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大气自净容量的算法及关键物理因子分析

许云凡 向伟玲 王自发

许云凡, 向伟玲, 王自发. 2022. 大气自净容量的算法及关键物理因子分析[J]. 气候与环境研究, 27(4): 458−468 doi: 10.3878/j.issn.1006-9585.2021.21031
引用本文: 许云凡, 向伟玲, 王自发. 2022. 大气自净容量的算法及关键物理因子分析[J]. 气候与环境研究, 27(4): 458−468 doi: 10.3878/j.issn.1006-9585.2021.21031
XU Yunfan, XIANG Weiling, WANG Zifa. 2022. Algorithm of Atmospheric Self-Purification Capacity and Its Critical Physical Factors [J]. Climatic and Environmental Research (in Chinese), 27 (4): 458−468 doi: 10.3878/j.issn.1006-9585.2021.21031
Citation: XU Yunfan, XIANG Weiling, WANG Zifa. 2022. Algorithm of Atmospheric Self-Purification Capacity and Its Critical Physical Factors [J]. Climatic and Environmental Research (in Chinese), 27 (4): 458−468 doi: 10.3878/j.issn.1006-9585.2021.21031

大气自净容量的算法及关键物理因子分析

doi: 10.3878/j.issn.1006-9585.2021.21031
基金项目: 国家重点研发计划2017YFC0213004
详细信息
    作者简介:

    许云凡,女,1993年出生,博士,主要研究方向为大气环境容量与承载力。E-mail:xuyunfan1993@outlook.com

    通讯作者:

    向伟玲,E-mail:xiangweiling@mail.iap.ac.cn

  • 中图分类号: X513

Algorithm of Atmospheric Self-Purification Capacity and Its Critical Physical Factors

Funds: National Key Research and Development Program of China (Grant 2017YFC0213004)
  • 摘要: 为更科学地量化大气对污染物的清除能力,使用WRF-NAQPMS模式对2017年12月进行模拟,对比分析影响大气清除能力的主要关键物理因子,修正A值法和大气自净容量算法的差异,进一步计算大气自净容量余量及各关键物理化学过程的贡献量。结果表明,边界层高度、风廓线、湿清除系数等3个关键物理参数较混合层高度、10 m高度风速、雨洗强度等更适用于量化清除过程;修正A值法和大气自净容量算法虽均能表征大气清除能力的强弱,但前者受目标城市面积影响较大,结果远高于大气自净容量算法;大气自净容量余量与细颗粒物(PM2.5)浓度变化趋势呈负相关,污染越重,大气自净容量亏空越多,其中平流扩散对大气自净容量贡献最大,化学转化过程次之,湿沉降等过程也不可忽视。
  • 图  1  修正A值法技术路线

    Figure  1.  Technology flowchart of the modified A-value method

    图  2  大气自净容量算法技术路线

    Figure  2.  Fig. Technology flowchart of the atmospheric self-purification capacity method

    图  3  模式区域设置

    Figure  3.  Nested domains for the NAQPMS simulation

    图  4  2017年12月京津冀及周边地区“2+26”城市昼夜混合层高度与边界层高度对比

    Figure  4.  Comparison of diurnal mixing layer height and planetary boundary layer height in Beijing-Tianjin-Hebei and its surrounding areas in Dec 2017

    图  5  2017 年12 月京津冀及周边地区“2+26”城市(a)昼、(b)夜混合层高度和边界层高度之差及其对应大气自净容量之差的关系(散点的颜色表征海拔高度);(c)昼、(d)夜两种高度下大气自净量差异的概率密度分布

    Figure  5.  Relationship between (a) day and (b) night mixing layer height and planetary boundary layer height and the corresponding difference in atmospheric selfpurification capacity of "2+26" cities in Beijing−Tianjin−Hebei and its surrounding areas in Dec 2017 (colored dots show the variation of the height above sea level) and (c) day and (d) night probability density distribution of the difference between above two kinds of atmospheric self-purification capacity

    图  6  2017年12月京津冀及周边地区“2+26”城市1~12层昼夜风速廓线

    Figure  6.  Diurnal wind speed profiles at layers 1 to 12 of "2+26" cities in Beijing−Tianjin−Hebei and its surrounding areas in Dec 2017

    图  7  2017年12月京津冀及周边地区“2+26”城市(a)日间雨洗自净能力、(b)日间湿清除自净能力、(c)夜间雨洗自净能力、(d)夜间湿清除自净能力的空间分布

    Figure  7.  Spatial distributions of (a) daytime rain-washing self-purification capacity, (b) daytime wet scavenging self-purification capacity, (c) night rain-washing self-purification capacity, (d) night wet scavenging self-purification capacity of "2+26" cities in Beijing−Tianjin−Hebei and its surrounding areas in Dec 2017

    图  8  京津冀及周边地区 “2+26”城市面积及其2017年12月PM2.5自净容量与大气自净能力

    Figure  8.  "2+26" urban area and corresponding PM2.5 self-cleaning capacity and atmospheric air self-purification capacity in Beijing−Tianjin−Hebei and its surrounding areas in Dec 2017

    图  9  2017年12月北京市PM2.5观测浓度、自净容量余量及过程贡献量时间序列

    Figure  9.  Time series of PM2.5 observed concentration, self-purification capacity surplus and process contribution in Beijing in Dec 2017

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  • 收稿日期:  2021-02-08
  • 网络出版日期:  2021-08-26
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