大气与环境光学学报2024，Vol.19Issue(4)：479-488,10.DOI:10.3969/j.issn.1673-6141.2024.04.008
主成分分析法在合肥市空气质量评估中的应用
Application of principal component analysis in air quality assessment of Hefei City
摘要
Abstract
Based on the daily average concentration monitoring data of important pollutants and the meteorological data at ground national control stations from January 1,2019 to December 31,2020,a comprehensive assessment of urban air quality in Hefei City,China,was conducted using the principal component analysis method.The pollutant data includes daily values of important atmospheric pollutants such as fine particulate matter(PM2.5),inhalable particulate matter(PM10),nitrogen dioxide(NO2),sulfur dioxide(SO2),carbon monoxide(CO),and ozone(O3),and the corresponding daily mean meteorological parameters include temperature,wind speed,sunshine duration,precipitation,atmospheric pressure,and relative humidity.Firstly,the indicators that have a significant impact onthe air quality were selected through stepwise regression,and then these significant indicators were reduced to a lower dimension through the principal component analysis.According to the theory of principal component analysis,two principal components were extracted from five significant impact indicators,and the cumulative variance contribution rate of the two extracted principal components reached 82.9%.The first principal component was characterized by high loadings of PM2.5,CO,and PM10 concentrations,implying the significant impact of these parameters on the air quality of Hefei.The second principal component was characterized by high loadings of O3 concentration and sunshine duration,demonstrating their important role on the air quality of Hefei.Overall,good correlation was observed between the results from principal component analysis and the air quality index with a correlation coefficient of 0.78.In addition,it is found that the proposed method is more suitable to assess the air quality in winter and under good air quality conditions.These findings highlight the good performance of principal component analysis method on the assessment of urban air quality.关键词
主成分分析/逐步回归/空气质量指数/空气质量评估/合肥市Key words
principal component analysis/stepwise regression/air quality index/air quality assessment/Hefei City分类
资源环境引用本文复制引用
周闯,张琦锦,郭映映,牟福生,李素文..主成分分析法在合肥市空气质量评估中的应用[J].大气与环境光学学报,2024,19(4):479-488,10.基金项目
国家自然科学基金(41875040,41705012),安徽省高等学校创新团队项目(2023AH010043),安徽省自然科学研究基金项目(2208085QF215),安徽省高校自然科学研究项目(2023AH050338) （41875040,41705012）
