1961—2020年郑州主城区大气自净能力变化特征分析

doi:10.3969/j.issn.1673-503X.2022.03.011

Abstract

Abstract:

Based on the meteorological observation data from 1961 to 2020 and the air quality monitoring data from 2014 to 2018 in the main urban area of Zhengzhou, the long-term trend and influencing factors of atmospheric self-purification capacity(ASPC) index in this area were analyzed, and the relationship between the ASPC and PM_2.5 was studied.The results show that from 1981 to 2010, the ASPC index has an average value of 4.42 t·(d·km²)^-1, the largest value of 5.2 t·(d·km²)^-1 in spring, and the smallest value of 3.88 t·(d·km²)^-1 in autumn, which is disadvantage to the removal of air pollutants.From 1961 to 2020, the ASPC in the study region shows a significant weakening trend with a maximum value of 6.85 t·(d·km²)^-1 in 1969 and a minimum value of 3.06 t·(d·km²)^-1 in 2020.The mixing layer thickness is positively correlated with the ASPC index.The number of days with daily mean wind speed ≥2.5 m·s^-1 and light wind days are significantly positively and negatively correlated with the ASPC, respectively.Furthermore, the ASPC index is significantly correlated with the number of precipitation days.Specifically, the increase in the number of heavy precipitation days after 2015 has a certain influence on the enhancement of ASPC in the same period.In addition, the study also shows that there was a significantly negative correlation between ASPC and PM_2.5 concentration in the main urban area, indicating that the stronger ASPC is, the lower the corresponding PM_2.5 concentration is, and the better the ambient air quality is.

Key words: Atmospheric self-purification capability, Mixed layer thickness, Wind velocity, Precipitation, PM_2.5

CLC Number:

Mei LIU,Xing-jie JI,Li TIAN,Ya-lei DING,Xuan ZUO. Analysis of variation characteristics of atmospheric self-purification capability in the main urban area of Zhengzhou from 1961 to 2020[J]. Journal of Meteorology and Environment, 2022, 38(3): 93-100.

Figures/Tables 10

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Table 1

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References 29

1	董会忠, 曹正旭, 李旋, 等. 山东省产业结构、城市化与大气环境动态关系研究[J]. 山东理工大学学报: 社会科学版, 2020, 36 (4): 19- 25. doi: 10.3969/j.issn.1672-0040.2020.04.002
2	汪发元, 郑军, 汪宗顺. 城市化水平、工业化水平对空气质量的影响分析——基于湖北省16城市2005—2017年数据的时空模型[J]. 长江流域资源与环境, 2019, 28 (6): 1411- 1421.
3	王明仕, 何向东, 曹景丽, 等. 区域城市化程度与大气污染的相关性研究——以河南省为例[J]. 河南理工大学学报: 自然科学版, 2019, 38 (2): 71- 76.
4	徐大海, 王郁. 确定大气环境承载力的烟云足迹法[J]. 环境科学学报, 2013, 33 (6): 1734- 1740.
5	薛文博, 付飞, 王金南, 等. 基于全国城市PM_2.5达标约束的大气环境容量模拟[J]. 中国环境科学, 2014, 34 (10): 2490- 2496.
6	徐大海, 王郁, 朱蓉. 大气环境容量系数A值频率曲线拟合及其应用[J]. 中国环境科学, 2016, 36 (10): 2913- 2922. doi: 10.3969/j.issn.1000-6923.2016.10.006
7	徐大海, 朱蓉. 国家标准GB/T3840—91中城市大气污染物总量控制A—P值法的应用[J]. 城市环境与城市生态, 1993, 6 (2): 36- 41.
8	肖杨, 毛显强, 马根慧, 等. 基于ADMS和线性规划的区域大气环境容量测算[J]. 环境科学研究, 2008, 21 (3): 13- 16.
9	Moreira D M , Tirabassi T , Carvalho J C . Plume dispersion simulation in low wind conditions in stable and convective boundary layers[J]. Atmospheric Environment, 2005, 39 (20): 3643- 3650. doi: 10.1016/j.atmosenv.2005.03.004
10	Sharan M , Gopalakrishnan S G . Mathematical modeling of diffusion and transport of pollutants in the atmospheric boundary layer[J]. Pure and Applied Geophysics, 2003, 160, 357- 394. doi: 10.1007/s00024-003-8784-5
11	DeGaetano A T , Doherty O M . Temporal, spatial and meteorological variations in hourly PM_2.5 concentration extremes in New York City[J]. Atmospheric Environment, 2004, 38 (11): 1547- 1558. doi: 10.1016/j.atmosenv.2003.12.020
12	白雪, 张翠艳, 纪源, 等. 锦州市空气质量变化特征及其与气象条件关系[J]. 气象与环境学报, 2016, 32 (2): 52- 58.
13	毛卓成, 马井会, 翟元昊, 等. 2015年上海地区空气质量状况及其与气象条件的关系[J]. 气象与环境学报, 2018, 34 (2): 52- 60.
14	严晓瑜, 缑晓辉, 刘玉兰, 等. 银川市大气污染物浓度变化特征及其与气象条件的关系[J]. 气象与环境学报, 2015, 31 (2): 21- 30.
15	Han Z Y , Zhou B T , Xu Y , et al. Projected changes in haze pollution potential in China: An ensemble of regional climate model simulations[J]. Atmospheric Chemistry and Physics, 2017, 17 (16): 10109- 10123. doi: 10.5194/acp-17-10109-2017
16	王振, 杨卫芬, 叶香, 等. 气象因素对常州市区PM_2.5浓度影响[J]. 气象与环境学报, 2020, 36 (3): 26- 32.
17	熊险平, 王琼, 张唯, 等. 沧州市大气自净能力特征分析[J]. 环境科学导刊, 2019, 38 (6): 44- 50.
18	郁珍艳, 李正泉, 高大伟, 等. 浙江省空气质量与大气自净能力的特征分析[J]. 气象, 2017, 43 (3): 323- 332.
19	唐颖潇, 韩素芹, 蔡子颖, 等. 2013—2017年天津市大气自净能力与大气颗粒物质量浓度特征分析[J]. 气象与环境学报, 2019, 35 (6): 55- 66.
20	张天宇, 张丹, 王勇, 等. 1951—2018年重庆主城区大气自净能力变化特征分析[J]. 高原气象, 2019, 38 (4): 901- 910.
21	朱红蕊, 刘赫男, 张洪玲, 等. 2008—2018年黑龙江省大气自净能力变化特征分析[J]. 气象与环境学报, 2020, 36 (4): 89- 94.
22	杨旭, 康延臻, 王式功, 等. 郑州市大气污染特征及其与气象条件的关系[J]. 兰州大学学报: 自然科学版, 2017, 53 (3): 348- 354.
23	韩艳, 李东璞, 李思杰, 等. 河南省供暖期大气污染特征及预测分析——以郑州市为例[J]. 河南大学学报: 自然科学版, 2018, 48 (6): 639- 649.
24	郭蒙蒙, 姜楠, 王申博, 等. 郑州市2014—2017年大气污染特征及气象条件影响分析[J]. 环境科学, 2019, 40 (9): 3856- 3867.
25	王维思, 王楠, 高玉娟, 等. 2019年郑州冬、春季重污染期间PM_2.5污染特征分析[J]. 环境科学学报, 2020, 40 (5): 1594- 1603.
26	中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. 风力等级(GB/T 28591—2012)[S]. 北京: 中国标准出版社, 2012.
27	中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. 降水量等级(GB/T 28592—2012)[S]. 北京: 中国标准出版社, 2012.
28	朱蓉, 张存杰, 梅梅. 大气自净能力指数的气候特征与应用研究[J]. 中国环境科学, 2018, 38 (10): 3601- 3610.
29	环境保护部, 国家质量监督检验检疫总局. 环境空气质量标准(GB 3095—2012)[S]. 北京: 中国环境科学出版社, 2012.

年份	大气自净能力指数/[t·(d·km²)]^-1	优良天数/d	PM_2.5年均浓度/(μg·m^-3)
2014	3.33	163	88.1
2015	3.41	135	95.9
2016	3.53	157	78.2
2017	3.34	166	71.7
2018	3.38	202	62.9

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Analysis of variation characteristics of atmospheric self-purification capability in the main urban area of Zhengzhou from 1961 to 2020

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