量子电子学报 ›› 2023, Vol. 40 ›› Issue (4): 436-446.doi: 10.3969/j.issn.1007-5461.2023.04.002

• 光谱 • 上一篇    下一篇

基于激光诱导击穿光谱的果木炭燃烧对空气成分影响的研究

费晔 1, 孙仲谋 1, 田东鹏 1, 刘骁源 1, 刘玉柱 1,2*   

  1. ( 1 南京信息工程大学江苏省大气海洋光电探测重点实验室, 江苏 南京 210044; 2 江苏省大气环境与装备技术协同创新中心, 江苏 南京 210044 )
  • 收稿日期:2023-01-19 修回日期:2023-02-24 出版日期:2023-07-28 发布日期:2023-07-28
  • 通讯作者: yuzhu.liu@gmail.com E-mail:yuzhu.liu@gmail.com
  • 作者简介:费 晔 ( 2002 - ), 女, 江苏苏州人, 主要从事环境光学方面的研究。 E-mail: 202083430026@nuist.edu.cn
  • 基金资助:
    国家自然科学基金 (U1932149), 江苏高校 "青蓝工程"

Influence of fruit charcoal combustion on air composition based on laser⁃induced breakdown spectroscopy

FEI Ye 1, SUN Zhongmou 1, TIAN Dongpeng 1, LIU Xiaoyuan 1, LIU Yuzhu 1,2*   

  1. ( 1 Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean, Nanjing University of Information Science & Technology, Nanjing 210044, China; 2 Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), Nanjing 210044, China )
  • Received:2023-01-19 Revised:2023-02-24 Published:2023-07-28 Online:2023-07-28

摘要: 果木炭是一种常见的燃料, 其燃烧过程中产生的气体和烟尘气溶胶会影响环境空气质量并损害人体健康, 因此对果木炭燃烧过程中空气成分进行检测与分析具有重要意义。采用激光诱导击穿光谱 (LIBS) 技术对果木炭燃 烧时的空气、烟尘气溶胶进行检测, 同时检测果木炭及其燃烧灰烬作为辅助分析。对四种样品的谱线进行标定, 发现 果木炭燃烧时空气中碳浓度增大, 生成的气溶胶中含有Ca、Mg、K、Si 等元素。果木炭和灰烬的元素组成较为相似, 均含有C、 Fe、 Mg、 Ca、 Sr、 K、 Na 和Ba 等元素, 果木炭光谱中C、H 元素谱线强度均高于灰烬。此外, 结合机器学习 算法对有无果木炭燃烧时的空气进行区分, 选取C、CN 分子特征谱线所在的波段作为聚类分析的原始特征。主成分 分析 (PCA) 结果表明在有无果木炭燃烧两种条件下的空气能被较好地区分, 证明LIBS 结合PCA 技术能有效地识别 果木炭的燃烧并检测果木炭燃烧造成的空气污染。进一步利用 LIBS 结合机器学习算法对果木炭及其燃烧灰烬进行 区分, 发现区分效果良好, 为果木炭燃烧后的回收利用提供了参考。

关键词: 光谱学, 激光诱导击穿光谱, 果木炭, 空气污染, 碳排放, 主成分分析

Abstract: Fruit charcoal is a kind of common fuel, and the gases and aerosols produced in its combustion process can affect environmental air quality and harm human health. Therefore, it is of great significance to detect and identify the air composition during the combustion process of fruit charcoal. Laser-induced breakdown spectroscopy (LIBS) is used to detect the air and aerosol during the combustion of fruitcharcoal, and at the same time, fruit charcoal and its combustion ash are also detected as auxiliary analysis. The spectral lines of four samples are calibrated, and it is found that when the charcoal is burning, the carbon concentration in the air increases, and the generated aerosols contain Ca, Mg, K, Si and other elements. The elemental composition of fruit charcoal and ash is similar, both containing C, Fe, Mg, Ca, Sr, K, Na, Ba, and the intensity of C and H in fruit charcoal spectrum is higher than that in ash spectrum. Considering that the combustion of fruit charcoal produce more gas and less particulate matter, it is difficult to judge whether the fruit charcoal is burning or has burned in the room from the perspective of image recognition, so the air with and without combustion of fruit charcoal are further distinguished by principal component analysis (PCA) algorithm, and the bands where the characteristic spectral lines of C and CN are selected as the original features of cluster analysis. The results show that the two kinds of air with and without fruit charcoal combustion can be well distinguished, which proves that LIBS combined with PCA can effectively identify the combustion of fruit charcoal and can be used to detect the air pollution caused by the combustion of fruit charcoal. Furthermore, the composition of fruit charcoal and ash are also distinguished in the same way, and it is found that the distinction effect is good, which provides a reference for the recovery and utilization of fruit charcoal after combustion.

Key words: spectroscopy, laser-induced breakdown spectroscopy, fruit charcoal, air pollution, carbon emission, principal component analysis

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