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    赵宇

    • 副教授       硕士生导师
    • 性别:男
    • 毕业院校:哈尔滨工业大学
    • 学位:博士
    • 所在单位:土木工程系
    • 学科:供热、供燃气、通风及空调工程
    • 办公地点:厚兴楼602 B室
    • 联系方式:0411-84706203
    • 电子邮箱:zhaoyu1220@dlut.edu.cn

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    Seasonal patterns of PM10, PM2.5, and PM1.0 concentrations in a naturally ventilated residential underground garage

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    论文类型:期刊论文

    发表时间:2017-11-01

    发表刊物:BUILDING AND ENVIRONMENT

    收录刊物:Scopus、SCIE、EI

    卷号:124

    页面范围:294-314

    ISSN号:0360-1323

    关键字:Underground parking garage; Particulate matter; Natural ventilation; Traffic flow

    摘要:In China, residential areas are prevalently equipped with underground parking garages. Particulate matter has been confirmed as a major pollutant in garage spaces, and exposure to these particles, especially submicron and ultrafine particles, is closely associated with the health of vehicle owners and people who work in garages. In this study, we evaluated the seasonal patterns of PM10, PM2.5, and PM1.0 in a naturally ventilated underground residential parking garage using field measurements collected at various times over a one-year period. The impacts of traffic flow, air exchange rate, and outdoor particles were determined by employing Pearson correlation and a mass-balance model. The results showed significant seasonal diurnal patterns of PM10, PM2.5, and PM1.0, with maximum values during winter and minimum values during summer. The daily mean PM10 and PM2.5 in the garage exceeded the long-term (24 h) exposure limit of the Chinese standard (0.15 mg/m(3) for PM10 and 0.075 mg/m(3) for PM2.5) during spring, fall and winter, with the highest PM10 and PM2.5 concentration exceeding the limit eightfold. Use of natural ventilation only in the residential underground parking garage could not guarantee that particle pollution was at a "safe" exposure level in the study. During the measurements, the hourly mean PM10, PM2.5, and PM1.0 appeared to vary linearly under the combined effects of the air exchange rate multiplied by the outdoor particles; traffic flow; and mean PM10, PM2.5, and PM1.0 during the past hour. (C) 2017 Elsevier Ltd. All rights reserved.