干旱气象 ›› 2020, Vol. 38 ›› Issue (03): 440-447.

• 论文 • 上一篇    下一篇

2014—2017年西安市PM2.5污染特征及影响因子

黄蕾,毕旭,杨晓春,翟园,金丽娜,高宇星   

  1. 陕西省西安市气象台,陕西西安710016
  • 出版日期:2020-06-28 发布日期:2020-07-02

Characteristics of PM2.5 Pollution and Influence of Meteorological Factors in Xi’an During 2014-2017

HUANG Lei, BI Xu, YANG Xiaochun, ZHAI Yuan, JIN Lina, GAO Yuxing   

  1. Xi’an Meteorological Bureau of Shaanxi Province, Xi’an 710016, China
  • Online:2020-06-28 Published:2020-07-02

摘要: 利用2014—2017年西安市PM2.5日平均质量浓度资料,分析PM2.5质量浓度的年、月及采暖期和非采暖期的变化特征,并结合气象要素日观测资料分析各气象要素在不同季节与PM2.5质量浓度的相关性;利用2017年13个国控环境空气质量监测站点的PM2.5逐时质量浓度数据分析西安地区PM2.5空间分布差异及日变化特征。结果表明:PM2.5质量浓度月际变化呈现出明显的“U”型特征,冬季PM2.5质量浓度较高,夏季相对较低;每年1—2月、11—12月PM2.5差异显著, 该时段平均风速、降水量及冷空气活动次数对PM2.5质量浓度有一定影响。供暖期PM2.5超标日数及其所占全年超标日数的百分比均有逐年增加趋势,而非供暖期两者则呈逐年下降趋势。夏季西安各地区PM2.5质量浓度差异相对较小,而冬季则相对较大。西安PM2.5质量浓度存在明显日变化特征,其昼夜变化规律为“M”型,不同站点的PM2.5污染差异主要在夜间。不同季节气温、相对湿度、风速及降水与PM2.5质量浓度的相关性不同,低温高湿、小风速及无降水日出现高等级PM2.5污染的可能性较高。统计得到不同等级PM2.5污染时各气象要素范围,对PM2.5污染的空气质量预报有一定的指示意义。

关键词: PM2.5, 时间变化, 空间分布, 气象条件

Abstract: Based on daily PM2.5 concentration data during 2014-2017, the annual and monthly variations of PM2.5 concentration were analyzed in Xi’an, and in heating and non-heating seasons its difference was obvious. Combined with daily meteorological elements observations from  meteorological stations, the correlation between meteorological elements and PM2.5 concentration in different seasons was analyzed. The hourly PM2.5 concentration data of 13 air-quality automatic monitoring stations in 2017 were used to analyze the spatial distribution and diurnal variation of PM2.5 concentration in Xi’an. The main conclusions are as follows: The PM2.5 concentration showed a U-shaped characteristic within a year, which was higher in winter but lower in summer. The difference of PM2.5 concentration in recent years was mainly in January, February, November and December,during this period, the wind speed, precipitation and cold air activity frequency had some influence on PM2.5 concentration. The days of PM2.5 exceeding standard in heating season and its ratio to PM2.5 exceeding standard days in the whole year increased but both of them declined in non-heating season. The difference of PM2.5 pollution in various regions was larger in winter but it was smaller in summer. The PM2.5 concentration presented obvious diurnal variation, and its fluctuation curve was M-shaped. The correlation between meteorological factors such as temperature, relative humidity, wind speed and precipitation and PM2.5  concentration was different in different seasons. High level PM2.5 pollution was more likely to occur on those days with low temperature, high humidity, low wind speed and less precipitation. The range of basic meteorological elements under different levels of PM2.5 pollution condition obtained by statistics had some indicative significance for the air quality forecast of PM2.5 pollution.

Key words:  PM2.5 concentration, temporal variation, spatial distribution, meteorological factors

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