摘要
利用重庆市南川区2017-2020年环境监测数据,综合采用数理统计方法对空气质量及其大气污染物浓度的特征进行分析,并基于灰色关联度和PCA主成分对空气质量进行分析。结果表明:南川空气质量及大气污染浓度季节变化明显,均呈下降趋势;南川以优良天数为主,无严重污染过程,轻度污染占比多于中度和重度污染天数;O_(3)对空气质量影响最大是出现在夏季,其余季节不明显,PM_(2.5)和PM_(10)是除夏季外,对空气质量影响最大的要素,特别是冬季;基于PCA主成分分析,PM_(10)与PM_(2.5)是主要污染物,O_(3)主要是夏季仅次于PM_(2.5)、PM_(10)的污染物。
Based on the environmental monitoring data of Nanchuan from 2017 to 2020,the characteristics of air quality and air pollutant concentration were analyzed by using mathematical statistics method,and the air quality was analyzed based on grey correlation degree and PCA principal component analysis.The results show that:the seasonal variation of air quality and air pollution concentration in Nanchuan is obvious,and both of them show a downward trend;In Nanchuan,the number of days with good quality was the majority,and there was no serious pollution process,and the proportion of light pollution days was more than that of moderate and severe pollution days;O_(3) has the greatest impact on air quality in summer,and it is not obvious in other seasons,and in addition to summer,PM_(2.5) and PM_(10) have the greatest impact on air quality,especially in winter;Based on PCA principal component analysis,PM_(10) and PM_(2.5) are the main pollutants,and O_(3) is the third main pollutant which is next to PM_(2.5) and PM_(10) in summer.
作者
范颖
吉莉
FAN Ying;JI Li(Chongqing Nanchuan District Ecological Environment Monitoring Station,Chongqing 408400,China;Weather Bureau in Beibei District of Chongqing City,Chongqing 400700,China)
出处
《成都信息工程大学学报》
2023年第1期116-122,共7页
Journal of Chengdu University of Information Technology
基金
重庆市气象局业务技术攻关资助项目(YWJSGG-202134)。
关键词
空气质量
灰色关联度
PCA主成分
air quality
grey correlation degree
principal component analysis
