Ignasi Rodríguez-Roda

Designing and building real environmental decision support systems

The complexity of environmental problems makes necessary the development and application of new tools capable of processing not only numerical aspects, but also experience from experts and wide public participation, which are all needed in decision-making processes. Environmental decision support systems (EDSSs) are among the most promising approaches to confront this complexity. The fact that different tools (artificial intelligence techniques, statistical/numerical methods, geographical information systems, and environmental ontologies) can be integrated under different architectures confers EDSSs the ability to confront complex problems, and the capability to support learning and decision-making processes. In this paper, we present our experience, obtained over the last 10 years, in designing and building two real EDSSs, one for wastewater plant supervision, and one for the selection of wastewater treatment systems for communities with less than 2000 inhabitants. The flow diagram followed to build the EDSS is presented for each of the systems, together with a discussion of the tasks involved in each step (problem analysis, data collection and knowledge acquisition, model selection, model implementation, and EDSS validation). In addition, the architecture used is presented, showing how the five levels on which it is based (data gathering, diagnosis, decision support, plans, and actions) have been implemented. Finally, we present our opinion on the research issues that need to be addressed in order to improve the ability of EDSSs to cope with complexity in environmental problems (integration of data and knowledge, improvement of knowledge acquisition methods, new protocols to share and reuse knowledge, development of benchmarks, involvement of end-users), thus increasing our understanding of the environment and contributing to the sustainable development of society.  2003 Elsevier Ltd. All rights reserved.

Biological nutrient removal in an MBR treating municipal wastewater with special focus on biological phosphorus removal

The performance of an MBR pilot plant for biological nutrient removal was evaluated during 210days of operation. The set point values for the internal recycles were determined in advance with the use of an optimisation spreadsheet based on the ASM2d model to optimise the simultaneous removal of C, N and P. The biological nutrient removal (BNR) efficiencies were high from the start of operation with COD and N removal efficiencies of 92+/-6% and 89+/-7, respectively. During the course of the experiment P removal efficiencies increased and finally a P-removal efficiency of 92% was achieved. The activity of poly-phosphate accumulating organisms (PAOs) and denitrifying poly-phosphate accumulating organisms (DPAOs) increased and the specific phosphate accumulation rates after 150days of operation amounted to 13.6mgPg(-1)VSSh(-1) and 5.6mgPg(-1)VSSh(-1), for PAOs and DPAOs, respectively.

Comprehensive study of ibuprofen and its metabolites in activated sludge batch experiments and aquatic environment

Even though Ibuprofen is one of the most studied pharmaceutical in the aquatic environment, there is still a lack of information about its fate and the generation of different transformation products along wastewater treatment plants (WWTPs). Ibuprofen biotransformation products can be generated by human metabolism or by microorganisms present in WWTPs and in natural waters, soils, and sediments, which increase the probability to find them in environment. In this work, the presence of ibuprofen and its main metabolites: ibuprofen carboxylic acid (CBX IBU), 2-hydroxylated ibuprofen (2-OH IBU) and 1-hydroxylated ibuprofen (1-OH IBU), was monitored quantitatively along the biodegradation processes occurring in different batch activated sludge (BAS) experiments under different working conditions. Total ibuprofen removal, achieved in almost all the experiments, was related in part to the formation of the metabolites mentioned. Another ibuprofen metabolite, 1,2-dihydroxy ibuprofen, was detected in BAS experiments for the first time. The metabolites 2-OH IBU and 1-OH IBU remained in solution at the end of ibuprofen biodegradation experiments whereas CBX IBU disappeared faster than hydroxylated metabolites. In addition, also the biodegradation of 1-OH IBU, 2-OH IBU and CBX IBU was evaluated in batch experiments: CBX IBU removal occurred at the highest rate followed by IBU, 2-OH IBU, and 1-OH IBU, which exhibited the lowest removal rate. Finally, Ibuprofen and ibuprofen metabolites were monitored in sewage and natural water samples, where they were found at higher levels than expected: the maximum concentration in influent wastewater samples were 13.74, 5.8, 38.4, 94.0μg/L for IBU, 1-OH IBU, CBX IBU and 2-OH IBU respectively; whereas maximum levels in effluent wastewater samples were 1.9, 1.4, 10.7, 5.9 μg/L for IBU, 1-OH IBU, CBX IBU and 2-OH IBU respectively. High levels of the compounds were also found in river samples, in particular for CBX IBU, which was detected up to 3.9 μg/L.

Pharmaceuticals occurrence in a WWTP with significant industrial contribution and its input into the river system

Occurrence and removal of 81 representative Pharmaceutical Active Compounds (PhACs) were assessed in a municipal WWTP located in a highly industrialized area, with partial water reuse after UV tertiary treatment and discharge to a Mediterranean river. Water monitoring was performed in an integrated way at different points in the WWTP and river along three seasons. Consistent differences between therapeutic classes were observed in terms of influent concentration, removal efficiencies and seasonal variation. Conventional (primary and secondary) treatment was unable to completely remove numerous compounds and UV-based tertiary treatment played a complementary role for some of them. Industrial activity influence was highlighted in terms of PhACs presence and seasonal distribution. Even if global WWTP effluent impact on the studied river appeared to be minor, PhACs resulted widespread pollutants in river waters. Contamination can be particularly critical in summer in water scarcity areas, when water flow decreases considerably.

Multi-criteria evaluation of wastewater treatment plant control strategies under uncertainty

The evaluation of activated sludge control strategies in wastewater treatment plants (WWTP) via mathematical modelling is a complex activity because several objectives; e.g. economic, environmental, technical and legal; must be taken into account at the same time, i.e. the evaluation of the alternatives is a multi-criteria problem. Activated sludge models are not well characterized and some of the parameters can present uncertainty, e.g. the influent fractions arriving to the facility and the effect of either temperature or toxic compounds on the kinetic parameters, having a strong influence in the model predictions used during the evaluation of the alternatives and affecting the resulting rank of preferences. Using a simplified version of the IWA Benchmark Simulation Model No. 2 as a case study, this article shows the variations in the decision making when the uncertainty in activated sludge model (ASM) parameters is either included or not during the evaluation of WWTP control strategies. This paper comprises two main sections. Firstly, there is the evaluation of six WWTP control strategies using multi-criteria decision analysis setting the ASM parameters at their default value. In the following section, the uncertainty is introduced, i.e. input uncertainty, which is characterized by probability distribution functions based on the available process knowledge. Next, Monte Carlo simulations are run to propagate input through the model and affect the different outcomes. Thus (i) the variation in the overall degree of satisfaction of the control objectives for the generated WWTP control strategies is quantified, (ii) the contributions of environmental, legal, technical and economic objectives to the existing variance are identified and finally (iii) the influence of the relative importance of the control objectives during the selection of alternatives is analyzed. The results show that the control strategies with an external carbon source reduce the output uncertainty in the criteria used to quantify the degree of satisfaction of environmental, technical and legal objectives, but increasing the economical costs and their variability as a trade-off. Also, it is shown how a preliminary selected alternative with cascade ammonium controller becomes less desirable when input uncertainty is included, having simpler alternatives more chance of success.

Removal of microbial indicators from municipal wastewater by a membrane bioreactor (MBR).

The impact of removable and irremovable fouling on the retention of viral and bacterial indicators by the submerged microfiltration membrane in an MBR pilot plant was evaluated. Escherichia coli, sulphite-reducing Clostridium spores, somatic coliphages and F-specific RNA bacteriophages were used as indicators. The membrane demonstrated almost complete removal of E. coli and sulphite-reducing Clostridium spores. However, there was no correlation with membrane fouling. The phage removal varied in accordance with the irremovable fouling, rising from 2.6 to 5.6 log(10) units as the irremovable fouling increased (measured by the change in the transmembrane pressure). In contrast, removable fouling did not have any effect on the retention of viruses by the membrane. These results indicate that irremovable membrane fouling may affect the removal efficiency of MBRs and, therefore, their capacity to ensure the required microbiological standards for the permeate achieved.

Risk assessment modelling of microbiology-related solids separation problems in activated sludge systems

This paper proposes a risk assessment model for settling problems of microbiological origin in activated sludge systems (filamentous bulking, foaming and rising sludge). The aim of the model is not to diagnose microbiology-related solids separation problems with absolute certainty but to quantify in dynamic scenarios whether simulated operational procedures and control strategies lead to favourable conditions for them to arise or not. The rationale behind the model (which integrates the mechanisms of standard activated sludge models with empirical knowledge), its implementation in a fuzzy rule-based system and the details of its operation are illustrated in the different sections of the paper. The performance of the risk assessment model is illustrated by evaluating a number of control strategies facing different short-term influent conditions as well as long-term variability using the IWA/COST simulation benchmark. The results demonstrate that some control strategies, although performing better regarding operating costs and effluent quality, induce a higher risk for solids separation problems. In view of these results, it is suggested to integrate empirical knowledge into mechanistic models to increase reliability and to allow assessment of potential side-effects when simulating complex processes.

A comparative study on the use of similarity measures in case-based reasoning to improve the classification of environmental system situations

The step of identifying to which class of operational situation belongs the current environmental system (ES) situation is a key element to build successful environmental decision support systems (EDSS). This diagnosis phase is especially difficult due to multiple features involved in most environmental systems. It is not an easy task for environmental managers to acquire, to integrate and to understand all the increasing amount of data obtained from an environmental process and to get meaningful knowledge from it. Thus, a deeper classification task in a EDSS needs a full integration of gathered data, including the use of statistics, pattern recognition, clustering techniques, similarity-based reasoning and other advanced information technology techniques. Consequently, it is necessary to use automatic knowledge acquisition and management methods to build consistent and robust decision support systems. Additionally, some environmental problems can only be solved by experts who use their own experience in the resolution of similar situations. This is the reason why many artificial intelligence (AI) techniques have been used in recent past years trying to solve these classification tasks. Integration of AI techniques in EDSS has led to more accurate and reliable EDSS. Case-based reasoning (CBR) is a good technique to solve new problems based on previous experience. Main assumption in CBR relies on the hypothesis that similar problems should have similar solutions. When working with labelled cases, the retrieval step in CBR cycle can be seen as a classification task. The new cases will be labelled (classified) with the label (class) of the most similar case retrieved from the case base. In environmental systems, these classes are operational situations. Thus, similarity measures are key elements in obtaining a reliable classification of new situations. This paper describes a comparative analysis of several commonly used similarity measures, and a study on its performance for classification tasks. In addition, it introduces L’Eixample distance, a new similarity measure for case retrieval. This measure has been tested with good accuracy results, which improve the performance of the classification task. The testing has been done using two environmental data sets and other data sets from the UCI Machine Learning Database Repository.  2003 Elsevier Ltd. All rights reserved.

Multiple-objective evaluation of wastewater treatment plant control alternatives

Besides the evaluation of the environmental issues, the correct assessment of wastewater treatment plants (WWTP) should take into account several objectives such as: economic e.g. operation costs; technical e.g. risk of suffering microbiology-related TSS separation problems; or legal e.g. accomplishment with the effluent standards in terms of the different pollution loads. For this reason, the main objective of this paper is to show the benefits of complementing the environmental assessment carried out by life cycle assessment with economical, technical and legal criteria. Using a preliminary version of the BSM2 as a case study, different combinations of controllers are implemented, simulated and evaluated. In the following step, the resulting multi-criteria matrix is mined using multivariate statistical techniques. The results showed that the presence of an external carbon source addition, the type of aeration system and the TSS controller are the key elements creating the differences amongst the alternatives. Also, it was possible to characterize the different control strategies according to a set of aggregated criteria. Additionally, the existing synergies amongst different objectives and their consequent trade-offs were identified. Finally, it was discovered that from the initial extensive list of evaluation criteria, only a small set of five are really discriminant, being useful to differentiate within the generated alternatives.

Effects on activated sludge bacterial community exposed to sulfamethoxazole.

The bacterial community shift on a lab scale Sequencing Batch Reactor (SBR) fed with synthetic wastewater and exposed to 50μgL(-1) of sulfamethoxazole (SFX) for 2months was investigated in this study. The impact on biological nutrient removal performance and SFX removal efficiencies were also studied. Satisfactory biological nutrient removal was observed as regards to COD and Nitrogen. SFX removal efficiencies ranged between 20% and 50% throughout the experimental period, enhanced within the aerobic phases of the SBR cycle, with no evident signs of biomass acclimation. Nevertheless, denaturing gradient gel electrophoresis (DGGE) analysis showed significant variance leading to not only the fading, but also the emergence of new species in the bioreactor bacterial community after SFX dosage. According to the phylogenetic analysis, bacteria belonging to Betaproteobacteria and Gammaproteobacteria classes were the dominant species, among them, the Thiotrix spp. (Gammaproteobacteria) cell number increased due to its tolerance to the antibiotic. On the other hand, the classes Sphingobacteria, Actinobacteria, Chloroflexi and Chlorobi were found to be more vulnerable to the antibiotic load and disappeared. The sulphonamide resistance gene sulI was also quantified and discussed, as there are very few studies on bacterial resistance in lab-scale treatment reactors.