IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v8y2011i5p1420-1440d12299.html
   My bibliography  Save this article

A Geostatistical Approach to Assess the Spatial Association between Indoor Radon Concentration, Geological Features and Building Characteristics: The Case of Lombardy, Northern Italy

Author

Listed:
  • Riccardo Borgoni

    (Department of Statistics, University of Milan-Bicocca, Via Bicocca degli Arcimboldi 8, 20126 Milan, Italy)

  • Valeria Tritto

    (Department of Statistics, University of Milan-Bicocca, Via Bicocca degli Arcimboldi 8, 20126 Milan, Italy)

  • Carlo Bigliotto

    (Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto—Department of Padova, Via Ospedale 22, 35121 Padova, Italy)

  • Daniela De Bartolo

    (Agenzia Regionale per la Protezione dell’Ambiente della Lombardia—Central Department, Viale Restelli 3/1, 20124 Milano, Italy)

Abstract

Radon is a natural gas known to be the main contributor to natural background radiation exposure and second to smoking, a major leading cause of lung cancer. The main source of radon is the soil, but the gas can enter buildings in many different ways and reach high indoor concentrations. Monitoring surveys have been promoted in many countries in order to assess the exposure of people to radon. In this paper, two complementary aspects are investigated. Firstly, we mapped indoor radon concentration in a large and inhomogeneous region using a geostatistical approach which borrows strength from the geologic nature of the soil. Secondly, knowing that geologic and anthropogenic factors, such as building characteristics, can foster the gas to flow into a building or protect against this, we evaluated these effects through a multiple regression model which takes into account the spatial correlation of the data. This allows us to rank different building typologies, identified by architectonic and geological characteristics, according to their proneness to radon. Our results suggest the opportunity to differentiate construction requirements in a large and inhomogeneous area, as the one considered in this paper, according to different places and provide a method to identify those dwellings which should be monitored more carefully.

Suggested Citation

  • Riccardo Borgoni & Valeria Tritto & Carlo Bigliotto & Daniela De Bartolo, 2011. "A Geostatistical Approach to Assess the Spatial Association between Indoor Radon Concentration, Geological Features and Building Characteristics: The Case of Lombardy, Northern Italy," IJERPH, MDPI, vol. 8(5), pages 1-21, May.
    • Handle: RePEc:gam:jijerp:v:8:y:2011:i:5:p:1420-1440:d:12299
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/8/5/1420/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/8/5/1420/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rob Foxall & Adrian Baddeley, 2002. "Nonparametric measures of association between a spatial point process and a random set, with geological applications," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(2), pages 165-182, May.
    2. Riccardo Borgoni & Piero Quatto & Giorgio Somà & Daniela Bartolo, 2010. "A geostatistical approach to define guidelines for radon prone area identification," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(2), pages 255-276, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Riccardo Borgoni & Valeria Tritto & Daniela de Bartolo, 2013. "Identifying radon-prone building typologies by marginal modelling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 2069-2086, September.
    2. M. Lieshout, 2006. "A J-Function for Marked Point Patterns," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(2), pages 235-259, June.

    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:gam:jijerp:v:8:y:2011:i:5:p:1420-1440:d:12299. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.