Towards integrated operation of membrane bioreactors : effects of aeration on biological and filtration performance

Two experimental studies evaluated the effect of aerobic and membrane aeration changes on sludge properties, biological nutrient removal and filtration processes in a pilot plant membrane bioreactor. The optimal operating conditions were found at an aerobic dissolved oxygen set-point (DO) of 0.5mgO2L-1 and a membrane specific aeration demand (SADm) of 1mh-1, where membrane aeration can be used for nitrification. Under these conditions, a total flow reduction of 42% was achieved (75% energy reduction) without compromising nutrient removal efficiencies, maintaining sludge characteristics and controlled filtration. Below these optimal operating conditions, the nutrient removal efficiency was reduced, increasing 20% for soluble microbial products, 14% for capillarity suction time and reducing a 15% for filterability. Below this DO set-point, fouling increased with a transmembrane pressure 75% higher. SADm below 1mh-1 doubled the values of transmembrane pressure, without recovery after achieving the initial conditions

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.

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

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

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

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

Brook Trout Removal as a Conservation Tool to Restore Eagle Lake Rainbow Trout

Nonnative brook trout Salvelinus fontinalis are abundant in Pine Creek and its main tributary, Bogard Spring Creek, California. These creeks historically provided the most spawning and rearing habitat for endemic Eagle Lake rainbow trout Oncorhynchus mykiss aquilarum. Three-pass electrofishing removal was conducted in 2007–2009 over the entire 2.8-km length of Bogard Spring Creek to determine whether brook trout removal was a feasible restoration tool and to document the life history characteristics of brook trout in a California meadow stream. After the first 2 years of removal, brook trout density and biomass were severely reduced from 15,803 to 1,192 fish/ha and from 277 to 31 kg/ha, respectively. Average removal efficiency was 92–97%, and most of the remaining fish were removed in the third year. The lack of a decrease in age-0 brook trout abundance between 2007 and 2008 after the removal of more than 4,000 adults in 2007 suggests compensatory reproduction of mature fish that survived and higher survival of age-0 fish. However, recruitment was greatly reduced after 2 years of removal and is likely to be even more depressed after the third year of removal assuming that immigration of fish from outside the creek continues to be minimal. Brook trout condition, growth, and fecundity indicated a stunted population at the start of the study, but all three features increased significantly every year, demonstrating compensatory effects. Although highly labor intensive, the use of electrofishing to eradicate brook trout may be feasible in Bogard Spring Creek and similar small streams if removal and monitoring are continued annually and if other control measures (e.g., construction of barriers) are implemented. Our evidence shows that if brook trout control measures continue and if only Eagle Lake rainbow trout are allowed access to the creek, then a self-sustaining population ofEagle Lake rainbow trout can become reestablished

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