Abstract <p>Based on the monitoring data on&#xa0;PM<sub>2.5</sub>&#xa0;and five other atmospheric pollutants as well as meteorologic data, the methods of kriging interpolation in ArcGIS software and Spearman correlation analysis in SPSS software were selected to study the spatial and temporal distribution characteristics of&#xa0;PM<sub>2.5</sub>&#xa0;mass concentration in Hengyang and its influencing factors. It was revealed that the annual average&#xa0;PM<sub>2.5</sub>&#xa0;mass concentration showed a decreasing trend, the monthly average value tended to be “U” shaped, and daily average values demonstrated a bimodal distribution. The seasonal average spatial distribution of&#xa0;PM<sub>2.5</sub>&#xa0;mass concentration was characterized by a typical seasonal change (winter autumn spring summer), in which Hengyang county and the main urban zone were the main high value areas. It has been also revealed that the correlation between&#xa0;PM<sub>2.5</sub>&#xa0;mass concentrations and meteorological elements such as temperature, wind speed, sunshine hours, precipitation, relative humidity, and atmospheric pollutants such as&#xa0;PM<sub>10</sub>,&#xa0;SO<sub>2</sub>, NO<sub>2</sub>, CO, and&#xa0;O<sub>3</sub>&#xa0;is different in different seasons.</p>

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Spatial and Temporal Distribution Characteristics and Influencing Factors of PM2.5 Mass Concentration in Hengyang

  • Yuyao Liu,
  • Shuxin Mu,
  • Xingli Geng,
  • Hanqing Wang

摘要

Abstract

Based on the monitoring data on PM2.5 and five other atmospheric pollutants as well as meteorologic data, the methods of kriging interpolation in ArcGIS software and Spearman correlation analysis in SPSS software were selected to study the spatial and temporal distribution characteristics of PM2.5 mass concentration in Hengyang and its influencing factors. It was revealed that the annual average PM2.5 mass concentration showed a decreasing trend, the monthly average value tended to be “U” shaped, and daily average values demonstrated a bimodal distribution. The seasonal average spatial distribution of PM2.5 mass concentration was characterized by a typical seasonal change (winter autumn spring summer), in which Hengyang county and the main urban zone were the main high value areas. It has been also revealed that the correlation between PM2.5 mass concentrations and meteorological elements such as temperature, wind speed, sunshine hours, precipitation, relative humidity, and atmospheric pollutants such as PM10, SO2, NO2, CO, and O3 is different in different seasons.