摘要
利用2014年本溪市大气颗粒物质量浓度监测资料和风速、气温、相对湿度、气压等常规地面气象要素观测资料,分析了本溪地区大气颗粒物质量浓度的月、季变化特征及其与气象要素的相关性。结果表明:2014年7月和10月本溪市大气颗粒物质量浓度较高,5月和9月大气颗粒物质量浓度较低,6月和11月大气颗粒物质量浓度比值较高。夏季PM10质量浓度较低,平均浓度为115.1μg·m^(-3);冬季PM_(2.5)和PM_(1.0)质量浓度较高,平均浓度分别为99.5μg·m^(-3)和86.1μg·m^(-3)。春季和冬季平均风速与大气颗粒物质量浓度的相关性最好,夏季和冬季相对湿度与大气颗粒物质量浓度的相关性最好。当ρ(PM_(2.5))≥200.0μg·m^(-3)时,ρ(PM_(2.5))与平均气温呈显著的正相关关系,相关系数为0.5288,ρ(PM_(2.5))与相对湿度的相关系数也高达0.6981,高温、高湿和小风等气象条件是本溪地区大气颗粒物高质量浓度事件发生的有利气象条件。
Data of the particulate matter mass concentrations and surface meteorological elements （i. e. wind speed, air temperature, relative humidity and atmospheric pressure） throughout 2014 in Benxi were used to evaluate the monthly and seasonally variations of particulate matters and their correlations with meteorological elements. The results show that the particulate matter concentrations are relatively high in July and October, while relatively low in May and September. Moreover, the concentration ratios of particulate matters in June and November are high. The concentrations of PM10 are lower with the average value of 115. 1 μg.m^-3 ,whereas those of PM2.5 and PM1.0 are higher, with the average values of 99. 5 μg. m^-3 and 86.1μg. m^- 3, respectively. The correlations between particulate matter mass concentrations and wind speeds appear the most significant in spring and winter, and those be- tween particulate matter mass concentrations and relative humidity appear the most significant in summer and win- ter. The mass concentrations of PM2.5 and average temperatures show significantly positive correlations in case that they are below 200 p^g.m-3 with the coefficient of 0. 5288 ,and that of the mass concentrations of PM2.5 and relative humidities are as high as 0. 6981. Higher temperature and humidity, as well as lower wind speed, are the active meteorological conditions leading to pollution events with high particulate matter concentrations over Benxi.
出处
《气象与环境学报》
2017年第1期58-65,共8页
Journal of Meteorology and Environment
基金
辽宁省气象局博士科研业务费专项"东北区域城市和背景区大气气溶胶化学特性及典型城市群气溶胶光学特性研究"(D201501)
国家自然科学基金面上项目(41475124)共同资助
关键词
大气颗粒物
时间变化
气象要素
相关性
Particulate matter
Temporal variation
Meteorological elements
Correlation
