Combination of compositional data analysis and machine learning approaches to identify sources and geochemical associations of potentially toxic elements in soil and assess the associated human health risk in a mining city.
Environ Pollut
; 261: 114210, 2020 Jun.
Article
em En
| MEDLINE
| ID: mdl-32109822
ABSTRACT
Mining activities change the chemical composition of the environment and have negative reflection on people's health and there is no single measure to deal with adverse consequences of mining activities, as each case is specific and needs to be understood and mitigated in a unique way. In this study, the combination of compositional data analysis (CoDA), k-means algorithm, hierarchical cluster analysis applied to reveal the geochemical associations of potentially toxic elements (PTE) in soil of Alaverdi city (Armenia) (Ti, Fe, Ba, Mn, Co, V, Pb, Zn, Cu, Cr, Mo, As). Additionally, to assess PTE-induced health risk, two commonly used approaches were used. The obtained results show that the combination of CoDA and machine learning algorithms allow to identify and describe three geochemical associations of the studied elements the natural, manmade and hybrid. Moreover, the revealed geochemical associations were linked to the natural pattern of distribution of the element concentrations including the influence of the natural mineralization of the parent rocks, as well as the emission from the copper smelter and urban management related activities. The health risk assessment using the US EPA method demonstrated that the observed contents of studied elements are posing a non-carcinogenic risk to children in the entire territory of the city. In the case of adults, the non-carcinogenic risk was identified in areas situated close to the copper smelter. The Summary pollution index (Zc) values were in line with the results of the US EPA method and indicated that the main residential part of the city was under the hazardous pollution level suggesting the possibility of increase in the overall incidence of diseases among frequently ill individuals, children with chronic diseases and functional disorders of vascular system. The obtained results indicated the need for further in-depth studies with special focus on the synergic effect of PTE.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Poluentes do Solo
/
Monitoramento Ambiental
/
Medição de Risco
/
Aprendizado de Máquina
/
Análise de Dados
/
Mineração
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article