A Comparison on Function of Kriging and Inverse Distance Weighting Models in PM10 Zoning in Urban Area

سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 505

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شناسه ملی سند علمی:

JR_JEHSD-2-4_003

تاریخ نمایه سازی: 1 مرداد 1397

چکیده مقاله:

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 samp le 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 SquareError (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.

نویسندگان

Mohammad Hassan Ehrampoush

Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

Sara Jamshidi

Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Mohammad Javad Zare Sakhvidi

Occupational Health Research Center, Department of Occupational Health, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Mohammad Miri

Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran