Research Projects

Rationale: Sewage sludge management poses several environmental challenges, with conventional methods like landfilling and incineration contributing to greenhouse gas emissions and toxic pollutant release. Gasification is a sustainable pathway to convert sludge into biochar, enabling carbon sequestration. Integrating sustainability and economic analysis along with machine learning (ML) and process simulation can make this technology even more attractive. Furthermore, applying this biochar for PFAS removal addresses emerging water pollution concerns, aligning with circular economy. Objectives: 1. Optimize gasification parameters for sewage sludge and sludge-biomass blends to maximize biochar yield and quality. 2. Develop process models using Aspen plus for mass/energy balances and scalability. 3. Modify biochar via chemical activation/functionalization for efficient PFAS adsorption. 4. Implement ML models to predict biochar properties and optimize PFAS removal. 5. Conduct integrated LCA and TEA of the sludge-to-biochar-to-wastewater pathway. The hypothesis is optimized gasification parameters and modified biochar will significantly enhance biochar quality and PFAS removal efficiency. A predictive model will be tested that can forecast process outcomes, while LCA/TEA would quantify environmental and economic advantages over conventional methods. Experiments: Firstly, the feedstocks will be characterized (proximate/ultimate analysis etc). Then gasification experiments will be designed and conducted by varying process parameters such as temperature, equivalence ratio, and blend ratios. The produced biochar and syngas will be analyzed using analytical techniques (GC-MS, FTIR, BET etc). Then aspen models will simulate mass/energy balances and scalability of the process. The biochar will then be activated and used for removing PFAS from wastewater under varied pH/dosage. All the experimental data will then be used to train several ML algorithms (ANN, XGBoost, SVR, etc) to develop predictive models for optimising biochar yield and quality as well as PFAS adsorption. Lastly, LCA and cost analysis will be conducted. Significance: This project will deliver a practical, modular sludge gasification system that produces biochar for use in decentralized water filtration, directly addressing rural water quality and waste management challenges. This technology is backed by novel integration of experimental, computational, and ML methods. This technology aligns with initiatives such as the MNRE’s waste-to-energy programme which mandate 50% wastewater reuse by 2030 and the national policy on biofuels 2018 which promotes waste valorization for energy and resource recovery. This work also addresses India’s 2024 liquid waste management rules. It also advances several UN’s Sustainable Development Goals, including SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), and SDG 13 (Climate Action) by promoting carbon sequestration and reducing emissions.