Adsorption studies on coir pith for heavy metal removal

Biosorption efficiency of coir pith, a waste product from coir industry, was investigated in this study for the removal of metallic pollutants such as Ni, Cu and Zn from aqueous solutions. The disposal of coir pith is a major problem associated with the coir industries, especially working in the small-scale sector. The present study explores the effectiveness of utilization of coir pith, an accumulating waste, as a biosorbent for heavy metal removal. Batch mode studies were done to evaluate the efficiency of removal of metals under varying adsorption conditions of pH, metal concentration and contact time. Characterization studies of the biosorbent and SEM analysis were done. Kinetic modelling studies were tried using Lagergren pseudo-first-order and second-order models. Equilibrium studies were done using well-known Freundlich, Langmuir and D–R isotherm models. It was found that all isotherms are fitting well indicating the efficiency of coir pith as an adsorbent of heavy metals. The applicability of all the three isotherms to the sorption processes shows that both monolayer adsorption and heterogeneous energetic distribution of active sites on the surface of the adsorbent are possible. Due to the abundance and low cost of these materials, adsorption technologies developed can act as good sustainable options for the future in heavy metal removal from industrial effluents.     

Biodegradation of styrene laden waste gas stream using a compost-based biofilter

Biological treatment of waste gas styrene vapor was investigated in a three-stage bench-scale biofilter. Yard waste compost mixed with shredded hard plastics in a 25:75 v/v ratio of plastics:compost was inoculated with thickened municipal activated sludge. Microbial acclimation to styrene was achieved by exposing the system to an inlet concentration (C(In)) of 0.25 gm(-3) styrene and an empty bed retention time (EBRT) of 360 s for 30 days. Under steady-state conditions, maximum elimination capacity (EC) obtained was 45 gm(-3)h(-1) at a loading rate (L) of 60 gm(-3)h(-1) (C(In) of 2 gm(-3) and EBRT of 120 s). Reduction of retention time adversely impacted the performance resulting in the maximum EC of 39 and 27 gm(-3)h(-1) for EBRT of 60 and 30 s, respectively. Evaluation of the concentration profile along the bed height indicated dominance of first-order kinetics at C(In) < or = 0.45 gm(-3) and zero-order for higher concentrations.     

Effect of seasonal variations on the surface sediment heavy metal enrichment of a lake in South India

Environmental effects due to continuous accumulation of hazardous materials like heavy metals in the surface sediments of lake systems can stress fragile ecosystems. Elucidating the mechanisms influencing the concentration and distribution of heavy metals becomes vital in formulating lake management strategies to preserve the quality of the water environment. Studying of the effect of seasonal variations on surface sediments will help in understanding the different factors and sources contributing and diluting these persistent pollutants. In this study, heavy metal pollution in a tropical shallow lake (Akkulam-Veli) in South India was investigated by monitoring the seasonal variations of heavy metals and major elements in surface sediments. The metallic pollutants (Cr, Ni, Co, Cu, Zn, Pb, Fe, and Mn) and major elements (Si, Ti, Al, Ca, Mg, Na, K, and P (measured as oxides) in the surface sediments of this lake were monitored during four consecutive seasons. The results were subjected to correlation analysis and principal component analysis to study the interrelationships of different parameters as well to determine the possible origin of pollutants. Although metal concentrations were found to be unaffected by seasonal variations, the factors contributing to occurrence of these heavy metals were found to be affected by seasonal fluctuations.     

Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: A case study on Jajrood River (Tehran,Iran)

In this paper, principal component analysis (PCA) and hierarchical cluster analysis (CA) methods have been used to investigate the water quality of Jajrood River (Iran) and to assess and discriminate the relative magnitude of anthropogenic and “natural” influences on the quality of river water. T, EC, pH, TDS, NH₄, NO₃, NO₂, Turb., T.Hard., Ca, Mg, Na, K, Cl, SO₄, SiO₂ as physicochemical and TC, FC as biochemical variables have been analyzed in the water samples collected every month over a three-year period from 18 sampling stations along a 50 km section of Jajrood River that is under the influence of anthropogenic and natural changes. Exploratory analysis of experimental data has been carried out by means of PCA and CA in an attempt to discriminate sources of variation in water quality. PCA has allowed identification of a reduced number of mean 5 varifactors, pointing out 85% of both temporal and spatial changes. CA classified similar water quality stations and indicated Out-Meygoon as the most polluted one. Ahar, Baghgol, Rooteh, Befor Zaygan, Fasham, Roodak and Lashgarak were identified as affected by organic pollution. A Scree plot of stations in the first and second extracted components on PCA also gave us a classification of stations due to the similarity of pollution sources. CA and PCA led to similar results, though Out-Meygoon was identified as the most polluted station in both methods. Box-plots showed that PCA could approximately demonstrate temporal and spatial variations. CA gave us an overview of the problem and helped us to classify and better explain the PCA results.