A Machine Learning Approach for Spatial Mapping of the Health Risk Associated with Arsenic-Contaminated Groundwater in Taiwan’s Lanyang Plain
Groundwater resources are abundant and widely used in Taiwan’s Lanyang Plain. However, in some places the groundwater arsenic (As) concentrations far exceed the World Health Organization’s standards for drinking water quality. Measurements of the As concentrations in groundwater show considerable sp...
Guardado en:
Autores principales: | Ching-Ping Liang, Chi-Chien Sun, Heejun Suk, Sheng-Wei Wang, Jui-Sheng Chen |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/98601a5e8f014185b6cd68037ec0bbe0 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Groundwater suitability analysis for drinking using GIS based fuzzy logic
por: Santanu Mallik, et al.
Publicado: (2021) -
Influence of phosphorus on the arsenic uptake by tomato (Solanum lycopersicum L) irrigated with arsenic solutions at four different concentrations
por: Pigna,M, et al.
Publicado: (2012) -
Probability of Non-Exceedance of Arsenic Concentration in Groundwater Estimated Using Stochastic Multicomponent Reactive Transport Modeling
por: Nico Dalla Libera, et al.
Publicado: (2021) -
Potential health risk assessment related to arsenic pollution and hydrogeochemistry of groundwaters in Akşehir and surroundings (Konya/Turkey)
por: Simge Varol
Publicado: (2021) -
Risk assessment of heavy metal and trace elements contamination in groundwater in some parts of Ogun state
por: O. O. Adewoyin, et al.
Publicado: (2019)