对SHEDS-PM模型中暴露于环境烟草烟雾(ETS)建模的评价。

Ye Cao, H Christopher Frey, Xiaozhen Liu, Bela K Deshpande
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摘要

据估计,环境烟草烟雾(ETS)是室内PM浓度和人类暴露于2.5微米或更小的细颗粒物(PM2.5)的主要因素。美国环境保护署开发的随机人体暴露和剂量模拟(SHEDS-PM)模型根据环境浓度和室内排放源估算特定人群的室外和室内PM2.5暴露分布。由于室内暴露于碳排放化合物可能很高,特别是在室内住宅微环境中,因此对SHEDS-PM中用于估计室内暴露于碳排放化合物的方法和数据进行了关键评估。对于住宅微环境,shed采用了与最佳实践相媲美的质量平衡方法。审查了SHEDS-PM中的默认输入,并确定了更近期和更广泛的数据源。敏感性分析用于确定哪些输入应该优先更新。有关香烟排放率的数据被认为是最重要的。目前,SHEDS-PM不计入车内排放的污染物;然而,车内碳排放系统相关的PM2.5水平可能会超过住宅微环境的10倍或更多。因此,我们评估了一种基于质量平衡的方法来估计车内ETS PM2.5浓度。就更新SHEDS-PM模型中与排放交易体系暴露相关的输入数据和算法提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of the Modeling of Exposure to Environmental Tobacco Smoke (ETS) in the SHEDS-PM Model.

Environmental tobacco smoke (ETS) is estimated to be a major contributor to indoor PM concentration and human exposures to fine particulate matter of 2.5 microns or smaller (PM2.5). The Stochastic Human Exposure and Dose Simulation for Particulate Matter (SHEDS-PM) model developed by the US Environmental Protection Agency estimates distributions of outdoor and indoor PM2.5 exposure for a specified population based on ambient concentrations and indoor emissions sources. Because indoor exposures to ETS can be high, especially in indoor residential microenvironments, a critical assessment was conducted of the methodology and data used in SHEDS-PM for estimation of indoor exposure to ETS. For the residential microenvironment, SHEDS uses a mass-balance approach which is comparable to best practices. The default inputs in SHEDS-PM were reviewed and more recent and extensive data sources were identified. Sensitivity analysis was used to determine which inputs should be prioritized for updating. Data regarding the cigarette emission rate was found to be the most important. SHEDS-PM does not currently account for in-vehicle ETS exposure; however, in-vehicle ETS-related PM2.5 levels can exceed those in residential microenvironments by a factor of 10 or more. Therefore, a mass-balance based methodology for estimating in-vehicle ETS PM2.5 concentration is evaluated. Recommendations are made regarding updating of input data and algorithms related to ETS exposure in the SHEDS-PM model.

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