干旱区生态环境知识资源中心(Arid): Understanding the activity of Radon-222 in a sand dune aquifer of an arid region through the application of machine learning

Arid

DOI	10.1016/j.gsd.2021.100667
	Understanding the activity of Radon-222 in a sand dune aquifer of an arid region through the application of machine learning
	Khan, Qasim; Alshamsi, Dalal; Hussein, Saber; Mohamed, Mohamed
通讯作者	Mohamed, M (corresponding author), United Arab Emirates Univ, Civil & Environm Engn Dept, Al Ain 15551, U Arab Emirates.
来源期刊	GROUNDWATER FOR SUSTAINABLE DEVELOPMENT
ISSN	2352-801X
出版年	2021
卷号	15
英文摘要	Groundwater samples, collected from the sand dune aquifer of Abu Dhabi Emirates, were analyzed for Radon222 and total dissolved solids (TDS) concentrations. Results indicated that mean Radon-222 concentrations are 7.1 Bq/L in Remah and 7.6 Bq/L in Al Khatim-Al Khaznah areas. These concentrations of Radon-222 were found to be below both WHO and USEPA standard limits; and less than those of Al Ain carbonate aquifer in the vicinity of study area. The TDS concentration was 3184 mg/L and 9878 in Remah and Al Khatim-Al Khaznah groundwater samples, respectively. The correlation between Radon-222 and TDS concentrations was found to be weak, indicating that anthropogenic factors are altering the characteristics of groundwater in the study areas. Higher concentration of TDS in Al Khatim can be attributed to the long-distance rock-water interaction as well as agricultural activities. Radon-222 concentrations in both study areas are due to natural radioactivity of the source aquifer. The effective dose estimation based on these concentrations showed many samples exceeding WHO (2006) limit of 0.04 mSv/a. The carcinogenic risk on the population due to ingestion (stomach and tissue cancer) and inhalation (lungs cancer) was estimated to be in the range of 0.6-23 in a million and 0.15 to 5.7 in a million, respectively. Additional analysis was carried out using unsupervised machine learning algorithms. The k-means algorithm showed two clusters with Radon-222 higher and lower than 11.1 Bq/L. The DBSCAN algorithm showed that there is a presence of possible high concentration of Uranium-238 source near the groundwater at Al Khatim study area.
英文关键词	Groundwater Radon-222 Total dissolved solids Abu dhabi
类型	Article
语种	英语
收录类别	ESCI
WOS记录号	WOS:000718374800021
WOS关键词	GROUNDWATER
WOS类目	Engineering, Environmental ; Environmental Sciences ; Water Resources
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/374329
作者单位	[Khan, Qasim; Mohamed, Mohamed] United Arab Emirates Univ, Civil & Environm Engn Dept, Al Ain 15551, U Arab Emirates; [Alshamsi, Dalal; Hussein, Saber] United Arab Emirates Univ, Dept Geol, Al Ain 15551, U Arab Emirates; [Mohamed, Mohamed] United Arab Emirates Univ, Natl Water & Energy Ctr, Al Ain 15551, U Arab Emirates
推荐引用方式 GB/T 7714	Khan, Qasim,Alshamsi, Dalal,Hussein, Saber,et al. Understanding the activity of Radon-222 in a sand dune aquifer of an arid region through the application of machine learning[J],2021,15.
APA	Khan, Qasim,Alshamsi, Dalal,Hussein, Saber,&Mohamed, Mohamed.(2021).Understanding the activity of Radon-222 in a sand dune aquifer of an arid region through the application of machine learning.GROUNDWATER FOR SUSTAINABLE DEVELOPMENT,15.
MLA	Khan, Qasim,et al."Understanding the activity of Radon-222 in a sand dune aquifer of an arid region through the application of machine learning".GROUNDWATER FOR SUSTAINABLE DEVELOPMENT 15(2021).