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.

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

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

Dewaterability of sewage sludge by ultrasonic, thermal and chemical treatments

Sludges resulting from wastewater treatment processes have a characteristically high water content, which complicates handling operations such as pumping, transport and disposal. To enhance the dewatering of secondary sludge, the effect of ultrasound waves, thermal treatment and chemical conditioning with NaOH have been studied. Two features of treated sludges were examined: their rheological behavior and their dewaterability. The rheological tests consisted of recording shear stress when the shear rate increases and decreases continuously and linearly with time, and when it increases and decreases in steps. Steady-state viscosity and thixotropy were obtained from the rheological tests, and both decreased significantly in all cases with increased treatment intensity. Centrifugation of ultrasonicated and thermally treated sludges allowed the total solid content to be increased by approximately 16.2% and 17.6%, respectively. These dewatered sludges had a lower viscosity and thixotropy than the untreated sludge. In contrast, alkali conditioning barely allowed the sludge to be dewatered by centrifugation, despite decreasing its viscosity and thixotropy.

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

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