In this study natural bentonite (NB) and acid-thermal co-modified bentonite (MB) were utilized as adsorbents for the removal of Thymol Blue (TB) from aqueous solution. The batch adsorption experiments were conducted under different experimental conditions. The artificial neural network (ANN) and adaptive neuro fuzzy inference systems (ANFIS) were applied to estimate removal percentage (%) of TB. Mean squared error (MSE), root mean square error (RMSE) and coefficient of determination (R2) values were used to evaluate the results. In addition, the experimental data were fitted isotherm models (Langmuir, Freundlich and Temkin) and kinetic models (pseudo first order (PFO), pseudo second order (PSO) and intra-particle diffusion (IPD)). The adsorption of TB on both the NB and MB followed well the PSO kinetic model, and was best suited Langmuir isotherm model. When the temperature was increased from 298 K to 323 K for 20 mg/L of TB initial concentration, the removal percentage of TB onto the NB and MB increased from 74.91% to 84.07% and 81.19% to 93.12%, respectively. This results were confirmed by the positive ΔH° values indicated that the removal process was endothermic for both the NB and MB. The maximum adsorption capacity was found as 48.7805 mg/g and 117.6471 mg/g for the NB and MB, respectively (at 323 K). As a result, with high surface area and adsorption capacity, the MB is a great candidate for TB dye removal from wastewater, and the ANFIS model is better than the ANN model at estimating the removal percentage of the dye.

Climate change could be exacerbated by waste disposal problems, which destroy the ecosystem. Utilizing waste byproducts in creating eco-friendlier geopolymer concrete was hypothesised to be suitable and sustainable to overcome the negative impacts of wastes. The researchers had missed out on developing an alternate binder due to increasing demand for fly ash, high alkaline activators, and higher curing temperatures. This research used waste wood ash that is readily accessible in local restaurants and has an inherent potassium constituent. It has decided to replace the fly ash with waste wood ash obtained through nearby restaurants at intervals of 10 percent. The fresh and mechanical features have been discovered over long curing periods to assess the impact of waste wood ash. SEM and XRD have been used for characterising the microstructure of selected geopolymer mixes. In terms of setting properties and all mechanical parameters, replacing 30 percent waste wood ash produced enhanced results. The optimised mix could be used in geopolymer to replace fly ash and reduce the cost of alkaline activators while also reducing ecosystem damage.

Polycyclic aromatic hydrocarbons (PAHs), abundant in mixed contaminant sites, often coexist with heavy metals. The fate and remediation of PAHs depend heavily on the sorption and desorption behavior of these contaminants. The sorption behavior can in turn be highly affected by certain soil components and properties, such as soil organic matter (SOM) and the presence of heavy metals. Through review of the literature focused on research from 2006 to 2018, this paper discusses interactions, challenges, influencing factors and potential synergies in sorption/desorption of mixed PAHs and heavy metal contamination of soil. The presence of either natural organic matter or heavy metals can enhance the sorption capability of fine soil, retarding the PAHs in the solid matrix. The co-existence of SOM and heavy metals has been reported to have synergistic effect on PAHs sorption. Enhanced and surfactant desorption of PAHs are also affected by the presence of both SOM and metals. Remediation techniques for PAHs removal from soil, such as soil washing, soil flushing and electrokinetics, can be affected by the presence of SOM and heavy metals. More detailed studies on the simultaneous effects of soil components and properties on the sorption/desorption of PAHs are needed to enhance the effectiveness of PAHs remediation technologies.

The study investigates the effect of aluminium oxide nanoparticles as an additive to Madhuca Indica (mahua) methyl ester blends on performance, emission analysis of a single-cylinder direct injection diesel engine operated at a constant speed at different operating conditions. The test fuels are indicated as B10A0.2, B10A0.4, B20A0.2, B20A0.4 and diesel respectively. The results indicate that the brake thermal efficiency for aluminium oxide nanoparticles blended biodiesel increases slightly when compared to the mineral diesel. The carbon monoxide (CO), unburnt hydrocarbon (HC) and smoke emission marginally decrease as compared to mineral diesel. Oxides of nitrogen (NOx) emissions are minimum for the aluminium oxide nanoparticles blended mahua methyl esters. Higher cylinder gas pressure and heat release rate were observed for aluminium oxide nanoparticles blended mahua methyl ester. From the study, the blending of aluminium oxide nanoparticles in biodiesel blends produces a most promising results in engine performance and also reduces the harmful emission from the engines.

The main objective of this study is to evaluate heavy metals contamination of highly consumed vegetables and hazardous effects of consuming these vegetables. The study was conducted in vegetable fields in three different regions according to the level of environmental pollutions, including "Isfahan", "Flavarjan" and "Faridan, Golpayegan and Natanz". Six types of vegetables in each field with three replicates in each region were selected in the summer of 2017 by the random sampling method from vegetable fields. The level of heavy metals (Pb, Cu, Co, Cd and Cr) in vegetables has been measured for each sample. The result showed that in the Isfahan region, the highest daily intake of Pb, Cu, Co, Cd and Cr for the consumption of all the vegetables was obtained in the recipients. The highest target hazard quotient for non-cancerous diseases of contaminated vegetables was 28.9 and 21.1 in "Isfahan" for children and adults, respectively. The target hazard quotient for vegetable consumption was greater than one and at high hazard for both age groups. The principal component analysis showed that the contamination by the heavy metals in the "Isfahan" and "Falavarjan" regions overlapped and the risk of contamination of heavy metals in urban vegetables in both regions increased the hazard of non-cancerous diseases. It is highly recommended that the quality standards of foods that are imposed on the production of food crops.

Microbial fuel cell represents an emerging technology to attain electrical energy from wastewater. There are several alternative methods available for wastewater treatment; Microbial fuel cell is one of them, which generates green energy from wastewater for making a contribution to renewable sources of energy. This study states the performance of microbial fuel cell with different parameters i.e., catholyte, electrodes, and initial COD concentration. Sodium chloride was used as catholyte and graphite rods were used as both electrodes. The sodium chloride concentrations in the cathode and initial chemical oxygen demand have also been optimized. The optimum sodium chloride of 70 mM in the cathode solution generates the maximum power density of 408.98μW/m2. As the sodium chloride concentration increases in catholyte, the capacity for power production also increases. The voltage output of Microbial fuel cell increases when the initial concentration of chemical oxygen demand increases to a peak value of 1500 mg/l and if the value exceeds this limit, the performance of Microbial fuel cell (in terms of voltage) starts decreasing. The chemical oxygen demand removal efficiency of a microbial fuel cell with simple graphite electrode and graphite electrodes with coated iron were 79% and 90% respectively.

Mathematical models for pollutant transport in semi-infinite aquifers are based on the advection-dispersion equation (ADE) and its variants. This study employs the ADE incorporating time-dependent dispersion and velocity and space-time dependent source and sink, expressed by one function. The dispersion theory allows mechanical dispersion to be directly proportional to seepage velocity. Initially the aquifer is assumed contaminant free and an additional source term is considered at the inlet boundary. A flux type boundary condition is considered in the semi-infinite part of the domain. Laplace transform technique (LTT) is then applied to obtain a closed form analytical solution. The effect of source/sink term as a function in the one-dimensional advection-dispersion equation is explained through the graphical representation for the set of input data based on similar data available in hydrological literature. Matlab software is used to obtain the graphical representation of the obtained solution. The obtained analytical solution of the proposed model may be helpful in the groundwater hydrology areas.

In this research, a response surface methodology (RSM) was used to investigate the effects of independent parameters (pH, contact time, temperature, adsorbent dosage, and initial concentration of pollutant), their simultaneous interactions, and quadratic effects on crystal violet adsorption onto two starch based materials in the form of batch experiments. The characterizing results indicated that there is no significant difference between the potato starch and synthesized starch phosphate, as phosphorylation has not changed the crystalline structure of starch inside the granules. The maximum removal efficiency of crystal violet ions was obtained 99 % at the optimum adsorption conditions of initial concentration 213.54 mg/L, adsorbent dosage 0.25 g, contact time 14.99 min, temperature 15 °C, and initial pH of solution 9. RSM outputs showed that the maximum adsorption of crystal violet ions by could be achieved by raising pH and adsorbent dosage, and decreasing the initial crystal violet concentration. While temperature and contact time are not effective parameters in crystal violet removal from aqueous solutions using synthesized starch phosphate. Generally, the RSM model is suitable to optimize the experiments for dye elimination by adsorption, where the modified starch phosphate would be an effective adsorbent for treating crystal violet solution.

This study utilized Swietenia mahagoni bark–a wood processing industry waste, for the preparation of activated carbon, and then investigated for the removal of methyl orange (MO) dye by the Swietenia mahagoni bark activated carbon (SMBAC). The effect of pH (3–10), adsorbent dose (1–30 g/L), initial MO dye concentration (10–100 mg/L), and contact time (1–240 min) were evaluated. The surface morphology of the SMBAC was characterized by using fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Maximum removal efficiency of MO by SMBAC was 92%, when initial MO dye concentration was 10 mg/L, pH 3.0, adsorbent dose 10.0 g/L and 120 min equilibrium contact time. The adsorption data fitted well with the Freundlich (R2=0.997) and Halsey (R2=0.997) isotherm models than the Langmuir (R2=0.979) model, and express the multilayer adsorption on heterogeneous surface. The maximum adsorption capacity was 6.071 mg/g. The kinetics data were fitted well to pseudo-second order model (R2=0.999) and more than one process were involved during adsorption mechanism but film diffusion was the potential rate controlling step.  The study results showed that SMBAC adsorbed MO effectively, and could be used as a low cost potential bioadsorbent for the removal of anionic dyes in wastewater treatment.

The entrance of Cd (II) to aqueous environments causes a major problem to human health. The current article examines the efficiency of TiO2 and γ-Al2O3 nanoparticles in Cd (II) removal from aqueous medium as influenced by different chemical factors, such as pH, initial concentration, background electrolyte, and ionic strength, in accordance with standard experimental methods. It conducts Batch experiments, fitting various isotherm models (Freundlich, Langmuir, Temkin, and Dubinin-Radushkevich) to the equilibrium data. Saturation indices (SI) of TiO2 and γ-Al2O3 nanosorbents indicate that adsorption is a predominant mechanism for Cd (II) removal from aqueous solution, giving maximum Cd (II) adsorption rates of 3348 and 1173 mg/kg for TiO2 and γ-Al2O3 nanoparticles, respectively, both obtained at the highest pH level (pH = 8) as well as the highest initial Cd (II) concentration (equal to 80 mg/ L). Cadmium removal efficiency with TiO2 and γ-Al2O3 nanoparticles has increased by raising pH from 6 to 8. The Freundlich adsorption isotherm model could fit the experimental equilibrium data well at different pH levels. Also, it has been revealed that cadmium adsorption drops as the ionic strength is increased. The maximum Cd (II) adsorption (1625 mg/kg) has been attained at 0.01 M ionic strength in the presence of NaCl. Thermodynamic calculations demonstrate the spontaneous nature of Cd (II) adsorption by TiO2 and γ-Al2O3 nanoparticles. The former (TiO2) have high adsorption capacities, suggesting they are probably effective metal sorbents, compared to the latter (γ-Al2O3).