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Effects of H2O on NO Emission during Oxy-coal Combustion with Wet Recycle

This study investigated the characteristics of NO emissions during oxy-coal combustion with wet-recycle, especially in the presence of high H2O concentrations. The oxy-combustion was carried out using two types of coal, namely Leiyang (LY) anthracite and Zhundong (ZD) bituminous coals, inside a 24 kW drop tube furnace under different O2/CO2/H2O atmospheres. The results showed that the NO conversion increased with decreasing CO2 concentration from 70% to 30% and decreased with increasing H2O concentration from 10% to 40%. Under the experimental conditions employed in this study, the fuel-N conversion for both LY and ZD coals under the oxy-coal wet recycled combustion was lower than that under the oxy-coal dry recycled combustion. The results indicated that H2O and CO2 showed a competitive effect on NO emissions, though both of them have positive effect on NO reduction. In order to investigate the effects of H2O/CO2 on recycled NO, oxy-coal combustion experiments were also performed with the initial additio...
- Huazhong University of Science and Technology China (People's Republic of)
- State Key Laboratory of Coal Combustion China (People's Republic of)
- Universiti Teknologi MARA Malaysia
- Universiti Teknologi MARA Malaysia
- Henan Polytechnic University China (People's Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).25 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
