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