首页|基于PCA的汉中市中心城区空气质量影响因素研究

基于PCA的汉中市中心城区空气质量影响因素研究

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根据2022年汉中市中心城区环境空气质量监测数据和气象数据，运用主成分分析法(PCA)研究了影响空气质量的主要因素和重要因素，并对比分析了气象指标和各污染物浓度之间的关系。结果表明:主成分分析法提取的3个主成分方差贡献率为79。388%，达到了预期效果。主成分1的方差贡献率为51。745%，其中PM2。5、CO、NO2、PM10权重较高，说明PM2。5、CO、NO2、PM10是影响空气质量的主要因素，且它们高度正相关，相关系数最高为0。905(PM2。5-CO)，最低为0。751(PM10-CO)，分析表明加强对工业源、移动源CO、NOx以及颗粒物排放管控是改善空气质量的有效途径。主成分2、主成分3的方差贡献率合计为27。643%，主要包含了风向、O3、风级、气温等信息，是影响空气质量的重要因素。气温对各污染物浓度影响最明显，与O3显著正相关，与其他污染物负相关，影响程度大小依次为CO＞O3＞NO2＞PM2。5＞PM10＞SO2，在7℃时，PM2。5、PM10、NO2、CO、SO2浓度相对较高;在偏东北风时PM2。5、PM10、CO平均浓度较高，O3平均浓度较低，偏西南风时具有相反特征;风级增大污染物浓度降低，但O3浓度在1级～2级风时较高。
Research on Impacting Factors of Air Quality in the Central Urban Area of Hanzhong City based on Principal Component Analysis(PCA)
According to the data of ambient air and meteorology in the central urban area of Hanzhong City in 2022,the main and important factors of air quality were studied base on Principal Component Analysis(PCA),and the relationships between meteorological indicators and various pollutant concentrations were compared and analyzed.The results showed that the three principal components were extracted by PCA,which reached 79.388%of cumulative variance contribution.This method achieved the desired effect.The first principal component accounted for 51.745%of the variance and mainly including PM2.5,CO,NO2 and PM10,which indicated that PM2.5,CO,NO2 and PM10 were the main factors of air quality.The four indicators were highly positively correlated,the highest correlation coefficient was PM2.5-CO(0.905)and the lowest was PM10-CO(0.751).These results suggested that it was the effective way to improve the air quality by intensively controlling CO,NOx and PM emission of industrial source and mobile source.The second principal component and third principal component accounted for 27.643%of the variance and mainly including wind direction,O3,wind scale and temperature,these indicators were important factor of air quality.The temperature had an obviously impact on the pollutant concentrations,which was significantly positively correlated with O3 and had a negative correlation with other pollutants.The order of influence was CO>O3>NO2>NO2>PM2.5>PM10>SO2.When the temperature was at 5～7℃,the concentrations of PM2.5,PM10,NO2,and CO were relatively higher.In the northeast winds,the average concentrations of PM2.5,PM10 and CO were higher,but O3 was lower,the opposite characteristics exist in the southwest winds.The rising wind scale could help to reduce the concentration of pollutants,but the first and second wind may increase the concentration of O3.

principal component analysis(PCA)air qualitymeteorological factorHanzhong City

吕晓虎、邵天杰、黄小刚

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汉中市生态环境局,陕西汉中 723001

陕西师范大学地理科学与旅游学院,陕西西安 710119

PCA(主成分分析) 空气质量 气象因素 汉中市

共青团陕西省秦岭生态环境保护科学考察项目

2024

环境科学导刊
云南环境科学研究院

环境科学导刊

影响因子：0.525
ISSN：1673-9655
年,卷(期)：2024.43(2)
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