Review of existing heavy metal contamination indices and development of an entropy-based improved indexing approach

2019 ◽  
Vol 22 (8) ◽  
pp. 7847-7864
Author(s):  
Kunwar Raghvendra Singh ◽  
Rahul Dutta ◽  
Ajay S. Kalamdhad ◽  
Bimlesh Kumar
2009 ◽  
Vol 8 (6) ◽  
pp. 1541-1551
Author(s):  
Corneliu Horaicu ◽  
Florea Cornel Gabrian ◽  
Irina Grozavu ◽  
Catalin Constantin Calu ◽  
Monica Horaicu ◽  
...  

1993 ◽  
Vol 27 (7-8) ◽  
pp. 263-269 ◽  
Author(s):  
B. Iosefzon-Kuyavskaya ◽  
N. Myrlyan ◽  
A. Shames

Electron Spin Resonance (ESR) was used for the examination oi dust samples collected from snow in an urban area. On the main doublet ESR line attributed to the signal of paramagnetic metals, a singlet line characteristic for stable free radical centers (FRC) was observed. A negative correlation of significant level between FRC signal intensity and heavy metal (HM) content was established. It was shown that FRC line intensity of dust may be used as a surrogate parameter for the estimation of air pollution by HM.


Author(s):  
Sangeetha Annam ◽  
Anshu Singla

Abstract: Soil is a major and important natural resource, which not only supports human life but also furnish commodities for ecological and economic growth. Ecological risk has posed a serious threat to the ecosystem by the degradation of soil. The high-stress level of heavy metals like chromium, copper, cadmium, etc. produce ecological risks which include: decrease in the fertility of the soil; reduction in crop yield & degradation of metabolism of living beings, and hence ecological health. The ecological risk associated, demands the assessment of heavy metal stress levels in soils. As the rate of stress level of heavy metals is exponentially increasing in recent times, it is apparent to assess or predict heavy metal contamination in soil. The assessment will help the concerned authorities to take corrective as well as preventive measures to enhance the ecological and hence economic growth. This study reviews the efficient assessment models to predict soil heavy metal contamination.


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