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Comparison of Fuzzy Synthetic Evaluation Techniques for Evaluation of Air Quality: A Case Study

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Recent Developments and the New Direction in Soft-Computing Foundations and Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 361))

Abstract

Urban air quality has degraded at an alarming rate due to rapid urbanisation and industrialization in megacities. Therefore, there is an urgent need to assess air quality and suggest risk mitigation measures. In this paper, air quality of Chennai city was evaluated using different Fuzzy Synthetic Evaluation (FSE) techniques i.e. Fuzzy similarity method (FSM) and Simple fuzzy classification (SFC) and the results are compared with the National air quality index (NAQI). In the case of SFC weights for different pollutants were computed using Shannon’s information entropy. Seasonal analysis of the criteria pollutants shows highest concentration during the winter season followed by pre-monsoon and summer season. The lowest concentration was observed during Monsoon in most cases. The FSE results are optimistic as compared to the NAQI due to aggregation of pollutant concentration as opposed to maximising function in NAQI which reconfirms the findings of earlier researchers. FSE can be used as a decision making tool to communicate the overall air quality to policy makers/end users (Public) in a simplified qualitative form.

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Authors and Affiliations

  1. Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, 600036, India

    Hrishikesh Chandra Gautam & S. M. Shiva Nagendra

Authors
  1. Hrishikesh Chandra Gautam
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  2. S. M. Shiva Nagendra
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Corresponding author

Correspondence to Hrishikesh Chandra Gautam .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  2. Machine Intelligence Institute, Iona College, New Rochelle, New York, USA

    Ronald R. Yager

  3. Department of Information Technology and Programming, Azerbaijan Technical University, Baku, Azerbaijan

    Shahnaz N. Shahbazova

  4. Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Z. Reformat

  5. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

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Gautam, H.C., Shiva Nagendra, S.M. (2018). Comparison of Fuzzy Synthetic Evaluation Techniques for Evaluation of Air Quality: A Case Study. In: Zadeh, L., Yager, R., Shahbazova, S., Reformat, M., Kreinovich, V. (eds) Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-75408-6_47

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  • DOI: https://doi.org/10.1007/978-3-319-75408-6_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75407-9

  • Online ISBN: 978-3-319-75408-6

  • eBook Packages: EngineeringEngineering (R0)

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