Hamid Taheri Shahraiyni 1,2, Sahar Sodoudi1, Andreas Kerschbaumer3, Ulrich Cubasch1

  • 1 Institut für Meteorologie, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6-10, 12165 Berlin, Germany
  • 2 Faculty of Civil Engineering, Shahrood University, Shahrood, Iran
  • 3 Senate Department for Urban Development and the Environment, Berlin, Germany

Received: December 8, 2014
Revised: January 23, 2015
Accepted: January 23, 2015
Download Citation: ||https://doi.org/10.4209/aaqr.2014.12.0317  

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Cite this article:
Shahraiyni, H.T., Sodoudi, S., Kerschbaumer, A. and Cubasch, U. (2015). New Technique for Ranking of Air Pollution Monitoring Stations in the Urban Areas Based upon Spatial Representativity (Case Study: PM Monitoring Stations in Berlin). Aerosol Air Qual. Res. 15: 743-748. https://doi.org/10.4209/aaqr.2014.12.0317


HIGHLIGHTS

  • New approach to the spatial representativity of background stations is presented.
  • Here, spatial representativity is expressed independent of the location of station.
  • A ranking method is developed for the ranking of stations using this new approach.
  • This new ranking method was applied for the ranking of PM stations in Berlin.
  • Ranking method was able to rank the stations based upon spatial representativity.

 

ABSTRACT


The spatial representativity of monitoring stations plays a major role for the reasonable estimation of air pollutants. The ranking of air pollution monitoring stations based upon their spatial representativity identifies the level of representativeness of the stations and is very useful for developing optimum monitoring networks. In this study, a new ranking method, named RTFI (Ranking Technique based upon Fuzzy Interpolation) is introduced. This ranking method is able to rank air pollution monitoring stations in the urban areas based upon their spatial representativity. Although spatial correlation techniques are often used in the ranking techniques in order to consider spatial representativity, in this ranking technique, the spatial representativity of a station is not limited to its surroundings and is measured independently of its location. RTFI was applied to airborne Particulate Matter (PM) at seven stations in Berlin, and ranked them according to their spatial representativity. The results showed that the Neukölln-Nanenstr station (MC 42) is the most spatially representative station among the studied stations.


Keywords: Airborne particulate matter; Spatial representative; Monitoring network; Ranking Technique based upon Fuzzy Interpolation (RTFI); Background stations


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