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Regional and global hotspots of arsenic contamination of topsoil identified by deep learning

Environmental Studies and Forestry

Regional and global hotspots of arsenic contamination of topsoil identified by deep learning

M. Wu, C. Qi, et al.

This groundbreaking research by Mengting Wu, Chongchong Qi, Sybil Derrible, Yosoon Choi, Andy Fourie, and Yong Sik Ok unveils a cost-effective technique for assessing topsoil arsenic contamination worldwide. Utilizing VNIR spectroscopy and an optimized deep learning model, the study reveals hotspots like China, Brazil, and California, while calling attention to lesser-known regions like Gabon. Dive into this innovative approach tackling a serious ecological and human health threat!

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