The Development of Sensors for the Detection of Hydrocarbons in Oil spills

Abstract

The detection and control of petroleum contaminants resulting from oil spillage pollution of the environment remain a global challenge. Due to its adverse effects, crude oil discharge to the environment is regulated; one of the key parameters used for compliance monitoring is the measure of oil concentration. Typically, national environmental regulations require oil companies to keep the total hydrocarbons concentration resulting from oil spills at or below 50 mg/kg soil (50 ppm). For mitigation and compliance monitoring, most soil analyses for oil spillages rely on the use of the standard gas chromatographic methods, but these methods are expensive, require user-expertise and are not suitable for in situ analysis. This study develops and evaluates sensors for in situ detection of hydrocarbons in soil, targeting low power consumption and the use of inexpensive chemiresistive materials. This project is a field-academic collaboration sponsored by Schlumberger through its Faculty for the Future Foundation (FFTF), focusing on improving local communities through women in STEM. As such, in developing and demonstrating the proposed approach, contaminated soils were obtained from a crude oil field site in Akata, Niger Delta in Nigeria, as a case study. These samples were collected at three depths (0-20, 20-40, and 40-60 cm), two months and two years after a spill; oil from the samples was extracted using Soxhlet and Soxtec techniques. The extracts were analysed by gas chromatography-flame ionization detection to determine the types of hydrocarbons and their concentrations, as required to be detected by chemiresistors. The experimental results show that the concentration of the hydrocarbons increases with increasing distance and time from the epicentre of the spill and then decreases over time, indicating vertical migration. The analysis detected oil with carbon numbers ranging from C8 – C38 with concentrations as high as 65,000 mg/kg in the soil. The results obtained in this study afford an insight into the level of damage caused by oil spillages in the Akata community of the Niger Delta region in Africa. This thesis presents an attractive approach of using chemiresistors as an alternative to the conventional gas chromatographic-based methods for the detection of petroleum hydrocarbons in the soil. The proposed system is intended to be used at different stages of the pollution in order to prevent further infiltration into the soil. As such, this work focuses on the right choice of materials, cost, and the technical capability of sorption processes to rapidly detect and quantify these contaminants. Composites of non-conducting polymers, poly(methyl) methacrylate, (PMMA) and poly(vinyl) chloride (PVC), and conductive filler carbon black (CB) were selected and prepared to make polymer-based sensors. The films were dried to evaporate the solvent; the morphology of the films was characterised using scanning electron microscopy (SEM). The impact of carbon concentration and geometry on the measured resistance of the polymer composite to hydrocarbons was determined. The films’ performance were consistent with increasing mass fraction with an optimum response at 10% w/w carbon black and 90% w/w polymer. Two sets of polymer-based sensors CB-PMMA and CB-PVC, were fabricated by depositing thin films of a CB-polymer onto interdigitated electrodes. The deposited composite films completed a circuit, providing electrical resistance. The detected concentration is proportional to the relative differential resistance response. Polymer composition and stability and the sensor response data obtained resulted in the fabrication of chemiresistors for the detection of hydrocarbon compounds, including eicosane – a high molecular weight compound not previously tested in electronic nose technology. Experimental optimisation studies allowed variation in the nature of the responses obtained. The result obtained provided information on sensor responses relat

Date of Award	1 Aug 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Krishna Persaud (Supervisor)