新冠肺炎疫情期间天津市重污染天气的边界层特征

孟丽红; 郝囝; 邱晓滨; 吴彬贵

doi:10.12153/j.issn.1674-991X.20210154

新冠肺炎疫情期间天津市重污染天气的边界层特征

doi: 10.12153/j.issn.1674-991X.20210154

孟丽红^{1, 2,},
郝囝^{1, 2},
邱晓滨^{1, 2},
吴彬贵^{1, 2}

1.
天津市海洋气象重点实验室
2.
天津市气象科学研究所

基金项目: 国家自然科学基金项目(41675018)；天津市气象局项目(202113ybxm05)；环渤海区域科技协同创新基金重点项目(QYXM201901，QYXM202014)

详细信息

作者简介:
孟丽红(1979—)，女，高级工程师，主要从事边界层与大气环境研究，menglh@126.com

中图分类号: X51
计量
- 文章访问数: 291
- HTML全文浏览量: 140
- PDF下载量: 21
- 被引次数: 0
出版历程
- 收稿日期: 2021-04-26
- 网络出版日期: 2022-06-07

Boundary layer characteristics of heavy pollution process in Tianjin during the epidemic period of COVID-19

MENG Lihong^{1, 2
,},
HAO Jian^{1, 2},
QIU Xiaobin^{1, 2},
WU Bingui^{1, 2}

1.
Tianjin Key Laboratory for Oceanic Meteorology
2.
Tianjin Institute of Meteorological Science

摘要

摘要:
为探讨新冠肺炎疫情期间天津市重污染天气成因，利用环境监测、气象常规观测及255 m气象塔梯度观测，结合WRF-Chem模式研究了天津市2020年2月9—13日新冠肺炎疫情期间重污染过程来源及边界层特征。结果表明：水平和垂直扩散条件变差、地面弱气压场和暖湿明显为此次重污染天气的主要特征；重污染天气过程外来源的区域输送率达54.6%；稳定类层结（E类和F类）占比高达67.5%，较为稳定的大气造成大气扩散条件变差，是污染发生的重要气象条件；污染过程逆温率达50.0%，垂直温差、逆温厚度、逆温强度与PM_2.5浓度相关性分别为0.99、0.90和0.56，逆温层的存在是污染过程维持的主要因素。
- 重污染天气 /
- PM_2.5 /
- 边界层 /
- 逆温 /
- 稳定度 /
- 天津市
Abstract:
In order to investigate the causes of heavy pollution in Tianjin during the epidemic period of COVID-19 in 2020, the environmental monitoring, routine meteorological observation and 255 m meteorological tower gradient observation, together with WRF-Chem model simulation were used to discuss the sources and boundary layer characteristics of heavy pollution process during February 9-13th, 2020 in Tianjin. The results showed that the deterioration of horizontal and vertical diffusion conditions, weak air pressure field and warm and humid atmosphere on the ground were the main weather characteristics of this heavy pollution case. The regional transportation rate of external sources in the process of heavy pollution was 54.6%. The stable stratification (E and F) accounted for 67.5%, and the relatively stable atmosphere decreased the atmospheric diffusion condition, which was an important meteorological condition for the occurrence of this pollution. The inversion rate of the pollution process reached 50.0%, and the correlations between the vertical temperature difference, inversion thickness, inversion intensity and PM_2.5 concentration were 0.99, 0.90 and 0.56, respectively. The existence of inversion layer was the main factor to maintain the pollution process.
- heavy pollution /
- PM_2.5 /
- boundary layer /
- thermal inversion /
- stability /
- Tianjin City

HTML全文

图 1 天津市城市气候监测站位置

Figure 1. Distribution of meteorological sites in Tianjin City

下载: 全尺寸图片幻灯片

图 2 2016年天津市PM_2.5浓度模拟值与实测值对比

Figure 2. Comparison between measured and simulated PM_2.5 data in Tianjin City in 2016

下载: 全尺寸图片幻灯片

图 3 2020年2月7—14日天津市区及周边城市PM_2.5浓度日变化

Figure 3. Daily variation of PM_2.5 concentration in Tianjin and its surrounding cities from Feb. 7 to 14, 2020

下载: 全尺寸图片幻灯片

图 4 天津市重污染天气过程主要气象条件

Figure 4. Main meteorological conditions of heavy pollution process in Tianjin

下载: 全尺寸图片幻灯片

图 5 重污染过程WRF-Chem模拟的PM_2.5来源

Figure 5. WRF-Chem simulated source ratio of PM_2.5 in the pollution process

下载: 全尺寸图片幻灯片

图 6 2月8日20:00及2月9日02：00、05:00和08:00边界层观测温湿廓线

Figure 6. Temperature and humidity profile of boundary layer at 20:00 on Feb. 8 and 02:00, 05:00 and 08:00 on Feb. 9

下载: 全尺寸图片幻灯片

图 7 污染过程垂直温差与PM_2.5浓度关系

Figure 7. Relationship between vertical temperature difference and PM_2.5 concentration in the pollution process

下载: 全尺寸图片幻灯片

图 8 污染过程逆温强度与PM_2.5浓度关系

Figure 8. Relationship between inversion intensity and PM_2.5 concentration in the pollution process

下载: 全尺寸图片幻灯片

图 9 污染过程逆温厚度与PM_2.5浓度关系

Figure 9. Relationship between inversion thickness and PM_2.5 concentration in the pollution process

下载: 全尺寸图片幻灯片

图 10 2月9—14日地面和140 m高度处PM_2.5浓度变化

Figure 10. PM_2.5 concentration variation on the ground and at a height of 140 m on Feb. 9 to 14, 2020

下载: 全尺寸图片幻灯片

表 1 温差-风速法确定大气稳定度的分类标准

Table 1. Classification standard for determining atmospheric stability by temperature difference-wind speed method

ν/(m/s)	ΔT/℃
0.0~0.9	A≤−1.13<B≤−1.03<C≤−0.91<D≤−0.37<E≤0.78<F
1.0~1.9	A≤−1.18<B≤−1.05<C≤−0.91<D≤−0.22<E≤1.12<F
2.0~2.9	A≤−1.39<B≤−1.18<C≤−0.97<D≤−0.16<E≤1.25<F
3.0~3.9	A≤−1.61<B≤−1.33<C≤−1.0<D≤−0.10<E≤1.32<F
4.0~4.9	A≤−1.82<B≤−1.48<C≤−1.04<D≤−0.04<E≤1.39<F
5.0~5.9	B≤−1.62<C≤−1.08<D≤0.02<E≤1.46<F
6.0~6.9	B≤−1.77<C≤−1.16<D≤0.08<E
7.0~7.9	C≤−1.25<D
8.0~8.9	C≤−1.40<D
≥9.0	D

下载: 导出CSV

表 2 污染过程大气稳定度统计

Table 2. Statistics of atmospheric stability during the heavy pollution process

日期（月-日）	02:00	05:00	08:00	11:00	14:00	17:00	20:00	23:00
02-08	E	E	E	E	D	D	D	E
02-09	E	D	D	E	D	D	E	E
02-10	F	E	E	D	F	E	E	F
02-11	F	F	F	E	D	D	E	F
02-12	F	E	E	D	D	D	E	E

下载: 导出CSV

参考文献(35)

[1]	CHANG X, WANG S X, ZHAO B, et al. Contributions of inter-city and regional transport to PM_2.5 concentrations in the Beijing-Tianjin-Hebei Region and its implications on regional joint air pollution control[J]. The Science of the Total Environment,2019,660:1191-1200.
[2]	唐倩, 郑博, 薛文博, 等.京津冀及周边地区秋冬季大气污染物排放变化因素解析[J]. 环境科学,2021,42(4):1591-1599. TANG Q, ZHENG B, XUE W B, et al. Contributors to air pollutant emission changes in autumn and winter in Beijing-Tianjin-Hebei and surrounding areas[J]. Environmental Science,2021,42(4):1591-1599.
[3]	岳毅, 李金娟, 马千里.临安本底站2010—2015年PM₁₀污染特征及影响因素分析[J]. 中国环境科学,2017,37(8):2877-2887. doi: 10.3969/j.issn.1000-6923.2017.08.009 YUE Y, LI J J, MA Q L. Variation characteristics of PM₁₀ and its influencing factors at Lin'an regional background station in Yangtze River Delta region during 2010-2015[J]. China Environmental Science,2017,37(8):2877-2887. doi: 10.3969/j.issn.1000-6923.2017.08.009
[4]	张人禾, 李强, 张若楠.2013年1月中国东部持续性强雾霾天气产生的气象条件分析[J]. 中国科学:地球科学,2014,44(1):27-36.
[5]	MARCAZZAN G M, VACCARO S, VALLI G, et al. Characterisation of PM₁₀ and PM_2.5 particulate matter in the ambient air of Milan (Italy)[J]. Atmospheric Environment,2001,35(27):4639-4650.
[6]	DUAN F K, HE K B, MA Y L, et al. Concentration and chemical characteristics of PM_2.5 in Beijing, China: 2001-2002[J]. The Science of the Total Environment,2006,355(1/2/3):264-275.
[7]	LI L, WANG W, FENG J L, et al. Composition, source, mass closure of PM_2.5 aerosols for four forests in eastern China[J]. Journal of Environment Science,2010,31(3):405-412.
[8]	ZHAO X J, ZHAO P S, XU J, et al. Analysis of a winter regional haze event and its formation mechanism in the North China Plain[J]. Atmospheric Chemistry and Physics,2013,13(11):5685-5696.
[9]	廖晓农, 张小玲, 王迎春, 等.北京地区冬夏季持续性雾-霾发生的环境气象条件对比分析[J]. 环境科学,2014,35(6):2031-2044. LIAO X N, ZHANG X L, WANG Y C, et al. Comparative analysis on meteorological condition for persistent haze cases in summer and winter in Beijing[J]. Environmental Science,2014,35(6):2031-2044.
[10]	刘瑞婷, 韩志伟, 李嘉伟.北京冬季雾霾事件的气象特征分析[J]. 气候与环境研究,2014,19(2):164-172. doi: 10.3878/j.issn.1006-9585.2014.13224 LIU R T, HAN Z W, LI J W. Analysis of meteorological characteristics during winter haze events in Beijing[J]. Climatic and Environmental Research,2014,19(2):164-172. doi: 10.3878/j.issn.1006-9585.2014.13224
[11]	曹伟华, 梁旭东, 李青春.北京一次持续性雾霾过程的阶段性特征及影响因子分析[J]. 气象学报,2013,71(5):940-951. doi: 10.11676/qxxb2013.072 CAO W H, LIANG X D, LI Q C. A study of the stageful characteristics and influencing factors of a long-lasting fog/haze event in Beijing[J]. Acta Meteorologica Sinica,2013,71(5):940-951. doi: 10.11676/qxxb2013.072
[12]	刘端阳, 张靖, 吴序鹏, 等.淮安一次雾霾过程的污染物变化特征及来源分析[J]. 大气科学学报,2014,37(4):484-492. LIU D Y, ZHANG J, WU X P, et al. Characteristics and sources of atmospheric pollutants during a fog-haze process in Huai'an[J]. Transactions of Atmospheric Sciences,2014,37(4):484-492.
[13]	谢真珍, 范秀莲, 王月林, 等.淮安地区一次持续性雾霾过程阶段性特征及影响因子分析[J]. 气象与环境学报,2015,31(5):79-85. XIE Z Z, FAN X L, WANG Y L, et al. Phase characteristics of a persistent fog and haze process and its influencing factors in Huaian Area[J]. Journal of Meteorology and Environment,2015,31(5):79-85.
[14]	邓雪娇, 吴兑, 唐浩华, 等.南岭山地一次锋面浓雾过程的边界层结构分析[J]. 高原气象,2007,26(4):881-889. DENG X J, WU D, TANG H H, et al. Analyses on boundary layer structure of a frontal heavy fog process in Nanling Mountain Area[J]. Plateau Meteorology,2007,26(4):881-889.
[15]	孟丽红, 郝天依, 李培彦, 等.天津市夏季重污染天气过程PM_2.5输送特征[J]. 环境工程技术学报,2020,10(1):39-46. doi: 10.12153/j.issn.1674-991X.20190058 MENG L H, HAO T Y, LI P Y, et al. Transport characteristics of PM_2.5 of heavy pollution weather in Tianjin in summer[J]. Journal of Environmental Engineering Technology,2020,10(1):39-46. doi: 10.12153/j.issn.1674-991X.20190058
[16]	杨军, 王蕾, 刘端阳, 等.一次深厚浓雾过程的边界层特征和生消物理机制[J]. 气象学报,2010,68(6):998-1006. doi: 10.11676/qxxb2010.094 YANG J, WANG L, LIU D Y, et al. The boundary layer structure and the evolution mechanisms of a deep dense fog event[J]. Acta Meteorologica Sinica,2010,68(6):998-1006. doi: 10.11676/qxxb2010.094
[17]	孟丽红, 张敏, 韩素芹.天津市郊区冬季大气边界层风、温场结构与特征[J]. 中国环境科学,2012,32(10):1758-1763. doi: 10.3969/j.issn.1000-6923.2012.10.005 MENG L H, ZHANG M, HAN S Q. Structures and characteristics of the atmospheric boundary layer in winter of the Tianjin Suburb[J]. China Environmental Science,2012,32(10):1758-1763. doi: 10.3969/j.issn.1000-6923.2012.10.005
[18]	孟丽红, 李英华, 韩素芹, 等.海陆风对天津市PM_2.5和O₃质量浓度的影响[J]. 环境科学研究,2019,32(3):390-398. MENG L H, LI Y H, HAN S Q, et al. Influence of sea-land breeze on the concentrations of PM_2.5 and O₃ in Tianjin City[J]. Research of Environmental Sciences,2019,32(3):390-398.
[19]	郭蕊, 段浩, 马翠平, 等.河北中南部连续12 d重霾污染天气过程特征及影响因素分析[J]. 气象,2016,42(5):589-597. doi: 10.7519/j.issn.1000-0526.2016.05.008 GUO R, DUAN H, MA C P, et al. Analysis on the characters and influencing factors of a 12 d heavy haze pollution weather process[J]. Meteorological Monthly,2016,42(5):589-597. doi: 10.7519/j.issn.1000-0526.2016.05.008
[20]	周奕珂, 朱彬, 韩志伟, 等.长江三角洲地区冬季能见度特征及影响因子分析[J]. 中国环境科学,2016,36(3):660-669. doi: 10.3969/j.issn.1000-6923.2016.03.005 ZHOU Y K, ZHU B, HAN Z W, et al. Analysis of visibility characteristics and connecting factors over the Yangtze River Delta Region during winter time[J]. China Environmental Science,2016,36(3):660-669. doi: 10.3969/j.issn.1000-6923.2016.03.005
[21]	孙霞, 银燕, 孙玉稳, 等.石家庄地区春季晴、霾天气溶胶观测研究[J]. 中国环境科学,2011,31(5):705-713. SUN X, YIN Y, SUN Y W, et al. An observational study of aerosol particles tlsing aircroft over Shijiazhuang Area in clean and hazy days during spring[J]. China Environmental Science,2011,31(5):705-713.
[22]	解以扬, 刘学军.天津气象塔风温梯度观测资料的统计特征[J]. 气象,2003,29(1):12-16. doi: 10.3969/j.issn.1000-0526.2003.01.003 XIE Y Y, LIU X J. A statistical analysis of wind and temperature gradient data from Tianjin meteorological tower[J]. Meteorological Monthly,2003,29(1):12-16. doi: 10.3969/j.issn.1000-0526.2003.01.003
[23]	蔡子颖, 韩素芹, 吴彬贵, 等.天津一次雾过程的边界层特征研究[J]. 气象,2012,38(9):1103-1109. CAI Z Y, HAN S Q, WU B G, et al. Analysis on characteristics of atmospheric boundary layer during a fog process in Tianjin[J]. Meteorological Monthly,2012,38(9):1103-1109.
[24]	姚青, 蔡子颖, 韩素芹, 等.一次沙尘过程对天津气溶胶浓度分布的影响[J]. 中国沙漠,2013,33(4):1138-1143. doi: 10.7522/j.issn.1000-694X.2013.00161 YAO Q, CAI Z Y, HAN S Q, et al. Influence of A sand-dust weather process on aerosol mass concentration and number concentration in Tianjin, China[J]. Journal of Desert Research,2013,33(4):1138-1143. doi: 10.7522/j.issn.1000-694X.2013.00161
[25]	韩素芹, 刘彬贤, 解以扬, 等.利用255 m铁塔研究城市化对地面粗糙度的影响[J]. 气象,2008,34(1):54-58. doi: 10.7519/j.issn.1000-0526.2008.01.008 HAN S Q, LIU B X, XIE Y Y, et al. Research of urbanization on surface roughness with 255 m meteorological tower[J]. Meteorological Monthly,2008,34(1):54-58. doi: 10.7519/j.issn.1000-0526.2008.01.008
[26]	ZHANG Y L, ZHU B, GAO J H, et al. The source apportionment of primary PM_2.5 in an aerosol pollution event over Beijing-Tianjin-Hebei Region using WRF-Chem, China[J]. Aerosol and Air Quality Research,2017,17(12):2966-2980.
[27]	孟丽红, 杨旭, 刘丽丽, 等.气溶胶在重污染过程对气象和PM_2.5的反馈作用[J]. 环境科学与技术,2020,43(12):63-71. MENG L H, YANG X, LIU L L, et al. Feedback effect of aerosol radiation on meteorology and PM_2.5 in heavy pollution process[J]. Environmental Science & Technology,2020,43(12):63-71.
[28]	HAO T Y, HAN S Q, CHEN S C, et al. The role of fog in haze episode in Tianjin, China: a case study for November 2015[J]. Atmospheric Research,2017,194:235-244.
[29]	赵晨曦, 王云琦, 王玉杰, 等.北京地区冬春PM_2.5和PM₁₀污染水平时空分布及其与气象条件的关系[J]. 环境科学,2014,35(2):418-427. ZHAO C X, WANG Y Q, WANG Y J, et al. Temporal and spatial distribution of PM_2.5 and PM₁₀ pollution status and the correlation of particulate matters and meteorological factors during winter and spring in Beijing[J]. Environmental Science,2014,35(2):418-427.
[30]	孟丽红, 蔡子颖, 李英华, 等.天津市PM_2.5浓度时空分布特征及重污染过程来源模拟分析[J]. 环境科学研究,2020,33(1):9-17. MENG L H, CAI Z Y, LI Y H, et al. Spatial and temporal distributions and source simulation during heavy pollution of PM_2.5 in Tianjin City[J]. Research of Environmental Sciences,2020,33(1):9-17.
[31]	杨旭, 蔡子颖, 韩素芹, 等.基于无人机探空和数值模拟天津一次重污染过程分析[J]. 环境科学,2021,42(1):9-18. YANG X, CAI Z Y, HAN S Q, et al. Heavy pollution episode in Tianjin based on UAV meteorological sounding and numerical model[J]. Environmental Science,2021,42(1):9-18.
[32]	杨静, 武疆艳, 李霞, 等.乌鲁木齐冬季大气边界层结构特征及其对大气污染的影响[J]. 干旱区研究,2011,28(4):717-723. YANG J, WU J Y, LI X, et al. Analysis on atmospheric boundary layer structure and its effect on air pollution over Urumqi City in winter[J]. Arid Zone Research,2011,28(4):717-723.
[33]	蔡子颖, 韩素芹, 张敏, 等.天津地区污染天气分析中垂直扩散指标构建及运用[J]. 环境科学,2018,39(6):2548-2556.
[34]	潘亮, 阎凤霞, 吴峻石, 等.2013—2019年上海早晨接地逆温指标与PM_2.5定量关系研究[J]. 中国环境科学,2021,41(2):517-526. doi: 10.3969/j.issn.1000-6923.2021.02.003 PAN L, YAN F X, WU J S, et al. Parameters of surface based inversion in the morning during 2013 to 2019 and its quantitative relationship with PM_2.5 in Shanghai[J]. China Environmental Science,2021,41(2):517-526. doi: 10.3969/j.issn.1000-6923.2021.02.003
[35]	HAN S, ZHANG Y, WU J, et al. Evaluation of regional background particulate matter concentration based on vertical distribution characteristics[J]. Atmospheric Chemistry and Physics,2015,15(19):11165-11177. □