Heavy equipment maintenance exposure assessment: using a time-activity model to estimate surrogate values for replacement of missing data.

This study on four pieces of heavy construction equipment was conducted to determine the concentration of airborne asbestos fibers during in-frame maintenance and repair activities, which included aggressive techniques that resulted in visible dust from work involving friction products and gaskets. Despite execution of a carefully planned sampling strategy, approximately 10% (47) of the samples collected could not be analyzed due to overloading or filter damage. To include the overloaded samples in the data analysis, surrogate values were estimated following a time-activity model. Twelve long-term personal samples, 2 short-term, 30-min personal samples, and 31 long-term area samples were modeled. Personal and area time-weighted average (TWA) data were analyzed both with and without the estimated surrogate values and compared. A total of 444 samples were collected over 9 days. Four experienced heavy equipment mechanics removed and replaced friction products and gaskets. Samples were analyzed using NIOSH Method 7400 Phase Contrast Microscopy followed by NIOSH Method 7402 Transmission Electron Microscopy. Sample data information including the surrogate values for the full-shift, TWA personal sample results ranged from 0.002 to 0.064 asbestos f/cc. Personal, short-term, 30-min sample results, including the two surrogate values, ranged from 0.038 to 0.561 asbestos f/cc. Full-shift TWA area samples, including the 31 surrogate values, ranged from 0.005 to 0.039 asbestos f/cc. Area air sample results at the end of the project were similar to levels measured before the start of the project. No fiber concentration buildup within the work area was indicated over the 9-day study. All full-shift personal and area TWA sample results were below 0.1 f/cc, and short-term 30-min personal samples were below 1.0 f/cc. Statistical results of the sample data with and without the surrogate values were consistent. Use of the time-activity model reduced the uncertainty associated with this data analysis and provided a consistent logical process for estimating surrogate values to replace missing data.