On the Characterization of the Generation Rate and Size-Dependent Crystalline Silica Content of the Dust from Cutting Fiber Cement Siding

摘要

A laboratory testing system was developed to systematically characterize the dust generation rate and size-dependent crystalline silica content when cutting or shaping silica containing materials. The tests of cutting fiber cement siding in this system verify that it provides high test repeatability, making it suitable for the targeted characterizations. The mass-based size distributions obtained from a gravimetric-based instrument and a direct reading instrument both show bimodal lognormal distributions with a larger mode similar to 13 A mu m and another mode < 5 A mu m for the dusts from cutting four different brands of fiber cement siding. The generation rates of respirable dust obtained from the two instruments are comparable, and the results from each instrument are similar for the four brands. The silica content in the airborne dusts, however, strongly depends on the amount of silica used in the respective product. It is also observed that the silica content in the airborne dust from cutting the four brands of fiber cement siding showed the same trend of an increase with the aerodynamic diameter of the dust, approaching the silica content levels found in their respective bulk samples. Combining the results for both the dust size distribution and size-dependent silica content, it is found that most of the respirable crystalline silica (RCS) resides in the dust similar to 2.5 A mu m in aerodynamic diameter. These results would help guide the development of specific engineering control measures targeted at lowering workers' exposure to RCS while cutting fiber cement siding. With the high repeatability using the laboratory testing system, the dust generation rate could then be characterized under different operating conditions, and with the deployment of various engineering control measures. This would greatly facilitate the systematic evaluation of the control effectiveness and the selection of the optimal control solutions for field trials.