Abstract
A need exists to develop realistic surfaces, with differing degrees of surface roughness, to standardize methods for sampling and cleaning of environmental contaminants. This study reports on development and characterization of a novel means to create reproducible wood surfaces that are approximately 7 × 10 cm2 and have differing degree of surface roughness. Three unique specimens were prepared by creating 3-dimensional digital-scans of actual wood surfaces found in three St. Louis homes. These surfaces had distinct depressions that likely arose from tool marks. A reverse image die of each specimen was made from high density plastic. Replicates of the three specimens were created by placing a die and wood veneer section into a rolling-press leaving the original topographies gathered from the homes. These specimens were used in a separate study to evaluate cleaning leaded dust using wipe or vacuuming treatments. The separate cleaning studies found no difference in cleaning due to the effects of the different surfaces. An in-depth examination of the three specimens was held to determine if differences in surface roughness of the specimens explained removal of lead from its surface. A method using optical, 3-D laser profilometry was used to determine if there were statistical differences between the surface roughness of the three specimens and within the specimens themselves. Area-scale analyses were made to calculate relative areas as a function of scale as a way of characterizing the roughness. Statistical differences were found for surface roughness between each of three surface specimens at a scale where small particles, deposited in the cleaning studies may adhere to the wood. However, within the specimens, surface roughness, at the scale where fine particles may lodge, were not consistent inside or outside tool marks. Therefore, differences in surface roughness were found within and between surfaces but they may not be large enough or different enough for detection using simple cleaning methods. Specimens with larger differences in surface roughness may be needed to simulate differences in cleaning effectiveness. This work should be continued to understand the scales for the different interactions of particle deposition, adhesion, and removal toward development of standard reference surfaces with well-characterized textures.
