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Cluster Analysis for Daily Patterns of SO2 and NO2 Measured by the DOAS System in Xiamen

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Volume: 14 | Issue: 5 | Pages: 1455-1465
DOI: 10.4209/aaqr.2013.05.0160
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Peng Shi1, Pin-Hua Xie2, Min Qin2, Fu-Qi Si2, Ke Dou2, Ke Du 1,3

  • 1 Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
  • 2 Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
  • 3 Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB, Canada

Abstract

Daily patterns of air pollutants are important to improve measurement retrievals and to model the regimes of local air quality. In this study, the daily patterns of SO2 and NO2 as well as their association with visibility and meteorological conditions in a suburban area of Xiamen are investigated. To achieve this goal, continuous field measurements were collected with a Differential Optical Absorption Spectroscopy (DOAS) system in 2011. The K-means clustering is used to classify the daily variation cycles of these measurements associated with different visibility and meteorological conditions such as temperature, relative humidity, wind speed and direction. The Davies-Bouldin index strategy is used to determine the optimal number of clusters. The regime of each cluster associated with visibility and meteorological conditions was then explored and compared. The comparative analyses show that both the maximum hourly average concentrations and the maximum daily average concentrations of SO2 and NO2 occurred in spring. Only 0.04 percent and 3.19 percent of the days with SO2 and NO2, respectively, did not comply with the latest national ambient air quality standards of China (GB 3095-2012). Moreover, the clustering results highlighted three representative patterns of daily SO2 concentrations and four representative patterns of daily NO2 concentrations. Both similarities and differences were presented among these clusters. The consistent changes in aerosol concentration with the changes in the measurements of NO2 and SO2 in each cluster provided supplemental evidence for the presence of the daily patterns of SO2 and NO2.

Keywords

NO2 SO2 DOAS Cluster analysis


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