Volume 2, Issue 4 (December 2017)                   J Environ Health Sustain Dev 2017, 2(4): 379-387 | Back to browse issues page

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Ehrampoush M H, Jamshidi S, Zare Sakhvidi M J, Miri M. A Comparison on Function of Kriging and Inverse Distance Weighting Models in PM10 Zoning in Urban Area. J Environ Health Sustain Dev 2017; 2 (4) :379-387
URL: http://jehsd.ssu.ac.ir/article-1-90-en.html
Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Abstract:   (2827 Views)
Introduction: The present study aimed to compare the performance of two widely-used models for spatial assessment of particulate matter less than 10 microns (PM10) in ambient air of Yazd city. Finally, effective factors on concentrations of pollutants and corresponding standards were investigated.
Materials and Methods: A number of 13 sampling stations were employed in different areas of Yazd to sample PM10 within two seasons of winter and spring of 2012 and 2013. PM10 was measured by HAZ-DUST EPAM-5000 particulate air monitor. In order to assess the efficiency of Kriging and Inverse Distance Weighting (IDW) models for PM10 zoning, the statistical Root Mean Square Error (RMSE) and %RMSE methods were used in the Arc GIS software version 10.1.
Results: The highest (297 µg/m3) and lowest concentrations (35.8 µg/m3) of  PM10 in spring were found in high-traffic historical regions and low-traffic suburban areas, respectively. High-traffic and historical regions had higher levels of PM10 compared to other regions. Given the values of RMSE and %RMSE indicators, Kriging interpolation method was better for zoning of the pollutant PM10 in both winter and spring.
Conclusion: According to higher concentration of PM10 compared to WHO standard values particularly in spring, necessary actions and solutions should be taken for the pollution reduction. This study indicated that Kriging model has a better efficiency for spatial analysis of suspended particles, compared to IDW method.
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Type of Study: Original articles | Subject: Special
Received: 2017/08/11 | Accepted: 2017/11/20 | Published: 2017/12/19

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