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Two experimental campaigns were conducted to optimize the applicability of the Sediment Washing treatment on the marine sediments of Augusta Bay contaminated with heavy metals and total petroleum hydrocarbons (TPH). In the first campaign were used EDTA, citric acid, and acetic acid to removal only heavy metals (Ni, Cu, Zn, Cr, and Hg) from the sediments, while in the second campaign EDTA, citric acid, and EDDS were used to removal heavy metals (Ni, Cu, Cr, and Pb) and TPH. The tests were conducted at different pH values and contact times with 1:10 solid:liquid weight ratio. In the first experimental, at pH values 4, contact time 3 h, and citric acid, high removal efficiencies (78-82%) have been obtained for Ni, Cu, Zn, and Cr metals, while, in the second experimental campaign, at pH value 4, contact time 0.5 h, and citric acid, high removal efficiencies have been achieved especially for Pb and TPH. Finally, on the basis of the results obtained, a conceptual sediment washing treatment layout was proposed and the related costs estimated. [ABSTRACT FROM AUTHOR]

The objective of this paper is the definition of a methodology to evaluate the impact of the temporal resolution of rainfall measurements in urban drainage modelling applications. More specifically the effect of the temporal resolution on urban water quality modelling is detected analysing the uncertainty of the response of rainfall-runoff modelling. Analyses have been carried out using historical rainfall-discharge data collected for the Fossolo catchment (Bologna, Italy). According to the methodology, the historical rainfall data are taken as a reference, and resampled data have been obtained through a rescaling procedure with variable temporal windows. The shape comparison between 'true' and rescaled rainfall data has been carried out using a non-dimensional accuracy index. Monte Carlo simulations have been carried out applying a parsimonious urban water quality model, using the recorded data and the resampled events. The results of the simulations were used to derive the cumulative probabilities of quantity and quality model outputs (peak discharges, flow volume, peak concentrations and pollutant mass) conditioned on the observation according to the GLUE (Generalized Likelihood Uncertainty Estimation) methodology. The results showed that when coarser rainfall information is available, the model calibration process is still efficient even if modelling uncertainty progressively increases especially with regards to water quality aspects. [ABSTRACT FROM AUTHOR]

Over the last decade new technologies are emerging even more for wastewater treatment. Among the new technologies, a recent possible solution regards Moving Bed Biofilm Reactors (MBBRs) that represent an effective alternative to conventional processes. More specifically such systems consist in the introduction of plastic elements inside the aerobic reactor as carrier material for the growth of attached biomass. Recently, one of the mostly used alternatives is to couple the Moving Bed Biofilm Reactor (MBBR) process with the conventional activated sludge process, and the resulting process is usually called HMBBR (Hybrid MBBR). In the MBBR process the biofilm grows attached on small plastic elements that are kept in constant motion throughout the entire volume of the reactor. Indeed, in such a system, a competition between the two biomasses, suspended and attached, can arise for the availability of the substrates, leading, as a consequence, to a modification in the biokinetic parameters of the two biomasses, compared to that of a pure suspended or attached biomass process. This paper presents the first results of a study aimed at estimating the kinetic heterotrophic constants in a HMBBR pilot plant using respirometric techniques. The pilot plant was built at the Acqua dei Corsari (Palermo) wastewater treatment plant and consisted of two parallel lines realized in a pre-anoxic scheme, in one of which the carrier material was added to the aerobic reactor with a filling ratio of 30%. [ABSTRACT FROM AUTHOR]

In the past, emission standard indicators have been adopted by environmental regulation authorities in order to preserve the quality of a receiving water body. Such indicators are based on the frequency or magnitude of a polluted discharge that may be continuous or intermittent. In order to properly maintain the quality of receiving waters, the Water Framework Directive, following the basic ideas of British Urban Pollution Manual, has been established. The Directive has overtaken the emission-standard concept, substituting it with the stream-standard concept that fixes discharge limits for each polluting substance depending on the self-depurative characteristics of receiving waters. Stream-standard assessment requires the deployment of measurement campaigns that can be very expensive; furthermore, the measurement campaigns are usually not able to provide a link between the receiving water quality and the polluting sources. Therefore, it would be very useful to find a correlation between the quality status of the natural waters and the emission-based indicators. Thus, this study is aimed to finding a possible connection between the receiving water quality indicators drawn by environmental regulation authorities and emission-based indicators while considering both continuous (i.e. from the wastewater treatment plants) and intermittent pollution discharges (mainly from combined sewer overflows). Such research has been carried out by means of long-term analysis adopting a holistic modelling approach. The different parts of the integrated urban drainage system were modelled by a parsimonious integrated model. The analysis was applied to an ephemeral river bounding Bologna (Italy). The study concluded that the correlation between receiving water quality and polluting emissions cannot be generally stated. Nevertheless, specific analyses on polluting emissions were pointed out in the study highlighting cause-effect link between polluting sources and receiving water quality. [ABSTRACT FROM AUTHOR]

Summary: The evaluation of urban stormwater quality is of relevant importance for urban drainage, and mathematical models may be of great interest in this respect. To date, several detailed mathematical models are available to predict stormwater quantity–quality characteristics in urban drainage systems. However, only a few models take sewer sediments into account, considering their cohesive-like properties that influence the build-up process of the pollutant load. Furthermore, the model data requirements, especially for the quality aspects, are extensive, which limit their applicability and affect model results with large uncertainty. Uncertainty analysis provides a measure or index regarding the significance and the accuracy of the results obtained by mathematical modelling and is therefore of high interest. Nevertheless, only few studies have been carried out in the urban drainage field, and very few deal with water quality issues. One of the main reasons for this lack of research is the computational burden required by detailed models that preserve this analysis and generally require several Monte Carlo simulation runs. A possible to this problem may be the adoption of simplified parsimonious models that generally require shorter computational times. In this context, this paper presents a parsimonious conceptual model for the evaluation of the pollutant load in-sewers. The model contains two modules: a hydrological and hydraulic module that calculates the hydrographs at the inlet and at the outlet of the sewer system, and a solid transfer module that calculates the pollutographs. The cohesive properties of sewer sediments were carefully considered. Further, the effectiveness of the innovative sewer sediment modelling approach has been verified by taking into account the uncertainty assessed according to the GLUE methodology. The model has been tested using experimental quantity–quality data gathered in two Italian catchments, Fossolo (Bologna) and Parco d’Orlèans (Palermo). [Copyright &y& Elsevier]

The paper presents the comparison between the traditional activated sludge system (AS) and a hybrid moving bed biofilm reactor (HMBBR). In particular, an experimental campaign has been carried out at the WWTP in Palermo (Italy), on a pilot plant consisting of two pre-anoxic schemes. The aerated tank of the HMBBR line was filled with suspended carriers (AnoxKaldnes® K1), with a 30% filling ratio. The hydraulic load of the HMBBR line was increased up to two times the AS one. Further, in order to distinguish the additional contribution of the attached biomass for the HMBBR system, in the two lines the Mixed Liquor Suspended Solids (MLSS) was maintained as equal as possible. The monitoring period lasted three months during which several parameters were monitored. The obtained results showed a good treatment ability of the HMBBR system, referring to the organic matter removal as well as to the ammonium removal. In particular, in spite of the increase of the hydraulic load for the HMBBR line, the two systems showed a similar performance in terms of both organic and nitrogen removal. The results demonstrate the higher treatment capacity of the HMBBR addressing such system as an effective technology for the upgrading of overloaded wastewater treatment plants. [ABSTRACT FROM AUTHOR]

Water quality modelling is of crucial importance for the assessment of physical, chemical, and biological changes in water bodies. Mathematical approaches to water modelling have become more prevalent over recent years. Different model types ranging from detailed physical models to simplified conceptual models are available. Actually, a possible middle ground between detailed and simplified models may be parsimonious models that represent the simplest approach that fits the application. The appropriate modelling approach depends on the research goal as well as on data available for correct model application. When there is inadequate data, it is mandatory to focus on a simple river water quality model rather than detailed ones. The study presents a parsimonious river water quality model to evaluate the propagation of pollutants in natural rivers. The model is made up of two sub-models: a quantity one and a quality one. The model employs a river schematisation that considers different stretches according to the geometric characteristics and to the gradient of the river bed. Each stretch is represented with a conceptual model of a series of linear channels and reservoirs. The channels determine the delay in the pollution wave and the reservoirs cause its dispersion. To assess the river water quality, the model employs four state variables: DO, BOD, NH4, and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project in which quantity and quality data were gathered. A sensitivity analysis of the model output to the model input or parameters was done based on the Generalised Likelihood Uncertainty Estimation methodology. The results demonstrate the suitability of such a model as a tool for river water quality management. [ABSTRACT FROM AUTHOR]

In this study, diffuse and point source pollutant loads were evaluated using an Italian case study: the Nocella catchment, which has been subject to extensive monitoring. The Nocella catchment is located in Sicily (Italy) and has an area of about 60km2. The river receives wastewater and stormwater from two urban areas drained by combined sewers. The two sewer systems, two wastewater treatment plants and a river reach were monitored during both dry and wet weather periods. Thereafter, an integrated catchment-scale model was applied to simulate point pollutant sources, i.e., pollution coming from the urban drainage system, and nonpoint pollutant sources, i.e., pollution coming from agricultural and wildlife activities. Different models were combined and long-term simulations were carried out in order to reconstruct the total pollutant loads discharged into the receiving water body and identify the roles of the different pollutant sources. This study demonstrates the complexity of water quality assessment in partially urbanised natural basins where neither point nor nonpoint sources can be neglected. Point sources are mainly responsible for acute oxygen demanding polluting impact during wet weather periods, and both point and nonpoint sources are responsible for the impact of nutrients on the receiving water body. [ABSTRACT FROM AUTHOR]

Abstract: Methane (CH4) diffuse emissions from Municipal Solid Waste (MSW) landfills represent one of the most important anthropogenic sources of greenhouse gas. CH4 is produced by anaerobic biodegradation of organic matter in landfilled MSW and constitutes a major component of landfill gas (LFG). Gas recovery is a suitable method to effectively control CH4 emissions from landfill sites and the quantification of CH4 emissions represents a good tool to evaluate the effectiveness of a gas recovery system in reducing LFG emissions. In particular, LFG emissions can indirectly be evaluated from mass balance equations between LFG production, recovery and oxidation in the landfill, as well as by a direct approach based on LFG emission measurements from the landfill surface. However, up to now few direct measurements of landfill CH4 diffuse emissions have been reported in the technical literature. In the present study, both modeling and direct emission measuring methodologies have been applied to the case study of Bellolampo landfill located in Palermo, Italy. The main aim of the present study was to evaluate CH4 diffuse emissions, based on direct measurements carried out with the flux accumulation chamber (static, non-stationary) method, as well as to obtain the CH4 contoured flux map of the landfill. Such emissions were compared with the estimate achieved by means of CH4 mass balance equations. The results showed that the emissions obtained by applying the flux chamber method are in good agreement with the ones derived by the application of the mass balance equation, and that the evaluated contoured flux maps represent a reliable tool to locate areas with abnormal emissions in order to optimize the gas recovery system efficiency. [Copyright &y& Elsevier]

Abstract: A mathematical model for the simulation of physical-biological organic removal by means of a membrane bioreactor (MBR) has been previously developed and tested. This paper presents an analysis of the uncertainty of the MBR model. Particularly, the research explores the applicability of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology that is one of the most widely used methods for investigating the uncertainties in the hydrology and that now on is spreading in other research field. For the application of the GLUE methodology, several Monte Carlo simulations have been run varying the all model influential parameters simultaneously. The model was applied to an MBR pilot plant located at the Acqua dei Corsari WWTP (Palermo, IT) where water quality data were gathered. In particular, the MBR pilot plant consists of a lab-scale hollow fibre membrane module in submerged configuration. The GLUE methodology enabled us to gain useful insight about the robustness of the model approach. Particularly, the results showed that the biological process is influenced mainly by the parameters characterising the formation and degradation of Soluble Microbial Products, whereas the fouling phenomenon is mainly influenced by the backwashing efficiency. The application of the GLUE methodology shows that the model considered for the MBR simulation is somehow too simple in order to predict plants performances. Indeed, GLUE enabled us to identify the main model components that needs to be improved and where much attention has to be paid both in terms of model algorithms and quality data to be gathered. This studies confirmed the suitability of the GLUE methodology as a powerful tool for simplified screening methodology to assess the uncertainty also in the field of wastewater treatment. [ABSTRACT FROM AUTHOR]

Abstract: In urban water quality management, several models are connected and integrated for analysing the fate of pollutants from the sources in the urban catchment to the final recipient; classical problems connected with the selection and calibration of parameters are amplified by the complexity of the modelling approach increasing their uncertainty. The present paper aims at studying the influence of reductions in available data on the modelling response uncertainty with respect to the different integrated modelling outputs (both considering quantity and quality variables). At this scope, a parsimonious integrated home-made model has been used allowing for analysing the combinative effect of data availability regarding the different parts of the integrated urban drainage system; the uncertainty analysis approach has been applied to an experimental catchment in Bologna (Italy). The number of available data points has been fictitiously reduced obtaining data sets ranging between 25% and 100% of the actually measured data. For each of the data sets, uncertainty has been evaluated and its propagation from the upstream sub-model to the downstream ones has been assessed. The present study demonstrates that model calibration and modelling efficiency assessment may induce the operator to be excessively confident in the model results when available data are scarce. Quite the opposite is indeed true, that limited data availability increases modelling uncertainty. A conclusion of this article is that uncertainty analysis should always be conducted in order to effectively evaluate model reliability. [Copyright &y& Elsevier]

Urban stormwater quality modelling plays a central role in evaluation of the quality of the receiving water body. However, the complexity of the physical processes that must be simulated and the limited amount of data available for calibration may lead to high uncertainty in the model results. This study was conducted to assess modelling uncertainty associated with catchment surface pollution evaluation. Eight models were compared based on the results of a case study in which there was limited data available for calibration. Uncertainty analysis was then conducted using three different methods: the Bayesian Monte Carlo method, the GLUE pseudo-Bayesian method and the GLUE method revised by means of a formal distribution of residuals between the model and measured data (GLUE_f). The uncertainty assessment of the models enabled evaluation of the advantages and limitations of the three methodologies adopted. The models were then tested using the quantity–quality data gathered for the Fossolo catchment in Bologna, Italy. The results revealed that all of the models evaluated here provided good calibration results, even if the model reliability (in terms of related uncertainty) varied, which suggests the adoption of a specific modelling approach with respect to the others. Additionally, a comparison of uncertainty analysis approaches showed that, regarding the models evaluated here, the classical Bayesian method is more effective at discriminating models according to their uncertainty, but the GLUE approach performs similarly when it is based on the same founding assumptions as the Bayesian method. [Copyright &y& Elsevier]

Summary: Over the last few years, the use of mathematical models has gained importance in urban drainage system management; indeed, such models enable the combined analysis of different components that constitute a drainage system; the sewer system, wastewater treatment plant and the receiving water body. The effectiveness of an integrated approach has been widely demonstrated in the past and is presented in the EU Water Framework Directive, which also introduces a new point of view regarding the water quality management of the whole system, requiring a global analysis at the river basin scale for pollutant sources. However, integrated urban drainage models introduce several uncertain factors that are due to the high complexity level of the adopted approaches as well as to the lack of data for a robust model calibration. This paper presents the uncertainty assessment of an integrated urban drainage model developed in previous studies by means of the Generalized Likelihood Uncertainty Estimation methodology. The analysis has been applied to an experimental catchment in Bologna (Italy) which covers a part of the Bologna sewer network and a reach of the Savena River. [Copyright &y& Elsevier]

Abstract: In urban drainage, new computational possibilities have supported the development of new integrated approaches aimed at joint water quantity and quality analysis of the whole urban drainage system. Although the benefit of an integrated approach has been widely demonstrated, to date, several aspects prevent its applicability such as scarce availability of field data if compared with model complexity. These aspects sometimes prevent the correct estimation of parameters thus leading to large uncertainty in modelling response. This is a typical parameter identifiability problem that is discussed in the present paper evaluating the effect of identifiability procedures in increasing operator confidence in modelling results. The methodology presented has been applied to a home-made integrated urban drainage model that has been calibrated/validated considering field data collected in the Savena experimental catchment (Bologna, Italy). The results demonstrate the effectiveness of the identifiability analysis in obtaining a tool for urban integrated modelling applications and field data gathering campaigns. [Copyright &y& Elsevier]

Introduction: A wastewater-based epidemiology approach was performed to estimate the drug consumption in Palermo city, the fifth largest city of Italy with a population of 671 696 inhabitants, and to investigate the monthly variability of drug loads in wastewater from different areas of the city. A seven-months detection campaign was conducted at the two wastewater treatment plants of the city., Methods: Following a pre-treatment, 32 samples of wastewater were analyzed by liquid chromatography-tandem mass spectrometry., Results: We estimated a mean cocaine use in Palermo of 0.19 g/day/1000 people, corresponding to 1.90 doses/1000 people and cannabinoids use of 2.85 g/day/1000 people, corresponding to 35.62 doses/1000 people. Amphetamines residues in wastewater were always recovered in concentrations lower than the limit of quantification., Conclusion: Our findings showed that drugs consumption in Palermo is in line with those of other Italian cities and that no significant differences on prevalence on cocaine and cannabinoids consumption were recorded in the different months of the survey, except for the summer period in a wastewater treatment plant of the city.

Sanitary landfills for Municipal Solid Waste (MSW) disposal have been identified as one of the most important anthropogenic sources of methane (CH4) emissions; in order to minimize its negative effects on the environment, landfill gas (LFG) recovery is a suitable tool to control CH4 emissions from a landfill site; further, the measurement of CH4 emissions can represent a good way to evaluate the effectiveness of LFG recovering systems. In general, LFG will escape through any faults in the landfill capping or in the LFG collection system. Indeed, some areas of the capping can be more permeable than others (e.g. portions of a side slope), especially when considering a temporarily capped zone (covered area that is not expected to receive any further waste for a period of at least 3 months, but for engineering reasons does not have a permanent cap yet). These areas, which are characterized by abnormal emissions, are usually defined as "features": in particular, a feature is a small, discrete area or an installation where CH4 emissions significantly differ from the surrounding zones. In the present study, the influence that specific features have on CH4 emissions has been investigated, based on direct measurements carried out in different seasons by means of a flux chamber to the case study of Palermo (IT) landfill (Bellolampo). The results showed that the flux chamber method is reliable and easy to perform, and the contoured flux maps, obtained by processing the measured data were found to be a suitable tool for identifying areas with abnormal (high) emissions. Further, it was found that a relationship between methane emission rates and landfill side slope can be established. Concerning the influence of the temporary HDPE cover system on CH4 recovery efficiency, it contributed to a significant decrease of the free surface area available for uncontrolled emissions; this aspect, coupled to the increase of the CH4 volumes collected by the LFG recovery system, led to a significant increase of the recovery efficiency., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Numerical modelling can be a useful tool to assess a receiving water body's quality state. Indeed, the use of mathematical models in river water quality management has become a common practice to show the cause-effect relationship between emissions and water body quality and to design as well as assess the effectiveness of mitigation measures. In the present study, a hydrodynamic river water quality model is presented. The model consists of a quantity and a quality sub-model. The quantity sub-model is based on the Saint Venant equations. The solution of the Saint Venant equations is obtained by means of an explicit scheme based on space-time conservation. The method considers the unification of space and time and the enforcement of flux conservation in both space and time. On the other hand, the quality sub-model is based on the advection dispersion equation. Particularly, the principle of upstream weighting applied to finite difference methods is employed. This method enable us to reduce the numerical dispersion avoiding oscillation phenomena. The optimal weighting coefficient was calculated on the basis of the mesh Peclet number. Regarding the quality processes, the model takes into account the main physical/chemical processes; these are degradation of dissolved carbonaceous substances, ammonium oxidation, algal uptake and denitrification, dissolved oxygen balance, including depletion by degradation processes and supply by physical reaeration and photosynthetic production. To properly simulate the river water quality, four state variables were considered: DO, BOD, NH4, and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project for which quantity and quality data were gathered. A sensitivity analysis of the model output compared to the model input or parameters was carried out.