2.4. Environmental and Operational Influences
Environmental and operational elements together with other factors helped to determine the radon measurement results. Radon, which is a radioactive noble gas that develops from uranium decay in rocks and soils enters buildings through floor cracks and pipe gaps and unsealed foundations [
23]. People cannot detect this substance because it exists without color or smell, but its presence can be revealed through active measurement [
24].
The process of radon migration strongly depends on temperature conditions. Radon entry into buildings increases when pressure differences between indoor and outdoor air develop because of temperature differences between seasons. Natural ventilation through open windows and increased air exchange during warmer months results in reduced indoor radon concentrations [
25].
Indoor radon accumulation can be best controlled through proper ventilation systems. Buildings with limited ventilation systems tend to have elevated radon concentrations yet mechanical ventilation systems including HVAC or exhaust fans work to decrease indoor radon concentrations to safer amounts. The systems can create hazardous radon accumulation when they remain inactive or when their maintenance is improper [
26].
Heating systems operating with forced air distribution methods help move radon-contaminated air throughout the entire building. Heating operations that cause temperature changes in the air affect pressure gradients which modify radon entry patterns [
27].
Measurements of radon concentrations show changes due to human activities that take place inside the building. The movement of people combined with door usage and regular occupancy helps enhance air circulation which leads to decreased radon concentrations. Abandoned spaces along with inactive periods tend to have higher radon levels because their indoor air remains stagnant [
28].
The geological features of the measurement location play a vital role in determining radon behavior patterns. Regions containing uranium-rich bedrock along with permeable soils enable more efficient radon migration toward the Earth’s surface [
29]. The examination of geothermal activity and radon emissions takes place within this specific environmental context.
To systematically investigate these parameters and their relationships, five unique days were selected from the data set, each representing a different environmental and operational situation. These selected days include a weekday with high occupancy, a Sunday with zero activity, a day with particularly low outdoor temperatures, a day when the heating system was operating, and a typical day showing radon fluctuations. These selections were designed to ensure that the study would capture changes in radon concentration under various ventilation patterns, heating influences, and human activity levels. The selection of these days allows for a comparative analysis showing the extent to which external and internal variables affect radon accumulation and diffusion.
The relationships between radon levels and these environmental variables will be examined in depth using graphical representations depicting their behavior over 24-hour cycles. These diagrams will correspond to the following hypotheses, allowing for comparative data analysis and a better understanding of the dynamic interactions that affect indoor radon concentrations.
H1: Radon concentrations are higher on colder days due to reduced ventilation and increased temperature differences [
29].
H2: Periods of low activity, such as vacations or holidays, lead to increased radon accumulation due to stagnant air [
30].
H3: The activation of heating systems leads to temporary increases in radon levels due to air mixing and pressure changes [
25].
H4: Increased human activity and ventilation reduce radon concentrations by enhancing air circulation [
31].
H5: Radon concentrations follow diurnal fluctuations, with higher levels during the night hours due to reduced ventilation and lower values during the day, when human activity and natural ventilation are increased [
32].
The aim of the research in evaluating the data from these selected days is to capture the variations in radon levels under various scenarios and environmental conditions. The findings of these investigations will help advance our understanding of the behavior of radon indoors, thereby contributing to efforts to design more effective radon reduction and air quality management measures.
To confirm the hypotheses developed in the previous section, a series of data-driven investigations were carried out using radon measurements collected over a specific period. Five critical days were selected for a full examination, each reflecting a different activity and environmental situation. These include a weekday with high occupancy, a weekend with little activity, a holiday with no human presence, a day with low outdoor temperatures and a day when the heating systems were on.
Changes in radon concentration during these days were graphically depicted in 24-hour cycles. The study focuses on identifying trends, such as the effect of human activity on air circulation, the relationship between heating system operation and radon levels, and the role of ventilation in reducing indoor radon accumulation. Each graph depicts how radon behaves under various conditions, allowing for comparison of different factors that affect it.
The purpose of these diagrams is to assess whether the hypotheses are accurate. The findings will serve as a foundation for the evaluation and conclusions in the next section, where each hypothesis will be assessed for its validity and implications.
Figure 1.
The figure presents the changes in radon concentration during a cold day to test the hypothesis that low temperatures increase radon levels because of reduced ventilation and temperature differences.
Figure 1.
The figure presents the changes in radon concentration during a cold day to test the hypothesis that low temperatures increase radon levels because of reduced ventilation and temperature differences.
The measurements show that radon concentrations reach their highest levels during the first part of the day. The concentrations decrease gradually after reaching their peak levels in a pattern that matches the linear trend. The radon accumulation at the beginning of the day occurs because the space remains sealed and air exchange rates decrease during nighttime.
The day-by-day reduction in concentrations occurs because brief ventilation episodes and indoor condition modifications enable gas removal. The high initial radon concentrations support the hypothesis that cold temperatures allow radon accumulation because low outdoor temperatures restrict ventilation and create pressure differences that influence radon transport into buildings.
The collected data confirms that radon concentrations rise on cold days thus requiring proper ventilation and indoor air quality control measures.
Figure 2.
The results from diagram 2 show the radon concentration during a holiday, specifically Sunday, and tests the hypothesis that periods of low activity led to increased radon accumulation due to limited air circulation.
Figure 2.
The results from diagram 2 show the radon concentration during a holiday, specifically Sunday, and tests the hypothesis that periods of low activity led to increased radon accumulation due to limited air circulation.
The graph shows radon concentration rising steadily throughout the day while the linear trend shows a positive slope. The observed radon concentration rise matches the hypothesis that reduced air exchange and limited activity and no ventilation during holidays cause radon to build up in indoor spaces.
The concentration shows occasional variations which could stem from brief changes in air circulation patterns or environmental elements. The overall upward trend indicates that both human inactivity and restricted air renewal play essential roles in raising radon concentrations.
These data validate the hypothesis about low activity periods resulting in radon accumulation which supports the requirement for proper ventilation systems during periods of reduced human occupancy.
Figure 3.
Diagram 3 shows the variation of radon concentration during the day, under the influence of the operation of heating systems. The recording of radon concentration shows strong fluctuations during the first hours, with the appearance of several peaks, which suggests that heating may be associated with increased emissions or changes in the concentration of the gas due to turbulence in the indoor air.
Figure 3.
Diagram 3 shows the variation of radon concentration during the day, under the influence of the operation of heating systems. The recording of radon concentration shows strong fluctuations during the first hours, with the appearance of several peaks, which suggests that heating may be associated with increased emissions or changes in the concentration of the gas due to turbulence in the indoor air.
The diagram shows a general decrease in concentration throughout the day through its linear trend. The observed radon concentration decrease may result from the establishment of a dynamic equilibrium between radon concentration and air exchange or modifications in heating operations during daytime hours.
The observed time period shows that warming onset leads to short-term radon concentration increases which align with the hypothesis predictions. Additional research along with environmental and operational factor analysis is needed to determine the specific cause of these concentration variations.
The relationship between human activity and radon concentration shows variations through
Figure 4 which presents radon level changes during a busy day. According to Hypothesis 4 the combination of more activity and better ventilation helps decrease radon concentration through improved air circulation.
Figure 4.
1 weekday with high human activity.
Figure 4.
1 weekday with high human activity.
The radon concentration shows distinct changes throughout the day with rising and falling patterns. The minimum radon values appear at various times because continuous air movement creates conditions that decrease radon concentrations inside the building space. The highest radon readings appear at times when ventilation decreases, or air circulation stops.
The diagram shows a straight line that indicates radon levels decrease briefly during increased activity, but this does not produce a steady downward pattern. The ongoing radon emissions from soil and building materials function as counteracting factors that prevent ventilation from eliminating radon presence.
The analysis of data reveals that human activity together with ventilation affects radon concentration, but the effect remains partial. The data supports Hypothesis 4 because radon concentration decreases but the evidence does not show enough support to prove ventilation eliminates radon from the indoor space.
Figure 4.
The graph demonstrates the typical 24-hour radon concentration pattern which matches the theoretical prediction of increased radon levels at night and decreased levels during daytime.
Figure 4.
The graph demonstrates the typical 24-hour radon concentration pattern which matches the theoretical prediction of increased radon levels at night and decreased levels during daytime.
The radon concentrations begin the 24-hour period at elevated levels which show multiple fluctuations because the gas accumulated during hours with minimal ventilation. The initial peaks in radon concentration appear because ventilation remains poor, and air stagnates within indoor spaces.
The radon concentration decreases steadily throughout the day because human activity increases and natural or artificial ventilation becomes more effective. The downward trend shown in the dotted line demonstrates that radon concentration levels decrease throughout the day.
The middle section of the 24-hour period shows minor variations because air circulation patterns might shift, or heating and air conditioning systems could be operating. The values show stabilization or a minor increase during the last part of the period because ventilation decreases during evening hours.
The diagram supports the investigated hypothesis by demonstrating that radon concentrations increase at night because of poor ventilation while they decrease throughout the day because of better air circulation.
Figure 5.
Correlation 1 & 2.
Figure 5.
Correlation 1 & 2.
The correlation analysis presented in
Figure 6 demonstrates opposing patterns between the two hypotheses regarding radon concentrations. The first hypothesis proposes that radon levels increase on colder days because ventilation decreases, and temperature differences become more pronounced. The second hypothesis states that radon accumulation rises during holidays because the air remains stagnant.
Figure 6.
Correlation 1 & 3.
Figure 6.
Correlation 1 & 3.
The graphical illustration demonstrates that the first hypothesis curve decreases which suggests radon concentration levels decrease because of enhanced air exchange throughout the day. The second hypothesis curve demonstrates an upward direction which shows that radon concentrations rise when human activities decrease.
The opposing patterns between these two mechanisms could be caused by different factors that affect radon concentration levels. The gas retention indoors becomes more effective during cold temperatures and ventilation limitations during off-season periods lead to increased gas concentration. The different trends between these two hypotheses indicate that understanding radon accumulation requires analyzing temperature and ventilation conditions together.
The connection between hypotheses 1 and 3 investigates the relationship between temperature fluctuations and heating system operation on radon concentration levels. Hypothesis 1 predicts that radon concentrations increase when temperatures drop because ventilation decreases while temperature differences enhance radon gas transport between buildings and the ground. Hypothesis 3 proposes that heating system activation leads to brief radon increases because of air circulation and pressure variations.
The curve of hypothesis 1 in diagram 7 demonstrates elevated radon concentrations at the start of the day which then decreases progressively to show radon accumulation patterns during cold temperatures. The curve of hypothesis 3 demonstrates minor variations which represent the impact of heating on gas distribution patterns. The trend lines demonstrate that radon levels rise from both factors, yet the cold environment maintains stable concentrations while heating produces brief variations.
Low temperatures elevate the standard radon concentration while heating system activation produces brief peaks because of air circulation and internal pressure variations. The general decline in both cases appears to result from increased daily ventilation or equalization of atmospheric pressure.
Figure 6.
Correlation 2 & 4.
Figure 6.
Correlation 2 & 4.
Figure 7.
Correlation 3 & 5.
Figure 7.
Correlation 3 & 5.
The graph in
Figure 8 shows radon concentration measurements between low human activity times and high human activity times with improved ventilation systems. Radon concentration shows a steady rise in the first scenario because of the lack of ventilation and decreased air movement enabling the gas to build up inside indoor spaces.
Figure 8.
Correlation 4 & 5.
Figure 8.
Correlation 4 & 5.
The high human activity conditions result in stable and significantly lower radon concentrations which supports the hypothesis that ventilation together with air mobility work as radon removal systems. The first case shows a linear trend that increases steadily which supports the idea that enclosed spaces with air will cause radon concentrations to rise continuously.
The analysis of these two hypotheses shows how human activity affects radon levels and proves that ventilation systems both natural and artificial play a crucial role in controlling indoor gas concentrations.
The comparison between hypotheses 3 and 5 in
Figure 9 demonstrates how radon concentration changes when environmental conditions differ. The activation of heating systems under hypothesis 3 leads to short-term radon level increases because of air recirculation and pressure changes. The fifth hypothesis studies how radon concentrations change throughout the day by showing higher nighttime values because of reduced ventilation and lower daytime values because of increased human activity.
The diagram displays significant changes in radon concentration through its visual presentation of both hypotheses. The early morning hours produce peaks in hypothesis 5 which matches the theoretical explanation of nighttime radon concentration elevation due to minimal air renewal. The time series data in hypothesis 3 demonstrates sudden spikes which support the hypothesis that heating system activation produces these effects.
The two data trend lines demonstrate a general decline in both cases but with different steepness. The observed decrease could stem from ventilation growth alongside the diminishing heating effects that occur after a specific period. The data comparison reveals that the two factors interact because heating-related air recirculation strengthens or transforms the natural daily patterns of radon concentrations.
The analysis of this data confirms that radon concentrations follow dynamic patterns because of thermal and environmental factors which validate both hypotheses.
The data presented in
Figure 10 demonstrates how human activity together with ventilation affects indoor radon concentrations between hypotheses 4 and 5. According to hypothesis 4 the combination of human activity and ventilation leads to decreased radon concentrations because it promotes better air circulation. The fifth hypothesis examines diurnal radon variations by showing elevated nighttime radon levels because of decreased ventilation and reduced daytime radon levels because of increased human activity.
The two hypotheses present data patterns that do not match each other well. The initial radon concentration values in hypothesis 5 decrease gradually throughout the observation period in accordance with the predicted daily pattern. The data distribution in hypothesis 4 remains stable while showing minimal variations because human activity and ventilation work to keep radon levels low.
The downward trend in both data points exists but Case 5 demonstrates more significant variations between its values. The data shows that radon levels decrease throughout the day but there are occasional spikes which could result from changes in ventilation or human activities.