Predicting the Bioaccessibility of Soil Cd, Pb, and As with Advanced Machine Learning for Continental-Scale Soil Environmental Criteria Determination in China-Reference-Cited by-同舟云学术

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Predicting the Bioaccessibility of Soil Cd, Pb, and As with Advanced Machine Learning for Continental-Scale Soil Environmental Criteria Determination in China

Published:2024-06-06 Issue: Volume: Page:
ISSN:2833-8278
Container-title:Environment & Health
language:en
Short-container-title:Environ. Health

Author:

Xie Kunting¹,Ou Jiajun²,He Minghao¹,Peng Weijie¹,Yuan Yong¹^ORCID

Affiliation:

1. Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China

2. School of Automation, Guangdong University of Technology, Guangzhou 510006, China

Funder

National Key Research and Development Program of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/envhealth.4c00035

Reference57 articles.

1. Release of toxic elements in fishpond sediments under dynamic redox conditions: Assessing the potential environmental risk for a safe management of fisheries systems and degraded waterlogged sediments

2. Evaluation of potential ecological risks in potential toxic elements contaminated agricultural soils: Correlations between soil contamination and polymetallic mining activity

3. A combined management scheme to simultaneously mitigate As and Cd concentrations in rice cultivated in contaminated paddy soil

4. National Soil Contamination Survey Report; Ministry of Environmental Protection of the People’s Republic of China, 2014.

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