摘要
采集2019年兰州市西固区细颗粒物监测数据,用气相色谱-质谱联用仪(GC-MS)对PM_(2.5)中的有机组分进行定性和定量分析,着重探讨PM_(2.5)与烷醇类的分布特征.同时收集同期近地面气象观测数据,采用相关性(Pearson)与非参数分析(Spearman)方法,研究PM_(2.5)和烷醇类与气象因素之间的关系并比较Pearson和Spearman两种方法的适用性.结果表明:2019年兰州市西固区PM_(2.5)年平均浓度为51μg/m3,是我国环境空气质量年平均二级标准(35μg/m3)的1.5倍,其中烷醇类占比达0.3%,PM_(2.5)和烷醇类均呈现明显的季节性规律,均为冬季>春季>秋季>夏季.Pearson和Spearman对温度和相对湿度的分析结果一致,对风速的计算结果在显著性水平方面稍有差别,对大气压统计结果有明显差异.
The PM_(2.5)data of Xigu district of Lanzhou in 2019 were collected,and the organic components in PM_(2.5)were analyzed qualitatively and quantitatively by gas chromatography-mass spectrometry(GC-MS).The distribution characteristics of PM_(2.5)and alkanol were mainly discussed.Relationship between PM_(2.5)and alkanols distribution and meteorological parameters was assessed by correlation(Pearson)and non-parametric analysis(Spearman)methods,and the applicability of the two methods was compared simultaneously.The results showed that the annual mean concentration of PM_(2.5)in 2019 was 51μg/m3,which was 1.5 times of China’s average annual air quality standards(GradeⅡ,35μg/m3)in which the alkanols in PM_(2.5)was accounting for 0.3%.For seasonal trends,both PM_(2.5)and alkanols were all decreased in the order of winter>spring>autumn>summer.Pearson and Spearman’s analysis of temperature and relative humidity were consistent,while their calculation results of wind speed were slightly different in terms of significance level,and the statistical results of atmospheric pressure were significantly different.
作者
张国祯
李丹丹
岳永丽
刘鹏飞
ZHANG Guo-zhen;LI Dan-dan;YUE Yong-li;LIU Peng-fei(Gansu Province Environmental Monitoring Center, Lanzhou 730020, China)
出处
《兰州理工大学学报》
CAS
北大核心
2021年第2期65-71,共7页
Journal of Lanzhou University of Technology
基金
甘肃省科技厅重点研发计划-社会发展类(18YF1FA033)。