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Abstract

Summary

This study develops a systematic, data-driven methodology for identifying optimal Direct Air Capture (DAC) deployment sites in Germany by integrating geospatial analysis, K-means clustering, and multi-criteria decision-making. A comprehensive spatial dataset was compiled, incorporating onshore and offshore constraints such as infrastructure accessibility, environmental protection, geological suitability, and socio-economic factors. The K-means clustering algorithm was applied to classify sites based on their spatial characteristics, while a multicriterial ranking system was used to validate the results against established CO storage suitability criteria. The findings contribute to refining DAC site selection strategies for large-scale CO removal and storage in Germany.

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2025-09-01
2026-02-15
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