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The prediction of elemental composition of biomass based on proximate analysis

机译：基于近似分析的生物质元素组成预测

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摘要

Elemental composition is one of the most important properties for biomass utilization. The experimental determination of ultimate analysis data require special instrumentation, while proximate analysis data can be obtained easily by using common equipments. This paper presents new correlations for calculating the elemental composition based on proximate analysis of biomass. The correlations with the effect of ash content taken into account are derived by using 66 data points, and validated by using 20 data points selected from different categories of biomass than that for correlations derivation. The correlations are given as: C = 0.635FC + 0.460VM - 0.095ASH, H = 0.059FC + 0.060VM + 0.010ASH, O=0.340FC + 0.469VM - 0.023ASH, where 9.2% ≤ FC ≤ 32.79%, 57.2% ≤ VM ≤ 90.6%, 0.1% ≤ ASH ≤ 24.6%, 36.2% ≤ C ≤ 53.1%, 4.7% ≤ H ≤ 6.61%, and 31.37% ≤ O ≤ 48.0% in wt.% on dry basis. The average absolute errors of these correlations are 3.17%. 4.47% and 3.16%, and the average bias errors are 0.19%, -0.34% and 0.19% compared with measured values of C, H and O, respectively. The new developed correlations can be used to compute elemental composition of biomass accurately, especially for those biomass whose ash content are high, based on simple proximate analysis.
机译：元素组成是生物质利用的最重要属性之一。最终分析数据的实验测定需要特殊的仪器，而使用通用设备即可轻松获得最近的分析数据。本文介绍了基于生物量的近邻分析计算元素组成的新相关性。通过使用66个数据点导出考虑了灰分含量影响的相关性，并使用从与相关性推导不同的生物质类别中选择的20个数据点进行验证。相关性为：C = 0.635FC + 0.460VM-0.095ASH，H = 0.059FC + 0.060VM + 0.010ASH，O = 0.340FC + 0.469VM-0.023ASH，其中9.2％≤FC≤32.79％，57.2％以干重计，≤VM≤90.6％，0.1％≤ASH≤24.6％，36.2％≤C≤53.1％，4.7％≤H≤6.61％和31.37％≤O≤48.0％（以干基计）。这些相关性的平均绝对误差为3.17％。与C，H和O的测量值相比，平均偏差误差分别为4.47％和3.16％，分别为0.19％，-0.34％和0.19％。基于简单的近距离分析，新开发的相关性可用于精确计算生物质的元素组成，尤其是那些灰分含量高的生物质。

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  • 来源
    《Energy Conversion & Management》 |2010年第5期|p.983-987|共5页
  • 作者

    Jianfeng Shen; Shuguang Zhu; Xinzhi Liu; Houlei Zhang; Junjie Tan;

  • 作者单位

    School of Power Engineering, Nanjing University of Science & Technology, Xiaolingwei 200, Nanjing 210094, China;

    School of Power Engineering, Nanjing University of Science & Technology, Xiaolingwei 200, Nanjing 210094, China;

    School of Power Engineering, Nanjing University of Science & Technology, Xiaolingwei 200, Nanjing 210094, China;

    School of Power Engineering, Nanjing University of Science & Technology, Xiaolingwei 200, Nanjing 210094, China;

    School of Power Engineering, Nanjing University of Science & Technology, Xiaolingwei 200, Nanjing 210094, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    biomass; ultimate analysis; proximate analysis; elemental composition prediction;

    机译：生物质最终分析;近距离分析;元素组成预测;

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