Quantitative estimation of excess mortality for drivers and passengers exposed to particulate matters in long-distance buses

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• 作者：Chia-Pin Chio^a ; Yi-Hsien Cheng^a ; Min-Pei Ling^b ; Szu-Chieh Chen^c ; ^d ; Chung-Min Liao^a ; ^{cmliao@ntu.edu.tw}
• 关键词：Particulate matter ; Long-distance bus ; Driver ; Passenger ; Excess mortality
• 刊名：Atmospheric Environment
• 出版年：2012
• 期刊代码：11_13522310
• 类别：env
• 出版时间：May, 2012
• 卷：51
• 期：Complete
• 页码：260-267
• 文件大小：530 K

摘要

The purpose of this study was to estimate quantitatively the excess mortality for driver/passenger in long-distance buses in terms of long driving time and inhaled particulate matters (PMs) concentrations. This study used an area under the curve (AUC) approach integrating the driving time and a predicted single pulsed PM concentration to estimate the fluctuating PM exposures in long-distance buses. Different peak functions were used to fit a unique fluctuating PM dataset adopted from previous study in Taiwan. We showed that gamma distribution had a best-fitting performance with the minimum values of coefficient of variation (CV) for PM_2.5 and PM₁₀ of 2.9%and 11.7%. The results also indicated that the predicted CV values for PM_2.5 (5.3%) and PM₁₀ (14.0%) from fitted normal distributions were also agreeable compared with the original dataset. The results indicated that the PM_2.5-associated excess mortality estimates ranged from 0.64 to 1.04 and 4103-6833 individuals per 10⁵ population for passengers under short-term and drivers under long-term PM exposures. Moreover, the interquartile ranges of the excess mortality estimate in the proposed model were 2.5-5.6 times less than that in the original dataset. We concluded that our AUC-based model may successfully reduce the variations in PM exposure estimates, and thereby provide more accurate values for improving risk estimation of future excess mortality attributable to traffic-related air pollutants.