環境汚染物質の分解をスケール横断的にモニタリングするための統合的フレームワークに向けて

Organic contaminants from natural and anthropogenic sources threaten global water and food security. While bioremediation offers significant mitigation potential, tracking compound degradation in complex ecosystems remains challenging. Detection technologies span from microscale methods - biosensors, imaging, and volatile organic analysis - to landscape-scale remote sensing. Each technique provides unique information, but integrating these disparate data streams is a major bottleneck hindering ecological-scale tracking and assessment. In this review, we propose a holistic monitoring framework for detecting contaminants and tracking the progress of bioremediation, highlighting minimally invasive detection techniques and cross-scale sensor integration. We discuss emerging technologies and the generation of standardized datasets essential for machine-learning applications in predicting degradation trajectories using fabricated ecosystems. Integrating environmental sensing, microbiome science, and advanced analytics provides a new chassis for interrogating remediation efforts.