Integrating advanced techniques and machine learning for landfill leachate treatment: Addressing limitations and environmental concerns

Gaur, Vivek Kumar; Gautam, Krishna; Vishvakarma, Reena; Sharma, Poonam; Pandey, Upasana; Srivastava, Janmejai Kumar; Varjani, Sunita; Chang, Jo-Shu; Ngo, Huu Hao; Wong, Jonathan W.C.

doi:10.1016/j.envpol.2024.124134

Environmental Pollution

2024

DOI: 10.1016/j.envpol.2024.124134

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Integrating advanced techniques and machine learning for landfill leachate treatment: Addressing limitations and environmental concerns

Vivek Kumar Gaur,

Krishna Gautam,

Reena Vishvakarma

et al.

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Cited by 3 publications

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Turning trash into treasure: Exploring the potential of AI in municipal waste management - An in-depth review and future prospects

El jaouhari,

Samadhiya,

Kumar

et al. 2025

Journal of Environmental Management

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Turning trash into treasure: Exploring the potential of AI in municipal waste management - An in-depth review and future prospects

El jaouhari,

Samadhiya,

Kumar

et al. 2025

Journal of Environmental Management

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Unlocking the potential of soil microbial communities for bioremediation of emerging organic contaminants: omics-based approaches

Alidoosti,

Giyahchi,

Moien

et al. 2024

Microb Cell Fact

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The remediation of emerging contaminants presents a pressing environmental challenge, necessitating innovative approaches for effective mitigation. This review article delves into the untapped potential of soil microbial communities in the bioremediation of emerging contaminants. Bioremediation, while a promising method, often proves time-consuming and requires a deep comprehension of microbial intricacies for enhancement. Given the challenges presented by the inability to culture many of these microorganisms, conventional methods are inadequate for achieving this goal. While omics-based methods provide an innovative approach to understanding the fundamental aspects, processes, and connections among microorganisms that are essential for improving bioremediation strategies. By exploring the latest advancements in omics technologies, this review aims to shed light on how these approaches can unlock the hidden capabilities of soil microbial communities, paving the way for more efficient and sustainable remediation solutions.

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Digital twin modeling method for environmental governance of abandoned landfills based on multi-agent systems

Liu,

Zhang,

Zhang

et al. 2024

digitaltwin

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Background It is currently observed that some landfills are experiencing severe overloading, with some having ceased operations. However, they continue to threaten the environment and public health. There is an urgent need for governance, although the process is complex and requires more intelligent and efficient governance approaches. Methods This study explored the application of digital twin technology based on multi-agent systems in the environmental governance of abandoned landfills. This paper addresses the demands of landfill governance by integrating modules, including twin models, mechanisms, and big data, and integrating each module with corresponding intelligent agents, forming a thoughtful, collaborative, and adaptive digital twin agent system. Results This method can collect and analyze on-site data more systematically and provide feedback to management personnel to guide the adjustment of on-site plans and improve the on-site management efficiency by 30%. Conclusions Through application cases, the operation process of this system in specific landfill environmental governance scenarios was demonstrated, confirming its superiority in environmental governance. This system can facilitate environmental monitoring, intelligent analysis, and decision control during the governance of abandoned landfills.

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Integrating advanced techniques and machine learning for landfill leachate treatment: Addressing limitations and environmental concerns

Cited by 3 publications

References 141 publications

Turning trash into treasure: Exploring the potential of AI in municipal waste management - An in-depth review and future prospects

Turning trash into treasure: Exploring the potential of AI in municipal waste management - An in-depth review and future prospects

Unlocking the potential of soil microbial communities for bioremediation of emerging organic contaminants: omics-based approaches

Digital twin modeling method for environmental governance of abandoned landfills based on multi-agent systems

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