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通过优化二次风多层分布降低生物质颗粒燃烧污染物排放及结渣率

Reduced Pollutant Emissions and Slagging Rate of Biomass Pellet Combustion by Optimizing the Multilayer Distribution of Secondary Air.

作者信息

He Zhisen, Liu Shanjian, Wang Shuaichao, Liu Weidong, Li Yongjun, Feng Xiangdong

机构信息

School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255049, China.

State Key Laboratory of Utilization of Woody Oil Resource, Zibo 255049, China.

出版信息

ACS Omega. 2022 Aug 8;7(33):28962-28973. doi: 10.1021/acsomega.2c02587. eCollection 2022 Aug 23.

Abstract

The utilization of coal and other fossil fuels is becoming increasingly restricted. Biomass, as a clean and renewable energy, plays a significant role in achieving zero carbon emissions. However, biomass is prone to slagging in the combustion process due to its high alkali metal content. The ash slagging rate and pollutant emission level of flue gas can be reduced by optimizing the air distribution, in order to decrease the fuel layer temperature in the combustion chamber. The results reveal opposite change trends of CO and NO concentrations in the flue gas. The NO emissions of corn stalk combustion under the multilayer secondary air distribution are obvious compared with those of rice husk combustion. The slagging rate of corn stalks is highly correlated with temperature of the fuel bed. The silica ratio (), alkali/acid ratio (/), Na content index (Na (index)), and alkaline index (Al ) cannot accurately predict the slagging tendency when temperature changes. Therefore, the modified predictive index ( ) was proposed to predict the slagging tendency of corn stalks with the combustion zone temperature effectively. The experimental results can contribute to the efficient combustion and low pollutant emissions of biomass.

摘要

煤炭和其他化石燃料的使用正受到越来越多的限制。生物质作为一种清洁的可再生能源,在实现零碳排放方面发挥着重要作用。然而,生物质由于其高碱金属含量,在燃烧过程中容易结渣。通过优化配风可以降低灰渣结渣率和烟气污染物排放水平,以降低燃烧室中的燃料层温度。结果表明,烟气中CO和NO浓度呈现相反的变化趋势。与稻壳燃烧相比,多层二次风配风条件下玉米秸秆燃烧的NO排放量明显。玉米秸秆的结渣率与燃料床温度高度相关。当温度变化时,硅铝比()、碱酸比(/)、Na含量指数(Na(指数))和碱性指数(Al )不能准确预测结渣倾向。因此,提出了修正预测指数( )以有效预测燃烧区温度 下玉米秸秆的结渣倾向。实验结果有助于生物质的高效燃烧和低污染物排放。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57b4/9404495/ab45375b3c10/ao2c02587_0002.jpg

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