4.7 Article

Spatial-temporal patterns of PM(2.5 )concentrations for 338 Chinese cities

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 631-632, 期 -, 页码 524-533

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2018.03.057

关键词

PM(2.5 )concentrations; Spatial-temporal patterns; Spatial autocorrelation; China

资金

  1. National Key R&D Program of China [2016YFA0602601]

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Air pollution has become a major concern in cities worldwide. The present study explores the spatial-temporal patterns of PM2.5 (partides with an aerodynamic diameters <= 2.5 mu m) and the variation in the attainment rate (the number of cities attaining the national PM2.5 standard each day) at different time-scales based on PM(2.5 )concentrations. One-year of monitoring was conducted in 338 cities at or above the prefectural level in China. Spatial hot spots of PM2.5 were analyzed using exploratory spatial data analysis. Meteorological factors affecting PM2.5 distributions were analyzed. The results indicate the following: (1) Diurnal variations of PM2.5 exhibited a Wshaped trend, with the lowest value observed in the afternoon. The peak concentrations occurred after the ends of the morning and evening rush hours. (2) Out of 338 cities, 235 exceeded the national annual PM2.5 standards (535 mu g/m(3)), with slightly polluted (75-115 mu g/m(3)) cities occupying the greatest proportion. (3) The attainment rate showed an inverted U-shape, while there was a U-shaped pattern observed for daily and monthly mean PM2.5. (4) The spatial distribution of PM2.5 concentrations varied greatly, PM2.5 has significant spatial autocorrelation and clustering characteristics. Hot spots for pollution were mainly concentrated in the Beijing-Tianjin-Hebei area and neighboring regions, in part because of the large amount of smoke and dust emissions in this region. However, weather factors (temperature, humidity, and wind speed) also had an effect. In addition, southwest Xinjiang experienced heavy PM2.5 pollution that was mainly caused by the frequent occurrence of sandstorms, although no significant relationship was observed between PM2.5 and meteorological elements in this region. (C) 2018 Elsevier B.V. All tights reserved.

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