Your browser doesn't support javascript.
loading
Cadmium accumulation in tropical island paddy soils: From environment and health risk assessment to model prediction.
Guo, Yan; Yang, Yi; Li, Ruxia; Liao, Xiaoyong; Li, Yonghua.
Afiliación
  • Guo Y; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Yang Y; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Li R; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Liao X; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
  • Li Y; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China. Electronic address: yhli@igsnrr.ac.cn.
J Hazard Mater ; 465: 133212, 2024 03 05.
Article en En | MEDLINE | ID: mdl-38101012
ABSTRACT
Cultivated soil quality is crucial because it directly affects food safety and human health, and rice is of primary concern because of its centrality to global food networks. However, a detailed understanding of cadmium (Cd) geochemical cycling in paddy soils is complicated by the multiple influencing factors present in many rice-growing areas that overlap with industrial centers. This study analyzed the pollution characteristics and health risks of Cd in paddy soils across Hainan Island and identified key influencing factors based on multi-source environmental data and prediction models. Approximately 27.07% of the soil samples exceeded the risk control standard screening value for Cd in China, posing an uncontaminated to moderate contamination risk. Cd concentration and exposure duration contributed the most to non-carcinogenic and carcinogenic risks to children, teens, and adults through ingestion. Among the nine prediction models tested, Extreme Gradient Boosting (XGBoost) exhibited the best performance for Cd prediction with soil properties having the highest importance, followed by climatic variables and topographic attributes. In summary, XGBoost reliably predicted the soil Cd concentrations on tropical islands. Further research should incorporate additional soil properties and environmental variables for more accurate predictions and to comprehensively identify their driving factors and corresponding contribution rates.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oryza / Contaminantes del Suelo Límite: Adolescent / Adult / Child / Humans País/Región como asunto: Asia Idioma: En Revista: J Hazard Mater Asunto de la revista: SAUDE AMBIENTAL Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oryza / Contaminantes del Suelo Límite: Adolescent / Adult / Child / Humans País/Región como asunto: Asia Idioma: En Revista: J Hazard Mater Asunto de la revista: SAUDE AMBIENTAL Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos