Effects of the Limestone Particle Size on the Sulfation Reactivity at Low SO2 Concentrations Using a LC-TGA

被引:9
|
作者
Cai, Runxia [1 ]
Huang, Yiqun [1 ]
Li, Yiran [1 ]
Wu, Yuxin [1 ]
Zhang, Hai [1 ,2 ]
Zhang, Man [1 ]
Yang, Hairui [1 ]
Lyu, Junfu [1 ]
机构
[1] Tsinghua Univ, Dept Energy & Power Engn, Minist Educ, Key Lab Thermal Sci & Power Engn, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Tsinghua Univ Univ Waterloo Joint Res Ctr Micro N, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Limestone; particle size; sulfation; TGA; model; FLUIDIZED-BED COMBUSTION; SULFUR-DIOXIDE; PORE-STRUCTURE; COAL; OPTIMIZATION; CALCINATION; CARBONATE; REMOVAL; BOILERS; CAPTURE;
D O I
10.3390/ma12091496
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Limestone particle size has a crucial influence on SO2 capture efficiency, however there are few studies on the sulfation reactivity, which covers a broad range of particle sizes at low SO2 concentrations. In this paper, a large-capacity thermogravimetric analyzer (LC-TGA) was developed to obtain the sulfur removal reaction rate under a wide range of particle sizes (3 m-600 m) and SO2 concentrations (250 ppm-2000 ppm), and then compared with the results of a traditional fixed bed reactor and a commercial TGA. The experimental results showed that the LC-TGA can well eliminate the external mass transfer and obtain a better measurement performance. Both the final conversion and the reaction rate reduced with the decreasing of SO2 concentration, but ultrafine limestone particles still showed the good sulfation reactivity even at 250 ppm SO2. An empirical sulfation model was established based on the experimental results, which can well predict the sulfation process of different limestone particle sizes at low SO2 concentrations. The model parameters have a strong negative correlation against the particle size, and the fit of the reaction order of SO2 was found to be about 0.6. The model form is very simple to incorporate it into available fluidized bed combustion models to predict SO2 emission.
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页数:17
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