Global sensitivity analysis for micropollutant modeling by means of an urban integrated approach

The paper presents the sensitivity analysis of an integrated urban water quality system by means of the global sensitivity analysis (GSA). Specifically, an home-made integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole - SMX). The model is able to estimate also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and the receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Five scenarios each characterized by different combinations of sub-systems (i.e., SS, WWTP and RWB) have been considered applying the Extended-FAST method. Results demonstrated that GSA is a powerful tool for increasing operator confidence in the modelling results; the approach can be used for blocking some non-identifiable parameters thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling

Sensitivity and uncertainty analysis of an integrated membrane bioreactor model

Sensitivity and uncertainty analysis, although can be of primarily importance in mathematical modelling approaches, are scarcely applied in the field of membrane bioreactor (MBR). An integrated mathematical model for MBR is applied with the final aim to pin down sources of uncertainty in MBR modelling. The uncertainty analysis has been performed combining global sensitivity analysis (GSA) with the generalized likelihood uncertainty estimation (GLUE). The model and methodology were applied to a University Cape Town pilot plant. Results show that the complexity of the modelled processes and the propagation effect from the influent to the effluent increase the uncertainty of the model prediction. It was found that the uncertainty of nitrogen and phosphorus model outputs increases from the first reactor-section plant to the last. Results show also that the GSA-GLUE methodology is a valid tool for uncertainty assessment for MBR modelling. Furthermore, the GSA-GLUE allows to identify the most critical processes/plant sections and the key sources of uncertainty where attention should be paid in view of model predictions improvement

A mathematical model for a sequential batch membrane bioreactor pilot plant

A mathematical model to quantify the nitrogen removal for a membrane bioreactor (MBR) has been presented in this study. The model has been applied to a pilot plant having a pre-denitrification MBR scheme. The pilot plant was cyclically filled with real saline wastewater according to the fill-draw-batch operation. The model was calibrated by adopting a specific protocol based on extensive field dataset. The Standardized Regression Coefficient (SRC) method was adopted to select the most influential model factors to be calibrated. Results related to the SRC method have shown that model factors of the efficiency of backwashing and the biological factors affecting the soluble microbial products (utilization-associated products) (namely, fUAP and KH,UAP) strongly affects the membrane resistance. In terms of model calibration excellent results in terms of model efficiency were found for the total membrane resistance model output (efficiency equal to 0.79). Regarding the biological model outputs acceptable were found in the case an high number of measured data was available. In terms of uncertainty, it was found that for the great part of the analyzed model outputs the measured data lay inside the uncertainty bands

Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods

Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important (factor prioritisation) and non-influential (factor fixing) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality-quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiarities, applicability, and reliability of the three methods is presented. Moreover, a graphical Venn diagram based classification scheme and a precise terminology for better identifying important, interacting and non-influential factors for each method is proposed. In terms of convergence, it was shown that sensitivity indices related to factors of the quantity model achieve convergence faster. Results for the Morris screening method deviated considerably from the other methods. Factors related to the quality model require a much higher number of simulations than the number suggested in literature for achieving convergence with this method. In fact, the results have shown that the term "screening" is improperly used as the method may exclude important factors from further analysis. Moreover, for the presented application the convergence analysis shows more stable sensitivity coefficients for the Extended-FAST method compared to SRC and Morris screening. Substantial agreement in terms of factor fixing was found between the Morris screening and Extended FAST methods. In general, the water quality related factors exhibited more important interactions than factors related to water quantity. Furthermore, in contrast to water quantity model outputs, water quality model outputs were found to be characterised by high non-linearity

Removal of carbon and nutrients from wastewater in a moving bed membrane biofilm reactor: the influence of the sludge retention time

A University of Cape Town (UCT) pilot plant combining both membrane bioreactor (MBR) and moving bed biofilm reactor (MBBR) technology was monitored. Three experimental Phases were carried out by varying the mixed liquor sludge retention time (SRT) (indefinite, 30 and 15 days, respectively). The system performance has been investigated during experiments in terms of: organic carbon, nitrogen and phosphorus removal, biokinetic/stoichiometric constants, membrane fouling tendency and sludge dewaterability. The observed results showed that by decreasing the SRT the UCT pilot plant was able to maintain very high total COD removal efficiencies, whilst the biological COD removal efficiency showed a slight decrease. Nitrification was only slightly affected by the decrease of the mixed liquor SRT, showing high performance (as average). This result could be related to the presence of the biofilm able to sustain nitrification throughout experiments. Conversely, the average P removal efficiency was quite moderate, likely due to the increase of the ammonium loading rate that could promote an increased NO3-N recycled from the anoxic to the anaerobic tank, interfering with phosphorus accumulating organisms (PAOs) activity inside the anaerobic tank. Membrane fouling increased at 30 days SRT likely due to a reduction of protective cake pre-filter effect. Moreover, it was noticed the increase of the resistance due to pore blocking and a general worsening of the membrane filtration properties

Interlinkages between operational conditions and direct and indirect greenhouse gas emissions in a moving bed membrane biofilm reactor

Nitrous oxide (N2O) can be emitted during wastewater treatment contributing to the global warming due to its high global warming potential,. During the last ten years, several efforts have been provided to improve knowledge on: key mechanisms, operating factors and influent features affecting the N2O production/emission. However, the knowledge on the investigated issues is not completely mature. Indeed, in terms of mathematical modelling, literature shows that a reliable model has not yet been established due to the huge data set required and the complexity of the mechanistic models indicated as the most accurate. In this work, the first attempt to perform a multiregression analysis is presented with the final aim to get a simple and easy tool for N2O estimation from wastewater treatment plant. The multiregression analysis has been performed by testing both simple and complex equations by means of Monte Carlo simulations. Data acquired from an University Cape Town moving bed membrane bioreactor pilot plant have been adopted. The pilot plant has been operated at different sludge retention times. Results of the simple linear regression analysis show that such approaches are suitable to predict N2O flux emitted from each tank of the plant and dissolved in the permeate. For some tested cases, a high efficiency (obtained comparing simulated and measured data) was obtained (e.g., 0.96 for N2O-N dissolved in the effluent). The results show that the dependence with the available measured data changes with the operational conditions. Conversely, results related to the complex multiregression analysis reveal that no unique equation valid for different operational conditions can be established

Destino dei radionuclidi negli impianti di depurazione delle acque reflue urbane

Lo studio presentato in questo lavoro ha avuto come obiettivo il monitoraggio e l’analisi del destino dei radionuclidi negli impianti di depurazione ed è stato condotto in collaborazione tra l’Università di Palermo e ARPA Sicilia. Esso ha previsto lo svolgimento di due fasi sperimentali. Nel corso della prima sono stati monitorati gli impianti di depurazione a servizio dei Comuni di Palermo (in località Acqua dei Corsari e Fondo Verde), Bagheria e Cefalù; nella seconda fase l’indagine è stata limitata al solo impianto di Acqua dei Corsari, nel quale si erano riscontrati in precedenza i maggiori spunti di interesse. In entrambe le fasi sono stati prelevati campioni istantanei in diverse sezioni degli impianti oggetto del monitoraggio: influente, vasca a fanghi attivi, ricircolo di fango, effluente del sedimentatore secondario e fango disidratato. I campioni sono stati analizzati con l’obiettivo di determinare l’attività dei principali radioisotopi di origine antropica, per via del loro uso medicale, o presenti nell’ambiente. L’identificazione e la quantificazione dell’attività dei radioisotopi nei campioni prelevati sono state condotte mediante tecniche di spettrometria gamma, utilizzando le strumentazioni disponibili presso l’Università di Palermo e il Laboratorio di radioattività della Struttura Territoriale di Palermo di ARPA Sicilia. Le attività dei radionuclidi rilevate nei vari punti di campionamento sono state utilizzate per la valutazione del rischio radiologico dei lavoratori e verificare il rispetto dei limiti di esposizione. I risultati ottenuti hanno generalmente evidenziato che il radiosotopo maggiormente presente nei campioni analizzati è risultato lo 131I, verosimilmente a causa del suo elevato tempo di dimezzamento. Inoltre è stata riscontrata una maggiore affinità dei radionuclidi nei confronti della componente solida presente nelle acque reflue, circostanza questa che comporta il loro progressivo trasferimento nei fanghi di depurazione, con particolare riferimento, per lo 131I alla frazione organica in essi presente. Tuttavia le attività di 131I rilevate nei fanghi depurazione sono risultate inferiori ai valori limite imposti dalla normativa vigente (D.Lgs. 230/95, D.Lgs. 241/00), per il loro smaltimento

Carbon and nutrient biological removal in a University of Cape Town membrane bioreactor: Analysis of a pilot plant operated under two different C/N ratios

The effect of the carbon-to-nitrogen (C/N) ratio variation in a University of Cape Town Membrane bioreactor (UCT-MBR) was investigated. The experimental campaign was divided into two phases, each characterized by a different C/N ratio (namely, 10 and 5, Phase I and Phase II, respectively). The UCT-MBR pilot plant was analysed in terms of carbon and nutrients removal, biomass respiratory activity, activated sludge features and membrane fouling. The results highlighted that the nutrients removal was significantly affected by the decrease of the C/N ratio during the Phase II. The biological carbon removal was also affected by the low C/N value during the Phase II. Indeed, the average biological COD removal efficiency was equal to 72.9% during the Phase II, while the average value was 82.8% in the Phase I. The respirometric batch test suggested that both heterotrophic and autotrophic species were severely affected by the lower C/N ratio in the Phase II. Moreover, a decrease of the membrane filtration properties was observed during the Phase II, mainly due to the worsening of the activated sludge features, which enhanced the increase of SMP production

Towards a conceptual mathematical tool linking physical and biological processes for a reduction of ghg emissions from an mb-mbr plant

The current study explores the influence of the air flow rate on greenhouse gas (GHG) emissions (direct and indirect), the operational costs (OCs), the effluent quality index (EQI) and effluent fines (EF). An University Cape Town (UCT) moving bed (MB) membrane bioreactor (MBR) pilot plant has been considered as case study where the influence of the air flow rate on the biological and physical processes has been analyzed. Constitutive relationships between the air flow rate and some performance indicators (i.e., EQI, OCs, direct and indirect GHG emissions) have been identified. Results showed that the EQI increases at low flow rate likely due to the dissolved oxygen (DO) limitation in the biological processes. Direct GHGs are influenced by air flow exponentially increasing with the increase of the air flow due to the anoxic N2O contribution. Irreversible membrane fouling reduce from 98% to 85% with the increasing of the air flow rate from 0.57 m3 h-1 to 2.56 m3 h- 1. However, the increase of the air flow rate leads to the increase of the N2O-N flux emitted from the MBR (from 40% to 80%). In order to establish a mathematical tool to reduce GHG emissions maintaining good effluent quality, results suggest of adopting a relationship based on a “multiple objective”

Nitrous oxide emission from a moving bed membrane biofilm reactor: the effect of the sludge retention time

The aim of the present study was to investigate the nitrous oxide (N2O) emissions from a University of Cape Town (UCT) moving bed membrane bioreactor pilot plant. An experimental campaign was carried out during 60 days with three different sludge retention time (SRT). The pilot plant reactor was provided of funnel shape covers that guaranteed gas accumulation in the headspace. The results highlighted that N2O concentrations significantly increased when the biofilm concentrations increased within the aerobic and anoxic compartments. Furthermore, results have shown an increase of N2O with the decrease of SRT. Moreover, the MBR tank resulted the key emission source (up to 70% of the total N2O emission during SRT=∞ period) whereas the highest N2O production occurred in the anoxic reactor. Moreover, N2O concentrations measured in the permeate flow were not negligible, thus highlighting its potential detrimental contribution for the receiving water body