The Spatio-Temporal Distribution of Particulate Matter during Natural Dust Episodes at an Urban Scale

PLoS One. 2016 Aug 11;11(8):e0160800. doi: 10.1371/journal.pone.0160800. eCollection 2016.

Abstract

Dust storms are a common phenomenon in arid and semi-arid areas, and their impacts on both physical and human environments are of great interest. Number of studies have associated atmospheric PM pollution in urban environments with origin in natural soil/dust, but less evaluated the dust spatial patterns over a city. We aimed to analyze the spatial-temporal behavior of PM concentrations over the city of Beer Sheva, in southern Israel, where dust storms are quite frequent. PM data were recorded during the peak of each dust episode simultaneously in 23 predetermined fixed points around the city. Data were analyzed for both dust days and non-dust days (background). The database was constructed using Geographic Information System and includes distributions of PM that were derived using inverse distance weighted (IDW) interpolation. The results show that the daily averages of atmospheric PM10 concentrations during the background period are within a narrow range of 31 to 48 μg m-3 with low variations. During dust days however, the temporal variations are significant and can range from an hourly PM10 concentration of 100 μg m-3 to more than 1280 μg m-3 during strong storms. IDW analysis demonstrates that during the peak time of the storm the spatial variations in PM between locations in the city can reach 400 μg m-3. An analysis of site and storm contribution to total PM concentration revealed that higher concentrations are found in parts of the city that are proximal to dust sources. The results improve the understanding of the dynamics of natural PM and the dependence on wind direction. This may have implications for environmental and health outcomes.

MeSH terms

  • Air Pollutants / analysis*
  • Dust / analysis*
  • Environmental Monitoring*
  • Humans
  • Israel
  • Models, Theoretical
  • Particulate Matter / analysis*
  • Seasons
  • Spatio-Temporal Analysis*
  • Urban Renewal

Substances

  • Air Pollutants
  • Dust
  • Particulate Matter

Grants and funding

The research was supported by a grant from the Environment and Health Fund (No. RGA1004).