PM_（2.5） has become an increasing public concern recently because of its visibility reduction and severe health risks. For the whole year of 2013, hourly PM_（2.5） data of 496 monitoring sites scattered in 74 citie...PM_（2.5） has become an increasing public concern recently because of its visibility reduction and severe health risks. For the whole year of 2013, hourly PM_（2.5） data of 496 monitoring sites scattered in 74 cities of China are collected to analyze temporal and spatial variability of PM_（2.5） concentration. Different temporal scales（seasonal variation, monthly variation and daily variation） and spatial scales（urban versus rural, typical areas and national scale） are discussed. Results show that PM_（2.5） concentration changes significantly in both long-term and short-term scales. An apparent bimodal pattern exists in daily variation of PM_（2.5） concentration and the daytime peak appears around 10：00 am while the lowest concentration appears around 16：00 pm. Spatial autocorrelation analysis and Ordinary Kriging are used to characterize spatial variability. Moran＇s I of PM_（2.5） concentration in three typical regions, the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the Pearl River Delta region, is 0.906, 0.693, 0.746, respectively, which indicates that PM_（2.5） is strong spatial correlated. Spatial distribution of annual PM_（2.5） concentration simulated by Ordinary Kriging shows that 7.94 million km2（83%） areas fail in meeting the requirement of China＇s National Ambient Air Quality Standards Level-2（35 mg/m3） and there are at least three concentrated highly polluted areas across the country.展开更多
基金Supported by the National Natural Science Foundation of China(41571385)
文摘PM_（2.5） has become an increasing public concern recently because of its visibility reduction and severe health risks. For the whole year of 2013, hourly PM_（2.5） data of 496 monitoring sites scattered in 74 cities of China are collected to analyze temporal and spatial variability of PM_（2.5） concentration. Different temporal scales（seasonal variation, monthly variation and daily variation） and spatial scales（urban versus rural, typical areas and national scale） are discussed. Results show that PM_（2.5） concentration changes significantly in both long-term and short-term scales. An apparent bimodal pattern exists in daily variation of PM_（2.5） concentration and the daytime peak appears around 10：00 am while the lowest concentration appears around 16：00 pm. Spatial autocorrelation analysis and Ordinary Kriging are used to characterize spatial variability. Moran＇s I of PM_（2.5） concentration in three typical regions, the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the Pearl River Delta region, is 0.906, 0.693, 0.746, respectively, which indicates that PM_（2.5） is strong spatial correlated. Spatial distribution of annual PM_（2.5） concentration simulated by Ordinary Kriging shows that 7.94 million km2（83%） areas fail in meeting the requirement of China＇s National Ambient Air Quality Standards Level-2（35 mg/m3） and there are at least three concentrated highly polluted areas across the country.
