Response surface methodology (RSM) and principal component analyses (PCA) modelling tools have been used in this study to quantitatively describe the interaction effects of more than one factor on system response for the modelling and optimization of experimental data. In Nigeria, there are no stringent policies in place by the government on paint production and this has led to unregulated paint products by producers in the commercial markets. Water-based paints currently available in Nigerian market were sampled. Experimental data of Metals (As, Ca, Cd, Cr, Cu, Fe, Mg, and Pb) and Ethylene glycol butyl ether (Volatile organic compounds (VOC)) measured using Inductively Coupled Plasma-Optical Emission Spectrometer (ICP-OES) and Gas Chromatography-Flame Ionisation Detector (GC-FID), respectively was used to develop a mathematical model. The principal component analyses were explained with a cumulative variance of 82% for the VOC and 76% for metals based on manufacturers. Estimated responses were compared with the experimentally determined responses and prediction capabilities of Response Surface Methodology. In the RSM, the 2 developed model had R value of 0.9569, with optimized value at 0.10 % (1000ppm) of Ethylene glycol butyl ether and concentration (ppm) ranges of As (383.0-1,930.0), Ca (614.0-10,400.0), Cd (98.0-2,000.0), Cr (10.3- 225.0), Cu (133.0-1,840.0), Fe 742.0-2,910.0, Mg (4,000.0-99,510.0), Pb (170.0-3,230.0). The correlation and optimization study employed are applicable for assessing the impact of hazardous air pollutants on indoor air quality and a good applicability in paint industries to produce products within the set limit of international standards. For the purpose of reducing sick building syndrome and protecting public health, it was important to investigate paints and sealers extensively.
Keywords: VOCs; Paint; metals; Ethylene glycol butyl ether; Response Surface Method
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