# Fine Dust Creation during Hardwood Machine Sanding
## 3 Results and Discussion
[66] found that in six different Asian hardwoods, a high wood density causes the creation of dust particles with smaller sizes than a low wood density. [PERSON] and [PERSON] [67] studied 21 hardwood species and reported the same relationship. This was also confirmed by the results of research on the influence of thermal wood modification on the size of dust particles created during sanding [68; 69; 70]. The decrease in wood density due to modification produces coarser dust. In addition, [PERSON] et al. [42] sanded alder, beech, and oak wood and showed that alder produced the smallest particles which had the lowest density. These studies were performed using sieve analysis only. The sieving of wood dust, which is not uniformly shaped, often having long and thin particles, may be inaccurate. These particles can clog the sieve mesh, so many of very small particles cannot pass through the fine sieve. It is unfortunately possible that the measurement method strongly influences the particle size estimation. The sieving method underestimates the results of the particle size analysis of coarse dust, but fine dust cannot pass through the small sieves. The laser diffraction method overestimates the results of the particle size measurement of wood dust due to the non-spherical shape of particles. Long and thin particles can be recognized as spheres with a diameter equal to the particle length [61; 71]. Therefore, in order to avoid this error, many complementary measuring methods should be used. The average mass content of particles smaller than 10 \(\upmu\)m in dust from the tested wood species ranged from 2.8% to 8.9% for walnut and oak, respectively. No statistical differences (\(p=0.05\)) of the average content of particles smaller than 10 \(\upmu\)m were found in ash, beech, and hornbeam (Figure 4). A similar content of fine dust from the sanding of most hardwood species means that they should be treated with the same considerations to ensure the health and safety of wood industry workers [4]. Figure 3: Particle mean diameter of the hardwood species investigated in this work (identical superscripts a, b, c, denote no significant difference for \(p<0.05\), error bars represent the standard deviation). The average content of particles smaller than 2.5 \(\upmu\)m in dust from tested species of wood did not exceed 1.9%, and the highest content was observed for beech wood. However, in terms of posing a health risk, the sanding conditions of beech wood should be adjusted to limit the formation of large amounts of dust because it contains a significantly higher content of particles that can penetrate the lower respiratory tract [1]. In other cases, the content of this dust fraction was significantly lower than in beech dust (\(p\) = 0.05), and the dust produced by sanding walnut wood had the smallest content of the fraction <2.5 \(\upmu\)m, i.e., 0.4% (Figure 4). Since wood dust is not homogeneous, further research should be carried out to characterize and reduce its formation. The selection of methods is very important, and it seems that sieving is not a good method for estimating the wood dust particle size, especially for very fine fractions, because they may not pass through fine sieves due to their non-spherical shape [44]. This results in a disproportionately high fraction of particles retained on these sieves; therefore, comprehensive and complementary methods, such as microscope image analysis or laser diffraction analysis, should be used to characterize fine wood dust [35; 72; 73]. Scanning electron microscopy and image analysis as well as energy-dispersive X-ray analysis allow us to take into account the shape identity of the particles when measuring the particle-size distribution [74; 75]. Unfortunately, these methods have limitations that do not allow their common use in the industry, mainly associated with the sample representativeness. A relatively small number of particles can be recognized in an image. In addition, measurements are time-consuming and require experienced staff [61].