4.7 Article

Thermal characteristics of the combustion process of biomass and sewage sludge

期刊

JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
卷 114, 期 2, 页码 519-529

出版社

SPRINGER
DOI: 10.1007/s10973-012-2933-y

关键词

Biomass; Sewage sludge; Combustion; Thermogravimetric analysis; Mass spectrometry; Kinetic analysis

资金

  1. Polish Ministry of Science and Higher Education [AGH 15.11.110.088]

向作者/读者索取更多资源

The combustion of two kinds of biomass and sewage sludge was studied. The biomass fuels were wood biomass (pellets) and agriculture biomass (oat). The sewage sludge came from waste water treatment plant. The biomass and sludge percentage in blends with coal were 10 %. The studied materials were characterised in terms of their proximate and ultimate analysis and calorific value. The composition of the ash of the studied fuels was also carried out. The behaviour of studied fuels was investigated by thermogravimetric analysis (TG, DTG and DTA). The samples were heated from an ambient temperature up to 1,000 A degrees C at a constant three rates: 10, 40 and 100 A degrees C min(-1) in 40 mL min(-1) air flow. TG, DTG and DTA analysis showed differences between coal, biomass fuels and sewage sludge. 10 % addition of studied fuels to the mixture with coal changed its combustion profile in the case of sewage sludge addition. The combustion characteristics of fuel mixtures showed, respectively, qualitative summarise behaviour based on single fuels. Evolved gaseous products from the decomposition of studied samples were identified. This study showed that thermogravimetric analysis connected with mass spectrometry is useful techniques to investigate the combustion and co-combustion of biomass fuels, and sewage sludge, together with coal. Non-isothermal kinetic analysis was used to evaluate the Arrhenius activation energy and the pre-exponential factor. The kinetic parameters were calculated using Kissinger-Akahira-Sunose model.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据