The environmental concerns of C02 emissions resulting from the increasing consumption of fossil fuels over the past decades has called for greater utilisation of renewable energy resources such as solar energy, wind power and biomass energy. Currently, biomass combustion is the dominant conversion technology that is used to extract energy from biomass feedstock at all scales. However, biomass combustion can lead to significant amounts of gaseous (e.g. NOx, CO) and particulate matter (PM) emissions, which is a particular concern for simple and small scale biomass combustion stoves and boilers. The present PhD work aims to achieve low emissions of NOx, CO and PM with a 50kW commercial boiler burning different woody and non-woody biomass pellets by the use of combustion modifications and a particulate removal unit. The combustion performance and emissions of NOx, CO and PM of the boiler were experimentally investigated with three different types of woody and non-woody biomass fuels. Different operating conditions for the minimisation of NOx and CO emissions, including the 'air staging' method and the novel 'reverse flame box' system, have been studied. An innovative particulate filter unit was installed in the flue path of the boiler as a means to reduce PM emissions. CFD modelling of the tested boiler has been carried out and the simulation results have been presented and discussed in this thesis. The experimental results showed that the modified biomass boiler could handle woody biomass pellets while maintaining low levels of CO and NOx emissions. It could also handle non-woody biomass pellets if appropriate additives are added. An approximate 40% NOx reduction was achieved when the boiler was incorporated with a novel low emissions strategy termed as a 'reverse flame box', compared to the original boiler design. With the use of the innovative particulate filter unit, the PM emissions were reduced to about 1 mg/m3, which shows the particulate filter unit reduces PM emissions by over 98%. For the CFD simulation, the modelling results showed the correct trends, although it did not predict adequately the degree to which the boiler configurations affect the emissions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:659188 |
| Date | January 2014 |
| Creators | Li, Jinxing |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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