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

Abstract

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.