沈阳大气污染物浓度变化及气象因素影响分析

Analysis of Change Characteristics of Air Pollutants and Meteorological Influencing Factors in Shenyang

为深入探究沈阳市区大气污染物浓度变化特征和气象因子对大气污染物浓度的影响,文章利用2014-2019年沈阳市区PM10、PM2.5、O3质量浓度监测数据及地面气象观测数据,研究沈阳市区大气污染物质量浓度和空气质量变化特征,选取气温、气压、相对湿度、风速、降水量和日照时数,利用Person相关分析方法研究气象因子对大气污染物PM10、PM2.5和O3质量浓度的影响,根据大气污染物浓度与气象因子相关性建立多元回归方程预报大气污染物浓度,并评估预报效果。结果表明:2014-2019年沈阳市区大气污染得到改善,总污染天数及其占比逐年降低,优良天数明显增加,重度及以上污染天数急剧减少;PM10、PM2.5质量浓度逐年下降,O3质量浓度稍有上升;PM10、PM2.5月均浓度呈"U"型分布,O3月均浓度呈倒"U"型分布;PM10、PM2.5质量浓度秋冬季高、春夏季低,O3反之。Person相关性分析表明,风速、相对湿度是影响沈阳市区PM10和PM2.5质量浓度的主要气象要素,温度和日照时数是影响O3质量浓度的主要气象要素。小风、适宜的湿度和温度、足够的日照以及适量的降水通常会导致大气污染物浓度升高。多元回归方程对于PM10、PM2.5、O3浓度日均值拟合度为12%65%,准确率为29%70%,级别命中率为38%73%,回归方程能够准确反映大气污染物浓度变化趋势,气象条件的改变主要影响大气污染物浓度的变化趋势。

In order to deeply explore the variation characteristics of air pollution pollutants and the impact of meteorological factors on air pollutant mass concentration in Shenyang urban district,by using daily monitoring data of PM10,PM2.5,O3 and ground meteorological data in Shenyang City,We studied the characteristics of air pollutant mass concentration and variation characteristics of air quality in Shenyang from 2014 to 2019,the data air temperature,air pressure,relative humidity,wind speed,precipitation and sunshine duration were selected respectively,Pearson correlation analysis method was also used to study the influence of meteorological factors on the mass concentration of atmospheric pollutants PM10,PM2.5 and O3.Based on the correlation between pollutant concentration and meteorological factors,a multiple regression equation was established to predict pollutant concentration and evaluated the prediction effect.The research indicates that the air pollution situation in Shenyang has been significantly improved from 2014 to 2019,the total number of polluted days and its proportion in the number of days of the year declined by years,the number of days with good air quality has increased,the number of severe polluted days and above has decreased sharply;The mass concentration of PM10,PM2.5 decreased year by year,and the mass concentration of O3 slightly increased;PM10,PM2.5 monthly average concentration showed a"U"distribution,the monthly average concentration of O3 shows an inverted"U"shape distribution.PM10,PM2.5 mass concentration is high in autumn and winter,low in spring and summer,O3 is opposite.Person correlation analysis results shows that wind speed,relative humidity are the main meteorological factors that affect the mass concentration of PM10 and PM2.5 in Shenyang City,temperature and sunshine duration are the main meteorological factors affecting O3 mass concentration.Low wind speed,the right humidity and temperature,enough sunlight,and the right amount of precipitation usually lead to higher concentrations of atmospheric pollutants.For PM10,PM2.5 and O3 concentrations,the daily mean fitting degree of the multiple regression equation is12%65%,the accuracy is 29%70%,and the level hit ratio is 38%73%.The regression equation can accurately reflect the trend of pollutant concentration change,and the change of meteorological factors mainly affects the trend of pollutant concentration change.