主分量分析法在环境空气监测数据分析中的应用

根据西宁市13个环境空气监测站点2013—2017年大气污染物细颗粒物(PM2. 5)、可吸入颗粒物(PM10)、二氧化硫(SO_2)、二氧化氮(NO_2)、臭氧最大8 h平均(O_3-8h)和一氧化碳(CO)的监测数据,采用主分量分析法对西宁市环境空气质量进行了综合评估。结果表明,2013—2017年西宁市大部分环境空气监测站点周边环境空气质量逐渐提升,4个国控站综合得分(F)趋势变化幅度较大,其周边环境空气质量状况改善较为明显;城南新区、湟源县气象局和西钢监测站点周边环境空气质量呈逐年下降趋势,与其附近工业生产有关。

Application of Principal Component Analysis in Evaluating of Ambient Air Automatic Monitoring Station

According to the monitoring data of fine particulate matter (PM_2.5), respirable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone up to 8 hours average (O₃-8h) and carbon monoxide (CO) in Xining City from 2013 to 2017, the principal component analysis method was used to comprehensively evaluate the ambient air quality in Xining City. The results showed that the ambient air quality of most environmental air monitoring stations in Xining City has gradually increased in recent years, and the integrated score(F) trend of the 4 state controlled stations varied mostly, the ambient air quality surrounding them improved obviously. While the air quality observed in the sites of Chengnan new area, Meteorological Bureau of Huangyuan county and Xigang showed declining year by year, which was related to the industrial production nearby.