Preprints
https://doi.org/10.5194/egusphere-2023-1480
https://doi.org/10.5194/egusphere-2023-1480
06 Sep 2023
 | 06 Sep 2023

Indoor 222Rn Modeling in Data-Scarce Regions: An Interactive Dashboard Approach for Bogotá, Colombia

Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet

Abstract. Radon (222Rn) is a naturally occurring gas that represents a health threat due to its causal relationship with lung cancer. Despite its potential health impacts, several regions have not conducted studies, mainly due to data scarcity and/or economic constraints. This study aims to bridge the baseline information gap by building an interactive dashboard that uses inferential statistical methods to estimate indoor radon concentration’s (IRC) spatial distribution for a target area. We demonstrate the functionality of the dashboard by modeling IRC in the city of Bogotá, Colombia, using 30 in situ measurements. IRC measured were the highest reported in the country, with a geometric mean of 91 ±14 Bq/m3 and a maximum concentration of 407 Bq/m3. In 57 % of the residences RC exceeded the WHO's recommendation of 100 Bq/m3. A prediction map for houses registered in Bogotá’s cadaster was built in the dashboard by using a log-linear regression model fitted with the in situ measurements, together with meteorological, geologic and building specific variables. The model showed a cross-validation Root Mean Squared Error of 56.5 Bq/m3. Furthermore, the model showed that the age of the house presented a statistically significant positive association with RC. According to the model, IRC measured in houses built before 1980 present a statistically significant increase of 72 % compared to those built after 1980 (p-value = 0.045). The prediction map exhibited higher IRC in older buildings most likely related to cracks in the structure that could enhance gas migration in older houses. This study highlights the importance of expanding 222Rn studies in countries with a lack of baseline values and provides a cost-effective alternative that could help deal with the scarcity of IRC data and get a better understanding of place-specific variables that affect IRC spatial distribution.

Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1480', Anonymous Referee #1, 29 Dec 2023
    • AC1: 'Reply on RC1', Martín Domínguez, 08 Jan 2024
  • RC2: 'Comment on egusphere-2023-1480', Anonymous Referee #2, 09 Jan 2024
    • AC1: 'Reply on RC1', Martín Domínguez, 08 Jan 2024
    • AC2: 'Reply on RC2', Martín Domínguez, 14 Jan 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1480', Anonymous Referee #1, 29 Dec 2023
    • AC1: 'Reply on RC1', Martín Domínguez, 08 Jan 2024
  • RC2: 'Comment on egusphere-2023-1480', Anonymous Referee #2, 09 Jan 2024
    • AC1: 'Reply on RC1', Martín Domínguez, 08 Jan 2024
    • AC2: 'Reply on RC2', Martín Domínguez, 14 Jan 2024
Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet

Model code and software

IRC Dashboard repository Martín Domínguez Durán https://github.com/mdominguezd/IRC_modeling_dashboard

Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet

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Short summary
In this study we created a cost-effective alternative to bridge the baseline information gap of Indoor radon (A highly carcinogenic gas) in regions where measurements are scarce. We model indoor radon concentrations to understand its spatial distribution and the potential influential factors. We evaluated the performance of this alternative using a small number of measurements taken in Bogotá, Colombia. Our results show that this alternative could help in the making of future studies and policy.