Sauvé Jean-François, Beaudry Charles, Bégin Denis, Dion Chantal, Gérin Michel, Lavoué Jérôme
Université de Montréal, Department of Environmental and Occupational Health, P.O. Box 6128, Main Station, Montréal, QC, Canada.
J Environ Monit. 2012 Sep;14(9):2512-20. doi: 10.1039/c2em30443k. Epub 2012 Aug 8.
A quantitative determinants-of-exposure analysis of respirable crystalline silica (RCS) levels in the construction industry was performed using a database compiled from an extensive literature review. Statistical models were developed to predict work-shift exposure levels by trade. Monte Carlo simulation was used to recreate exposures derived from summarized measurements which were combined with single measurements for analysis. Modeling was performed using Tobit models within a multimodel inference framework, with year, sampling duration, type of environment, project purpose, project type, sampling strategy and use of exposure controls as potential predictors. 1346 RCS measurements were included in the analysis, of which 318 were non-detects and 228 were simulated from summary statistics. The model containing all the variables explained 22% of total variability. Apart from trade, sampling duration, year and strategy were the most influential predictors of RCS levels. The use of exposure controls was associated with an average decrease of 19% in exposure levels compared to none, and increased concentrations were found for industrial, demolition and renovation projects. Predicted geometric means for year 1999 were the highest for drilling rig operators (0.238 mg m(-3)) and tunnel construction workers (0.224 mg m(-3)), while the estimated exceedance fraction of the ACGIH TLV by trade ranged from 47% to 91%. The predicted geometric means in this study indicated important overexposure compared to the TLV. However, the low proportion of variability explained by the models suggests that the construction trade is only a moderate predictor of work-shift exposure levels. The impact of the different tasks performed during a work shift should also be assessed to provide better management and control of RCS exposure levels on construction sites.
利用通过广泛文献综述汇编而成的数据库，对建筑业中可吸入结晶二氧化硅（RCS）水平进行了暴露定量决定因素分析。开发了统计模型，按行业预测工作班次暴露水平。采用蒙特卡罗模拟法，重新创建了从汇总测量值得出的暴露情况，并将其与单次测量值相结合进行分析。在多模型推理框架内，使用托比特模型进行建模，将年份、采样持续时间、环境类型、项目目的、项目类型、采样策略以及暴露控制措施的使用作为潜在预测因素。分析纳入了1346次RCS测量值，其中318次为未检出值，228次是根据汇总统计数据模拟得出的。包含所有变量的模型解释了总变异性的22%。除行业外，采样持续时间、年份和策略是RCS水平最具影响力的预测因素。与未采取暴露控制措施相比，采取暴露控制措施使暴露水平平均降低了19%，并且发现工业、拆除和翻新项目的浓度有所增加。1999年钻机操作员（0.238毫克/立方米）和隧道建设工人（0.224毫克/立方米）的预测几何均值最高，而按行业估计的超过美国政府工业卫生学家会议（ACGIH）阈限值（TLV）的比例在47%至91%之间。本研究中的预测几何均值表明，与TLV相比存在严重的过度暴露。然而，模型解释的变异性比例较低，这表明建筑行业只是工作班次暴露水平的一个中等预测因素。还应评估工作班次期间执行的不同任务的影响，以便更好地管理和控制建筑工地上的RCS暴露水平。
