Mayank Pandey

Assessment of metal species in river Ganga sediment at Varanasi, India using sequential extraction procedure and SEM-EDS.

Aim of the present study was to assess impact of urban drains over river water and sediments by physico-chemical and metal analysis. Metal speciation (Sequential Extraction Procedure) and elemental composition analysis (SEM-EDS) was used to quantify metal pollution load in river sediments. Metal speciation analysis showed dominance of available and labile fractions of all heavy metals (Cr, Ni, Cu, Zn, Cd and Pb) except Mn and Fe which were dominant in residual forms. Cluster analysis (CA), Principal Components Analysis (PCA) and Partial Least Square Regression (PLSR) were applied as source receptor modeling for pollutants. Results classified river stretch into three zones i.e. moderately, severely and extremely polluted, on the basis of pollutant concentration released from anthropogenic sources. SEM-EDS study revealed the elemental composition percentage in river sediments. Pollution Load Index (PLI) varied from 1.8 (S1)-3.9 (S15). The Geo accumulation index (GAI) was found highest for Cd (6.88-8.97) and Pb (2.41-3.24).

Application of chemometric analysis and self Organizing Map-Artificial Neural Network as source receptor modeling for metal speciation in river sediment.

Present study deals with the river Ganga water quality and its impact on metal speciation in its sediments. Concentration of physico-chemical parameters was highest in summer season followed by winter and lowest in rainy season. Metal speciation study in river sediments revealed that exchangeable, reducible and oxidizable fractions were dominant in all the studied metals (Cr, Ni, Cu, Zn, Cd, Pb) except Mn and Fe. High pollution load index (1.64-3.89) recommends urgent need of mitigation measures. Self-organizing Map-Artificial Neural Network (SOM-ANN) was applied to the data set for the prediction of major point sources of pollution in the river Ganga.

Assessment of Air Pollution Tolerance Index of some plants to develop vertical gardens near street canyons of a polluted tropical city.

The aim of the present study was to examine Air Pollution Tolerance Index (APTI) of some climber plant species to develop vertical gardens in Varanasi city which has characteristics of tall building and narrow roads. This condition results in street canyon like structure and hinders the vertical dispersal of air pollutants. We have selected 24 climber plant species which are commonly found in of Varanasi city. Chosen plants can be easily grown either in planter boxes or directly in the ground, with a vertical support they can climb on walls to form green walls or vertical garden. Air Pollution Tolerance Index (APTI) of the selected plant species was calculated and plants with higher APTI are recommended for the development of Vertical garden. Highest APTI was noted for Ipomoea palmata (25.39) followed by Aristolochia elegans (23.28), Thunbergia grandiflora (23.14), Quisqualis indica (22.42), and Clerodendrum splendens (22.36). However, lowest APTI value (8.75) was recorded for the species Hemidesmus indicus. Moreover, the linear regression analysis has revealed a high positive correlation between APTI and ascorbic acid content (R2=0.8837) and positive correlation between APTI and Chlorophyll content (R2=0.6687). On the basis of higher APTI values (greater than 17), nine species of climber plants viz. I. palmata, T. grandiflora, C. splendens, A. elegans, Q. indica, Petria volubilis, Antigonon leptopus, Cryptolepis buchuanni and Tinospora cordifolia have been recommended to develop vertical greenery systems in a compact tropical city.