Evaluating aerial pollution using rainwater chemistry for sustainable environmental development

Abstract

Purpose The purpose of this paper is to use rainwater quality parameters as indicators of pollution to assess the level of aerial pollution for sustainable environmental development. Design/methodology/approach Rainwaters were collected in open spaces within commercial, industrial and residential areas in Ibadan metropolis, Nigeria during onset, peak and late rainy season. Values of NO3−, NH4+, Cl−, SO42−, pH, electrical conductivity, total dissolved solid, total acidity and total alkalinity were determined using certified wet chemistry procedures, whereas those of Ca2+, Na+, K+ and Mg2+ were measured using atomic absorption spectrophotometry. Findings Overall results showed that the concentrations of the physical parameters, anions and cations, were comparatively higher at the onset of the rainy period than the latter periods, indicating washout of the pollutants as the rainy season progressed. Results of Pearson correlation matrix and Cluster analysis results showed that many of the parameters have similar source(s). Analysis of variance and t-test results indicated significant difference between the concentrations of the analyzed parameters at different rainy periods, whereas ratio values of sea salt fraction were higher than non-sea salt fraction for all species, depicting anthropogenic influences. Originality/value From the findings, the study concluded that the quality of the rainwaters was substandard due elevated levels of most of the analyzed quality parameters; this method proved to be economical, effective and simple compared to the conventional methods; it also proved rainwater quality to be a reliable pointer of aerial pollution and the concept can be used to assess the pollution level of areas of similar settings.

Validity and reliability of sustainable supply chain management frameworks in Indian smart manufacturing industries

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Environmental Regulation and Development Transformation in the Tropical and Subtropical Cities of China: A Big Data Analysis

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