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硫化氢(H2S)暴露危害评估:一种基于直接仪器读数生成暴露指数的算法。

Hydrogen Sulphide (H2S) Exposure Hazard Assessment: An Algorithm for Generating Exposure Index Based on Direct Instrument Readings.

机构信息

Department of Industrial Economics and Technology Management, NTNU-Norwegian University of Science and Technology, PO Box 8900, Torgarden, Trondheim N-7491, Norway.

Trondheim Municipality, Working Environment Office, PO Box 2300 Torgarden, N-7004 Trondheim, Norway.

出版信息

Ann Work Expo Health. 2022 Jan 7;66(1):124-129. doi: 10.1093/annweh/wxab047.

Abstract

OBJECTIVES

Increased use of small affordable alarm sensors with logging or network capabilities has improved the ability to monitor exposure. The large datasets generated from these monitors calls for development of a computer algorithm to assess these data.

METHODS

We examined 88 time series of hydrogen sulphide (H2S) from wastewater works previously used for developing the exposure index. The time series covered 331 h, where 16 h had readings different from zero.

RESULTS

The developed algorithm reproduced the manual assessed index almost perfectly (linear regression β = 1.02, R2 = 0.97, P < 0.001). Time-weighted average (TWA) values of the 88 time series showed a mean value of 0.04 ppm (range 0.0-0.9). The mean index value was 18 (range 0-337), with a good linear fit (β = 0.002, R2 = 0.93, and P < 0.001). The index gave us a better resolution and basis for risk assessment than the TWA, and managed to combine evaluation of TWA and exceedance of ceiling value in one number.

CONCLUSIONS

As long as peaks above ceiling value occur, we find alarm tools with an H2S sensor to be an essential personal protective equipment against H2S. The proposed method has been verified, and it removes some common human errors in graph evaluation. Use of the index is a possible way of quantifying risk level in exposure to H2S in one single number and provides better understanding of the risk of exposure, as it eases the analysis and evaluation of large numbers of time series.

摘要

目的

使用具有记录或网络功能的小型经济实惠的报警传感器可以提高监测暴露的能力。这些监测器生成的大型数据集需要开发一种计算机算法来评估这些数据。

方法

我们检查了先前用于开发暴露指数的 88 个来自污水处理厂的硫化氢 (H2S) 时间序列。这些时间序列涵盖了 331 小时,其中 16 小时的读数与零不同。

结果

开发的算法几乎完美地再现了手动评估指数(线性回归β=1.02,R2=0.97,P<0.001)。88 个时间序列的时间加权平均值 (TWA) 显示平均值为 0.04 ppm(范围为 0.0-0.9)。指数值的平均值为 18(范围为 0-337),具有良好的线性拟合(β=0.002,R2=0.93,P<0.001)。与 TWA 相比,该指数为风险评估提供了更好的分辨率和基础,并且设法将 TWA 的评估和上限值的超过合并到一个数字中。

结论

只要超过上限值的峰值出现,我们就发现带有 H2S 传感器的报警工具是防止 H2S 的基本个人防护设备。所提出的方法已经过验证,它消除了图形评估中一些常见的人为错误。使用该指数是量化 H2S 暴露风险水平的一种可能方法,可以通过单个数字提供对暴露风险的更好理解,因为它简化了对大量时间序列的分析和评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f568/8751804/e62de2b5bc97/wxab047f0001.jpg

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