Anàlisi comparativa dels processos emergents sharon i anammox per al tractament d’aigües amb una alta càrrega de nitrogen

Estudi de tractaments innovadors en aigües residuals amb elevada concentració de nitrogen mitjançant la tecnologia ANAMMOX (Anaerobic Ammonium Oxidation) i SHARON i posterior anàlisi teòrica de la gestió dels fangs residuals d’una EDAR

Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelationbetween variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision

The activated sludge process - the main biological technology usually applied towastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take thenecessary actions to restore the system’s performance. These decisions are oftenbased both on physical, chemical, microbiological principles (suitable to bemodelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AIarchitecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs

The objective of this paper was to show the potential additional insight that result from adding greenhouse gas (GHG) emissions to plant performance evaluation criteria, such as effluent quality (EQI) and operational cost (OCI) indices, when evaluating (plant-wide) control/operational strategies in wastewater treatment plants (WWTPs). The proposed GHG evaluation is based on a set of comprehensive dynamic models that estimate the most significant potential on-site and off-site sources of CO2, CH4 and N2O. The study calculates and discusses the changes in EQI, OCI and the emission of GHGs as a consequence of varying the following four process variables: (i) the set point of aeration control in the activated sludge section; (ii) the removal efficiency of total suspended solids (TSS) in the primary clarifier; (iii) the temperature in the anaerobic digester; and (iv) the control of the flow of anaerobic digester supernatants coming from sludge treatment. Based upon the assumptions built into the model structures, simulation results highlight the potential undesirable effects of increased GHG production when carrying out local energy optimization of the aeration system in the activated sludge section and energy recovery from the AD. Although off-site CO2 emissions may decrease, the effect is counterbalanced by increased N2O emissions, especially since N2O has a 300-fold stronger greenhouse effect than CO2. The reported results emphasize the importance and usefulness of using multiple evaluation criteria to compare and evaluate (plant-wide) control strategies in a WWTP for more informed operational decision making

Determinació de compostos orgànics contaminants en aigües residuals industrials

La determinació de compostos orgànics contaminants en aigües residuals d’origen urbà i industrial és un tema que ha suscitat un creixent interès, tant des del punt de vista del problema mediambiental que es deriva de l’abocament d’aquestes aigües al medi aquàtic públic com des de la perspectiva de reutilització de les aigües tractades en processos industrials. La majoria d’aquests contaminants no s’eliminen completament en plantes de tractament d’aigües convencionals, pel que s’han de controlar. Aquest fet implica desenvolupar nous processos de tractament que permetin millorar l'eficiència de l'eliminació de les plantes de tractament convencionals. Per tal d'investigar la presència d'aquests compostos contaminants a baixes concentracions és necessari desenvolupar nous mètodes analítics altament sensibles. En el nostre projecte s'han desenvolupat diferents mètodes analítics per determinar compostos orgànics contaminants en aigües residuals provinents de plantes de tractament d'aigües industrials, urbanes i plantes potabilitzadores, utilizant principalment la microextracció en fase sòlida (SPME) seguida de la cromatografia de gasos acoblada a un espectròmetre de masses (GC-MS). S'ha estudiat la presència de diferents famílies de compostos en aquestes aigües, com són: ftalats, amines alifàtiques primàries i nitrosamines. A més a més, s'han desenvolupat mètodes analítics per determinar amines alifàtiques primàries en llots actius provinents de diferents tipus de plantes de tractament d'aigües i plantes potabilitzadores.

Assessment of microbial community structure changes by amplified ribosomal DNA restriction analysis (ARDRA)

Amplified ribosomal DNA restriction analysis (ARDRA) is a simple method based on restriction endonuclease digestion of the amplified bacterial 16S rDNA. In this study we have evaluated the suitability of this method to detect differences in activated sludge bacterial communities fed on domestic or industrial wastewater, and subject to different operational conditions. The ability of ARDRA to detect these differences has been tested in modified Ludzack-Ettinger (MLE) configurations. Samples from three activated sludge wastewater treatment plants (WWTPs) with the MLE configuration were collected for both oxic and anoxic reactors, and ARDRA patterns using double enzyme digestions AluI+MspI were obtained. A matrix of Dice similarity coefficients was calculated and used to compare these restriction patterns. Differences in the community structure due to influent characteristics and temperature could be observed, but not between the oxic and anoxic reactors of each of the three MLE configurations. Other possible applications of ARDRA for detecting and monitoring changes in activated sludge systems are also discussed

Comparison of a deterministic and a data driven model to describe MBR fouling

Membrane bioreactors (MBRs) are a combination of activated sludge bioreactors and membrane filtration, enabling high quality effluent with a small footprint. However, they can be beset by fouling, which causes an increase in transmembrane pressure (TMP). Modelling and simulation of changes in TMP could be useful to describe fouling through the identification of the most relevant operating conditions. Using experimental data from a MBR pilot plant operated for 462days, two different models were developed: a deterministic model using activated sludge model n°2d (ASM2d) for the biological component and a resistance in-series model for the filtration component as well as a data-driven model based on multivariable regressions. Once validated, these models were used to describe membrane fouling (as changes in TMP over time) under different operating conditions. The deterministic model performed better at higher temperatures (>20°C), constant operating conditions (DO set-point, membrane air-flow, pH and ORP), and high mixed liquor suspended solids (>6.9gL-1) and flux changes. At low pH (<7) or periods with higher pH changes, the data-driven model was more accurate. Changes in the DO set-point of the aerobic reactor that affected the TMP were also better described by the data-driven model. By combining the use of both models, a better description of fouling can be achieved under different operating conditions

Non conventional biological treatment based on Trametes versicolor for the elimination of recalcitrant anticancer drugs in hospital wastewater

This work presents a study about the elimination of anticancer drugs, a group of pollutants considered recalcitrant during conventional activated sludge wastewater treatment, using a biological treatment based on the fungus Trametes versicolor. A 10-L fluidized bed bioreactor inoculated with this fungus was set up in order to evaluate the removal of 10 selected anticancer drugs in real hospital wastewater. Almost all the tested anticancer drugs were completely removed from the wastewater at the end of the batch experiment (8 d) with the exception of Ifosfamide and Tamoxifen. These two recalcitrant compounds, together with Cyclophosphamide, were selected for further studies to test their degradability by T. versicolor under optimal growth conditions. Cyclophosphamide and Ifosfamide were inalterable during batch experiments both at high and low concentration, whereas Tamoxifen exhibited a decrease in its concentration along the treatment. Two positional isomers of a hydroxylated form of Tamoxifen were identified during this experiment using a high resolution mass spectrometry based on ultra-high performance chromatography coupled to an Orbitrap detector (LTQ-Velos Orbitrap). Finally the identified transformation products of Tamoxifen were monitored in the bioreactor run with real hospital wastewater

Macroautophagic process was differentially modulated by long-term moderate exercise in rat brain and peripheral tissues

The autophagic process is a lysosomal degradation pathway, which is activated during stress conditions, such as starvation or exercise. Regular exercise has beneficial effects on human health, including neuroprotection. However, the cellular mechanisms underlying these effects are incompletely understood. Endurance and a single bout of exercise induce autophagy not only in brain but also in peripheral tissues. However, little is known whether autophagy could be modulated in brain and peripheral tissues by long-term moderate exercise. Here, we examined the effects on macroautophagy process of long-term moderate treadmill training (36 weeks) in adult rats both in brain (hippocampus and cerebral cortex) and peripheral tissues (skeletal muscle, liver and heart). We assessed mTOR activation and the autophagic proteins Beclin 1, p62, LC3B (LC3B-II/LC3B-I ratio) and the lysosomal protein LAMP1, as well as the ubiquitinated proteins. Our results showed in the cortex of exercised rats an inactivation of mTOR, greater autophagy flux (increased LC3-II/LC3-I ratio and reduced p62) besides increased LAMP1. Related with these effects a reduction in the ubiquitinated proteins was observed. No significant changes in the autophagic pathway were found either in hippocampus or in skeletal and cardiac muscle by exercise. Only in the liver of exercised rats mTOR phosphorylation and p62 levels increased, which could be related with beneficial metabolic effects in this organ induced by exercise. Thus, our findings suggest that long-term moderate exercise induces autophagy specifically in the cortex

Macroautophagic process was differentially modulated by long-term moderate exercise in rat brain and peripheral tissues

The autophagic process is a lysosomal degradation pathway, which is activated during stress conditions, such as starvation or exercise. Regular exercise has beneficial effects on human health, including neuroprotection. However, the cellular mechanisms underlying these effects are incompletely understood. Endurance and a single bout of exercise induce autophagy not only in brain but also in peripheral tissues. However, little is known whether autophagy could be modulated in brain and peripheral tissues by long-term moderate exercise. Here, we examined the effects on macroautophagy process of long-term moderate treadmill training (36 weeks) in adult rats both in brain (hippocampus and cerebral cortex) and peripheral tissues (skeletal muscle, liver and heart). We assessed mTOR activation and the autophagic proteins Beclin 1, p62, LC3B (LC3B-II/LC3B-I ratio) and the lysosomal protein LAMP1, as well as the ubiquitinated proteins. Our results showed in the cortex of exercised rats an inactivation of mTOR, greater autophagy flux (increased LC3-II/LC3-I ratio and reduced p62) besides increased LAMP1. Related with these effects a reduction in the ubiquitinated proteins was observed. No significant changes in the autophagic pathway were found either in hippocampus or in skeletal and cardiac muscle by exercise. Only in the liver of exercised rats mTOR phosphorylation and p62 levels increased, which could be related with beneficial metabolic effects in this organ induced by exercise. Thus, our findings suggest that long-term moderate exercise induces autophagy specifically in the cortex

Does bounded rationality lead to individual heterogeneity? The impact of the experimentation process and of memory constraints

In this paper we explore the effect of bounded rationality on the convergence of individual behavior toward equilibrium. In the context of a Cournot game with a unique and symmetric Nash equilibrium, firms are modeled as adaptive economic agents through a genetic algorithm. Computational experiments show that (1) there is remarkable heterogeneity across identical but boundedly rational agents; (2) such individual heterogeneity is not simply a consequence of the random elements contained in the genetic algorithm; (3) the more rational agents are in terms of memory abilities and pre-play evaluation of strategies, the less heterogeneous they are in their actions. At the limit case of full rationality, the outcome converges to the standard result of uniform individual behavior.

Cooperative vs. non-cooperative mechanisms in the EU decision making process

According to the account of the European Union (EU) decision making proposed in this paper, this is a bargaining process during which actors shift their policy positions with a view to reaching agreements on controversial issues.

From creative ideas to new emerging ventures: the process of identification and exploitation among finnish design entrepreneurs

This study focuses on identification and exploitation processes among Finnish design entrepreneurs (i.e. selfemployed industrial designers). More specifically, this study strives to find out what design entrepreneurs do when they create new ventures, how venture ideas are identified and how entrepreneurial processes are organized to identify and exploit such venture ideas in the given industrial context. Indeed, what does educated and creative individuals do when they decide to create new ventures, where do the venture ideas originally come from, and moreover, how are venture ideas identified and developed into viable business concepts that are introduced on the markets? From an academic perspective: there is a need to increase our understanding of the interaction between the identification and exploitation of emerging ventures, in this and other empirical contexts. Rather than assuming that venture ideas are constant in time, this study examines how emerging ideas are adjusted to enable exploitation in dynamic market settings. It builds on the insights from previous entrepreneurship process research. The interpretations from the theoretical discussion build on the assumption that the subprocesses of identification and exploitation interact, and moreover, they are closely entwined with each other (e.g. McKelvie & Wiklund, 2004, Davidsson, 2005). This explanation challenges the common assumption that entrepreneurs would first identify venture ideas and then exploit them (e.g. Shane, 2003). The assumption is that exploitation influences identification, just as identification influences exploitation. Based on interviews with design entrepreneurs and external actors (e.g. potential customers, suppliers and collaborators), it appears as identification and exploitation of venture ideas are carried out in close interaction between a number of actors, rather than alone by entrepreneurs. Due to their available resources, design entrepreneurs have a desire to focus on identification related activities and to find external actors that take care of exploitation related activities. The involvement of external actors may have a direct impact on decisionmaking and various activities along the processes of identification and exploitation, which is something that previous research does not particularly emphasize. For instance, Bhave (1994) suggests both operative and strategic feedback from the market, but does not explain how external parties are actually involved in the decisionmaking, and in carrying out various activities along the entrepreneurial process.