本文主要对哈尔滨市主城区大气颗粒物污染特征进行研究,利用哈尔滨市2015年~2019年冬季大气PM10、PM2.5的浓度监测数据,用传统统计分析方法对大气颗粒物的时间变化特征进行深入分析。并探讨这些大气颗粒污染物的来源,并对可能影响特征变化的因素进行分析。结果表明,哈尔滨市PM2.5污染较严重,PM2.5的浓度以及PM2.5超标率均表现为先减小后增大。其中,分析月份浓度得出12月的PM10和PM2.5的浓度均值大于1月和2月,说明1月大气颗粒物污染最严重,空气质量最差。利用方差分析得到,PM10、PM2.5、AQI的显著性均小于0.05,有统计学意义,AQI以及PM2.5、PM10差异明显。利用多重比较分析年份得出,2015年、2017年、2019年之间PM2.5、PM10、AQI差异明显,利用多重比较分析和方差分析月份得到,1月与2月,2月与12月比较,AQI、PM10、PM2.5均小于0.05,差异性明显。本研究拟通过对哈尔滨大气颗粒物污染特征的研究,找出哈尔滨市大气颗粒物的时间变化规律。本次研究可为哈尔滨市环保部门为治理环境提供有效地控制可吸入颗粒物的污染决策依据。This paper mainly studies the characteristics of atmospheric particulate matter pollution in the main urban area of Harbin city, and uses the concentration monitoring data of atmospheric PM10 and PM2.5 in winter of Harbin city from 2015 to 2019 to conduct an in-depth analysis of the temporal variation characteristics of atmospheric particulate matter by traditional statistical analysis methods. The sources of these air particle pollutants are discussed, and the factors that may affect the characteristic change are analyzed. The results show that the PM2.5 pollution is serious in Harbin city, and the PM2.5 concentration and PM2.5 overstandard rate both decrease first and then increase. Among them, the analysis of monthly concentrations shows that the average concentration of PM10 and PM2.5 in December is greater than that in January and February, indicating that the atmospheric particulate matter pollution is the most serious in January and the air quality is the worst. According to the analysis of variance, the significance of PM10, PM2.5 and AQI is less than 0.05, which is statistically significant, and the difference between AQI, PM2.5 and PM10 is obvious. According to the multiple comparative analysis of years, there were significant differences in PM2.5, PM10 and AQI between 2015, 2017 and 2019. According to the multiple comparative analysis and ANOVA of months, compared with January and February, and February and December, AQI, PM10 and PM2.5 were all less than 0.05, and the di
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