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大气污染资料同化与应用综述

朱江 唐晓 王自发 吴林

朱江, 唐晓, 王自发, 吴林. 大气污染资料同化与应用综述[J]. 大气科学, 2018, 42(3): 607-620. doi: 10.3878/j.issn.1006-9895.1802.17260
引用本文: 朱江, 唐晓, 王自发, 吴林. 大气污染资料同化与应用综述[J]. 大气科学, 2018, 42(3): 607-620. doi: 10.3878/j.issn.1006-9895.1802.17260
Jiang ZHU, Xiao TANG, Zifa WANG, Lin WU. A Review of Air Quality Data Assimilation Methods and Their Application[J]. Chinese Journal of Atmospheric Sciences, 2018, 42(3): 607-620. doi: 10.3878/j.issn.1006-9895.1802.17260
Citation: Jiang ZHU, Xiao TANG, Zifa WANG, Lin WU. A Review of Air Quality Data Assimilation Methods and Their Application[J]. Chinese Journal of Atmospheric Sciences, 2018, 42(3): 607-620. doi: 10.3878/j.issn.1006-9895.1802.17260

大气污染资料同化与应用综述

doi: 10.3878/j.issn.1006-9895.1802.17260
基金项目: 

国家自然科学基金项目 91644216

国家自然科学基金项目 41575128

详细信息
    作者简介:

    朱江, 男, 1963年出生, 研究员, 主要从事资料同化理论与应用研究。E-mail:jzhu@mail.iap.ac.cn

  • 中图分类号: P402

A Review of Air Quality Data Assimilation Methods and Their Application

Funds: 

National Natural Science Foundation 91644216

National Natural Science Foundation 41575128

  • 摘要: 我国正面临以高浓度臭氧和细颗粒物为典型特征的大气复合污染问题,对其进行模拟和预报是有效应对大气污染的关键。大气复合污染预报的不确定性来源复杂,同时存在化学非线性的影响,各种模式输入不确定性对模拟预报影响的时空差异较大,从而导致很多不确定性约束方法难以确定关键的不确定性因子而进行有针对性的约束和订正。利用资料同化方法融合模式、多源观测等信息,减小模式输入数据的不确定性成为提升大气污染模拟预报精度的关键。本文将简要介绍大气污染资料同化相关的模式不确定性、同化算法以及污染物浓度场同化、源反演研究上的进展,探讨大气污染资料同化面临的主要挑战和发展趋势。
  • 表  1  国际一些研究对大气化学模式输入变量不确定性的估计

    Table  1.   Estimate the uncertainty of input variables in atmospheric chemistry model by some international studies

    模式输入变量 不确定性估算的标准差
    Moore and Londergan(2001) Hanna et al.(1998) Beekmann and Derognat(2003)
    人为排放源(NOx 25%~50% 30%~40% 40%
    人为排放源(VOC) 25%~50% 50%~80% 40%
    生物排放源(NOx 25%~0 200%
    生物排放源(VOC) 25%~0 200% 50%
    风向 11° 30°
    风速 25%~0 30% 1.5 m/s
    垂直混合高度 25%~0 50% 50%
    温度 3 K 3 K 1.5 K
    相对湿度 30% 20%
    边界层高度 20%
    沉降速度 25%~0 30% 25%
    侧边界条件(O3 5%~10% 30%
    侧边界条件(NOx、VOC) 5%~10% 80%
    上边界条件(O3 5%~10% 70%
    上边界条件(NOx、VOC) 5%~10% 200%
    初始浓度(O3 15%~20% 30%
    初始浓度(NOx、VOC) 15%~20% 50%
    化学反应系数 25% 30% 10%~30%
    下载: 导出CSV

    表  2  近6年大气污染源反演的一些典型应用

    Table  2.   Typical applications of air pollution source inversion in recent six years

    文献出处 物种 观测数据 反演区域 空间分辨率 反演算法
    Bergamaschi et al.(2014) CH4、N2O 地面站点 欧洲 约1°×1° 四维变分
    Koohkan et al.(2013) VOCs 地面站点 西欧 0.5°×0.5° 四维变分
    Tang et al.(2013) CO 地面站点 北京及周边 约0.11°×0.08° 集合卡尔曼滤波
    Ghude et al.(2013) NOx 卫星观测 印度半岛 2.8°×2.8° 质量平衡方法
    Miyazaki et al.(2012) NO2、O3、CO、HNO3 卫星观测 全球 2.8°×2.8° 集合卡尔曼滤波
    Huneeus et al.(2012) 沙尘、海盐、BC(黑炭)、OC(有机碳)、SO2 卫星观测 全球 全球分为9至11个区域 四维变分
    Hooghiemstra et al.(2012) CO 卫星观测 全球 6°×4° 四维变分
    Sugimoto et al.(2010) 沙尘 激光雷达 蒙古及周边 约0.5°×0.4° 四维变分
    下载: 导出CSV
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  • 收稿日期:  2017-10-28
  • 网络出版日期:  2018-03-12
  • 刊出日期:  2018-05-15

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