2.1.1. Concentration of 222Rn in Homes

There were 11,500 data points on radon concentration measurements throughout Spain used in the preparation of this study. These measurements are taken from the national 222Rn concentration database in homes carried out in sampling campaigns between 1991 and 2016 grouped by municipalities [38]. The samples were taken inside houses, on the ground floor, and the measurements were made with track detectors (CR39) exposed for a period of three to six months.

The bulk of these 9500 measurements were collected by the University of Cantabria through different projects sponsored by CSN according to the internal location protocol of the Environmental Radioactivity Laboratory of the University of Cantabria (LaRUC), created using the indications of the CSN Safety Guide 11.01 [39]. The LaRUC Laboratory has

been validated by Public Health England (PHE) since 2002 [40] and accredited since 2016 through UNE-EN ISO/IEC 17025, ENAC [41], to carry out this type of radon measurement on air. This will be the dependent variable (variable 0) in this study.

#### 2.1.2. Gamma Radiation Exposure Data

The gamma radiation exposure data were obtained from the Natural Gamma Radiation Map (MARNA) [42]. This map assesses the rate of exposure to terrestrial gamma radiation at a height of 1 meter above the ground. It was produced by taking aerial and terrestrial measurements with a variety of analysis techniques, and these were later correlated through the MARNA project [43].

Terrestrial gamma radiation rates in Spain range from 44 to 287 nGy/h. This information is identified in 22 individualized rates. The information about the 22 terrestrial gamma radiation rates (rates of 44 at 287 nGy/h) in Spain was extracted after downloading the map image in high quality (.tiff) offered by the CSN website [42]. This will be the first independent variable (variable 1) analyzed.

#### 2.1.3. Lithostratigraphies

The Lithostratigraphic, Permeability and Hydrogeological Map of Spain at a scale of 1:200,000 [44] produced by the Geological and Mining Institute of Spain (IGME) was used, and 329 lithostratigraphic units were analyzed. This map includes the permeability of the lithological units, homogeneously representing the lithostratigraphies and grouping them by similar permeability values. This cartography is used because numerous studies show the importance of soil permeability in determining the radon potential inside buildings [45,46]. The digital cartography was downloaded in a compatible format (.shp) with the use of Geographic Information System (GIS) programs. This will be the second independent variable (variable 2) analyzed.

#### 2.1.4. Radon Potential

Information about radon potential in Spain was obtained after downloading the map image from the CSN website [11,36]. The 5 units shown were analyzed with homogeneous radon levels based on radon levels from the use of the 90th percentile: Unit 1 (>400 Bq/m3), Unit 2 (301–400 Bq/m3), Unit 3 (201–300 Bq/m3), Unit 4 (101–200 Bq/m3), and Unit 5 (<100 Bq/m3). This will be the variable (variable 3) used to perform the comparison of the data obtained in this work.

## *2.2. General Procedure*

#### 2.2.1. Framework

A Geographical Information System program (ESRI ArcGis v. 10.0, Environmental Systems Research Institute: Redlands, CA, USA) [47] was used to produce the cartography for this paper. The KaleidaGraph v. 4.1 (Synergy Software: PA, USA) [48] program was used to analyze the data obtained and to make graphs.

To follow a similar scheme to other EU member countries, we began working with a continental level projection system (GISCO-LAEA), and defined the European working area with a 10 km × 10 km grid with established limits (coordinates) as suggested by the Joint Research Centre of the European Commission EC-JRC [30,33]. To define the Spanish working area, we used the administrative boundaries provided by the National Geographic Institute [49], generating a total of 5478 cells of 10 km × 10 km. For each cell, an identifying code was created and its centroid in meters ("x" and "y" coordinates) was calculated.

#### 2.2.2. Harmonization of Input Data

The formats in which the source information for these variables appears are different, and so it was necessary to harmonize this information to later process the data:
