Cluster Analysis of Submicron Particle Number Size Distributions at the SORPES Station in the Yangtze River Delta of East China. Issue 13 (29th June 2021)

• Record Type: Journal Article
• Authors: Chen, Liangduo; Qi, Ximeng; Nie, Wei; Wang, Jiaping; Xu, Zheng; Wang, Tianyi; Liu, Yuliang; Shen, Yicheng; Xu, Zhengning; Kokkonen, Tom V.; Chi, Xuguang; Aalto, Pasi P.; Paasonen, Pauli; Kerminen, Veli‐Matti; Petäjä, Tuukka; Kulmala, Markku; Ding, Aijun
• Is Part Of: Journal of geophysical research. Volume 126:Issue 13(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-29
• Subjects: Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2020JD034004
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Submicron particles in polluted regions have received much attention because of their influences on human health and climate. A k‐means clustering technique was performed on a data set of particle number size distributions (PNSD) that was obtained over more than 3 years in the Yangtze River Delta (YRD) region of East China. With simultaneous measurements of meteorological conditions, trace gases and aerosol compositions, seven clusters were categorized and interpreted. Cluster 1 and cluster 2, which accounted for 9.9% of the total PNSD data, were attributed to new particle formation (NPF) and vehicle exhaust emissions with different intensities; Cluster 3 and Cluster 4, which accounted for 10.5% of the total PNSD data, were related to the growth of nucleation mode particles; Cluster 5, which accounted for 37.9% of the total data, was attributed to the humid YRD background; and Cluster 6 and Cluster 7, which accounted for 41.6% of the total data set, were both pollution‐related clusters with similar mass concentrations but completely different PNSD. Although the PM2.5 mass concentrations were somewhat similar, the particle number concentrations of the accumulation mode particles could vary by more than one order of magnitude from the urban background cluster to the pollution‐related clusters. The cluster proximity diagram and conversion flow chart of clusters clearly show the influence of NPF and growth on haze, as well as the conversion between background and polluted conditions. This study highlights the importance of PNSD for understanding urban air quality and recommends the clustering technique for analyzing complex PNSD datasets. Plain Language Summary: Submicron particles in polluted regions have significant influences on human health and climate. Based on long‐term field measurements, we used the k‐means clustering technique to characterize the number size distributions of submicron particles in the Yangtze River Delta (YRD) of China. Seven clusters were categorized and interpreted. New particle formation (NPF), fossil fuel combustion and biomass burning are the main sources of submicron particles in the YRD. The influences of NPF and growth on haze, as well as the conversion between background and polluted conditions, were found. Key Points: New particle formation (NPF), fossil fuel combustion and biomass burning are the main sources of submicron particles in Nanjing The influences of NPF and growth on haze, and the conversion between background and pollution conditions were found The k‐means cluster technique is an effective tool to categorize particle number size distribution data set