scholarly journals Investigation of SPAD values and morphometric characteristics of leaves in wild blackberry populations on Stara Planina Mt.

2021 ◽  
Vol 30 (1) ◽  
pp. 19-28
Author(s):  
Jovana Janković ◽  
Vera Vidaković ◽  
Srđan Bojović ◽  
Zorica Popović
Keyword(s):  
Heavy Metal ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Natural Populations ◽  
Forest Community ◽  
Leaf Width ◽  
Total Chlorophyll ◽  
Population Differences ◽  
Light Conditions ◽  
Morphometric Characteristics

Natural populations of Rubus hirtus Waldst. & Kit. were studied at three locations along the Gabrovnica river on Stara Planina mountain, to assess the inter-population differences in ecophysiological and ecomorphological parameters. The content of total chlorophyll in leaves, estimated by the SPAD method, as well as leaf width and leaf width/length ratio had the highest values in population A, which inhabits a forest community dominated by hornbeam and sessile oak and grows in vegetative shade. Populations B (which is also located within the forest complex) and C (which is located in a relatively open habitat) had lower values for the examined parameters. Inter-population differences in the examined parameters can be partially interpreted as an adaptation to habitat light conditions (significant differences between individuals from populations A and C). However, the values of parameters in population B cannot be explained by light conditions, indicating the need to consider complex environmental conditions at that site, primarily heavy metal contamination of soil and groundwater.

ASSESSMENT OF HEAVY METAL CONTAMINATION AND IMPACT ON SURFACE WATERS IN IASI CITY, ROMANIA

2009 ◽  
Vol 8 (6) ◽  
pp. 1541-1551
Author(s):  
Corneliu Horaicu ◽  
Florea Cornel Gabrian ◽  
Irina Grozavu ◽  
Catalin Constantin Calu ◽  
Monica Horaicu ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Surface Waters ◽  
Metal Contamination ◽  
Heavy Metal Contamination

Esr Indication of Heavy Metal Contamination of Urban Atmosphere

1993 ◽  
Vol 27 (7-8) ◽  
pp. 263-269 ◽  
Author(s):  
B. Iosefzon-Kuyavskaya ◽  
N. Myrlyan ◽  
A. Shames
Keyword(s):  
Heavy Metal ◽  
Air Pollution ◽  
Electron Spin Resonance ◽  
Free Radical ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Urban Atmosphere ◽  
Stable Free Radical ◽  
Spin Resonance ◽  
Line Characteristic

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.

A brief Survey of Assessment models to Predict stress Level of Heavy Metals in Soils

2020 ◽  
Vol 13 ◽  
Author(s):  
Sangeetha Annam ◽  
Anshu Singla
Keyword(s):  
Economic Growth ◽  
Heavy Metals ◽  
Heavy Metal ◽  
Ecological Risk ◽  
Stress Level ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Human Life ◽  
High Stress ◽  
Heavy Metal Stress

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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