Diesel Engine Exhaust Exposure in the Ontario Civil Infrastructure Construction Industry

OBJECTIVES

Diesel engine exhaust (DEE) is a known lung carcinogen and a common occupational exposure in Canada. The use of diesel-powered equipment in the construction industry is particularly widespread, but little is known about DEE exposures in this work setting. The objective of this study was to determine exposure levels and identify and characterize key determinants of DEE exposure at construction sites in Ontario.

METHODS

Elemental carbon (EC, a surrogate of DEE exposure) measurements were collected at seven civil infrastructure construction worksites and one trades training facility in Ontario using NIOSH method 5040. Full-shift personal air samples were collected using a constant-flow pump and SKC aluminium cyclone with quartz fibre filters in a 37-mm cassette. Exposures were compared with published health-based limits, including the Dutch Expert Committee on Occupational Safety (DECOS) limit (1.03 µg m-3 respirable EC) and the Finnish Institute of Occupational Health (FIOH) recommendation (5 µg m-3 respirable EC). Mixed-effects linear regression was used to identify determinants of EC exposure.

RESULTS

In total, 149 EC samples were collected, ranging from <0.25 to 52.58 µg m-3 with a geometric mean (GM) of 3.71 µg m-3 [geometric standard deviation (GSD) = 3.32]. Overall, 41.6% of samples exceeded the FIOH limit, mostly within underground worksites (93.5%), and 90.6% exceeded the DECOS limit. Underground workers (GM = 13.20 µg m-3, GSD = 1.83) had exposures approximately four times higher than below grade workers (GM = 3.56 µg m-3, GSD = 1.94) and nine times higher than above ground workers (GM = 1.49 µg m-3, GSD = 1.75). Training facility exposures were similar to above ground workers (GM = 1.86 µg m-3, GSD = 4.12); however, exposures were highly variable. Work setting and enclosed cabins were identified as the key determinants of exposure in the final model (adjusted R2 = 0.72, P < 0.001). The highest DEE exposures were observed in underground workplaces and when using unenclosed cabins.

CONCLUSIONS

This study provides data on current DEE exposure in Canadian construction workers. Most exposures were above recommended health-based limits, albeit in other jurisdictions, signifying a need to further reduce DEE levels in construction. These results can inform a hazard reduction strategy including targeted intervention/control measures to reduce DEE exposure and the burden of occupational lung cancer.

Estimating Historical Exposure to Respirable Crystalline Silica in the Mining Industry in Ontario, Canada Using a Newly Developed Exposure Database

OBJECTIVES

To use the recently developed Ontario Mining Exposure Database (OMED) to describe historical silica exposure in the Ontario metal mining industry and identify predictors of historical silica exposure.

METHODS

Personal respirable crystalline silica (RCS) data for metal mines were extracted from OMED and included both individual and summary measures, where multiple exposure measurements (n > 1) were aggregated and entered as a single exposure value (n = 1). Data were stratified by sample location (underground/surface) for analysis. Monte Carlo simulation was used to simulate individual measures from the summary measures. A fixed effects multiple linear regression model was used to assess the effects of commodity (ore mined), sample year, source of exposure data, and occupational group on RCS concentration. Parameter estimates (β), standard errors, and 95% upper and lower confidence intervals were reported.

RESULTS

The OMED contained 12 995 silica measurements. After limiting to RCS measurements in metal mines, and measures with sufficient information for analysis, 2883 RCS measurements collected from 1974 to 1991 remained, including 2816 individual and 67 summary measurements. In total, 321 individual RCS measurements were simulated from the 67 summary measures. The analysis database contained 2771 (12% simulated) underground measurements and 366 surface measurements (0% simulated). In the underground group, an overall geometric mean (GM) of 0.05 [geometric standard deviation (GSD) 3.09] mg m-3 was estimated with a 6% annual decrease over time. In this group, the commodity with the highest average RCS level was zinc mines (GM = 0.07 mg m-3) and the lowest was iron mines (GM = 0.01 mg m-3). In the surface group, an overall GM of 0.05 (GSD 3.70) mg m-3 was estimated with an 8% decreased over time. In this group, the commodity with the highest average RCS level was gold mines (GM = 0.07 mg m-3) and the lowest was zinc mines (GM = 0.03 mg m-3). In both groups, company collected data had lower estimated RCS compared with regulator collected data.

CONCLUSIONS

Historical RCS levels decreased over time. Mean measurements exceeded the American Conference of Governmental Industrial Hygienists current health-based threshold limit value (0.025 mg m-3). The main predictors of exposure were commodity, source of exposure data, and sample year. However, low R2 and high GSD values suggest additional predictors of RCS exposures in Ontario's metal mines exist that were unavailable in OMED.