The influence of concentration and size on the error of particulate matter detection using charge induction method

IF 3.9 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Kai Zhang , Yaqi Peng , Hong Yu , Pei Ning , Xueyong Hou , Ling Zhu , Shengyong Lu
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引用次数: 0

Abstract

Particulate matters generated from waste incineration carry charge due to collision and friction. By using charge induction method, it becomes feasible to detect particulate matter concentration by capturing the electrical signals emitted by particulate matters. In this study, a new charge induction device was constructed and tested. The investigation revealed a linear relationship between the sine wave eigenvalues of the electrical signals and the concentration of particulate matters. The corresponding formulas for peak-to-peak value, root mean square, and standard deviation were calculated, with R2 values greater than 0.98. Additionally, the influence of concentration and size on detection error was studied. The results showed that as the concentration increased or the size decreased, the detection error decreased. Furthermore, the study found that the impact of particulate matter concentration on detection results mitigated that of particulate matter size. The detection device, correlation formulas and influencing factors proposed in this study are expected to provide technical support and theoretical basis for particulate matter detection, offering significant value in the field of air pollution control.

浓度和粒度对电荷感应法颗粒物检测误差的影响
垃圾焚烧产生的微粒物质会因碰撞和摩擦而带电。利用电荷感应法,可以通过捕捉颗粒物发出的电信号来检测颗粒物的浓度。本研究构建并测试了一种新型电荷感应装置。研究发现,电信号的正弦波特征值与颗粒物浓度之间存在线性关系。计算出的峰峰值、均方根和标准偏差的相应公式的 R2 值大于 0.98。此外,还研究了浓度和粒度对检测误差的影响。结果表明,随着浓度的增加或大小的减小,检测误差也随之减小。此外,研究还发现,颗粒物浓度对检测结果的影响减轻了颗粒物大小对检测结果的影响。本研究提出的检测装置、相关公式和影响因素有望为颗粒物检测提供技术支持和理论依据,在大气污染控制领域具有重要价值。
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来源期刊
Atmospheric Pollution Research
Atmospheric Pollution Research ENVIRONMENTAL SCIENCES-
CiteScore
8.30
自引率
6.70%
发文量
256
审稿时长
36 days
期刊介绍: Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.
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