Ulteriori informazioni
This book is a proceedings of a conference International Conference on Environmental Science and Engineering to be held in Surat during December 2024. The theme of the conference include Pollution Modelling Sustainable Development and SDGs Climate Chemistry and Climate Change Environmental, Social and Governance Waste Characterization and Treatment Circular Economy and Environmental Impacts Control Strategies for Water, Waste, Air and Noise Application of AI/ML in Environmental Engineering Air, Water and Noise Quality Monitoring and Measurement Techniques.
Sommario
Simulation and Optimization of Cumene Production Process Using DWSIM Software.- Automating Sustainable Growth and Revolutionizing Hydroponic Farming.- Life Cycle Inventory of Residential Buildings for Cradle to Grave Approach.- Comprehensive Assessment of Carbon Footprints in Construction Logistics: Methodologies, Challenges, and Sustainable Reduction Strategies.- Thermo-Chemical Conversion of Sewage Sludge in a Fluidized Bed Reactor: A Sustainable Approach for Waste to Energy.- Mobile Air Quality Monitoring of Vatva GIDC and Naroda GIDC.- A Comparative Study on Air Quality Index Prediction Using Machine Learning and Hybrid Deep Learning Models.- Comprehensive Analysis of Particulate Matter Emissions and Meteorological Influences in the Stone Carving Industry.- Statistical Analysis of Air Pollutants and Meteorological Interactions in Kamptee, Nagpur, India.- Enhancing Tmrt Predictions with Machine Learning: Combining Field Data and ENVI-Met Simulations.- Enhancing Air Quality in Dhule City: Monitoring Dust Levels and Strategies for Reduction.- Assessment of Urban Noise Pollution and Its Multifaceted Health Impacts: An Exploratory Factor Approach.- Monitoring and Mapping of Noise Levels at Sensitive Areas of Jawaharlal Nehru Medical College and Hospital in Aligarh Smart City.- From Data to Decisions: A Comprehensive Assessment of Machine Learning Techniques for Air Quality Monitoring.
Info autore
Dr. M. Mansoor Ahammed is currently a professor of Environmental Engineering at the Department of Civil Engineering, Sardar Vallabhbai National Institute of Technology Surat, India. He obtained his Bachelor of Technology in Civil Engineering from Government Engineering College, Thrissur and M.Tech. and Ph.D. from the Indian Institute of Technology, Kanpur. His major areas of research interests include household water treatment, wastewater treatment and reuse, anaerobic treatment processes and use of waste materials in environmental engineering applications. He has published more than fifty papers in high impact journals. He has guided five Ph.D. students and forty M.Tech. students. He was principal investigator for three research projects sponsored by different government agencies.
Mukesh Khare is currently a professor Emeritus in Environmental Engineering at Indian Institute of Technology, Delhi. He obtained his Bachelors and master’s degree in Civil Engineering from University of Roorkee and Ph.D. from University of Newcastle Upon Tyne, UK. He is leading the colleagues in Environmental Engineering Group in its commitment to make a major contribution to the academic development of IIT Delhi, and in furthering its national and international status as a great institute since he joined in 1990. Khare is a distinguished Civil/Environmental Engineer, with broad industrial experience in the air and water sectors, manifest in a strong portfolio of interdisciplinary research and more than 250 research publications in the refereed open literature.
Riassunto
This book is a proceedings of a conference “International Conference on Environmental Science and Engineering” to be held in Surat during December 2024. The theme of the conference include Pollution Modelling Sustainable Development and SDGs Climate Chemistry and Climate Change Environmental, Social and Governance Waste Characterization and Treatment Circular Economy and Environmental Impacts Control Strategies for Water, Waste, Air and Noise Application of AI/ML in Environmental Engineering Air, Water and Noise—Quality Monitoring and Measurement Techniques.
