| Issue |
E3S Web Conf.
Volume 702, 2026
Second International Conference on Innovations in Sustainable and Digital Construction Practices (ISDCP 2026)
|
|
|---|---|---|
| Article Number | 02001 | |
| Number of page(s) | 12 | |
| Section | Environmental Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202670202001 | |
| Published online | 01 April 2026 | |
A Study Using Simulation to Remove Petroleum Hydrocarbons through Bioremediation and Resource Recovery
1 KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
2 Tribhuvan University, Pulchowk Campus, Kathmandu, Nepal
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Petroleum hydrocarbons are one of the most widespread and persistent organic pollutants, caused by the worldwide dependence on oil as an energy source. The presence of petroleum hydrocarbons in soil and wastewater around oil refineries and oil handling facilities is a serious threat to the environment and human health, as these substances are highly toxic and persistent. This paper proposes a bioremediation approach for petroleum hydrocarbons, with toluene used as a representative aromatic contaminant for simulation purposes, while simultaneously producing methane as valuable byproduct. The system uses kinetic modeling and real-time optimization in MATLAB based on simplified lumped Monod-type and first-order kinetic assumptions, while Aspen HYSYS is used for process simulation, material and energy balance calculations. The simulation results, obtained under steady-state anaerobic conditions at mesophilic temperature, show substantial removal of petroleum hydrocarbons and efficient methane-rich gas production, thus emphasizing the potential of system for sustainable resource management. The proposed method is consistent with SDG-United Nations for clean water, responsible production, and climate action. The study is fully simulation-based relies on literature-derived and assumed parameters, the quantitative results should be interpreted as indicative trends rather than exact predictions, and experimental validation is required to reduce uncertainty.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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