (Ayesa et al., 1998; Comas et al., 2003, 2008; Henze et al., 1993; Jenkins et al., 2003). This knowledge, based on on-line and off-line data as well as on the experts’ heuristics, is mainly represented by means of decision trees and/or knowledgebased flow diagrams (Corte´s et al., 2003; Poch et al., 2004; Rodrı´guez-Roda et al., 2002; Serra et al., 1994, 1997). The knowledge is organized in a hierarchical manner: top-down descriptions of interactions between different parameters and factors used to solve a problem. This allows for the easy interpretation of the available knowledge, mainly in terms of cause–effect relations for a specific problem. These decision trees do not account for different possible perspectives on the decision that may be in conflict. For instance, while guidelines may suggest that an industrial discharge cannot ACTIVATED SLUDGE SYSTEM Aeration tank Primary Effluent

Secondary settler (clarifier) Effluent

DO

Recycle (RAS)

Waste (WAS)

Fig. 1. Diagram of a typical activated sludge (AS) system. Primary effluent comes from a primary treatment and enters the aeration tank containing the microorganisms population: part of the activated sludge is recycled (RAS) whereas another part is purged (WAS). DO stands for the content of dissolved oxygen at the aeration tank.

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exceed the threshold of1500 mg/l of chemical oxygen demand (COD), an expert (e.g., the WWTP manager) may believe that this is not the case in all situations. Moreover, empirical evidence can have an influence on the decision (e.g., the WWTP is overloaded at that moment). This paper addresses the question of how to make decisions, as an argumentative process, in which the knowledge available in the decision-making trees can also be accounted for and represented as interacting arguments. The added value is that, in the argumentative process, alternative proposals or the identification of a potential complication caused by the interaction among diverse factors can naturally be integrated into the decision making via the submission of arguments and counter-arguments. In particular, this approach facilitates the active participation of experts in the decision-making process. Many aspects must be accounted for to allow such argumentative processes to take place in an efficient and effective way. In this section we focus on the first obvious question: what is to be argued about? Later, in Section 3, we discuss how to argue. Concerning the question when to argue, the answer is: whenever there are potentially conflicting arguments; an argumentation process can be useful for reaching consistent conclusions (Maudet et al., 2007).

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Whether or not an industrial discharge is expected to cause undesirable side effects depends on the wastewater’s content, the receiving media characteristics (e.g., characteristics of the WWTP), external factors such as the weather conditions and, finally, any complementary courses of actions that can be performed to prevent or mitigate the undesirable spill’s side effects. Let us consider the following four sets:

   

R: the set of facts in the current circumstances. A: the set of possible actions. S: the set of side effects that an industrial discharge may cause. G  : the set of undesirable goals that may be achieved because of an industrial discharge.

R is the set of facts constituting the circumstances in which the spill is intended to be discharged. R would thus contain all the known characteristics of the wastewater, the characteristics of the receiving media and other known environmental conditions. A contains the actions relevant to decision making. A would thus contain the discharge action and other alternative actions such as decrease the waste activated sludge (WAS) or add chlorine. S is the set of side effects of the discharge and G  contains the undesirable

Table 1 Sets of information used to construct arguments. Argument components

Notation

Description

Initial states (R)

r1:ind_ww(COD) r2:ind_ww(BOD) r3:ind_ww(N, P) r4:ind_ww(Cd) r5:ind_ww(Cr) r6:fungi

Industrial wastewater concentration of COD Industrial wastewater concentration of BOD Industrial wastewater concentration of nutrients (N and P) Industrial wastewater concentration of cadmium (Cd) Industrial wastewater concentration of chromium (Cr) Presence of fungi spp. in the active biomass (e.g., Pseudomonas sp., Aspergillus sp., Candida maltosa, etc.) ^ WWTP design parameters (desirable maximum flow, N/D capacity, type of reactory) Setpoints of operation variables: DO, WAS, RAS, HRT, etc. y

^ r10:WWTP_design r11: WWTP_setpoints rn: y

a4:primary.treatment N/D_(sets) an:y

Increase either DO, RAS or WAS to modify WWTP performance Decrease either DO, RAS or WAS to modify WWTP performance Add nutrients, caustic soda, chlorine, coagulants/flocculants to prevent or mitigate negative effects Avoid or enhance the process of N/D through a set of interrelated actions y

Final states (S)

s1:fil.B(type) s2:FFB(type) s3:EPS s4:overaeration s5:hydraulic.shock s6:overdose s7:reduction(HM) sn: y

Inhibition of filamentous bacteria Inhibition of foam-foaming filamentous bacteria Absence, insufficient or overloading of EPS Excess of DO, undesirable bubbles Hydraulic shock at the WWTP due to a heavy rain or storm Overdose application of coagulants/flocculants Reduction of a heavy metal (e.g., CrVI to CrIII) y

Undesirable goals (G  )

g1:fil.bulking

Overgrowth of filamentous bacteria

g2:viscous.bulking

Excessive productions of EPS by the floc-forming bacteria (viscous sludge is difficult to settle and become compact) Overgrowing of foam-forming filamentous bacteria The absence of EPS hinders the formation of flocs Denitrification occurs in clarifiers (instead of in reactors) The absence of filaments hinders the formation of large flocs Washout of biomass hence loss of active microorganisms Toxicity to aquatic organisms of WWTP effluent water with overdose of coagulants/ flocculants Overdose of coagulants/flocculants can cause a complete charge reversal and re-stabilize the colloid complex, thus settling problems Accumulation of toxic substances in the sludge, making them unavailable for posterior uses (e.g., compost for agriculture) y

Actions (A)

a1:increase_(DO, RAS, WAS) a2:decrease_(DO, RAS, WAS) a3:add_(N, P, NaOH, CHLy)

g3:bio.foaming g4:dispersed.growth g5:rising g6:pin-point floc g7:biomass.loss g8:aquatic.toxicity g9:charge.reversal g10:sludge.toxicity gn:y

Note: COD (chemical oxygen demand), BOD (biological oxygen demand), N (nitrogen), P (phosphorous), N/D (nitrification/denitrification), WAS (waste activated sludge), RAS (recycle activated sludge), DO (dissolved oxygen), CHL (chlorine), EPS (extracellular polymeric substances).

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goals that these side effects may have. Possible side effects are, for instance, undesired quantity of filamentous bacteria and overdose application of chlorine, which may, respectively, realize the presences of the undesirable goals of filamentous bulking and chlorine organic compounds (COCs) in the effluent. Table 1 illustrates a subset of possible values of R, A, S and G  . We can now reformulate the problem of deciding whether a spill is environmentally safe as a process of identifying the relevant facts in the current circumstances (r1,y,rn in R) because of which the wastewater discharge, along with other complementary actions (a1,y,an in A), may or may not cause any side effect (s1 in S), that realizes an undesirable goal g1 which justifies not performing the course of actions a1,y,an. Fig. 2 graphically depicts an example of the formation of an argument by linking the pieces of information organized as R, A, S and G  . These arguments can announce either an undesirable goal (argument con) or a favorable one (argument pro). One example of how it is done computationally is given by Tolchinsky et al. (2008). Thus, to argue against an industrial discharge means to indicate that there is a subset of R from which the proposed actions will cause a side effect that produces some undesirable goal. For example, the argument ‘‘The industrial discharge contains a concentration of readily biodegradable organic matter – rbCOD – that will cause an overgrowth of filamentous bacteria causing filamentous bulking’’. An argument defending the discharge’s safety will contradict such a statement: ‘‘The industrial discharge that contains a concentration of rbCOD will not cause the side effect overgrowth of filamentous bacteria achieving the undesirable goal filamentous bulking since the action add nutrients can be performed to avoid the side effect overgrowth of filamentous bacteria and thus, prevent filamentous bulking’’. Typical problems such as filamentous bulking can therefore be rephrased in terms of the interaction of these arguments constructed to instantiate the tuple R, A, S and G  . This tuple, in fact, defines an argument scheme (AS). As described by Walton (1996), AS are used to classify different types of arguments that embody stereotypical patterns of reasoning, i.e., to identify the premises and conclusion of an argument. In this case, the scheme embodies conventional patterns of reasoning over the safety of an action (Atkinson et al., 2005). An instantiated scheme (what we term an argument) can be questioned (attacked) by posing critical questions associated with the scheme. A critical question (CQ) challenges the validity of the given argument. The asking of a CQ

Fig. 2. Argument formation using as a basis a set of R, A, S and G  .

shifts the weight of presumption back to the arguer so that his/ her argument is defeated unless the question is answered. Each CQ can itself be posed as an attacking argument instantiating a particular scheme. This scheme is then itself subjected to critical questioning. Thus, CQ is used to evaluate the argument by probing into its potentially weak points. How the revision procedure can be handled is established by defining the set of attached CQs (Walton, 2005). AS and CQ together provide a natural basis for the definition of a protocol-based exchange of arguments. Indeed, such an approach is taken in Tolchinsky et al. (2007), where a protocolbased exchange of arguments is defined to argue about the safety of a proposed action. In the following section the model is briefly described.

3. The ProCLAIM model ProCLAIM defines a setting in which the different agents (e.g., those involved in the UWS management) can effectively deliberate the safety of the proposed actions. Broadly construed, the ProCLAIM model consists of a mediator agent (MA) directing proponent agents (e.g., industries, WWTP manager, etc.) in an argument-based collaborative decision-making dialog, in which the final action should comply with certain domain-dependent guidelines. However, the arguments submitted by the proponent agents may also persuade the MA to accept decisions that deviate from the guidelines. For example, the MA may able to reason that the submitted arguments in support of an alternative decision have proven to be correct in previous, similar deliberations. Thus, the MA has three main tasks to accomplish 1. Guide the proponent agents in the arguments they can submit at each stage of the deliberation. 2. Ensure that the submitted arguments are relevant (e.g., in the sense that instantiations of schemes are relevant in terms of the domain of discourse). 3. Evaluate the submitted arguments in order to identify the winning arguments and thus determine whether a proposed action is appropriate. This last task may require the MA to assign a preference relation to the submitted arguments that are in conflict and, possibly, to submit additional arguments. In order to carry out these tasks, the MA employs four knowledge resources that are part of the model – the argument scheme repository (ASR), the guideline knowledge (GK) base, the case based reasoning engine (CBRe) and the argument source manager (ASM) component – depicted in Fig. 3. The ASR encodes the full space of argumentation, i.e., all the possible lines of reasoning, or the argument schemes, that should be pursued with respect to a given issue. The repository is structured in such a way that it defines the protocol-based exchange of arguments. Associated with these argument schemes are CQs that enable agents to attack the validity of the various elements of the argument scheme and the connections between them. Each CQ can itself be posed as an attacking argument instantiating a particular scheme. The GK enables the MA to check whether the arguments comply with the domain knowledge and, in particular, whether the arguments are valid instantiations of abstract arguments in the ASR. CBRe assigns strengths to the submitted arguments on the basis of their associated evidence gathered from past deliberations, and provides additional arguments deemed relevant in previous similar situations. Finally, the ASM component enables us to readjust the strengths of these arguments depending on the source—from whom, or where, the arguments have been submitted. Hence, this

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Fig. 3. ProCLAIM’s architecture. Shaded boxes identify the model’s constituent parts specialized for the basin scenario. Shaded ovals identify the participant agents in the presented case (see Section 4.1).

latter component manages the knowledge related to the agent’s roles and/or reputations, and/or types of certificates or references that may empower agents to undertake some exceptional actions. The agents’ submitted arguments shape a graph of interacting arguments based on the attack relation. The arguments used to make these graphs are those available at the ASR that are constructed as explained in Section 2. The construction of arguments is done in two steps. The first step consists of building the ASR. In this phase the particular schemes too deliberate on a question are built. In the second step, these schemes have to be instantiated according to a few constrained variables. So, once these schemes are delivered to the agents, it is necessary to instantiate some variables. One example of how it is done computationally can be found in Tolchinsky et al. (2008).

4. Deliberating in the river basin scenario This section presents the river basin context in which industrial discharges are released. In recent years, water governance has undergone a remarkable paradigm shift. Old notions of water resource management dominated by a supply-orientation and reliance on civil engineering science and technical solutions to water problems have been discarded in favor of a softer governance regime that embraces stakeholder participatory processes (Guimara~ es and Corral, 2002). The Water Framework Directive supports this approach and other important policy principles for European member states (CEC, 2000). This scenario comprises, as the more relevant components, the land with its uses, rural and urban areas, and groundwater and surface water. Everyone lives in a river basin. People who live far away from natural water resources may also affect water quality and quantity, since everything in a river basin is interconnected and interdependent. For that reason, in the context of a river basin, a decision made affects all of its components. The participation of the different agents in the river basin management scenario emerges as key to reaching a consensus. In Section 4.1 the basin scenario is simplified to facilitate understanding of the argument-based method when dealing with

critical decisions in the system, focusing on the safety of an industrial discharge containing a polluting substance. There are many smaller catchments or watersheds within a river basin (i.e., a smaller part of the basin that drains water to a stream). This makes it possible, in a first stage, to build reduced prototypes and then amplify their scale. In the following sections, the agents used to illustrate an example are described (Section 4.1), and the process of argument submission, validation and preference assignment is exemplified (Section 4.2). 4.1. Urban wastewater system agents As mentioned in Section 1, an urban wastewater system (UWS) is constituted by an urban catchment that comprises a sewer system, a WWTP and an urban river stretch, which drains wastewater from human activity (i.e., communities and industries) as well as water from rainfall. Industries often deal with the wastewater they produce by connecting to the sewer system. Therefore, industries can be considered part of the UWS, whose main components are shown in Fig. 4. We consider every relevant element as a software agent, i.e., an autonomous entity that can interact with other entities to achieve an individual or common goal (Russell and Norvig, 2010; Wooldridge, 2001). In this example, we consider the following proponent agents that can participate in the argument-based deliberation when dealing with an industrial wastewater discharge into a UWS

 Industry agents (IA) represent individual industries and/or



groups of industries that need to manage their produced wastewater as a result of their production process. IA discharge their produced wastewater into the sewer system, where it is collected together with other inflows and transported to the WWTP (from here on this course of action is called a0). Wastewater treatment agents (WTA) represent the manager of WWTP. Their main function is to keep track of wastewater flow arriving at the WWTP as well as to supervise and control the treatment process. They sound convenient alarms when

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Fig. 4. Urban wastewater system (UWS). In bold the normal path followed by an industrial discharge. CSO: combined Sewer overflow.

submitted arguments. If accepted, they will be part of the argument graph for a specific deliberation process, such as the one depicted in Fig. 6. 4.2. An industrial discharge with a toxic substance Let us suppose that an industry, represented by its IA, proposes a wastewater discharge claiming that no undesirable effects will occur as a result of it. Accordingly, the IA poses argument Arg1 Fig. 5. Acquaintance model for the proposed case (i.e., industrial discharge containing a heavy metal). Arrows indicate agent acquaintances, whereas numbers inside the boxes indicate agents’ reputation, i.e., the priority order of their decisions.



necessary and give orders to change the operational set points. This responsibility is shared between the managers of the WWTP (WTAM) and the operators (WTAO). River consortium agents (RCA) represent the maximum authority in the catchment, and their main objective is to preserve the river quality. Their main functions are to manage and coordinate a group of WWTPs in the river catchment as well as to monitor river quality and prevent possible hazardous contamination by supervising IA and WTA.

All of these agents, representing experts in the wastewater, having different degrees of responsibility, and making use of their expertise in front of safety critical decisions treatment domain, can take part in the deliberation process. Fig. 3 shows all these agents in the context of ProCLAIM for this scenario. To illustrate the evaluation of the arguments posed by these experts it is important to know the acquaintances among them and the degree of confidence in their arguments. Fig. 5 shows the main relationships among the agents considered in this specific example. The number in the box indicates the order of the agents’ level of expertise specific to each type of discharge. WTAM knows the operation of the WWTP and thus the degree of confidence in their arguments is high (in fact, since the problem of concern involves a priority contaminant, WTAM responsibility g WTAO, consequently WTAM arguments will have more strength). However, the figure shows that when dealing with discharges containing priority polluting substances, the RCA is more reliable, so their arguments will be deemed stronger. All of these acquaintances will be taken into consideration by the MA to evaluate the arguments. The deliberation processes are posed and it is decided whether or not to accept the participant

Arg1: In the current circumstances (i.e., a wastewater discharge and a WWTP) industry Indi will effectuate the discharge (action a0) claiming that this action (a0) will not cause any side effect S so any undesirable goal g to the treatment system. Generally speaking, when an IA claims to discharge its wastewater because no negative effects occur (e.g., Arg1), a CQ that will naturally arise is ‘‘AS1_CQ1: Is there a contraindication for undertaking the proposed action?’’ This will help the MA to check if the following dialog move is relevant. Assuming that the WTA knows that the discharge contains Chromium VI and believes Chromium VI is a contraindication for the treatment process because there is evidence it can provoke both the inhibition of nitrification (significantly decreasing the ammonia removal efficiency) and the reduction of filament abundance, causing the appearance of pin-point floc and free-dispersed bacteria (Alkan et al., 2008; Samaras et al., 2009). The WTA reports the latter possibility by submitting Arg2 Arg2: If in current circumstances industry Indi effectuates the discharge (a0) containing Chromium VI (r5), this will reduce filaments abundance (s1) and provoke the appearance of pinpoint flocs (g6). Arg2 introduces new important information about the discharge (i.e., the discharge contains chromium that can cause the inhibition of filamentous bacteria). Different experts in the domain can start a dialog of attacking and supporting arguments, seeking more information, alternative actions, etc. before finally deciding on the possible actions to be taken to prevent WWTP problems. Until now, it has been documented that the degree of inhibition in activated sludge is influenced by several factors such as pH, the concentration of inhibitors, the species present, the concentration of suspended solids, the sludge age, the solubility of the inhibitor, and the concentration of other cations and

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323

Fig. 6. Argument graph that captures the moves in a dialog over the acceptability of a toxic industrial discharge into the WWTP. Each node of the tree holds one argument described in the table. Each new introduced factor is highlighted in bold.

molecules present (Alkan et al., 2008; Samaras et al., 2009). According to this, other possible counterarguments are raised by three new CQ (they are meant to limit the possible counterarguments, discarding ones that are not relevant for the discussion and looking for key information). AS2_CQ1: Are the current circumstances such that the stated effect will be achieved? That is equivalent, in the presented example, to questioning if the concentration of chromium, given the current circumstances, is enough to produce the undesirable effect (i.e., filamentous bacteria inhibition) even if it is under legal thresholds. AS2_CQ2: Are the current circumstances such that the achieved effect will realize the stated negative goal? That is, to explore other relevant circumstances in which no undesirable goal is realized (e.g., synergetic effects with other pollutants, precipitation of this heavy metal due to the presence of a specific cation, etc.). AS2_CQ3: Is there a course of action that prevents the achievement of the stated effect, i.e., to explore the possible actions that can prevent or mitigate the negative effect (e.g., try to precipitate the heavy metal, increase the capacity of the activated sludge to adsorb heavy metals by means of some added adsorbent, etc.). Fig. 6 shows some of the possible lines of reasoning when dealing with the industrial discharge containing a heavy metal (e.g., Chromium VI). Following the example, AS2_CQ1, AS2_CQ2 and AS2_CQ3 attack Arg2; consequently Arg3, Arg4 and Arg5 (see the table in Fig. 6) attack Arg2 (e.g., they are instances with new information about the discharge, possible synergetic effects of the current circumstances or an alternative action, respectively). Arg3: If in current circumstances industry Indi effectuates the discharge (a0) containing Chromium VI (r5), it will not cause as much inhibition of filamentous bacteria (s1) as necessary, hence it does not provoke pin-point flocs (g6). Arg4: If in current circumstances industry Indi effectuates the discharge (a0) containing Chromium VI (r5), it will not cause inhibition of filamentous bacteria (s1), hence it does not provoke pin-point flocs (g6) due to the positive present condition of activated biomass to reduce Chromium VI (i.e., the presence of several fungi (r6) species capable of reducing Chromium VI to a less unsafe form of this heavy metal –

Chromium III – together with the availability of organic matter). Arg5: If in current circumstances industry Indi effectuates the discharge (a0) containing Chromium (r5), it will not cause inhibition of filamentous bacteria (s1), hence it does not provoke pin-point flocs (g6) since an ion (a3) (e.g., ferrous) can be added to precipitate Chromium VI. As mentioned before, Arg3, Arg4 and Arg5 are instantiations of AS3,4,5 that introduce new facts, new information about the current situation or alternative/preventive actions, respectively. These may in turn warrant or cause some undesirable secondary effect(s). Consequently, associated with these arguments an important new CQ arises leading to Arg6 and Arg7 instances AS3,4,5_CQ1: Will the introduced factor cause some undesirable side effects? Arg6: If in current circumstances industry Indi effectuates the discharge (a0) containing Chromium VI (r5), the presence of specific active biomass (r6) can reduce its toxicity and prevent pin-point flocs (g6); however, the new form of chromium (Chromium III) will remain in the sludge. Arg7: If in current circumstances industry Indi effectuates the discharge (a0) containing Chromium VI (r5), the enhancement of chromium precipitation will prevent pin-point flocs (g6); however, the precipitate will remain in settled sludge, after being processed in the sludge line, making it unavailable for other uses, such as in agriculture (g10). In this fashion all possible lines of reasoning with regard to the discharge and its consequences can be effectively studied, if not questioned. Once the argument graph is constructed, the MA has to determine the winning arguments. In this example (see Fig. 6) we are going to consider the following: there is no evidence posed by any of the participant agents, that the stated Chromium VI load is safe, thus the line of reasoning on the left of the argument graph is discarded (no IA challenges the discharged load; this is depicted by a in Fig. 7). Therefore, the conflict between Arg4 and Arg6 needs to be resolved, i.e., whether the current state of the plant causes positive synergetic effects to mitigate the problem must be clarified (b1 or b2 in Fig. 7). A similar procedure should be started to resolve the conflict between Arg5 and Arg7 (c1 or c2 in Fig. 7). On the basis of the domain-consented

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Fig. 7. Graph of interacting arguments. Detail of reasoning lines w.r.t. Fig. 6. Within dashed squares the two possible final solutions of the particular reasoning line (b or c) is authorized. The double square frames the final evaluated reasoning line of the presented example.

knowledge (articulated in terms of R, A, S and G) and the reputation of the agents involved, different strengths can be given to each of the arguments in order to finally decide which is the winner and which course of action is safest for the actual WWTP performance. Accordingly, an expert operator of the WWTP (WTAO) stays with Arg4 since it reports the presence of a specific biomass that can reduce the most toxic form of chromium to a less unsafe form. However, as depicted in Fig. 5, in critical safety decisions WTAM have higher reputations and their arguments are ranked better than those of WTAO. So the reasoning line containing Arg5 (c of Fig. 7) is preferable. For this specific case, since the weight of the argument posed by the RCA (Arg7) is greater than the argument of WTAM defending Arg5, the discharge is considered unsafe. Although a mitigating action can avoid operational problems at the WWTP (e.g., sludge settling problems due to pin-point flocs), Arg7 attacks Arg5, finally supporting Arg2, and certifying the danger of the discharge given in the present conditions. From now, since the discharge proposed by the IA should be rejected due to the present circumstances, another course of action needs to be considered to manage the discharge (e.g., specific pretreatment at industry, storing the discharge – if storage tanks are available – until the system is in proper condition to hold the discharge, and/or any other possible action that could increase the argument graph for this specific problem). Moreover, since the action proposed by the IA, after being considered safe, is rejected, its reliability (in terms of reputation) will diminish. The aim of the overall system is to preserve the river water quality by allowing the agents to participate in the deliberation and to finally make the safest environmental decision. In a way, this is a Group Decision Support System that is based on an argumentation framework (Karacapilidis and Papadias, 2001).

wastewater make the management of industrial discharges both a challenge and a problem. Using timely and precise information to understand and make decisions about problems, and developing criteria for evaluating the possible solutions for each situation, is of special importance. We have presented the application of an agents’ deliberation framework based on argumentation to support decision-making processes. In particular, we are using the illustrated schema (see Fig. 2) to identify the ways in which evidence supports nonpolluting actions against the receiving media, with safety as the main goal of the decision-making process. The tool we present enables us to understand the problem focus on the undesirable side-effects, in order to prevent or mitigate them, easing the exploration of the current context and a possible set of actions, and thus articulating the problem beyond numerical thresholds (conflict resolution mechanisms, quantifiable metrics and algorithms have already been treated in previous contributions such as Tolchinsky et al., 2008; Fox et al., 2006). The argumentative approach in decision support systems to solve environmental problems is becoming more widespread and challenging other more traditional knowledge-based approaches. This paper proposes a different way to conceptualize the decision-making process, and offers a reliable way to understand the problems together with possible solutions (e.g., alternative actions). The use of answer set programming (ASP) – based on the work of Nieves et al. (2005) – is envisioned as the agent’s reasoning model. The pros and cons of applying such a reasoning framework are largely discussed in Aulinas (2009). As a result of this work, we offer some promising lines of future research

 Constructing an ontology to manage the knowledge related to

5. Conclusions and future work

 Industrial wastewater discharges represent a major concern for WWTP managers due to their potential impact on WWTP processes and the environment. The variability of possible industrial discharges, complex and often uncertain knowledge, and information related to activated sludge-based processes to treat



industry types, pollutants, polluting potential, etc. A clustering and categorization could be done to provide the basic knowledge to build the declarative rules and hence the arguments. Extending the argumentation framework to allow the development of plans of actions automatically (such as the ones achieved with the diagnosis phase). Performing an evaluation phase based on the execution of existing and well documented cases of discharges that could be used as gold standards.

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