干旱区生态环境知识资源中心(Arid): Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area

Arid

DOI	10.1007/s10653-023-01845-9
	Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area
	Sakizadeh, Mohamad; Zhang, Chaosheng; Milewski, Adam
通讯作者	Sakizadeh, M
来源期刊	ENVIRONMENTAL GEOCHEMISTRY AND HEALTH
ISSN	0269-4042
EISSN	1573-2983
出版年	2024
卷号	46 期号:3
英文摘要	Combining the results of base models to create a meta-model is one of the ensemble approaches known as stacking. In this study, stacking of five base learners, including eXtreme gradient boosting, random forest, feed-forward neural networks, generalized linear models with Lasso or Elastic Net regularization, and support vector machines, was used to study the spatial variation of Mn, Cd, Pb, and nitrate in Qom-Kahak Aquifers, Iran. The stacking strategy proved to be an effective substitute predictor for existing machine learning approaches due to its high accuracy and stability when compared to individual learners. Contrarily, there was not any best-performing base model for all of the involved parameters. For instance, in the case of cadmium, random forest produced the best results, with adjusted R2 and RMSE of 0.108 and 0.014, as opposed to 0.337 and 0.013 obtained by the stacking method. The Mn and Cd showed a tight link with phosphate by the redundancy analysis (RDA). This demonstrates the effect of phosphate fertilizers on agricultural operations. In order to analyze the causes of groundwater pollution, spatial methodologies can be used with multivariate analytic techniques, such as RDA, to help uncover hidden sources of contamination that would otherwise go undetected. Lead has a larger health risk than nitrate, according to the probabilistic health risk assessment, which found that 34.4% and 6.3% of the simulated values for children and adults, respectively, were higher than HQ = 1. Furthermore, cadmium exposure risk affected 84% of children and 47% of adults in the research area.
英文关键词	Ensemble machine learning Groundwater Probabilistic health risk assessment Redundancy analysis Stacking
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001163799100011
WOS关键词	WATER-QUALITY ; PREDICTION ; NORTHEAST ; METALS ; MODELS
WOS类目	Engineering, Environmental ; Environmental Sciences ; Public, Environmental & Occupational Health ; Water Resources
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Public, Environmental & Occupational Health ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/403570
推荐引用方式 GB/T 7714	Sakizadeh, Mohamad,Zhang, Chaosheng,Milewski, Adam. Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area[J],2024,46(3).
APA	Sakizadeh, Mohamad,Zhang, Chaosheng,&Milewski, Adam.(2024).Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area.ENVIRONMENTAL GEOCHEMISTRY AND HEALTH,46(3).
MLA	Sakizadeh, Mohamad,et al."Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area".ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 46.3(2024).