Optimal Production Planning and Pollution Control in Petroleum Refineries Using Mathematical Programming and Dispersion Models

Amani Alnahdi, Ali Elkamel, Munawar A. Shaik, Saad A. Al-Sobhi and Fatih S. Erenay
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Amani Alnahdi: Department of Chemical Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Ali Elkamel: Department of Chemical Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Munawar A. Shaik: Department of Chemical Engineering, Khalifa University, SAN Campus, Abu Dhabi 2533, UAE
Saad A. Al-Sobhi: Department of Chemical Engineering, Qatar University, Doha 2713, Qatar
Fatih S. Erenay: Department of Management Sciences, University of Waterloo, Waterloo, ON N2L 3G1, Canada

Sustainability, 2019, vol. 11, issue 14, 1-31

Abstract: Oil refineries, producing a large variety of products, are considered as one of the main sources of air contaminants such as sulfur oxides (SO x ), hydrocarbons, nitrogen oxides (NO x ), and carbon dioxide (CO 2 ), which are primarily caused by fuel combustion. Gases emanated from the combustion of fuel in an oil refinery need to be reduced, as it poses an environmental hazard. Several strategies can be applied in order to mitigate emissions and meet environmental regulations. This study proposes a mathematical programming model to derive the optimal pollution control strategies for an oil refinery, considering various reduction options for multiple pollutants. The objective of this study is to help decision makers select the most economic pollution control strategy, while satisfying given emission reduction targets. The proposed model is tested on an industrial scale oil refinery sited in North Toronto, Ontario, Canada considering emissions of NO x , SO x , and CO 2 . In this analysis, the dispersion of these air pollutants is captured using a screening model (SCREEN3) and a non-steady state CALPUFF model based on topographical and meteorological conditions. This way, the impacts of geographic location on the concentration of pollutant emissions were examined in a realistic way. The numerical experiments showed that the optimal production and pollution control plans derived from the proposed optimization model can reduce NO x , SO x , and CO 2 emission by up to 60% in exchange of up to 10.7% increase in cost. The results from the dispersion models verified that these optimal production and pollution control plans may achieve a significant reduction in pollutant emission in a large geographic area around the refinery site.

Keywords: refinery production planning; air pollution control; optimization of economic and environmental impacts; dispersion models (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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