• Journal of ILASS-Korea
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• v.18 no.2
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• pp.106-111
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• 2013

Adulterations fuel have been using in the vehicle in these days. Because gasoline, diesel prices are rising every day. so people find more cheap price fuel. Adulterations fuel caused a serious air pollution problems. Adulteration fuel were made from waste engine oil, waste paint. According to Government regulations permit to be used recycle fuel(adulteration fuel) only in industrial boiler. Unburned fuel pollutants are effected to human health. In this paper, the hazardous air pollutants characteristics in the diesel vehicles according to adulterations of vehicle fuels were carried out in the NEDC test mode in chassis dynamometer. It is revealed that the all of the regulation pollutants (THC, NOx, CO and PM) emission in the adulterations of vehicle fuels was increased also the green house gas, $CO_2$ was increased. In the hazardous air pollutants characteristics, the VOCs(Volitile Organic Compounds) BTEX(Benzene, Toluene, Ethylbenzene, Xylene) emissions in the adulterations of vehicle fuels showed higher level than these in the diesel fuels.

• Korean Journal of Agricultural Science
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• v.46 no.2
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• pp.257-271
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• 2019

The use of food grade hexane (FGH) for edible oil extraction is responsible for the presence of benzene in the crude oil. Benzene is a Group 1 carcinogen and could pose a serious threat to the health of consumer. However, its detection still depends on classical methods using chromatography which requires a rapid non-destructive detection method. Hence, the aim of this study was to investigate the feasibility of using Fourier transform infrared (FTIR) spectroscopy combined with multivariate analysis to detect and quantify the benzene residue in edible oil (sesame and cottonseed oil). Oil samples were adulterated with varying quantities of benzene, and their FTIR spectra were acquired with an attenuated total reflectance (ATR) method. Optimal variables for a partial least-squares regression (PLSR) model were selected using the variable importance in projection (VIP) and the selectivity ratio (SR) methods. The developed PLS models with whole variables and the VIP- and SR-selected variables were validated against an independent data set which resulted in $R^2$ values of 0.95, 0.96, and 0.95 and standard error of prediction (SEP) values of 38.5, 33.7, and 41.7 mg/L, respectively. The proposed technique of FTIR combined with multivariate analysis and variable selection methods can detect benzene residuals in edible oils with the advantages of being fast and simple and thus, can replace the conventional methods used for the same purpose.