Statistical aproach to unravelling heavy metal contamination on sub-soils and roadside dust

Nsukka is a rapidly developing City with considerable number of commercial activities, such as increasing number of vehicles, automobile shops and vehicular movement. Emissions from these vehicles, wastes from automobile shops and petrochemical retail shops pose a serious environmental concern. The aim of this study is centred on the assessment of heavy metal pollution in dust and top soil along major roads within in Nsukka metropolis using multivariate statistical analyses to unravel the relationships between the analysed parameters, and how they predict each other. A total of 21 samples of soil and dust were collected along the major and minor roads in Nsukka town at zero metre (0 m) and 0.5 m depth for dust and soil, respectively. Three control samples were collected at 400 m distance from the road for comparative reasons. For the two depths, two trends of relationships were established from the correlation, cluster and factor analyses. The first trend could be attributed to geogenic contamination due to its direct relationship with iron which happens to be the dominant heavy metal associated with Nsukka Formation. The second trend of analysis could be attributed to anthropogenic impacts due the presence of automobile and petrochemical wastes indicator parameters. There was no significant spatial variation (@p > 0.05) in the values of parameters such as arsenic and manganese for 0 m depth while in 0.5 m depth, there was no significant spatial variation (@p > 0.05) in the values of parameters such as arsenic, manganese and nickel.