National Research Centre for the Working Environment (NRCWE), Lersø Parkallé 105, DK-2100 Copenhagen, Denmark.
Federal Institute for Occupational Safety and Health (BAuA), Nöldnerstr. 40-42, 10317 Berlin, Germany.
Ann Work Expo Health. 2024 Mar 15;68(3):295-311. doi: 10.1093/annweh/wxae009.
Several exposure assessment models use dustiness as an input parameter for scaling or estimating exposure during powder handling. Use of different dustiness methods will result in considerable differences in the dustiness values as they are based on different emission generation principles. EN17199:2019 offers 4 different dustiness test methods considering different dust release scenarios (e.g. powder pouring, mixing and gentle agitation, and vibration). Conceptually, the dustiness value by a given method can be multiplied with a scenario-specific modifier, called a handling energy factor (Hi), that allows conversion of a dustiness value to a release constant. Therefore, a Hi, scaling the effective mechanical energy in the process to the energy supplied in the specific dustiness test, needs to be applied. To improve the accuracy in predictive exposure modelling, we derived experimental Hi to be used in exposure algorithms considering both the mass- and number-based dust release fraction determined by the EN17199-3 continuous drop (CD) and the EN17199-4 small rotating drum (SRD) test methods. Three materials were used to evaluate the relationship between dustiness and dust levels during pouring powder from different heights in a controlled environment. The results showed increasing scatter and difference between the Hi derived for the 2 test methods with increasing pouring height. Nearly all the Hi values obtained for both SRD and CD were <1 indicating that the dustiness tests involved more energy input than the simulated pouring activity and consequently de-agglomeration and dust generation were higher. This effect was most pronounced in CD method showing that SRD mechanistically resembles more closely the powder pouring.
几种暴露评估模型将粉尘度用作粉末处理过程中缩放或估计暴露的输入参数。由于使用了不同的粉尘度方法,因此它们基于不同的排放产生原理,因此粉尘度值会有很大差异。EN17199:2019 考虑了不同的粉尘释放情况(例如粉末倾倒、混合和温和搅拌以及振动),提供了 4 种不同的粉尘度测试方法。从概念上讲,可以用称为处理能量因子(Hi)的特定场景修正因子乘以给定方法的粉尘度值,从而将粉尘度值转换为释放常数。因此,需要应用 Hi,即将过程中的有效机械能与特定粉尘度测试中提供的能量进行缩放。为了提高预测暴露模型的准确性,我们推导了实验性 Hi,用于考虑通过 EN17199-3 连续滴(CD)和 EN17199-4 小旋转鼓(SRD)测试方法确定的基于质量和基于数量的粉尘释放分数的暴露算法。使用三种材料来评估在受控环境中从不同高度倾倒粉末时粉尘度与粉尘水平之间的关系。结果表明,随着倾倒高度的增加,两种测试方法的 Hi 之间的差异和分散度增加。对于 SRD 和 CD,几乎所有的 Hi 值都<1,这表明粉尘度测试涉及的能量输入比模拟倾倒活动更多,因此团聚体的解聚和粉尘的产生更高。CD 方法中的这种效果最为明显,表明 SRD 在机械上更接近粉末倾倒。