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

Towards a Reduction of Greenhouse Gases: a New Decision Support System for Design, Management and Operation of Wastewater Treatment Plants

The increasing attention for the environment has led to reduce the emissions from wastewater treatment plants (WWTPs). Moreover, the increasing interest towards the greenhouse gas (GHG) emissions from WWTPs suggests to reconsider the traditional tools used for designing and managing WWTPs. Indeed, nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4) 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 a 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

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

Use of carbon materials for produced water treatment: a review on adsorption process and performance

The oil and gas production is identified by consuming a large amount of water and generating massive produced water. The produced water is either reinjected into the underground layers or released into the rivers and oceans that can cause severe damage to the environment due to toxic elements such as salts, oil and grease, and polyaromatic hydrocarbons. So produced water treatment and management can reduce the significant threats to the soil and water resources and solve the lack of water in different water-consuming sectors. During the last decades, adsorption methods, such as using expanded graphite and activated carbon materials, have attracted scientists’ attention because these adsorbents are cost-effective and practical. This study aimed to review expanded graphite’s synthesis, adsorption process, and efficient factors in removing heavy oil, heavy metals, benzene, toluene, ethylbenzene, and xylenes, and organic acids from produced water and compare with other adsorbents, including activated carbon and residual biomass. Based on the results of extensive research works, expanded graphite’s high adsorption feature suggested that graphite can be a promising adsorbent in actual produced water treatment

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

Towards a new protocol for field measurements of greenhouse gases from wastewater treatment plant

Emissions into the atmosphere of greenhouse gases (GHGs), i.e., carbon dioxide, methane and nitrous oxide from wastewater treatment plants are of increasing concern in the water industry. In order to produce useful and comparable information for monitoring, assessing and reporting GHG emissions from wastewater treatment plants, there is a crescent need for a general accepted methodology. This paper aims at proposing the first protocol for monitoring and accounting GHG emissions from wastewater treatment plants taking into account both direct and internal indirect emissions focusing on sections known to be major responsible of GHG emissions i.e. oxidation tanks and sludge digestion. The main novelties of the proposed protocol are: (i) direct and indirect internal emissions ascribed to aeration devices which are related each other, (ii) the monitoring of biogas composition in case of anaerobic digestion which affects GHG emissions offset due to biogas valorization systems and (iii) monitoring of non-aerated tanks

A mobile black soldier fly farm for on-site disposal of animal dairy manure

Black soldier fly (BSF), Hermetia illucens (L.) (Diptera Stratiomyidae), is a saprophagous insect that is receiving a growing scientific and economic interest since during the larval stage it is extremely voracious and able to consume a wide range of organic materials. This ethological characteristic is particularly suitable for waste management at industrial scale. The extraordinary ability to accumulate high levels of proteins and lipids, allows the use of resulting larvae as animal feed or biodiesel production; the residue of the bioconversion process, that consists of larval frass and not converted organic matter is assimilable to organic fertilizer. The aim of this study was to evaluate the bioconversion process by black soldier fly larvae (BSFL) on fresh and mature dairy manure. A “mobile bioconversion unit” that works as a mobile breeding unit was used, allowing to carry out bioconversion tests directly on fields, in different livestock farms located on the Basilicata territory (Italy). Total larval and frass biomass, bioconversion yield, BSFL development time and substrate reduction were evaluated for each treatment. All the analysed parameters differed from the control (larvae fed in standard diet) but not between the two substrates from the zootechnical chain. Although development time significantly differed across treatments, BSF correctly grow and reduce all substrates confirming larvae can be used to bioconvert animal manure reducing the undesired effects occurring from mismanaged this kind of substrate

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

Towards a reduction of greenhouse gas emission from wastewater treatment plants: a new plant wide experimental and modelling approach

The increasing interest in greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) has led to the development of new tools for their design and management. Studies about gas emissions show that the sewer collection and the wastewater treatment plant are anthropogenic GHG potential sources, so they contribute to the climate change and air pollution. A wastewater treatment plant receives wastewater from sewers and, while produces treated water for discharge into surface water, emits the three major greenhouse gases, CO2, CH4, and N2O, during the treatment processes, and additional amounts of CO2 and CH4 from the energy demands (Bani Shahabadi et al., 2009). Indeed, energy consumption can be considered as an indirect source of GHGs. Greenhouse-gas emissions are generated by water-line and sludge- line processes and by the on-site combustion of biogas and fossil fuels for energy generation. GHGs may also be produced during sludge disposal or reuse (transportation and degradation of remaining biosolids off-site), off-site energy production and off-site chemicals production. In recent years, increasing attention is given to the assessment of N2O emissions from WWTPs. N2O is a powerful greenhouse gas that is almost 300 times stronger than CO2. Nevertheless, the source and magnitude of N2O are relatively unknown and the knowledge is still incomplete. This paper presents the first results of an ongoing research project aiming at setting-up an innovative mathematical model platform (Decision Support System—DSS) for the design and management of WWTPs. The project is constituted by four research units (UOs) and its final goal is to minimize, by means of this platform, the environmental impact of WWTPs through their optimization in terms of energy consumptions and pollutants, sludge and GHG emissions