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变革之风:改善空气以进行微生物环境控制。

Wind of change: Better air for microbial environmental control.

作者信息

Messina G, Amodeo D, Taddeini F, De Palma I, Puccio A, Cevenini G

机构信息

Post Graduate School of Public Health, University of Siena, Italy.

Department of Molecular and Developmental Medicine, University of Siena, Italy.

出版信息

Case Stud Chem Environ Eng. 2022 Dec;6:100240. doi: 10.1016/j.cscee.2022.100240. Epub 2022 Jul 31.

DOI:10.1016/j.cscee.2022.100240
PMID:37520926
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9339158/
Abstract

BACKGROUND

The COVID19 epidemic highlighted the importance of air in the transmission of pathogens. Air disinfection is one of the key points to reduce the risk of transmission both in the health sector and in public, civil and industrial environments. All bacteria and viruses tested to date can be inactivated by UV-C rays. Laboratory tested UV-C systems are increasingly popular and proposed as effective technologies for air purification; few studies have evaluated their performance in populated indoor environments. The aim of this investigation was to evaluate the effectiveness of a UV-C disinfection system for air in a real working context.

METHODS

This experimental study was conducted between December 2020 and February 2021 in an office of the Department of Molecular and Developmental Medicine of the University of Siena, Italy. A pre-final version air purifier (Cleaning Air T12), capable of treating 210 m/h of air, was first tested for its ability to filter particulates and reduce microbial air contamination in the absence of people. Subsequently, the experiments were conducted in the presence of 3-5 subjects who worked for several hours in an office. During the tests, microbiological samples of air were collected in real time, switching the system on and off periodically. Air samples were collected and incubated on Petri dishes at 36 °C and 22 °C. Statistical analysis was performed with Stata 16 software assuming a significance level of 95%. An interpolating model was identified to describe the dynamics of contamination reduction when the device operates.

RESULTS

Preliminary tests showed a significant 62.5% reduction in Colony-Forming Units (CFUs) with 36 °C incubation. Reductions in the particulate component were also observed. In the main test, comparison of CFU data, between the device-on phase (90 min) and the subsequent device-off phase (60 min), showed statistically significant increase (p = 0.001) of environmental contamination passing from a mean of 86.6 (65.8-107.4) to 171.1 (143.9-198.3) CFU/m, that is a rise of about 100%. The interpolating model exhibited a good fit of CFU reduction trend with the device on.

CONCLUSIONS

The system, which mainly uses UV-C lamps for disinfection, was able to significantly reduce environmental and human contamination in real time. Experimental tests have shown that as soon as the device is switched off, after at least half an hour of operation, the healthiness of the air decreases drastically within 10 minutes, bringing the airborne microbial contamination (induced by the presence of operators in the environment) to levels even higher than 150% of the last value with the device on. Re-engineering strategies for system improvement were also discussed.

摘要

背景

新冠疫情凸显了空气在病原体传播中的重要性。空气消毒是降低医疗部门以及公共、民用和工业环境中传播风险的关键点之一。迄今为止测试的所有细菌和病毒都可被紫外线C射线灭活。经过实验室测试的紫外线C系统越来越受欢迎,并被提议作为有效的空气净化技术;很少有研究评估它们在人员密集的室内环境中的性能。本调查的目的是评估紫外线C消毒系统在实际工作环境中对空气的消毒效果。

方法

本实验研究于2020年12月至2021年2月在意大利锡耶纳大学分子与发育医学系的一间办公室进行。首先对一台预最终版空气净化器(Cleaning Air T12)进行测试,该净化器每小时能够处理210立方米空气,测试其在无人情况下过滤颗粒物和减少空气中微生物污染的能力。随后,在有3至5名受试者在办公室工作数小时的情况下进行实验。在测试过程中,定期开启和关闭系统,同时实时采集空气微生物样本。采集空气样本并在36℃和22℃的培养皿中培养。使用Stata 16软件进行统计分析,假设显著性水平为95%。确定了一个插值模型来描述设备运行时污染减少的动态变化。

结果

初步测试显示,在36℃培养条件下,菌落形成单位(CFU)显著减少了62.5%。还观察到颗粒物成分的减少。在主要测试中,比较设备开启阶段(90分钟)和随后设备关闭阶段(60分钟)的CFU数据,结果显示环境污染在统计学上有显著增加(p = 0.001),从平均86.6(65.8 - 107.4)CFU/立方米增加到171.1(143.9 - 198.3)CFU/立方米,即增加了约100%。插值模型显示出与设备开启时CFU减少趋势的良好拟合。

结论

该主要使用紫外线C灯进行消毒的系统能够实时显著减少环境和人体污染。实验测试表明,该设备运行至少半小时后一旦关闭,空气的健康程度在10分钟内会急剧下降,使空气中的微生物污染(由环境中操作人员的存在引起)达到甚至高于设备开启时最后值的150%的水平。还讨论了系统改进的重新设计策略。

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