title: Effects of data sparsity and spatiotemporal variability on hazard maps of workplace noise.
abstract: Personal sampling, considered a state-of-the-art technique to assess worker exposures to occupational hazards, is often conducted for the duration of a work shift so that time-weighted average (TWA) exposures may be evaluated relative to published occupational exposure limits (OELs). Such cross-shift measurements, however, provide little information on the spatial variability of exposures, except after a very large number of samples. Hazard maps, contour plots (or similar depiction) of hazard intensity throughout the workplace, have gained popularity as a way to locate sources and to visualize spatial variability of physical and chemical hazards within a facility. However, these maps are often generated from short duration measures and have little ability to assess temporal variability. To assess the potential bias that results from the use of short-duration measurements to represent the TWA in a hazard map, noise intensity measurements were collected at high spatial and temporal resolution in two facilities. Static monitors were distributed throughout the facility and used to capture the temporal variability at these locations. Roving monitors (typical of the hazard mapping process) captured spatial variability over multiple traverses through the facility. The differences in hazards maps generated with different sampling techniques were evaluated. Hazard maps produced from sparse, roving monitor data were in good agreement with the TWA hazard maps at the facility with low temporal variability. Estimated values were within 5 dB of the TWA over approximately 90% of the facility. However, at the facility with higher temporal variability, large differences between hazard maps were observed for different traverses through the facility. On the second day of sampling, estimates were at least 5 dB different than the TWA for more than half of the locations within the facility. The temporal variability of noise was found to have a greater influence on map accuracy than the spatial sampling resolution.
authors.affiliation: a Department of Environmental and Radiological Health Sciences , Colorado State University , Fort Collins , Colorado.
authors.forename: Kirk
authors.initials: K
authors.lastname: Lake
authors.forename: Jun
authors.initials: J
authors.lastname: Zhu
authors.forename: Haonan
authors.initials: H
authors.lastname: Wang
authors.forename: John
authors.initials: J
authors.lastname: Volckens
authors.forename: Kirsten A
authors.initials: KA
authors.lastname: Koehler
mesh_terms: D003625:Data Collection / Q000592:standards; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods*; D008377:Maps as Topic; D009623:Noise, Occupational / Q000706:statistics & numerical data*; D016273:Occupational Exposure / Q000032:analysis*; D062211:Spatio-Temporal Analysis; D013997:Time Factors; D017132:Workplace
keywords: hazard mapping; noise exposure; spatiotemporal variability