Development of a Real–Time Petroleum Products Aduteration Detector

Abstract

Adulteration of petroleum products with the resultant safety, health, environmental and economic impact is a challenge in Nigeria and many developing countries. While the commonly used techniques by regulatory agencies and some end-users for quality assurance of petroleum products are time-consuming and expensive. This study was therefore designed to develop a device for real-time detection of petroleum products adulteration. Samples of petrol, diesel and kerosene were collected; samples of water, naphtha, alcohol, pure and used lubricating oil, and High Pour Fuel Oil (HPFO) were collected and used as liquid contaminants while saw dust, ash and fine sand were used as solid particulates. At temperatures between 23-28°C (1°C interval), binary mixtures were prepared using the pure products with liquid contaminants (95:5, ..,5: 95 V/V) and with particulates (0, 2, 4, 6, 8,10 g). New mixing rules were developed for the SG and IFT of the binary liquid mixtures and compared with Kay mixing rule. Developed mathematical models of the physical-chemical properties were used to simulate a meter designed and constructed around a microcontroller with multiple input/output pins and a load cell sensor. The SG and IFT of the pure liquid and solid binary mixtures ranged from 0.810 to 1.020, 25.5 to 47.2 dynes/cm and 0.820 to 1.080 and 26.3 and 50.2 dynes/cm respectively. For products contaminated with solid particulates, SG varied between 0.860 and 0.990. The new mixing rule gave coefficient of 0.84 and 27.8 for SG and IFT compared with 0.83 and 25.6 of Kay's model. Adulteration of products was detected at 20-30% by volume and 10-20% by mass of contamination, and displayed RED for adulterated samples, GREEN for pure samples and numerical values of SG in digital form which were within ±0.01 % of actual measurements. A device for real-time detection of adulteration in petroleum products was developed which can be adapted to real-time evaluation of similar binary mixtures.