IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-19-9658-0_12.html
   My bibliography  Save this book chapter

Using Analytics to Measure the Impact of Pollution Parameters in Major Cities of India

In: Analytics Enabled Decision Making

Author

Listed:
  • Manohar Kapse

    (Symbiosis International (Deemed University))

  • N. Elangovan

    (CHRIST (Deemed to Be University))

  • Abhishek Kumar

    (Tata Consultancy Services)

  • Joseph Durai Selvam

    (CHRIST (Deemed to Be University))

Abstract

Coronavirus is airborne and can spread easily. Air pollution may have an impact on breathing and also keep the virus airborne. The levels of air pollution were impacted by the lockdown measures, restricting the vehicular and industrial pollutants. Therefore, there is a need to understand the relation between air pollution levels and the Coronavirus infection rate. The study aims to find the effect of various pollutants across major cities of India on the R-value. The pollution data was collected from the Government’s official portal. The major pollutants on which the data was collected are “PM2.5, PM10, NO, NO2, NOx, SO2, CO, and Ozone”. The data on air pollution levels were also collected for the selected cities from April 2020 to April 2021. The spread is measured as the reproduction number at time ‘t’ (Rt), which is an estimate of infectious disease transmissibility throughout an outbreak, or it is the rating of Coronavirus or any disease’s ability to spread. The data is analysed using MS Excel and R Programming. Descriptive statistics and regularisation are performed on the data. The study results reveal that some pollutants positively and negatively affect the infection rate. However, the effect is very low, and it concluded that the pollution might not directly affect infection rates.

Suggested Citation

  • Manohar Kapse & N. Elangovan & Abhishek Kumar & Joseph Durai Selvam, 2023. "Using Analytics to Measure the Impact of Pollution Parameters in Major Cities of India," Springer Books, in: Vinod Sharma & Chandan Maheshkar & Jeanne Poulose (ed.), Analytics Enabled Decision Making, pages 265-280, Springer.
  • Handle: RePEc:spr:sprchp:978-981-19-9658-0_12
    DOI: 10.1007/978-981-19-9658-0_12
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-981-19-9658-0_12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.