Estimating Respirable Dust Exposure from Inhalable Dust Exposure

Abstract

Abstract In the sector of occupational safety and health only a limited amount of studies are concerned with the conversion of inhalable to respirable dust. This conversion is of high importance for retrospective evaluations of exposure levels or of occupational diseases. For this reason a possibility to convert inhalable into respirable dust is discussed in this study. To determine conversion functions from inhalable to respirable dust fractions, 15 120 parallel measurements in the exposure database MEGA (maintained at the Institute for Occupational Safety and Health of the German Social Accident Insurance) are investigated by regression analysis. For this purpose, the whole data set is split into the influencing factors working activity and material. Inhalable dust is the most important predictor variable and shows an adjusted coefficient of determination of 0.585 (R2 adjusted to sample size). Further improvement of the model is gained, when the data set is split into six working activities and three material groups (e.g. high temperature processing, adj. R2 = 0.668). The combination of these two variables leads to a group of data concerned with high temperature processing with metal, which gives rise to a better description than the whole data set (adj. R2 = 0.706). Although it is not possible to refine these groups further systematically, seven improved groups are formed by trial and error, with adj. R2 between 0.733 and 0.835: soldering, casting (metalworking), welding, high temperature cutting, blasting, chiseling/embossing, and wire drawing. The conversion functions for the seven groups are appropriate candidates for data reconstruction and retrospective exposure assessment. However, this is restricted to a careful analysis of the working conditions. All conversion functions are power functions with exponents between 0.454 and 0.946. Thus, the present data do not support the assumption that respirable and inhalable dust are linearly correlated in general.