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Evaluation of the recursive model approach for estimating particulate matter infiltration efficiencies using continuous light scattering data.

机译:用连续光散射数据估算颗粒物质渗透效率的递归模型方法的评价。

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Quantifying particulate matter (PM) infiltration efficiencies (F(inf)) in individual homes is an important part of PM exposure assessment because individuals spend the majority of time indoors. While F(inf) of fine PM has most commonly been estimated using tracer species such as sulfur, here we evaluate an alternative that does not require particle collection, weighing and compositional analysis, and can be applied in situations with indoor sources of sulfur, such as environmental tobacco smoke, gas pilot lights, and humidifier use. This alternative method involves applying a recursive mass balance model (recursive model, RM) to continuous indoor and outdoor concentration measurements (e.g., light scattering data from nephelometers). We show that the RM can reliably estimate F(inf), a crucial parameter for determining exposure to particles of outdoor origin. The RM F(inf) estimates showed good agreement with the conventional filter-based sulfur tracer approach. Our simulation results suggest that the RM F(inf) estimates are minimally impacted by measurement error. In addition, the average light scattering response per unit mass concentration was greater indoors than outdoors; after correcting for differences in light scattering response the median deviation from sulfur F(inf) was reduced from 15 to 11%. Thus, we have verified the RM applied to light scattering data. We show that the RM method is unable to provide satisfactory estimates of the individual components of F(inf) (penetration efficiency, air exchange rate, and deposition rate). However, this approach may allow F(inf) to be estimated in more residences, including those with indoor sources of sulfur. We show that individual homes vary in their infiltration efficiencies, thereby contributing to exposure misclassification in epidemiological studies that assign exposures using ambient monitoring data. This variation across homes indicates the need for home-specific estimation methods, such as the RM or sulfur tracer, instead of techniques that give average estimates of infiltration across homes.Journal of Exposure Science and Environmental Epidemiology (2007) 17, 468-477; doi:10.1038/sj.jes.7500539; published online 15 November 2006.
机译:量化颗粒物质(PM)浸润效率(PM)中的个别家庭中的渗透效率是PM暴露评估的重要组成部分,因为个人在室内花费了大部分时间。虽然F(INF)优化PM最常见的是使用硫磺等示踪物种估计,但在这里,我们评估不需要粒子收集,称重和组成分析的替代方案,并且可以在室内硫磺的情况下应用作为环境烟草烟雾,天然气先导灯和加湿器使用。该替代方法包括将递归质量平衡模型(递归模型,RM)应用于连续室内和室外浓度测量(例如,来自Nephelomers的光散射数据)。我们表明RM可以可靠地估计F(INF),这是用于确定户外血液粒子暴露的重要参数。 RM F(INF)估计与传统的基于滤光器的硫示踪方法进行了良好的一致性。我们的仿真结果表明,RM F(INF)估计估计通过测量误差来影响最小。此外,每单位质量浓度的平均光散射响应比在室内大于室外;在纠正光散射响应的差异之后,从硫(INF)的中值偏差从15%降低到11%。因此,我们已经验证了应用于光散射数据的RM。我们表明RM方法无法提供F(INF)(穿透效率,空气汇率和沉积速率)的各个组件的令人满意的估计。然而,这种方法可以允许F(INF)在更多的住所中估计,包括具有室内硫磺的那些。我们表明个体家庭在渗透效率下变化,从而有助于暴露流行病学研究中的错误分类,该研究使用环境监测数据分配风险。跨房屋的这种变化表明需要家用的估计方法,例如RM或硫示踪剂,而不是在家庭中提供平均渗透渗透的技术。曝光科学和环境流行病学(2007)17,468-477; DOI:10.1038 / sj.jes.7500539;在线发布于2006年11月15日。

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