包头城区冬春大气颗粒物污染特征及其与气象条件关系

摘要/Abstract

摘要：

包头2015~2016年冬春季节出现了连续的雾霾天气，不仅对能见度产生较大影响而且严重危害人体健康。选取了包头主城区8个空气质量浓度监测点的数据，对主城区的PM2.5和PM10污染特征进行分析，确定其空间差异特征和时间性变化特征。依据监测区功能的不同将包头主城区划分为5个区域，对各个区域监测点数据筛选整理，得到冬春季各个区域PM2.5和PM10质量浓度由高到低的顺序均为：工业区＞商业区＞文化区＞交通枢纽区＞公园游览区。各区域颗粒物月变化曲线呈双峰单谷型，12月最高，2月最低，并对成因进行分析总结；逐日变化反映PM2.5和PM10质量浓度具有较好的相关性，且受气象条件影响显著；日变化呈双峰双谷趋势。本文选取了气温、气压、相对湿度和风速等气象因子，利用Spearman秩相关分析研究各个气象因子对大气PM2.5和PM10质量浓度的影响。包头春季PM2.5和PM 10的质量浓度分别与气温、气压正相关，与风速、相对湿度（伴有降水时）负相关，风速、气压和相对湿度是影响污染物质量浓度分布的主要因素。

关键词: PM2.5, PM10, 大气颗粒物

Abstract:

Fogs and hazes broke out many times in winter and spring of 2015-2016 in Baotou, China. It is not only very seriously influential on visibility, but also seriously harmful for human health. Based on this, data of 8 monitoring stations recording characteristics of particulate matters (PM) were analyzed to determine the characteristics of temporal and spatial pollution variation of PM2.5 and PM10 in the central urban districts of Baotou. According to the different functions of monitoring region, 5 districts were divided and the data of each district were screened and sorted. Winter and spring regional PM mass concentration order from high to low were obtained as follows: industrial area＞commercial area＞cultural area＞transportation hub area＞park sight spot. The monthly changing characteristics of particles about each district were obtained, and then the cause of formation was analyzed and summarized. Monthly variation curve of PM2.5 and PM10 mass concentration showed single valley in double peak pattern: the maximum was in December and the minimum was in February; daily variation indicated a good correlation between PM2.5 and PM10,both of which were significantly influenced by meteorological conditions；diurnal variation curve showed adouble peak-valley type．Meteorological factors such as daily average temperature, atmospheric pressure, relative humidity, precipitation were chosen and their individual relationships with concentrations of PM2.5 and PM10 were investigated using Spearman rank correlation analyses. It was demonstrated that the concentrations of PM2.5 and PM10 were positively correlated with temperature and atmospheric pressure, respectively, and strongly negatively correlated with wind speed andrelative humidity. Wind speed, atmospheric pressure (with raining and snowing) and relative humidity were three key factors affecting the distributions of PM2.5 and PM10 concentration.

中图分类号:

X513

张连科鲁尚发焦坤灵王维大张保生于维佳. 包头城区冬春大气颗粒物污染特征及其与气象条件关系[J]. 大气与环境光学学报, 2017, 12(6): 401-410.

ZHANG Lian-Ke, LU Shang-Fa, JIAO Kun-Ling, WANG Wei-Da, ZHANG Bao-Sheng, XU Wei-Jia. Pollution Characteristics of Particulate Matter in Urban Districts of Baotou and Their Relationships with Meteorological Conditions[J]. Journal of Atmospheric and Environmental Optics, 2017, 12(6): 401-410.

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