Effect of fuel feeding cycle adjustments on emissions in spruce pellet combustion with the application of a four-tube electrostatic precipitator
Abstract Air quality protection and emission reduction are essential for ensuring a high quality of life and public health. This study evaluates the influence of fuel dosage on the performance of an automatic pellet boiler, focusing on heat output, gaseous emissions (carbon monoxide, nitrogen and su...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11761-w |
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| Summary: | Abstract Air quality protection and emission reduction are essential for ensuring a high quality of life and public health. This study evaluates the influence of fuel dosage on the performance of an automatic pellet boiler, focusing on heat output, gaseous emissions (carbon monoxide, nitrogen and sulfur oxides), particulate matter and the efficiency of an electrostatic precipitator. Fuel dosage was adjusted through supply/standstill ratios in seconds (11/15, 14/20, 18/25, 22/30, 25/35), and a four-tube precipitator was designed, increasing the collection surface area by 1.6 times and improving particle separation efficiency. Results showed that fuel dosage did not impact heat output or nitrogen oxides. Carbon monoxide slightly increased as the fuel dosage interval widened without the precipitator but decreased marginally when the precipitator was operational. However, the use of the electrostatic precipitator did not have a significant impact on carbon monoxide, these values differed only very slightly. Particulate matter at 10% oxygen increased from 18.83 mg∙m⁻3 (11/15) to 26.82 mg∙m⁻3 (22/30) without the precipitator and decreased significantly with the optimized precipitator, achieving a maximum collection efficiency of 90.27% (18/25). Regression models developed for particulate matter concentrations and separation efficiency demonstrated strong predictive accuracy, with coefficient of determination values of 0.946 and 0.694, respectively. |
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| ISSN: | 2045-2322 |