Towards A New Decision Support System for Design, Management and Operation of Wastewater Treatment Plants for the Reduction of Greenhouse Gases Emission

The increasing attention paid to the environment has led to a reduction in the emissions from wastewater treatment plants (WWTPs). Moreover, the increasing interest in the greenhouse gas (GHG) emissions from WWTPs suggests that we reconsider the traditional tools used for designing and managing WWTPs. Indeed, nitrous oxide, carbon dioxide and methane can be emitted from wastewater treatment, significantly contributing to the greenhouse gas (GHG) footprint. The reduction of energy consumption as well as GHG emission are of particular concern for large WWTPs which treat the majority of wastewater in terms of both volume and pollution load. Nowadays, there is an increasing need to develop new tools that include additional performance indicators related to GHG emissions and energy consumption as well as traditional effluent quality parameters. Energy consumption, in fact, can be considered as an indirect source of GHGs. This paper presents the development of an ongoing research project aiming at setting-up an innovative mathematical model platform for the design and management of WWTPs. The final goal of the project by means of this platform is to minimize the environmental impact of WWTPs through their optimization in terms of energy consumptions and emissions, which can be regarded as discharged pollutants, sludge and GHGs

Fuzzy Logic and Neuro-Fuzzy Networks for Environmental Hazard Assessment

Pollution and management of the environment are serious problems which concern the entire planet; the main responsibility should be attributed to human activities that contribute significantly to damage the environment, leading to an imbalance of natural ecosystems. In recent years, numerous studies focused on the three environmental compartments: soil, water and air. The pollution of groundwater is a widespread problem. The causes of pollution are often linked to human activities, including waste disposal. Solid waste management has become an important environmental issue in industrialized countries. The most serious problems are related to solid waste disposal. Landfill is still the most used disposal technique but not the safest. In fact, even controlled landfills could easily incur in the breakdown of containment elements. This breakdown could cause contamination of aquifer that is environmental pollution. Such contamination can be mitigated by performing remediation and environmental restoration. The assessment of environmental pollution risk can be performed with different degrees of detail and precision. Various statistical and mathematical models can be used for a qualitative risk assessment. The planning of a program for environmental remediation and restoration can be supported by expeditious methodologies that allow to obtain a hierarchical classification of contaminated sites. The literature offers some expeditious and qualitative methods including fuzzy logic (Zadeh, 1965), neural networks and neuro-fuzzy networks, which are more objective methods. The three artificial intelligence systems differ among themselves in some respects: fuzzy inference system learns knowledge of data only through the fuzzy rules; neural network is able to learn knowledge of data using the weights of synaptic connections; neuro-fuzzy systems are able to learn knowledge of neural data with neural paradigm and represent it in the form of fuzzy rules. Fuzzy logic was founded in 1965 by Zadeh. The first applications date back to the nineties. They were mainly used to control industrial processes, household electrical appliances and means of transport. Later, this approach was used in several fields including the environment. In fact it could be used for assessing environmental risk related to contamination of groundwater. The fuzzy approach is advantageous because it allows a quick assessment of the risk, but is disadvantageous because of the increasing complexity in the definition of fuzzy rules along with the increasing of the number of parameters. In many situations, when the number of parameters are considered high in the analysis, application of these techniques is cumbersome and complex and could be used for neuro-fuzzy models. These models reduce the complexity because they use training data. The neuro-fuzzy model were supported by a sensitivity analysis in order to address the problem of subjectivity and uncertainty of model input data

MODELLING OF AEROBIC REACTORS FOR LANDFILL METHANE OXIDATION

Landfill gas is produced by anaerobic degradation of organic waste. Landfills are one of the principal anthropogenic sources of atmospheric methane, a strong greenhouse gas. At the present, abatement techniques of landfill biogas consist in the energy recovery for the production of electrical energy, when the percentage of methane is in the order of 40 - 50% v/v. In this case, the complete combustion and the subsequent functioning of the engine for the production of energy is ensured. For percentages of the order of 30% v/v, the extracted biogas is conveyed to a system of gas flare which ensures the complete thermal oxidation before entering into the atmosphere. In all cases of low production of landfill gas or low methane concentration (small landfills or landfills in the terminal phase of stabilization), the combustion of biogas is difficult. In such conditions the biogas produced is often directly emitted into the atmosphere. Technical specifications for the operation of gas flares indicate a minimum flow of 50 Nm3/h and a methane concentration of 30% v/v. A flow of this size is equivalent to an annual emission of approximately 3200 tons of CO2eq. It is however known that methane can be metabolized by specific CH4-reducing microorganisms. The aim of this work is the evaluation of the efficiency of an aerobic bioreactor for the oxidation of methane, through the application of a mathematical model representative of the biological oxidation process, by implementing a calculation algorithm. The developed mathematical model describes the evolution of the phenomenon of methane oxidation. It is able to evaluate the efficiency of the system under varying operating conditions with the aim of optimizing the performance of the "biofilter". Literature data have been used in order to build the model and to drawing up the equations that describe the process. Through the implementation of the model in the MATLAB software, good results on the performance of this system were obtained. The factors that mostly affect the efficiency of the process of methane oxidation and that actually regulate the entire process have been highlighted in this work. The results obtained from the mathematical model showed that the biofilter system is simple to implement and manage and allows the achievement of high efficiency of methane oxidation

Removal of diclofenac from aqueous solutions by adsorption on thermo‑plasma expanded graphite

The adsorption of diclofenac on thermo-plasma expanded graphite (a commercial product) from water solutions was investigated. The adsorbent material was characterized by SEM, TEM, BET, Raman and X-ray diffraction analyses. Typical diffractogram and Raman spectrum of graphitic material, dimension of 24.02 nm as crystallite dimension and a surface area of 47 m2 g−1 were obtained. The effect of pH on the adsorption capacity was evaluated in the range 1–7 and the adsorption mechanism was described by kinetic and isothermal studies. Pseudo-second order and Dubinin–Radushkevich models agreed with theoretical values of adsorption capacity (i.e. 400 and 433 mg g−1, respectively) and resulted to be the best fit for kinetics and isothermal experimental data. The thermodynamics of the process was evaluated by plotting the adsorption capacity/concentration ratio at the equilibrium as a function of different values of the multiplicative inverse of temperature. Moreover, the adsorbent regeneration was also investigated, comparing two different remediation techniques. Solvent washing performed with NaOH 0.2 M and thermo-treatment carried out by heating in an oven at 105 °C for 2 h and then at 200 °C for 4 h. The thermo-treatment was the best technique to regenerate the adsorbent, ensuring same performance after 4 cycles of use and regeneration

Hierarchical Classification of Groundwater Pollution Risk of Contaminated Sites Using Fuzzy Logic: A Case Study in the Basilicata Region (Italy)

Groundwater is an important source of water. Since the control and removal of pollution are expensive, it is essential to identify the possible sources of contamination and to correctly classify groundwater on the basis of its intrinsic and integrated vulnerability. In the last years, many fuzzy models have been developed. There is a lack, however, of studies concerning the application of fuzzy logic for the assessment of the susceptibility of groundwater quality to anthropogenic activities and comparing these methods with traditional methods. The fuzzy model described in this paper assesses the aquifer integrated environmental vulnerability connected to the presence of illegal dumpsites and allows us to hierarchically classify them within a hazard scale. The results allowed us to carry out a comparison of the proposed fuzzy method with a traditional method. The fuzzy method proved to be a useful and objective tool for environmental planning

A comparison between Swat and a distributed hydrologic and water quality model for the Camastra basin (Southern Italy)

Over the last twenty years, the contribution of diffuse sources to the surface waters pollution has increased, despite several decades of research on agricultural management practices to minimize water pollution. The main purpose of this research is to make a comparison between Swat and a distributed hydrologic rainfall-runoff model applied to the Camastra river basin. The hydrologic and water quality distributed model, based upon a spatial discretization of the territory into elementary square cells, schematises the main hydrological processes of degradation and transport of nutrients, performed on a control volume build on the single cell. For the evaluation of the local generation of surface, sub-surface and groundwater run-off has been used an evolution of the WetSpa (Yongbo and De Smedt, 2000) distributed hydrologic model, coupled with a procedure for the nitrogen alteration and transport assessment. Preprocessing and following visualization of outputs has been carried out using GIS software. The study area is the 350 km2 of the Camastra lake basin (Southern Italy). The water quality data used for the model calibration have been collected in a monitoring campaign performed by the ARPAB (Basilicata Region Environmental Protection Agency). Two simulations over the identical time period have been conducted in the same region by using the developed model and the SWAT model The comparison shows the difficult of SWAT to give good simulations of the stream flows and reservoirs balance, that make complicated the use of the SWAT model to modelling water balance and water quality in the study region

Fuzzy logic model development for groundwater pollution risk assessment

The following paper presents a methodology for a rapid and effective assessment of groundwater pollution risk connected with the presence of uncontrolled landfills. Moreover, this methodology supplies an environmental planning tool to define a groundwater risk hierarchy index in function of some intrinsic characteristics of landfills and territory, in which they are located. The risk assessment was carried out with a fuzzy model, which includes the groundwater vulnerability and the intrinsic hazard of landfills. In particular, for the assessment of groundwater vulnerability the GNDCI-CNR method was used. This method examines the different geological, hydrogeological and morphological characteristics of the territory. Whereas, the hazard of landfills was evaluated together with the risk of contamination of the aquifers in the fuzzy model, taking into account the different descriptor parameters of the landfills. In addition, the fuzzy model was combined with the sensitivity analysis in order to overcome the problem of subjectivity and uncertainty associated with both input data and fuzzy conceptual model