Pesticides are an integral part of modern agriculture in most countries as a tool for controlling pests. In the last few decades, increasing use of pesticides is polluting environment and water resources day by day. Adsorption is one of the most used method for removal of these pollutions due to the simple ease of processing, low cost and effective even in very low concentrations. Active carbon is very efficient adsorbent for removing pesticides from aqueous solutions thanks to its high surface area and porosity. However, the high cost of active carbon can be sometimes restricted for several purposes. In recent years, research on the production of low cost adsorbents alternative to commercially available activated carbon has increased. Therefore, in this work, peanut shells were used as an adsorbent for removing 2,4-dichlorophenoxyacetic acid (2,4-D) from aqueous solutions. The adsorption performance was studied depending on initial concentrations of 2,4-D solutions.

Bioreactor landfills (BRLs) aim to increase moisture content of municipal solid waste to enhance the biodegradation kinetics of the organic fraction and biogas production. Prediction of biogas production is a key tool to design an appropriate energy recovery system from BRLs. In this paper, a fuzzy-based model to predict methane generation in full scale BRLs is proposed. Eleven deterministic inputs (pH, RedOx potential, chemical oxygen demand, volatile fatty acids, ammonium content, age of the waste, temperature, moisture content, organic fraction concentration, particle size and recirculation flow rate) were identified as antecedent variables. Two outputs, or consequents, were chosen: methane production rate and methane fraction in the biogas. Antecedents and consequents were transported in the fuzzy domain by a fuzzyfication procedure and then linked by 84 IF-THEN rules, which stated the effects of the input parameters in a linguistic form. The fuzzy model was built and tested on seven lab-scale studies, representing different operational conditions and waste qualities. The fuzzy model showed good performances in the prediction of methane generation, although lab-scale studies depicted ideal conditions that can be hardly reached in real BRLs. In order to deal with higher heterogeneities and lower data availability typical of full-scale landfills, new antecedents and rules were added to the proposed model. With few adjustments based on the available information, the fuzzy model could be applied to a retrofit BRLs located in Northern Italy. The results confirmed that fuzzy macro-approach can be a powerful and flexible tool able to model the complex processes taking place in BRLs.

Electronic waste or e-waste is the waste generated from discarded and end of life electronic items. In recent times with change in lifestyle and improved purchasing capacity of people has accelerated the demand of new and improved electronic items, quick technology obsolescence, as a consequence the generation of e-waste has seen a huge rise. In year 2016, globally 93.5 tons of E-waste was generated, India, one of the leading producers of e-waste, produced 1.65 Million tones of E-waste. Apart from domestic generation, a huge chunk of global e-waste was also dumped in India. 90 % of the e-waste is handled and managed by the unorganized sector. Hence there is a dire need to develop a mechanism to handle the enormous flux of e-waste in India. In this paper the e-waste sector has been reviewed. Also a detailed analysis of the material flow in the e-waste sector has been done. Results reveal that if mismanaged, e-waste can impose huge environmental penalty, however if it is regulated and handled scientifically it can become an asset for resource recovery whose carbon footprint is 70-80 % lower than its primary production

In the last decade has seen a reduction in the quantities of fossil raw materials for the production of conventional fuels, which in turn is accompanied by deepening environmental problems. There is a tendency to increase production of biofuels and increasing quantities of waste produced. They are classified as productive (technological) and operational (for utilization of biofuels and their values). This research work focuses on creating tools for supply chains (SC), describing the optimal management of production and operational waste. Developed are tools that includes a mathematical model and its optimization for production and use of biofuels on the following criteria: production technology, spatial distribution logistics and production units and environmental pollution with waste fuel gases containing mostly of CO2. Building SC also aims to provide the necessary quantities of fuels for heating and transport systems as well as their optimization environmentally friendly aspect.

In this study, the performance of tobacco biochar-AlCl3 composite for CO2 capture was investigated. Biochar-AlCl3 composites were prepared at different blend ratios (10:0.4; 10:2; 10:4, wt./wt.) and used for CO2 capture experiments to determine the optimal Al metal content at which CO2 adsorption was highest. Biochar composites were produced through slow pyrolysis under inert nitrogen atmosphere in a fixed bed reactor at 600oC for 3h. Properties of biochar-metal composites and raw biochar samples were characterized with SEM-EDS, XRD and FTIR analysis. CO2 experiments were conducted in TGA under N2 atmosphere with a flow rate of 50 ml/min at 25°C. The maximum CO2 adsorption was observed as 59.97 mg/g for biochar: AlCl3 composite at a ratio of 10:2. Finally, results of study showed that biochar-AlCl3 composites have great potential as a CO2 capture material due to its low-cost, sustainability and CO2 capture capacity.

Using magnetic nanoparticles (MNPs) is becoming popular method to remove heavy metal ions from different waste streams because it is simple, low-cost and effective. In this study, the bare and polymer coated Magnetite Iron Oxide (Fe3O4) MNPs were assessed for their adsorption capability in removing cupric (cu2+)ions from ammoniacal spent etchant solution, which is originated from the production of Printed Circuit boards (PCBs). The polymers used to coat the MNP in this study were chitosan, levan and oleic acid. The batch adsorption experiments were conducted at a temperature of 20oC and the pH of the solution was between 9.0 and 9.5. Experimental results showed that adsorption was achieved within 2 hours, and the maximum amount of Cu2+ ions adsorbed by unit weight of MNP was observed by chitosan coated MNP with an adsorption capacity of 125 mg/g. In addition, Zeta potential measurements showed that all MNPs used in adsorption tests had negative surface charges at around pH 9.0. The more negatively surface charge MNPs the more copper ions they can adsorb. From this experiment it can be concluded that chitosan coated magnetic nanoparticle can be widely used for the removal of copper ions from water and wastewaters.

In this study, bioethanol and biochar production from various algal biomass samples (Chlorella minutissima, Chlorella vulgaris, Nannochloropsis oculata microalgae and Laminaria digitata, Codium fragile, Ulva lactuca macroalgae) and an energy crop sample (sweet sorghum bagasse) were investigated. In bioethanol production, acid pre-treatments were performed with 2 N H2SO4 solution at the temperature of 100°C, and pre-treatment time of 60 minutes. Fermentation was carried out in erlenmeyer flasks which were placed in a shaking incubator set to the 150 rpm at the temperature of 30°C for 48 hours. The highest bioethanol yield was obtained as 44% by utilizing sweet sorghum. Biochar production was carried out at a heating rate of 20°C/min, 250 ml/min nitrogen flow rate and temperature of 400°C in a carbonization retort. The characterization of biomass samples were performed, and all biofuel yields were compared. Although sweet sorghum as an energy crop has higher bioethanol production potential than micro and macroalgae sources, especially macroalgae can be a remarkable solution of waste utilization as a new generation feedstock of biosorbent and biochar production.

The number of biogas plants has increased worldwide making the energy from Biomass one of the main renewable energy resources. Along with the increase of number of biogas plants, the prices of the substrates have been increased. Therefore, the optimization of the energy efficiencies in biogas plants has become a crucial subject. An option to improve the efficiency of the biogas plants is by optimizing their stirring system, where up to 51% from the internal energy consumption in biogas plants might be caused by the stirrers. The evaluation of the current mixing performance is done by performing velocity testing with a reliable technology - the bending beam-. The main advantages of this sensor in advance to the simple technology are the cost reliability, accuracy, resistivity against foul and ability to be installed inside the fermenters. The results showed the efficient use of the sensor and an inaccuracy of the range (4-6) %. The effect of the Total Solids content (TS) of the digestate on the mixing inside the fermenter was determined; at higher TS values, the flow of the substrates becomes more uniform than at lower TS values.