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Research Article Open access CC BY 4.0

Assessment of Heavy Metals in Rainwater from Metropolis and Suburbs, Lagos State, Nigeria

I. U. Iroegbulem, U. U. Egereonu, C. E. Ogukwe, J. C. Egereonu, N. J. Okoro, C. I. A. Nwoko

International Journal of Environment and Climate Change · pp. 831–857 · Published 10 Jul 2023

10.9734/ijecc/2023/v13i92304

Abstract

Heavy metal pollution poses a threat to rainwater which serves as a major alternative source for water for developing cities like Lagos. In the investigated of heavy metal in rainwater, 176 rainwater samples collected directly from the sky were analyzed from 2018 to 2019 during periods of light rainfall (Oct-Nov) and heavy rainfall (April-July). The pH> 5.6 indicated alkalinity. Light rainfall period average value 7.33 and heavy rainfall period 7.4.The MATLAB 7th degree polynomial regression described the relationship between dependent and independent variables for the pollutants. The correlation coefficient, R2 verified that the MATLAB models could accurately predict and forecast. Analysis of Variance (ANOVA) showed p<0.05 for Cadmium (Cd), Copper (Cu), Zinc (Zn), Iron (Fe) and Nickel (Ni), indicating that the probability that rainfall affected their concentration levels was high. The GIS Inverse Distance Weighted (IDW) pollution models revealed that the pollutants were present in the atmosphere throughout the year. It portrayed industrialized areas as the more affected areas thereby identifying anthropogenic activities as the main cause of these pollutants. During heavy rainfall periods hot spots appeared for Cd, Cu, Zn and Ni. In addition, Cd, Cu, Zn, Pb, and Ni were present in high concentration in the rainwater from suburb areas during periods of heavy rainfall. The concentration of heavy metals found in the rainwater follows the order: Fe>Zn>Ni>Cu>Cd>Pb. Cd and Pb exceeded WHO standards. Therefore there is need for rainwater treatment and monitoring by Government Agencies and parastatals to ensure public health and safety.

Rainwater heavy metals GIS model MATLAB model polynomial regression

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