Biochars intended for water filtration: A comparative study with activated carbons of their physicochemical properties and removal efficiency towards neutral and anionic organic pollutants.

Seven biochars (BCs) obtained from pyrolysis or gasification of different vegetal feedstocks were thoroughly characterized in comparison with three commercial activated carbons (ACs) routinely used in drinking water treatment plants. BCs and ACs characterization included the determinations of ash, iodine and methylene blue adsorption indexes, and the release of metals and polycyclic aromatic hydrocarbons, which were performed according to international standards applied for adsorption media to be used in drinking waters. Total specific surface area, micropore and mesopore specific surface area, pH of the point of zero charge, and the release of polychlorinated biphenyls were also determined in all chars. Principal component analysis and cluster analysis were performed in order to summarize the complex set of information deriving from the aforementioned characterizations, highlighting the BC most similar (BC6 from high temperature gasification of woody biomass) and most different (BC7 from low-temperature pyrolysis of corn cob) from ACs. These BCs were studied for their adsorption in ultrapure water towards diiodoacetic acid (an emergent disinfection by-product), benzene, and 1.2-dichlorobenzene, in comparison with ACs, and results obtained were fitted by linearized Freundlich equation. Overall, BC6 showed higher sorption performances compared to BC7, even though both BCs were less performing sorbents than ACs. However, the sorption properties of BCs were maintained also in real water samples collected from drinking water treatment plants.

Application of unsupervised learning and process simulation for energy optimization of a WWTP under various weather conditions.

This paper outlines a hybrid modeling approach to facilitate weather-based operation and energy optimization for the largest Italian wastewater treatment plant (WWTP). Two clustering methods, K-means algorithm and Gaussian mixture model (GMM) based on the expectation-maximization (EM) algorithm, were applied to an extensive dataset of historical and meteorological records. This study addresses the problem of determining the intrinsic structure of clustered data when no information other than the observed values is available. Two quantitative indexes, namely the Bayesian information criterion (BIC) and the Silhouette coefficient using Euclidean distance, as well as two general criteria, were implemented to assess the clustering quality. Furthermore, seven weather-based influent scenarios were introduced to the process simulation model, and sets of aeration strategies are proposed. The results indicate that incorporating weather-based aeration strategies in the operation of the WWTP improves plant energy efficiency.

Energy optimization of a wastewater treatment plant based on energy audit data: small investment with high return.

Ambitious energy targets in the 2020 European climate and energy package have encouraged many stakeholders to explore and implement measures improving the energy efficiency of water and wastewater treatment facilities. Model-based process optimization can improve the energy efficiency of wastewater treatment plants (WWTP) with modest investment and a short payback period. However, such methods are not widely practiced due to the labor-intensive workload required for monitoring and data collection processes. This study offers a multi-step simulation-based methodology to evaluate and optimize the energy consumption of the largest Italian WWTP using limited, preliminary energy audit data. An integrated modeling platform linking wastewater treatment processes, energy demand, and production sub-models is developed. The model is calibrated using a stepwise procedure based on available data. Further, a scenario-based optimization approach is proposed to obtain the non-dominated and optimized performance of the WWTP. The results confirmed that up to 5000 MWh annual energy saving in addition to improved effluent quality could be achieved in the studied case through operational changes only.

Integrated model for estimating odor emissions from civil wastewater treatment plants.

The objective of this research project was the design and development of an integrated model for odor emission estimation in wastewater treatment plants. The SMAT's plant, the largest wastewater treatment facility in Italy, was used as a case study. This article reports the results of the characterization phase that led to the definition and design of the proposed conceptual model for odor emission estimation. In this phase, concentrations of odor chemical tracers (VOC, H2S, NH3) and odor concentrations were monitored repeatedly. VOC screening with GC-MS analysis was also performed. VOC concentrations showed significant variability in space and magnitude. NH3 and H2S were also detected at considerable concentrations. Results were elaborated to define a spatially variable linear relationship between the sum of odor activity values (SOAV) and odor concentrations. Based on the results, a conceptual operational model was presented and discussed. The proposed system is composed by a network of continuous measurement stations, a set of algorithms for data elaboration and synchronization, and emission dispersion modeling with the application of Lagrangian atmospheric models.

Optimization of the wastewater treatment plant: From energy saving to environmental impact mitigation.

This paper outlines a multi-objective, integrated approach to analyze various possibilities for increasing energy efficiency of the largest Italian wastewater treatment plant (WWTP) at Castiglione Torinese. In this approach, wastewater and sludge treatment units are thoroughly investigated to find the potential ways for improving the energy efficiency of the system. Firstly, a multi-step simulation-based methodology is proposed to make a full link between treatment processes and the energy demand and production. Further, a scenario-based optimization approach is proposed to find the nondominated and optimized performance of the WWTP. The results prove a potential to save up to 5000 MWh of the annual energy consumption of the plant, in addition to improve the effluent quality through operational changes only. Even for what concerns the sludge line a model was proposed for the optimization of the energy recovery from the processes that in a WWTP are devoted to the management of sewage sludge. The obtained results show that the introduction of an advanced thickening stage and sludge pre-treatment would have a positive impact on the energy and greenhouse gas balance of the plant.

Towards the revision of the drinking water directive 98/83/EC. Development of a direct injection ion chromatographic-tandem mass spectrometric method for the monitoring of fifteen common and emerging disinfection by-products along the drinking water supply chain.

According to the recent proposal released by the European Commission for the revision of the 98/83/EC Directive, water suppliers will be requested to monitor the nine bromine- and chlorine congeners of haloacetic acids, HAAs, as well as the oxyhalides chlorite and chlorate, as disinfection by-products (DBPs) originated during the potabilization process. In this work, we propose a direct-injection method based on ion chromatography and mass spectrometric detection for the determination of the mentioned DBPs as well as bromate (already included in the 98/83/EC), implemented also for the following emerging HAAs monoiodo-, chloroiodo- and diiodo-acetic acids. The method was optimized to include the fifteen compounds in the same analytical run, tuning the chromatographic (column and gradient) and detection conditions (suppression current, transitions, RF lens settings and collision energies). To avoid matrix effect and to manage the instrumental conditions, optimization was performed directly in drinking water matrix. The method quantitation limits satisfy the new limits imposed by the future directive and range from 0.08 µg/L (monobromoacetic acid) to 0.34 µg/L (trichloroacetic acid). The performance of the method was checked along different strategic sampling points of three potabilization plants serving the city of Turin (Italy), including intermediate treatments and finished waters. Recovery was checked according to the ±30% limit of acceptability set by EPA regulations. The effect of disproportionate concentrations of chlorite and chlorate in respect to HAAs on HAA signals was studied; this aspect is underestimated in literature. The method is routinely applied by the potabilization plant of the city of Turin to confirm the effectiveness of all control measures in abstraction, treatment, distribution and storage. This study represents the first example in Italy of development and use of a cutting-edge technique for HAAs analysis along the potabilization processes.

Assessment of weather-based influent scenarios for a WWTP: Application of a pattern recognition technique.

This study proposes an integrated approach by combining a pattern recognition technique and a process simulation model, to assess the impact of various climatic conditions on influent characteristics of the largest Italian wastewater treatment plant (WWTP) at Castiglione Torinese. Eight years (viz. 2009-2016) of historical influent data namely influent flow rate (Qin), chemical oxygen demand (COD), ammonium (N-NH4) and total suspended solids (TSS), in addition to two climatic attributes, average temperature and daily mean precipitation rates (PI) from the plant catchment area, are evaluated in this study. Following the outlier removal and missing-data imputation, five influent climate-based scenarios are identified by K-means clustering approach. Statistical characteristics of clustered observations are further investigated. Finally, to demonstrate that the proposed approach could improve the process control and efficiency, a process simulation model was developed and calibrated. Steady-state simulations were conducted, and the performance of the plant was studied under five influent scenarios. Further, an optimization scenario-based method was conducted to improve the energy consumption of the plant while meeting effluent requirements. The results indicate that with the adaptation of suitable aeration strategies for each of the influent scenarios, 10-40% energy saving can be achieved while meeting effluent requirements.

Effectiveness of a neutral electrolysed oxidising water (NEOW) device in reducing Legionella pneumophila in a water distribution system: A comparison between culture, qPCR and PMA-qPCR detection methods.

Disinfection of hot water systems is critical for reducing Legionnaires' disease in high-risk buildings. The use of neutral electrolysed oxidising water (NEOW) is a promising method for the control of microorganisms in hot water systems. However, full-scale evaluations of the efficacy of NEOW devices to control Legionella pneumophila are currently lacking. The aim of this study was to assess the effectiveness of a NEOW device in reducing L. pneumophila in a hotel water network. Water samples (n = 67) were collected from different sites of a hotel distribution system before and after the installation of the NEOW device at the 1st, 4th, 8th and 12th week. Detection of L. pneumophila was performed comparing culture, qPCR and PMA-qPCR methods. Total bacterial counts (22 °C and 37 °C), Pseudomonas spp. and physico-chemical parameters were also monitored. The NEOW treatment resulted in a reduction of the amount of L. pneumophila positive samples (-32%) and of the number of heavily contaminated points (>104 CFU/L and >103 CFU/L) (-100% and -96%, respectively). Treatment maintained L. pneumophila at low levels (<102 CFU/L), which do not require specific intervention measures. The effectiveness of the disinfection system was also confirmed by PMA-qPCR (p < 0.001). The use of PMA resulted in a signal decrease in almost all samples upon the disinfection treatment. The NEOW disinfection device appears to be a promising approach to reduce the colonisation of hot water systems by L. pneumophila; however, further investigations are needed to ascertain its efficiency over longer time periods.

Achieving low concentrations of chromium in drinking water by nanofiltration: membrane performance and selection.

This study evaluates nanofiltration as a feasible process to reach low concentrations of chromium in drinking water and provides means for the selection of the most suitable membrane based on the specific treatment needs. Chromium removal is concerning since new stringent limits (10 µg/L) for hexavalent Cr concentration in potable water were recently adopted in various countries. Three commercial nanofiltration membranes were tested against this threshold value: two membranes made of semi-aromatic polyamide and the third having a sulfonated polyethersulfone asymmetric film as the selective layer. The rejection observed as a function of chemical composition in the feed solution suggests that electrostatic effect is an important mechanism of chromium(VI) removal for the membranes with higher surface charge and lower film density. The performance of such membranes is strongly affected by the presence of salts, especially divalent cations, which reduce both Cr(VI) rejection and the permeate flux. The removal of Cr(VI) by denser membranes is dominated by solution-diffusion and is not influenced by feed ionic strength. The exposure of membranes to high chromium concentrations and to hypochlorite, typically employed as an oxidizing agent in water treatment plants, was also investigated. An analysis of the operational membrane life is thus discussed, based on the loss in performance due to active film degradation. All three membranes showed adequate rejection of chromium from tap and well water of diverse chemical composition, suggesting that nanofiltration is an effective process to remove chromium for the production of safe drinking water. However, membranes with different properties should be adopted depending on specific feed water composition and on the productivity required from the system. A final analysis is presented to help with the choice of the most suitable nanofiltration membrane based on initial and target Cr(VI) concentration in feed and product water, respectively.

Viability of Legionella pneumophila in Water Samples: A Comparison of Propidium Monoazide (PMA) Treatment on Membrane Filters and in Liquid.

Legionella pneumophila is a ubiquitous microorganism widely distributed in aquatic environments and can cause Legionellosis in humans. A promising approach to detect viable cells in water samples involves the use of quantitative polymerase chain reaction (qPCR) in combination with photoactivatable DNA intercalator propidium monoazide (PMA). However, the PMA efficiency could be different depending on the experimental conditions used. The aim of this study was to compare two PMA exposure protocols: (A) directly on the membrane filter or (B) in liquid after filter washing. The overall PMA-induced qPCR means reductions in heat-killed L. pneumophila cells were 2.42 and 1.91 log units for exposure protocols A and B, respectively. A comparison between the results obtained reveals that filter exposure allows a higher PMA-qPCR signal reduction to be reached, mainly at low concentrations (p < 0.05). This confirms the potential use of this method to quantify L. pneumophila in water with low contamination.