Faculty Publications
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Item Effects of electric potential, NaCl, pH and distance between electrodes on efficiency of electrolysis in landfill leachate treatment(Taylor and Francis Inc. 325 Chestnut St, Suite 800 Philadelphia PA 19106, 2017) Erabee, I.K.; Ahsan, A.; Jose, B.; Arunkumar, T.; Sathyamurthy, R.; Idrus, S.; Daud, N.N.N.This study investigated the effects of different parameters on the removal efficiencies of organic and inorganic pollutants in landfill leachate treatment by electrolysis. Different parameters were considered such as the electric potential (e.g., 24, 40 and 60 V), hydraulic retention time (HRT) (e.g., 40, 60, 80, 100 and 120 min), sodium chloride (NaCl) concentration (e.g., 1, 3, 5 and 7%), pH (e.g., 3, 7 and 9), electrodes materials [e.g., aluminum (Al) and iron (Fe)] and distance between electrodes (e.g., 1, 2 and 3 cm). The best operational condition of electrolysis was then recommended. The electric potential of 60 V with HRT of 120 min at 5% of NaCl solution using Al as anode and Fe as cathode (kept at a distance of 3 cm) was the most efficient condition which increased the removal efficiencies of various parameters such as turbidity, salinity, total suspended solids (TSS), total dissolved solids (TDS), biochemical oxygen demand (BOD), chemical oxygen demand (COD) and heavy metals (e.g., Zn and Mn). The higher removal percentages of many parameters, especially COD (94%) and Mn (93%) indicated that the electrolysis is an efficient technique for multi-pollutants (e.g., organic, inorganic and heavy metals) removal from the landfill leachate. © 2017 Taylor & Francis Group, LLC.Item Adsorptive Treatment of Landfill Leachate using Activated Carbon Modified with Three Different Methods(Springer Verlag service@springer.de, 2018) Erabee, I.K.; Ahsan, A.; Jose, B.; Aziz, M.M.A.; Ng, A.W.M.; Idrus, S.; Daud, N.N.N.Activated Carbon (AC) is an adsorbent having high surface area which makes the process of removing heavy metals from wastewater (such as landfill leachate) very effective. This study explored the utilization of three methods of modification of AC produced from coconut shell by treating it with nitric acid (HNO3), potassium permanganate (KMnO4) and heating at 600°C to improve the adsorption capacity. The AC can remove multi-pollutants in the filtration process which was used to treat landfill leachate. The water quality parameters such as pH, TSS, Ammonia-Nitrogen and a few heavy metals were considered in the present study. Results showed that the removal of these parameters was proportional with the increase of contact time and the bed depth of AC. The isotherm analysis of the adsorption of modified AC showed the best Removal Efficiency (RE) can be achieved when AC treated with KMnO4 for NH3-N, zinc, TSS and sulphide. The morphology of the AC was studied through Scanning Electron Microscopy (SEM), Energy Dispersive X-ray spectroscopy (EDX) pattern analysis and Fourier Transform Infrared (FTIR) analysis. It was found that various types of oxygen functional groups were introduced onto the surface of coconut shell derived AC through oxidation using HNO3. FTIR was used to characterize the surface oxygen functional groups. The surface functional groups such as N-H and C-H stretching played a significant role in heavy metals adsorption. Hence, it can be concluded that the hybrid technique by using electrolysis process with AC adsorption be an effective way to remove the suspended solids and heavy metals from landfill leachate and thus able to reduce environmental pollution. © 2018, Korean Society of Civil Engineers.Item Predictive simulation of leachate transport in a coastal lateritic aquifer when remediated with reactive barrier of nano iron(Elsevier B.V., 2020) Divya, A.; Shrihari, S.; Ramesh, H.The current study focuses on determination of extent of groundwater contamination on a typical tropical coastal aquifer due to a landfill located at Vamnjoor in Dakshina Kannada district, India with the help of groundwater flow model, MODFLOW and MT3DMS when remediated with permanent reactive barrier of nano iron. The aquifer considered is a shallow, unconfined one with laterite soil which gets good rains during monsoon and will be dry during rest of the year. The adsorption by laterite soil has been considered. The specific yield and transmissivity were estimated to be 7.85% and 213m2/day respectively. After calibrating successfully with Nash–Sutcliffe efficiency 0.8, horizontal hydraulic conductivity was set as 7 m/day. Validation of model was then done with the field data and is applied for forecasting the spread of contaminant for anticipated future scenarios. The results show that in spite of retardation offered by lateritic soil, contaminant trail is expanding with a velocity of 0.15 m/day in downstream direction. When permeable reactive barrier of nano iron which can adsorb nearly 65% of chemical oxygen demand is installed, it is showing that the contaminant spread can be reduced to 400 mg/l at the observation well located at 1 km from landfill. Hence a comprehensive remedial alternative of permanent reactive barrier of nano iron can be recommended for preventing groundwater contamination from landfill leachate. © 2020 Elsevier B.V.Item Optimizing Solid Waste Management: A Holistic Approach by Informed Carbon Emission Reduction(Institute of Electrical and Electronics Engineers Inc., 2024) Hegde, S.; Sumith, N.; Pinto, T.; Shukla, S.; Patidar, V.Reducing carbon monoxide (CO) emissions is imperative for safeguarding human health and environment. CO adversely affects respiratory health, contributing to respiratory problems and, in severe cases, fatalities. Its reduction aligns with the broader efforts to combat climate change, as CO is often emitted alongside other greenhouse gases. Environmental consequences include air pollution and its detrimental impact on ecosystems. Compliance with emission standards is essential, and reducing Carbon emissions can lead to social and economic benefits, such as increased productivity and reduced healthcare costs. Moreover, the focus on emission reduction drives technological innovation, fostering the development of cleaner and sustainable technologies. In essence, addressing CO emissions is vital for creating a healthier, more sustainable future. However, in most of the cases, there has been no much importance given in scientific management of solid wastes. This has therefore resulted in large magnitude of carbon emission causing serious implications. This paper presents a novel approach to solid waste management, combining carbon emission assessment with advanced object detection technology. We develop an integrated waste management model that employs machine learning techniques for the identification and categorization of metals, non-metals, and plastics within the solid waste stream. To optimize waste sorting and recycling processes, we implement an efficient object detection system that leverages computer vision algorithms. This system enhances the precision of material identification within solid waste, thereby improving sorting accuracy. Additionally, we establish a database to quantify carbon emissions associated with distinct waste management methods, encompassing incineration, composting, recycling, bioremediation, and landfills is used for this work. The novelty of the work lies in the integration of CO2 emissions data and object detection resulting into a decision-making model, providing a holistic evaluation of the environmental impact of varied waste management scenarios. The formulation of recommendations for sustainable waste management practices based on the integrated assessment of carbon footprints and material identification is easy to implement in real world.The technical framework proposed here, aims to inform decision-makers on adopting environmentally conscious strategies for waste management. © 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.