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翔安海底隧道运营环境及污染物分布规律

王明年 王旭 于丽 邓涛

王明年, 王旭, 于丽, 邓涛. 翔安海底隧道运营环境及污染物分布规律[J]. 西南交通大学学报, 2020, 55(4): 695-703. doi: 10.3969/j.issn.0258-2724.20180714
引用本文: 王明年, 王旭, 于丽, 邓涛. 翔安海底隧道运营环境及污染物分布规律[J]. 西南交通大学学报, 2020, 55(4): 695-703. doi: 10.3969/j.issn.0258-2724.20180714
WANG Mingnian, WANG Xu, YU Li, DENG Tao. Operating Environment and Pollutant Distribution in Xiang’an Undersea Tunnel[J]. Journal of Southwest Jiaotong University, 2020, 55(4): 695-703. doi: 10.3969/j.issn.0258-2724.20180714
Citation: WANG Mingnian, WANG Xu, YU Li, DENG Tao. Operating Environment and Pollutant Distribution in Xiang’an Undersea Tunnel[J]. Journal of Southwest Jiaotong University, 2020, 55(4): 695-703. doi: 10.3969/j.issn.0258-2724.20180714

翔安海底隧道运营环境及污染物分布规律

doi: 10.3969/j.issn.0258-2724.20180714
基金项目: 国家自然科学基金(51878567);四川省科技计划项目(2018JY0566)
详细信息
    作者简介:

    王明年(1965—),男,教授,研究方向为隧道与地下工程,E-mail:19910622@163.com

  • 中图分类号: U459.2

Operating Environment and Pollutant Distribution in Xiang’an Undersea Tunnel

  • 摘要: 为了明确城市海底公路隧道内环境参数和污染物的分布规律,针对厦门翔安海底隧道运营通风效果进行了现场测试,获取了交通高峰期和非高峰期两个时段隧道内气压、温湿度、风速、CO、NO2和PM浓度的分布规律,结合一维扩散理论和Fluent组分输运模型研究了海底公路隧道内环境参数和污染物随交通流的分布规律. 研究结果表明:(1) 交通高峰期时段,温度沿车流方向逐渐升高,出口处达到最高温度36 ℃;湿度沿车流方向逐渐降低,入口处最大湿度为94%;CO、NO2和PM浓度随车流方向逐渐升高,在出口处达到最大,最大浓度分别为21.00 ppm、3.73 ppm和1.76 mg/m3,V型坡坡底处PM浓度也较高(2.03 mg/m3);根据烟尘质量浓度与消光系数的转换公式得到出口处和V型坡坡底处的消光系数分别为0.008 3 m−1和0.009 5 m−1,NO2和PM浓度超过了规范值.(2) 非交通高峰期NO2最大浓度为1.68 ppm,出口处和V型坡坡底处的消光系数分别为0.006 9 m−1和0.007 7 m−1,出口处NO2浓度和坡底处消光系数超过了规范值.

     

  • 图 1  翔安海底隧道纵断面

    Figure 1.  Longitudinal section of Xiang’an undersea tunnel

    图 2  翔安海底隧道通风系统

    Figure 2.  Ventilation system of Xiang’an undersea tunnel

    图 3  纵向测点布置

    Figure 3.  Longitudinal measuring points layout

    图 4  横向测点布置(单位:m)

    Figure 4.  Horizontal measuring points layout (unit: m)

    图 5  翔安海底隧道日交通量变化

    Figure 5.  Daily traffic volume in Xiang’an undersea tunnel

    图 6  环境参数沿隧道纵向分布规律

    Figure 6.  Longitudinal distribution of environmental parameters along the tunnel

    图 7  污染物沿隧道纵向分布规律

    Figure 7.  Longitudinal distribution of pollutants along the tunnel

    图 8  翔安海底隧道数值模型

    Figure 8.  Numerical model of Xiang’an undersea tunnel

    图 9  横断面网格划分

    Figure 9.  Cross section meshing diagram

    图 10  CO、NO2浓度沿隧道纵向分布规律

    Figure 10.  Longitudinal distribution of CO,NO2 concentration along the tunnel

    表  1  不同隧道污染物浓度测试结果比较

    Table  1.   Comparison of pollutant concentrations measured in different tunnels

    隧道名称地区长度/m交通量/
    (veh•h−1
    轻型车
    占比/%
    平均车速/
    (km•h−1
    出口浓度
    CO/ppmNO2/ppmPM/(mg•m−3
    狮子山隧道 香港 1 295 2 300 43~58 6.5 0.33
    雪山隧道 台湾 12 900 1 400 89.1 80 12.0~39.0 1.20~3.10 0.148~0.178
    Janio Quardros隧道 圣保罗 850 1 500~2 000 85.0 72 6.7 ± 1.8 0.20 0.123 ± 0.031
    Rodoanel隧道 圣保罗 1 150 3 000 70.0 83 6.3 ± 1.5 1.15 0.245 ± 0.059
    东延安路隧道 上海 2 261 2 700 95.0 20~40 17.4
    营盘路隧道 长沙 2 510 1 700~2 600 98.4 30 20.3 1.65
    翔安海底隧道 厦门 6 050 2 000~2 952 77.0 40~60 13.0~22.0 1.57~3.73 1.47~1.65
    下载: 导出CSV

    表  2  设计限值标准

    Table  2.   Design threshold criteria values

    标准名称地区CO/
    ppm
    NO2/
    ppm
    PM/
    (mg•m−3
    PIARC 2012国际7011.489
    公路隧道通风
    设计细则
    中国100必要时考虑1.596
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-09-11
  • 修回日期:  2019-01-10
  • 网络出版日期:  2020-03-03
  • 刊出日期:  2020-08-01

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