Journal of Atmospheric and Environmental Optics, Volume. 19, Issue 4, 479(2024)
Application of principal component analysis in air quality assessment of Hefei City
Figures & Tables(7)
Fig. 1. The distribution characteristics of AQI from January 1, 2019 to December 31, 2020. (a) The monthly average change trend of AQI; (b) distribution of air pollution levels
Fig. 2. Results of fitting the composite scores of principal components and AQI from January 1, 2019 to December 31, 2020.(a) Overall trends of change; (b) global linear fitting; (c) piecewise fitting of AQI values; (d) seasonal fitting of AQI values
Table 1. Descriptive statistics of pollutant data and meteorological data in Hefei from January 1，2019 to December 31，2020
View tableView in ArticleTable 1. Descriptive statistics of pollutant data and meteorological data in Hefei from January 1，2019 to December 31，2020
Indicator Sample size Average Standard
deviation
Maximum Minimum Number of missing Proportion of missing data/% NO2/(ug·m-3) 729 40.180 17.486 94 10 2 0.3 PM2.5/(ug·m-3) 729 6.580 2.732 17 2 2 0.3 PM10/(ug·m-3) 729 0.712 0.211 1.6 0.31 2 0.3 SO2/(ug·m-3) 729 96.780 44.985 233 6 2 0.3 CO/(mg·m-3) 729 66.660 32.418 312 13 2 0.3 O3_8h/(ug·m-3) 729 40.210 25.695 153 5 2 0.3 AQI 729 79.200 30.985 203 18 2 0.3 Average temperature/°C 730 16.280 9.134 33.3 -5.3 1 0.1 Average wind speed/(m·s-1) 731 2.232 0.940 6.2 2.232 0 0 Sunshine hours/h 730 5.338 4.303 12.9 0 1 0.1 Precipitation at 20-20 hours/mm 731 2.880 11.223 197.4 0 0 0 Average station pressure/hpa 731 1009.763 9.627 1009.763 1033.1 0 0 Average relative humidity/% 731 80.030 11.675 99 37 0 0
Table 2. Stepwise regression analysis results of AQI with air pollutants and meteorological factors
View tableView in ArticleTable 2. Stepwise regression analysis results of AQI with air pollutants and meteorological factors
Independent variable Regression coefficient Pearson correlation significance R2 F Constant -6.574 0.004 0.828 697.942 PM2.5 0.814 0.650 0.000 O3 0.304 0.442 0.000 PM10 0.208 0.236 0.000 Hours of sunshine 0.614 0.086 0.000 CO 13.417 0.089 0.001
Table 3. Correlation coefficient matrix
View tableView in ArticleTable 3. Correlation coefficient matrix
Indicator CO O3 PM10 PM2.5 Hours of sunshine CO 1.000 -0.222 0.536 0.83 -0.178 O3 -0.222 1.000 0.078 -0.292 0.621 PM10 0.536 0.078 1.000 0.668 0.272 PM2.5 0.830 -0.292 0.668 1.000 -0.151 Hours of sunshine -0.178 0.621 0.272 -0.151 1.000
Table 4. Total variance interpretation
View tableView in ArticleTable 4. Total variance interpretation
Ingredient Initial eigenvalue Sum of squares (extraction load) Characteristic
value
Percentage
(variance)
Cumulative
Contribution/%
Characteristic
value
Percentage
(variance)
Cumulative
Contribution/%
1 2.444 48.876 48.876 2.444 48.876 48.876 2 1.707 34.017 82.893 1.707 34.017 82.893 3 0.432 8.644 91.537 4 0.291 5.811 97.348 5 0.133 2.652 100.000
Table 5. Principal component score coefficient
View tableView in ArticleTable 5. Principal component score coefficient
Indicator Ingredient 1 2 PM2.5
CO
PM10
Hours of sunshine
O3
0.6096
0.5770
0.4522
-0.1599
-0.2559
0.0675
0.0460
0.4271
0.6717
0.6004
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Chuang ZHOU, Qijin ZHANG, Yingying GUO, Fusheng MOU, Suwen LI. Application of principal component analysis in air quality assessment of Hefei City[J]. Journal of Atmospheric and Environmental Optics, 2024, 19(4): 479
Paper Information
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Received: Jul. 19, 2022
Accepted: --
Published Online: Jan. 8, 2025
The Author Email: Fusheng MOU (swli@chnu.edu.cn), Suwen LI (moufusheng@163.com)
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