From Wastewater to Sustainability: Tackling Heavy Metal Contamination in Agriculture with Conventional and AI Techniques
摘要
The global distribution of population density and freshwater resources is uneven, compelling farmers to use wastewater for irrigating food crops. While wastewater can supply essential nutrients to plants, its use poses significant environmental, sanitary, and health risks due to the presence of harmful pollutants and pathogens. Contaminated irrigation water can elevate hazardous metal levels in agricultural soil, impacting soil fertility, crop quality, and human health. Arsenic, lead, cadmium, and chromium are notable examples of such heavy metals. Enhancing wastewater treatment efficiency requires the proper implementation of primary, secondary, and tertiary treatment stages. This review examines both conventional methods and advanced treatment strategies, highlighting the potential of reclaimed water as an alternative supply to address these challenges. Key considerations include urban planning, sanitation, remediation technologies, community awareness (especially among farmers), and government involvement. Furthermore, integrating artificial intelligence (AI) and computational techniques has shown promise in optimizing wastewater treatment processes, improving efficiency, and ensuring better water quality management. This review presents recent findings from the literature and offers recommendations for future research.
Graphical Abstract