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This book compiles cutting-edge research on mechanistic analysis, advanced monitoring, and targeted remediation of localized environmental contamination. Centered on regional-scale challenges, it bridges pollutant transmission mechanisms with geospatial modelling and machine learning to predict pathways. Innovations in real-time pollutant detection, including satellite-based hyperspectral imaging, AI-enhanced biosensors, and blockchain-integrated IoT networks, are detailed to address emerging contaminants like nanoplastics and pharmaceutical residues. Remediation strategies emphasize scalable, hybrid solutions, such as electrokinetic-bioremediation for heavy metals, algae-bacteria consortia for eutrophication control, and metal-organic framework (MOF) filters for industrial VOC abatement. By integrating environmental engineering, data science, and material chemistry, the proceedings advance practical frameworks for pollution governance, aligning with SDGs through case studies on industrial hotspots and coastal ecosystems, while prioritizing cost-effectiveness and policy actionable insights.