Machine learning-based source apportionment and nonlinear associations of influencing factors on potentially toxic elements in floodplain profiles of Pearl River Delta, China.
- DOI
- 10.1016/j.jenvman.2026.131008
- Published
- 2026 Sep 22
- Container
- Journal of environmental management
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jenvman.2026.131008,
title = {Machine learning-based source apportionment and nonlinear associations of influencing factors on potentially toxic elements in floodplain profiles of Pearl River Delta, China.},
author = {Huang C and Hou Q and Yang Z and Yu T and You Y and Li S},
year = {2026},
journal = {Journal of environmental management},
doi = {10.1016/j.jenvman.2026.131008},
url = {https://doi.org/10.1016/j.jenvman.2026.131008}
}RIS
TY - JOUR TI - Machine learning-based source apportionment and nonlinear associations of influencing factors on potentially toxic elements in floodplain profiles of Pearl River Delta, China. AU - Huang C AU - Hou Q AU - Yang Z AU - Yu T AU - You Y AU - Li S PY - 2026 JO - Journal of environmental management DO - 10.1016/j.jenvman.2026.131008 UR - https://doi.org/10.1016/j.jenvman.2026.131008 ER -
APA
C, H., Q, H., Z, Y., T, Y., Y, Y., & S, L. (2026). Machine learning-based source apportionment and nonlinear associations of influencing factors on potentially toxic elements in floodplain profiles of Pearl River Delta, China.. Journal of environmental management. https://doi.org/10.1016/j.jenvman.2026.131008
Source records
- pubmed · retrieved 2026-09-25T16:22:45.458Z