Abstract
Background.Several studies have demonstrated that chromium (Cr) and cadmium (Cd) have adverse impacts on the environment and human health. These elements are present in electronic waste (e-waste) recycling sites. Several interpolation methods have been used to evaluate geographical impacts on humans and the environment.Objectives.The aim of the present paper is to compare the accuracy of inverse distance weighting (IDW) and ordinary kriging (OK) in topsoil analysis of e-waste recycling sites in Douala, Cameroon.Methods.Selecting the proper spatial interpolation method is crucial for carrying out surface analysis. Ordinary kriging and IDW are interpolation methods used for spatial analysis and surface mapping. Two sets of samples were used and compared. The performances of interpolation methods were evaluated and compared using cross-validation.Results.The results showed that the OK method performed better than IDW prediction for the spatial distribution of Cr, but the two interpolation methods had the same result for Cd (in the first set of samples). Results from Kolmogorov-Smirnov and Shapiro-Wilk tests showed that the data were normally distributed in the study area. The p value (0.302 and 0.773) was greater than 0.05 for Cr and for Cd (0.267 and 0.712). In the second set of samples, the OK method results (for Cd and Cr) were greatly diminished and the concentrations dropped, looking more like an average on the maps. However, the IDW interpolation gave a better representation of the concentration of Cd and Cr on the maps of the study area. For the second set of samples, OK and IDW for Cd and Cr had more similar results, especially in terms of root mean square error (RMSE).Conclusions.Many parameters were better identified from the RMSE statistic obtained from cross-validation after exhaustive testing. Inverse distance weighting appeared more adequate in limited urban areas.Competing Interests. The authors declare no competing financial interests
Highlights
Soil is an important part of the urban ecosystem that directly and indirectly affects general quality of life.[1]
The results showed that the ordinary kriging (OK) method performed better than inverse distance weighting (IDW) prediction for the spatial distribution of Cr, but the two interpolation methods had the same result for Cd
It provided quantitative information on the best interpolation method for heavy metals in e-waste sites located in urban areas
Summary
Soil is an important part of the urban ecosystem that directly and indirectly affects general quality of life.[1]. Ordinary kriging and IDW are interpolation methods used for spatial analysis and surface mapping. J Health Pollution 26: (200605) 2020 © Pure Earth sampling and interpolation method employed.[7] Spatial interpolation techniques such as ordinary kriging (OK) and inverse distance weighted (IDW) are widely applied in soil geochemistry for the production of spatial distribution maps of soil parameters.[8,3] Geostatistical methods can provide reliable estimates in locations that have not been sampled.[9,10] Spatial prediction techniques, known as spatial interpolation techniques, differ from classical modeling approaches as they incorporate information on the geographic position of the sample data points.[11] The most common interpolation techniques evaluate the estimate for a property at any given location by a weighted average of nearby data.[12]
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