{"title":"160 Performance improvement of beta gauge particulate monitors","authors":"Qi-Xiang li, Chih-Wei lin, Sheng-Hsiu Huang, Chih-Chieh Chen","doi":"10.1093/annweh/wxae035.224","DOIUrl":null,"url":null,"abstract":"The Beta gauge is used in PM monitoring. It measures particle mass by utilizing beta attenuation. However, due to the high deviation of beta particles per second, commercial beta gauges have a high response time. That means achieving real-time monitoring is challenging. This study aims to improve the beta gauge’s detection limit(LOD) and response time(TR) for real-time monitoring. To reduce external environmental interference, aerosol generation system was established in laboratory to generate stable challenge particle size and distribution. The commercial beta gauge was used to evaluate the effects of the sampling area, sampling number, and smoothing time(TS). Lambert Beer’s law was used to convert the beta intensity into mass concentration per second, evaluating the beta gauge’s TR, S/N ratio, and LOD. By adjusting TS from 5 to 75 min, TR reaches from 0.3 to 60 minutes. At daily average PM2.5 of 35 μg/m3, the SD of readings decreases from 175 to 3.2 μg/m3. At quantitative standard (S/N ratio=10), when the sampling area is reduced from 2 to 0.4 cm2, the required TS is shortened by 33%. When the sample number is increased to 6, the required TS can be shortened by 60%. The LOD is about 12 μg/m3 with TS of 75 minutes. By increasing the sample number to 6, it can be achieved 1.5 μg/m3. To optimize its response time, the smoothing method can be utilized. To improve the stability of beta gauge measurement and achieve a lower LOD, it is recommended to reduce the sampling area and increase the number of samples.","PeriodicalId":8362,"journal":{"name":"Annals Of Work Exposures and Health","volume":"57 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals Of Work Exposures and Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/annweh/wxae035.224","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
The Beta gauge is used in PM monitoring. It measures particle mass by utilizing beta attenuation. However, due to the high deviation of beta particles per second, commercial beta gauges have a high response time. That means achieving real-time monitoring is challenging. This study aims to improve the beta gauge’s detection limit(LOD) and response time(TR) for real-time monitoring. To reduce external environmental interference, aerosol generation system was established in laboratory to generate stable challenge particle size and distribution. The commercial beta gauge was used to evaluate the effects of the sampling area, sampling number, and smoothing time(TS). Lambert Beer’s law was used to convert the beta intensity into mass concentration per second, evaluating the beta gauge’s TR, S/N ratio, and LOD. By adjusting TS from 5 to 75 min, TR reaches from 0.3 to 60 minutes. At daily average PM2.5 of 35 μg/m3, the SD of readings decreases from 175 to 3.2 μg/m3. At quantitative standard (S/N ratio=10), when the sampling area is reduced from 2 to 0.4 cm2, the required TS is shortened by 33%. When the sample number is increased to 6, the required TS can be shortened by 60%. The LOD is about 12 μg/m3 with TS of 75 minutes. By increasing the sample number to 6, it can be achieved 1.5 μg/m3. To optimize its response time, the smoothing method can be utilized. To improve the stability of beta gauge measurement and achieve a lower LOD, it is recommended to reduce the sampling area and increase the number of samples.
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About the Journal
Annals of Work Exposures and Health is dedicated to presenting advances in exposure science supporting the recognition, quantification, and control of exposures at work, and epidemiological studies on their effects on human health and well-being. A key question we apply to submission is, "Is this paper going to help readers better understand, quantify, and control conditions at work that adversely or positively affect health and well-being?"
We are interested in high quality scientific research addressing:
the quantification of work exposures, including chemical, biological, physical, biomechanical, and psychosocial, and the elements of work organization giving rise to such exposures;
the relationship between these exposures and the acute and chronic health consequences for those exposed and their families and communities;
populations at special risk of work-related exposures including women, under-represented minorities, immigrants, and other vulnerable groups such as temporary, contingent and informal sector workers;
the effectiveness of interventions addressing exposure and risk including production technologies, work process engineering, and personal protective systems;
policies and management approaches to reduce risk and improve health and well-being among workers, their families or communities;
methodologies and mechanisms that underlie the quantification and/or control of exposure and risk.
There is heavy pressure on space in the journal, and the above interests mean that we do not usually publish papers that simply report local conditions without generalizable results. We are also unlikely to publish reports on human health and well-being without information on the work exposure characteristics giving rise to the effects. We particularly welcome contributions from scientists based in, or addressing conditions in, developing economies that fall within the above scope.
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