Abstract
Abstract
In the present work, an experimental investigation on the effect of sulfur content in heavy fuel oil (HFO) on the gaseous emissions under swirling flame conditions was carried out. The sulfur content in HFO was varied by blending with ultra-low sulfur diesel and four fuel samples containing 3.15, 2.80, 1.97 and 0.52 % sulfur (by mass) were prepared. The fuels were then fired in a high-swirl stabilized, turbulent spray flame. The combustion performance of the fuels was evaluated by measuring flame temperature distribution, gaseous emissions (SOx, NOx, CO, CO2, and flue gas pH) and particulate matter (PM) emissions (morphology, composition, and pH). The results showed a significant reduction in the SO2 emissions and acidity of the flue gas when the sulfur content in the fuel was reduced, as expected. Flue gas SO2 concentration reduced from 620 ppm to 48 ppm when the sulfur content in the fuel was reduced from 3.15 to 0.52 % (by mass). Sulfur balance calculations indicate that nearly 97.5% of the sulfur in the fuel translates into gaseous emissions and the remaining 2.5% appears in PM emissions. Ninety-five percent of gaseous sulfur emissions are SO2, whereas the rest appears as SO3. Varying the sulfur content in the fuel did not have a major impact on the flame temperature distribution or NOx emissions. The morphologies and size distribution of the PM did not change significantly with sulfur content as asphaltenes content of the fuels remained the same.
Original language | English (US) |
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Pages (from-to) | 1-16 |
Number of pages | 16 |
Journal | Journal of Energy Resources Technology |
DOIs | |
State | Published - Oct 29 2020 |
Bibliographical note
KAUST Repository Item: Exported on 2020-11-04Acknowledgements: Research reported in this publication was supported by Saudi Electric Company (SEC) and by competitive research funding from King Abdullah University of Science and Technology (KAUST). The authors acknowledge support from the Clean Combustion Research Center under the Future Fuels research program. This research used resources of the Core Labs of King Abdullah University of Science and Technology (KAUST).