Statistical analysis of seasonal variation in the characteristics of soil like material and refuse derived fuel recovered from landfill mining.

Autor: Saravanan, Gurusamy, Ramesh, Srikrishnaperumal Thangam
Předmět:
Zdroj: Stochastic Environmental Research & Risk Assessment; Jan2024, Vol. 38 Issue 1, p127-146, 20p
Abstrakt: Landfill Mining (LFM) is the sustainable process of clearing legacy waste from Unscientifically Created Landfills/Dumpsites (UCLDs). The major fractions recovered from LFM are Soil like material (SLM) and Refuse Derived Fuel (RDF). The physicochemical properties and heavy metal concentrations in SLM and RDF recovered from the landfill mining process at the Ariyamangalam dumpyard Tiruchirappalli, India, were analysed to understand the seasonal variation in the characteristics over a period of one year. Multivariate Statistical techniques, such as correlation analysis, cluster analysis, and Principal Component Analysis (PCA), were applied to various SLM characteristics, including leachable heavy metals concentration and RDF parameters. Among the twelve months, most of the parameters and heavy metals have a greater concentration in the winter season. Correlation analysis indicates that heavy metals were observed to have a significant correlation among each other, out of which copper and zinc appear to have a stronger correlation. Biodegradability acts as an indicating factor by significantly correlating with nitrogen, phosphate, total organic carbon (TOC) and hexavalent chromium. The cluster analysis for monthly variation was presented as a dendrogram that shows the similarity between two months in each season and found below the Euclidean distance of 50 and 150 for SLM and RDF, respectively. PCA results suggest that Pb, Cu and Zn contribute higher loading among all the heavy metals for SLM and Fixed Carbon (FC) for RDF. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index