Ribas, D.; Calderer, M.; Martí, V.; Johnsen, A.; Aamand, J.; Nilsson, B.; Jensen, J.; Engesgaard, P.; Morici, C. Environmental technology Vol. 38, num. 21, p. 2725-2732 DOI: 10.1080/09593330.2016.1276220 Data de publicació: 2017-01-01 Article en revista
This study aims to investigate the depth distribution of the Nitrate Reduction Potential (NRP) on a natural and a re-established wetland. The obtained NRP provides a valuable data of the driving factors affecting denitrification, the Dissimilatory Nitrate Reduction to Ammonium (DNRA) process and the performance of a re-established wetland. Intact soil cores were collected and divided in slices for the determination of Organic Matter (OM) through Loss of Ignition (LOI) as well as Dissolved Organic Carbon (DOC) and NRP spiking nitrate in batch tests. The Nitrate Reduction (NR) was fitted as a pseudo-first order rate constant (k) from where NRPs were obtained. NR took place in a narrow superficial zone showing a dropping natural logarithmic trend along depth. The main driving factor of denitrification, besides depth, was OM. Although, DOC and LOI could not express by themselves and absolute correlation with NRP, high amounts of DOC ensured enough quantity and quality of labile OM for NR. Besides, high concentration of LOI but a scarce abundance of DOC failed to drive NR. DNRA was only important in superficial samples with high contents of OM. Lastly, the high NRP of the re-established wetland confirms that wetlands can be restored satisfactorily.
A novel nanocomposite (NC) based on magnetite nanoparticles (Fe3O4-NPs) immobilized on the surface of a cationic exchange polymer, C100, using a modification of the co-precipitation method was developed to obtain magnetic NCs for phosphate removal and recovery from water. High-resolution transmission electron microscopy-energy-dispersive spectroscopy, scanning electron microscopy, X-ray diffraction, and inductively coupled plasma optical emission spectrometry were used to characterize the NCs. Continuous adsorption process by the so-called breakthrough curves was used to determine the adsorption capacity of the Fe3O4-based NC. The adsorption capacity conditions were studied under different conditions (pH, phosphate concentration, and concentration of nanoparticles). The optimum concentration of iron in the NC for phosphate removal was 23.59 mgFe/gNC. The sorption isotherms of this material were performed at pH 5 and 7. Taking into account the real application of this novel material in real water, the experiments were performed at pH 7, achieving an adsorption capacity higher than 4.9 mgPO4–P/gNC. Moreover, Freundlich, Langmuir, and a combination of them fit the experimental data and were used for interpreting the influence of pH on the sorption and the adsorption mechanism for this novel material. Furthermore, regeneration and reusability of the NC were tested, obtaining 97.5% recovery of phosphate for the first cycle, and at least seven cycles of adsorption–desorption were carried out with more than 40% of recovery. Thus, this work described a novel magnetic nanoadsorbent with properties for phosphate recovery in wastewater.
Athalathil, S.; Fortuny, A.; Font, J.; Stueber, F.; Bengoa, C.; Fabregat, A. Environmental technology Vol. 36, num. 20, p. 2568-2576 DOI: 10.1080/09593330.2015.1037361 Data de publicació: 2015-10-18 Article en revista
Two highly efficient (K2CO3/sludge carbon and ZnCl2/sludge carbon) solids were prepared by chemical addition following carbonization at 800 degrees C and were tested for anaerobic reduction of tartrazine dye in a continuous upflow packed-bed biological reactor, and their performance was compared to that of commercial activated carbon (CAC). The chemical and structural information of the solids was subjected to various characterizations in order to understand the mechanism for anaerobic decolorization, and efficiency for SBCZN800 and SBCPC800 materials was 87% and 74%, respectively, at a short space time () of 2.0min. A first-order kinetic model fitted the experimental points and kinetic constants of 0.40, 0.92 and 1.46min(-1) were obtained for SBCZN800, SBCPC800 and CAC, respectively. The experimental results revealed that performance of solids in the anaerobic reduction of tartrazine dye can depend on several factors including chemical agents, carbonization, microbial population, chemical groups and surface chemistry. The Langmuir and Freundlich models are successfully described in the batch adsorption data. Based on these observations, a cost-effective sludge-based catalyst can be produced from harmful sewage sludge for the treatment of industrial effluents.
This study focused on the advanced oxidation of the hetero bi-functional reactive dye Sumifix Supra Yellow 3RF (CI Reactive Yellow 145) using dark Fenton and photo-Fenton conditions in a lab-scale experiment. A 2(3) factorial design was used to evaluate the effects of the three key factors: temperature, Fe(II) and H2O2 concentrations, for a dye concentration of 250 mg L-1 with chemical oxygen demand (COD) of 172 mg L-1 O-2 at pH = 3. The response function was the COD reduction. This methodology lets us find the effects and interactions of the studied variables and their roles in the efficiency of the treatment process. In the optimization, the correlation coefficients for the model (R-2) were 0.948 and 0.965 for Fenton and photo-Fenton treatments, respectively. Under optimized reaction conditions: pH = 3, temperature = 298 K, [H2O2] = 11.765 mM and [Fe(II)] = 1.075 mM; 60 min of treatment resulted in a 79% and 92.2% decrease in COD, for the dye taken as the model organic compound, after Fenton and photo-Fenton treatments, respectively
The procedure commonly used for the assessment of the parameters included in activated sludge models (ASMs) relies on the estimation of their optimal value within a confidence region (i.e. frequentist inference). Once optimal values are estimated, parameter uncertainty is computed through the covariance matrix. However, alternative approaches based on the consideration of the model parameters as probability distributions (i.e. Bayesian inference), may be of interest. The aim of this work is to apply (and compare) both Bayesian and frequentist inference methods when assessing uncertainty for an ASM-type model, which considers intracellular storage and biomass growth, simultaneously. Practical identifiability was addressed exclusively considering respirometric profiles based on the oxygen uptake rate and with the aid of probabilistic global sensitivity analysis. Parameter uncertainty was thus estimated according to both the Bayesian and frequentist inferential procedures. Results were compared in order to evidence the strengths and weaknesses of both approaches. Since it was demonstrated that Bayesian inference could be reduced to a frequentist approach under particular hypotheses, the former can be considered as a more generalist methodology. Hence, the use of Bayesian inference is encouraged for tackling inferential issues in ASM environments.
Despite being acknowledged as an emerging contaminant, sulphamethazine (SMT) degradation has received scarce attention in the advanced oxidation processes field. Thus, this work addresses the degradation of SMT in water solutions (12L of 25mgL(-1) samples) by means of a photo-Fenton process and a systematic H2O2 dosage protocol that enhances its performance. A conventional photo-Fenton process led to 86% mineralization after 120min treatment when adding the Fenton reactants at once (initial concentrations were 10mgL(-1) Fe(II) and 200mgL(-1)H(2)O(2)). Conversely, the process achieved the total mineralization of the samples in less than 75min when the same amount of H2O2 was continuously dosed according to a conveniently tuned dosage protocol. In both cases, total SMT degradation was achieved within 10min. Hence, this work's aim is to determine the efficient dosage conditions of H2O2. The results show that a significant improvement of the photo-Fenton mineralization of SMT solutions is possible by adjusting the dosage of H2O2.
Calderer, M.; Gibert, O.; Martí, V.; Rovira, M.; De Pablo, J.; Jordana, S.; Guimera, J.; Bruno, J. Environmental technology Vol. 31, num. 7, p. 799-814 DOI: 10.1080/09593331003667741 Data de publicació: 2010 Article en revista
Corominas, L.; López, H.; Campos, E.; Balaguer, M.; Colprim, J.; Flotats, X.; Magrí, A. Environmental technology Vol. 28, num. 3, p. 255-265 DOI: 10.1080/09593332808618791 Data de publicació: 2007 Article en revista
Rodríguez-Roda, I.; Sànchez-Marrè, M.; Comas, J.; Cortes, U.; Poch, M. Environmental technology Vol. 22, num. 4, p. 477-486 DOI: 10.1080/09593332208618277 Data de publicació: 2001-04 Article en revista
The development of a case-based reasoning system for the supervision of an activated sludge process is presented here. The methodology proposed permits the use of past experiences to solve new problems that arise in the process. These experiences are classified as cases or situations. The adaptation of cases and the generation of new cases are used to tune the response of the system and to learn from the new information generated by the process. The case and the case library definition the initial seed, the search and retrieval process, the adaptation, the action, the evaluation and the learning steps are presented and outlined. The process studied is the wastewater treatment plant of Girona, Spain. Two examples of the response of the system to two different operational situations are presented. The paper also outlines the integration of different fields in a multidisciplinary approach as the most optimal solution to ensure the successful control and supervision of complex processes like the activated sludge process. With this aim the integration of an array of specific supervisory intelligent systems (for the logical analysis and reasoning) and numerical computations for detailed engineering is suggested.