Pollution assessment and source apportionment of heavy metals in contaminated site soils

2018 ◽  
Author(s):  
Hongbo Zheng ◽  
Yan Ma
Keyword(s):  
Heavy Metals ◽  
Source Apportionment ◽  
Pollution Assessment ◽  
Contaminated Site

Assessment of Heavy Metals Content in the Proximity of a Contaminated Site From Cluj-Napoca (Romania)

2020 ◽  
Vol 65 (2) ◽  
pp. 17-37
Author(s):  
Georgiana Grosu ◽  
◽  
Carmen Andreea Roba ◽  
Ramona Bălc ◽  
Maria Lucia Bizău-Cârstea ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Sediment Contamination ◽  
Contaminated Site ◽  
Pollution Indices ◽  
Chemical Parameters ◽  
Multivariate Statistical ◽  
Water And Sediment ◽  
Physico Chemical

The present study was conducted in the proximity of a contaminated site from Cluj-Napoca city (Cluj County, Romania), where metal processing activities have been carried out for decades. Metal content and physico-chemical parameters were analyzed in soil, water and sediment samples, while organic matter (OM) and total organic carbon (TOC) was additionally analyzed for the soil samples. The sources of heavy metals were evaluated based on multivariate statistical analysis, while the soil and sediment contamination degree was assessed based on specific pollution indices. The calculated indices indicated a significant pollution with Cd and Pb, which may represent a risk if the area would become a residential area. Keywords: heavy metals, contaminated site, soil pollution indices, multivariate statistical analysis, Cluj-Napoca

Source apportionment of heavy metal pollution in farmland soils on a regional scale using geographically weighted PCA

2021 ◽  
Author(s):  
Liu Shuyi ◽  
Gao Bingbo
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Source Apportionment ◽  
Rapid Development ◽  
Regional Scale ◽  
Analytical Framework ◽  
Pollution Sources ◽  
Entire Study ◽  
Soil Heavy Metals ◽  
Farmland Soils

<p>Source apportionment of soil heavy metals is an challenge and urgent work as the result of the rapid development of industrialization and urbanization. The common approach is multivariate statistical analysis, such as PCA and APCS/MLR, which infers only a single pattern of sources of heavy metals in entire study area. Due to complicated pathways and processes, patterns of pollution sources in a whole region may include two or more. Hence, we developed an analytical framework based on GWPCA to explore multiple patterns of sources of soil heavy metals on a regional scale. Xiangtan county, an important grain-producing area in China, was taken as a case study, which suffers the problem of heavy metal pollutions. Our results revealed the pollution situations of five soil heavy metals(Pb, Cd, As, Cr and Hg) in farmland soils and suggested that there exists various pollution patterns of these heavy metals in Xiangtan county. In each pattern, the structure of contamination sources is different. Our study also indicates that the analytical framework considering the spatial heterogeneity of pollution sources can help take more precise practices to solve this vital problem.</p> <p> </p>

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