Extraction of Heavy Metals from Soil Affected by Landfill Leachate through Constructed Wetlands: A Phytoremediation Approach to Rejuvenating the Contaminated Environment

Water is one of the most essential elements of life. The water shortage is becoming a lurid issue in many regions, with over a billion people without passable water for drinking purposes. The leachate from landfill sites is a major problem and poses a threat to aquatic ecosystems and public health. To overcome this situation, either to remove contaminants or to reduce the amount of contamination, constructed wetlands using phytoremediation can be considered the best solution. This green low-cost technology uses plants to remove heavy metals from soil and water. The objective of this report is to study the removal of specific heavy metals such as Zinc (Zn), Nickel (Ni), Chromium (Cr), Cadmium (Cd), Iron (Fe) and Lead (Pb) from landfill leachate by using two laboratory scaled wetlands. These wetlands were filled with soil and planted with Typha Latifolia. One system was operated without recirculation and the other with effluent recirculation with an interval of one day. The influent and effluent physicochemical parameters were analyzed after 30 days and the concentrations of the heavy metals were observed. The wide variation is seen in the case of Nickel, Lead, Chromium, Cadmium, Zinc and Iron. The percentage of removal with recirculation and without recirculation is 100% for Cadmium and Iron, in the case of Nickel, Lead, Chromium and Zinc the percentage difference between recirculation and without recirculation was found to be 1.6, 2.4, 0, 0. Since the removal efficiency for Cadmium and Iron is predominant this study indicates that this technology gives good removal of heavy metals and has a scope for its effective analysis since it has low working and conservation costs; it is comparatively a step toward a sustainable economy

Development of alkali activated paver blocks for medium traffic conditions using industrial wastes and prediction of compressive strength using random forest algorithm

Abstract Geopolymer is an environment friendly construction material that could be synthesized using either the natural source or the industrial byproducts such as flyash and GGBS. The characteristics of the Geopolymer rely on the proportion of the flyash and GGBS and the concentration of the activator solution used. In this research work, the effect of partial replacement of flyash with GGBS in proportions such as 0, 10, 20, 30 and 40% is investigated. Also Molarity of NaOH are tested from 8 to 14 M and both the parameters are optimized. In this optimized Geopolymer concrete, the utilization of iron slag as a partial substitute for river sand in various proportions such as 10, 15, 20, 25, 30 35, 40 and 45% are investigated. The optimized Geopolymer concrete with iron slag is investigated for its performance as a paver block with incorporation of banana fiber in proportions such as 0, 0.5, 1 and 1.5 and is compared with conventional cement concrete paver block. The results show that there is a significant enhancement in the properties of Geopolymer concrete with the different levels of optimization and the utilization of natural banana fiber. The developed sustainable paver block was found to with stand medium traffic conditions as per IS 15658:2006. Further this study employed random forest (RF) algorithm for the prediction of compressive strength of geopolymer concrete specimens for the variable parameters such as molarity of alkaline solution, Flyash/GGBS ratio and partial replacement of river sand with iron slag. The performance evaluation parameters represented high accuracy of developed RF model. This research work unleashes a heft potential of Geopolymer concrete to develop economical eco-friendly sustainable paver blocks to the society through mitigation of environmental strain on the ecosystem

A Neural Network-Based Prediction of Superplasticizers Effect on the Workability and Compressive Characteristics of Portland Pozzolana Cement-Based Mortars

Portland Pozzolana Cement (PPC) mortars are predominantly employed in plastering works to achieve better workability, superior surface finish, and higher fineness to offer better cohesion with fine aggregates than the ordinary Portland cement (OPC) mortars. To achieve high performance in the cement mortar similar to cement concrete, the addition of a superplasticizer is recommended. The present study investigates the impact of addition of sulphonated naphthalene formaldehyde- (SNF)-based (0.5%, 0.6%, 0.7%, and 0.8%) and lignosulphate- (LS)-based (0.2%, 0.3%, 0.4%, and 0.5%) superplasticizers on the workability and compressive strength characteristics of PPC mortars. Plastering mortars of ratio 1 : 4 were prepared with natural sand and manufacturing sand (M sand) as fine aggregates. A flow table test was conducted on all the mortar mix proportions, and the effects of the inclusion of superplasticizers on flow properties were recorded at different time intervals (0, 30, 60, 90, and 120 minutes). PPC mortar cubes were prepared, cured, and examined to assess the inclusion of chemical admixtures on compressive strength at different ages (1, 3, 7, 14, and 28 days). The experimental findings from the workability and compressive strength of PPC mortars were analyzed, and the corresponding results were predicted using artificial intelligence. Experimental investigations demonstrated that the desired flow characteristics and higher compressive strength results were achieved from a 0.7% dosage of ligno-based superplasticizer. The predicted workability and compressive strength results at various ages acquired by implementing an Artificial Neural Network (ANN) were found to be in close agreement with the experimental results