Air pollution is a global environmental challenge that affects the health and well-being of millions of people worldwide. As the need for effective pollution control and mitigation measures continues to grow, so does the importance of advanced computational techniques in understanding, monitoring, and managing air quality. This contributed volume presents interdisciplinary cases that span the fields of environmental science, computer modeling, and data analysis to provide an overview of state-of-the-art computational methods used in tackling air pollution. This book offers an in-depth exploration of the tools, techniques, and strategies that have revolutionized our ability to study and address air quality issues.
Chapter
1. Introduction to computational approaches in air pollution.-
Chapter
2. Understanding the health and environmental impacts of air
pollutants.
Chapter
3. Assessing the health and environmental consequences
of air pollution.
Chapter
4. Assessment on health and environmental impacts
due to air pollution.
Chapter
5. Air pollution and its impact on health and
environment in India.
Chapter
6. Analyzing air pollution sources effect and
mitigation strategies.
Chapter
7. Towards a data-driven air pollution
control strategy.
Chapter
8. Air pollution modeling using computational
approaches.
Chapter
9. Machine learning in air quality prediction and
control.
Chapter
10. Transforming air quality forecasting with machine
learning techniques.
Chapter
11. Machine learning for air pollution
prediction: A case study of Bhilwara, Rajasthan.
Chapter
12. Emission
inventories to AI-based prediction for air pollutants.
Chapter
13.
Harnessing biodiversity for air pollution mitigation through nature-based
strategies and bioresource utilization.
Chapter
14. Digital pathways to
cleaner air: Reducing construction-related CO through BIM, digital twins,
and artificial intelligence.
Chapter
15. Investigating the relationship
between urbanization and air pollution: New insights from developed
countries.
Chapter
16. Air pollution and recent trends in control strategy.-
Chapter
17. COVID-19 emission inventory and air quality simulation in Madrin,
Spain.
Chapter
18. Intuitionistic Fuzzy MCDM Decision Making Technique for
the Selection of Property.
Chapter
19. Probabilistic and computational
health risk modelling for assessment of air pollution exposure.
Chapter
20.
Advancing sustainable and inclusive evaluation frameworks for health and
environmental impact assessment.
Chapter
21. Environmental and Public Health
Concerns in a Sustainable Future.
Akhilesh Kumar Yadav graduated with a Bachelor of Technology in Electronics and Communication Engineering from the Chaudhary Charan Singh University, Meerut, India. He subsequently obtained a Master of Technology in Environmental Engineering from Madan Mohan Malaviya Engineering College, Gorakhpur, India (affiliated with Dr. A. P. J. Abdul Kalam Technical University, Lucknow). His doctoral degree, with a research focus on air pollution, was awarded by the Indian Institute of Technology (Banaras Hindu University), Varanasi, India. Dr. Yadav has served at various institutions, including Indian Institute of Technology (Banaras Hindu University), Varanasi, India; Indian Institute of Technology Bombay, Mumbai, India; Bhabha Atomic Research Centre, Mumbai, India (as a research collaborator); and Chaoyang University of Technology, Taichung, Taiwan. He has authored/co-authored several research and review articles, book chapters, and edited/authored books, and holds a patent. Dr. Yadav received the Young Engineer Award from the Institution of Engineers (India) and the Young Scientist Award from VDGOOD Technology Factory, Kolkata. His research interests include air, water, and soil pollution; climate change; vulnerability; human health risk assessments; and GIS applications in environmental pollution and management. He is an active member of several reputed international professional bodies, including the IEI (Kolkata), ECI (New Delhi), AEACI (Mumbai), MSI (New Delhi), and IASTA (Mumbai).
