环境修复
环境科学
土壤污染
污染物
土壤健康
污染
土壤污染物
污染
土壤修复
食物链
人类健康
环境化学
环境工程
土壤水分
土壤有机质
生态学
土壤科学
化学
环境卫生
生物
医学
作者
Krishna Gautam,Poonam Sharma,Shreya Dwivedi,Amarnath Singh,Vivek Kumar Gaur,Sunita Varjani,Janmejai Kumar Srivastava,Ashok K. Pandey,Jo‐Shu Chang,Huu Hao Ngo
标识
DOI:10.1016/j.envres.2023.115592
摘要
“Save Soil Save Earth” is not just a catchphrase; it is a necessity to protect soil ecosystem from the unwanted and unregulated level of xenobiotic contamination. Numerous challenges such as type, lifespan, nature of pollutants and high cost of treatment has been associated with the treatment or remediation of contaminated soil, whether it be either on-site or off-site. Due to the food chain, the health of non-target soil species as well as human health were impacted by soil contaminants, both organic and inorganic. In this review, the use of microbial omics approaches and artificial intelligence or machine learning has been comprehensively explored with recent advancements in order to identify the sources, characterize, quantify, and mitigate soil pollutants from the environment for increased sustainability. This will generate novel insights into methods for soil remediation that will reduce the time and expense of soil treatment.
科研通智能强力驱动
Strongly Powered by AbleSci AI