Because pollution control and improved treatment
technologies are critical to tackling environmental sustainability challenges,
adhering to environmental management standards is necessary for living a more
sustainable lifestyle. Notably, rural inhabitants in both rich and low-income
countries are becoming increasingly concerned about the quality of their water.
Even while artificial intelligence (AI) can help with the majority of
environmental sustainability issues, including water management, machine learning
models can maximize water resource conservation. There is a large knowledge gap
regarding the application of AI to water pollution mitigation. Long-term
performance under ideal conditions for water resource conservation is decided
by the ability to implement adaptive and sustainable water management
techniques and technologies that ensure the successful use and conservation of
water resources in the foreseeable future. Furthermore, the amount of
pollution-related research—particularly advanced pollution control—published in
the literature has expanded dramatically over the years and continues to do so.
This review focuses on six key components of advanced water pollution
management technologies: adsorption, ion exchanges, electrokinetic processes,
chemical precipitation, phytobial remediation, and membrane technology. It also
discusses how artificial intelligence can be used to regulate water pollution
to protect environmental health, sustainability, and security. Water source
protection involves the protection of surface water sources (e.g. lakes,
rivers, man-made reservoirs) and groundwater sources (e.g. spring protection,
dug well protection, and drilled well protection) to avoid water pollution (see
also pathogens and contaminants). Water quality is more difficult to maintain
due to data gaps and pollution's impact on dimi water quality. As a result, a
complete system or strategy for water security and pollution management is required to handle
water-related challenges and give a thorough approach to water problem solving.
Author(s)details:-
Dr. Krishnakumar B.
Vaghela (B.Sc., M.Sc., M.Phil., Ph.D.)
Department of Life Science, School of Science, Gujarat University,
Ahmedabad, Gujarat, India.
Dr. Devangee P.
Shukla (B.Sc., M.Sc., M.Phil., Ph.D.)
Department of Life Science, School of Science, Gujarat University,
Ahmedabad, Gujarat, India.
Dr. Nayan K. Jain
(BSc (Hons), MSc, PhD)
Department of Life Science, School of Science, Gujarat University, Ahmedabad,
Gujarat, India.
Please See the book
here :- https://doi.org/10.9734/bpi/raeges/v4/510