YI Wenli1, ZHU Chanyuan1, GUO Chan1, ZHENG Haohao1,YANG Fei1,2
(1.Shaanxi Key Laboratory of Disasters Monitoring and Mechanism Simulation, Baoji University of Arts and Sciences, Baoji 721013, China;
2.Xingjiang Fukang Industrial Park Management Committee, Changji Hui Autonomous Prefecture, Fukang 831500, China)
Abstract: Hourly data of PM2.5 from December 2016 to May 2017 in Shaanxi province were employed to analyze its spatiotemporal characteristics by ArcGIS and to reveal the causes of difference in northern and southern Shaanxi, the time series and mutation characteristics of PM2.5 by wavelet analysis. The results showed that: 1)The spatial distribution of PM2.5 concentration is higher in Guanzhong area in central province and lower in southern and northern province, the temporal distribution showed higher values in winter and lower in spring. The difference in economic development and the heating activities in different regions is the main reason for PM2.5 spatial pattern. 2) The daily variation of PM2.5 showed a bimodal pattern both in winter and spring, with the lowest value appeared between 16:00 to 18:00. 3) The results of Morlet wavelet analysis showed that the PM2.5 daily average change sequence in Shaanxi has multi-time scale characteristic. The first main period of PM2.5 pollution in northern Shaanxi is about 40 days, while there are two same periods of 40 days and 65 days for Guanzhong area and Shangluo city, and two same periods of 20 days and 80 days for Ankang city and Hanzhong city. 4) PM2.5 mutation events were frequent in winter and less in spring, mostly occurred in January and February, and a large-scale dusty weather in spring has caused a sharp increase in PM2.5 concentration in eight cities of the province on May 5th.
Key words: PM2.5; spatial-temporal characteristics; wavelet analysis; mutation
EARTH AND ENVIRONMENT Vol.48, No.6, Tot No.338, 2020, Page 663-671
