Impact of Bedroom Ventilation Strategy on Air Change Rates and Indoor Air Parameters in the Autumn–Winter Seasons—In Situ Study in Poland

Abstract

Hybrid ventilation is indicated as one of the effective methods of maintaining thermal comfort and indoor air quality and reducing energy consumption in buildings. It assumes the capacity to switch between natural and mechanical ventilation, allowing the most efficient use of the outdoor air potential. This article aims to quantify the impact of changing ventilation system, from natural to hybrid, on indoor air parameters and air change rates in a bedroom of a single-family house. The distinct aspects of this study include longitudinal measurement over three years, natural ventilation substituted by hybrid ventilation halfway into the monitoring period, and unaltered building and user characteristics. The analysis is based on measurements of temperature, relative humidity, CO2 concentration, and window opening for three seven-month measurement periods from September 1 to March 31. The measurements are complemented by in-depth user feedback and an audit of the building structure and installed HVAC systems. A clear correlation was observed between the values of relative humidity and carbon dioxide concentration and the type of ventilation strategy. A significant influence of residents’ behavior on the achieved indoor air parameters was observed.

1. Introduction

The residential sector of the EU Member States contributes to over a quarter of the block’s final energy consumption [1]. Households use energy for space heating and cooling, water heating, cooking, lighting, and powering electrical appliances [2]. On average, space heating accounts for 63.5% of the total household final energy consumption, with significant differences across countries driven by climatic and cultural differences [2]. About 75% of the entire EU building stock is considered energy inefficient [1], contributing to negative social and environmental impacts, such as energy poverty or climate change.

According to the ISO 13789:2017 standard [3], heat losses in a building occur through heat transfer via the envelope and through ventilation. Heat loss through building envelopes is primarily related to their thermal insulation. In recent years, Polish energy policy has placed a significant emphasis on reducing energy consumption in buildings. A significant breakthrough came in 2002, when stringent restrictions related to the quality of building envelopes and, subsequently, primary energy demand were gradually introduced, resulting in a significant improvement in the quality of newly constructed buildings in Poland [4]. Improving the quality of building envelopes has led ventilation heat losses to become dominant in the energy balance of traditionally naturally ventilated residential buildings. At the same time, there is a risk that airtight, modernized buildings will experience indoor environmental quality problems due to limited ventilation if the modernization process does not address these issues [5]. All of this has led residential buildings in Poland to increasingly be equipped with mechanical ventilation systems with heat recovery (MVHR).

MVHR is designed to ensure a good indoor air quality (IAQ) and thermal comfort while reducing heat loss, particularly in colder climatic zones [6]. These systems recover heat from the exhaust air, which is crucial in reducing the energy input needed to condition the incoming air in the heating season. However, MVHR’s year-round operation relies on continuous use of fans. Ambiguity of the inhabitants about the need to consume energy for the functioning of the MVHR beyond the heating season has been captured by previous research [7]. An alternative solution is natural ventilation (NV), a method of ensuring air exchange in a building at no energy cost, though more reliant on residents’ home use practices, in particular, on window-opening behavior. The drawback of NV is that the outdoor air introduced into a building may lead to a significant increase in energy demand for heating and cooling in the case of a high temperature difference between the indoors and outdoors. NV may also be insufficient to ensure the required air exchange rate in rooms throughout the year [8], contributing to a poor indoor air quality or a mold risk. In the temperate climate zone, winter is a particularly sensitive period, as the low temperature of the ventilation air flowing into a building generates dominant energy losses and thermal discomfort. For this reason, a common problem for naturally ventilated residential buildings is a poor quality of indoor air, caused by the buildings’ excessive sealing [9]. The tendency to seal windows during the winter season has been shown to contribute to insufficient indoor air exchange, resulting in elevated concentrations of air pollutants, as shown by proxy indices of IAQ, such as carbon dioxide and relative humidity [10,11]. To address the identified drawbacks of each ventilation system, hybrid ventilation has been proposed, offering the capacity to switch between natural and mechanical ventilation, enabling the most efficient use of the outdoor air potential. However, HV involves a higher investment cost of implementing two parallel ventilation systems, thus making the case for its broader uptake, though that requires the validation of its in-use benefits compared to a single ventilation system.

Bedrooms pose specific ventilation challenges for natural, manually adjusted ventilation compared to other spaces in a dwelling. All indoor spaces except for bedrooms are used exclusively during the active hours of the inhabitants, and thus adjusting air change levels in line with occupants’ needs, e.g., by opening doors or windows, is feasible. In bedrooms, the ventilation context, such as the doors’ and windows’ positions, remains unaltered throughout the sleeping hours. As most bedrooms globally are naturally ventilated, it is relevant to study the in-use indoor air parameters against alternatives such as hybrid ventilation.

2. Overview

This paper focuses on the issue of shaping the parameters of indoor air in naturally and mechanically ventilated bedrooms—in the autumn-winter season, that is, during the period of particular sensitivity of residential buildings—in a temperate climate to ensure the effectiveness of the air exchange system used. In this climate, the warm season (spring–summer) is favorable for NV, with prevailing mild daytime temperatures, and nights allowing for passive cooling. In the autumn–winter period, low outdoor temperatures begin to cause large heat losses, and cold airflows become a cause of thermal discomfort. Additionally, according to the Central Emission Register of Buildings, in 2023 in Poland, over 40% of all heat sources relied on solid fuel combustion. Of those, nearly seven million sources, i.e., less than 2%, were devices meeting the Ecodesign standards [12]. Highly inefficient and polluting heating installations can be found in rural areas and low-income central urban households [13], which contributes to widespread air pollution [14]. This affects all households, including those using heat pumps, contributing to reduced natural ventilation flows, thus risking indoor air quality deterioration.

The difficulty in comparing the in-use effectiveness of mechanical and natural ventilation systems in occupied homes is due to the high sensitivity of indoor parameters to building and household characteristics, including the variability of preferences, behaviors, and skills [10] of the residents [15]. The indoor temperature also depends on many factors, such as the health, activity, or habits of the users [16]. Not only does the envelope airtightness but also the choice of interior finishes contribute to the variations in indoor air parameters observed between dwellings. Finishing materials with hygroscopic properties reduce fluctuations in relative humidity in a room by acting as a moisture buffer [17]. Relative humidity is also influenced by home use practices, such as the method of drying laundry or the cultivation of potted plants. Varied levels of user understanding of the as-designed ventilation strategy in new-built dwellings have been associated with different usage strategies and indoor air parameters [7]. There is a lack of real-world performance assessments of distinct ventilation systems in housing, and deficiencies in user knowledge and skills have been disregarded, though it is often concluded that an increased understanding would help overcome the observed indoor air quality issues [7].

To address the uncertainty of building- and user-related findings of ventilation studies based on cross-household comparisons, this research offers longitudinal insights into the performance of a single building occupied by the same users, where the key variable is the change in ventilation from NV to hybrid ventilation halfway into the data collection period. The hybrid ventilation allows for manually switching between NV and MVHR. Such a research focus allows us to answer the following research questions:

• What is the causal relationship between the specific ventilation strategy and indoor air parameters over the heating season in an air-tight, low-energy home?
• Does a high level of user knowledge and awareness about feasible ventilation strategies guarantee the maintenance of a high quality of the indoor environment regardless of the ventilation method used, or are there other limitations that affect the results obtained?

3. Methodology

3.1. Research Subjects

To address the research gap, an empirical case study approach was adopted. This allowed us to gain an in-depth understanding of the background of a building—the user context, tailored to the focus of this study—and distil the role of the ventilation strategy in the results observed. The context involves an energy-efficient, detached building with room sizes and an overall floor area close to the national average for new-built housing and highly unique residents in terms of their understanding and skills with regard to the ventilation strategies available. A comprehensive building performance evaluation methodology was deployed.

This research was conducted in a single-family house distinguished by specific characteristics that set it apart from typical residential buildings:

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The residents are professionals in engineering disciplines—architecture and environmental engineering with a specialization in HVAC systems;

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The main assumption for the design of the building and its installation was the hybrid operation of the ventilation system in the alternating mode, and the facility was equipped with both an MVHR system and a natural, manually operated system;

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The residents have a high level of knowledge and awareness of the operation of their technical systems and mechanisms influencing the quality of indoor air and the energy demand of the building and actively participate in shaping its indoor environment.

This selection of a case study allowed for obtaining results that reflect the actual effect of the work of various air exchange systems, in which conditions that are accidental and shaped by a lack of knowledge and involvement of the residents are minimized. The residents’ awareness of air exchange practices, including opening windows and naturally ventilating the space, was found to influence the performance results observed during periods when natural ventilation was used, as described in a previous study [11].

The analysis covered three autumn–winter periods from September to the end of March, differing in terms of the ventilation system used. September was selected as a transition month, in which the switch from natural to mechanical ventilation could realistically occur in response to periodic drops in outside temperature or the quality of the external environment. Based on the recorded data, it was therefore possible to identify the moment of switching to a mechanical ventilation mode and confirm the triggering factor.

3.2. Building and Its Use

The single-family house covered by this study, occupied since 2017, is located in a rural area, approx. 20 km from Wrocław, Poland. Of the total floor area of 190 m², 136 m² is the heated living space. The facility does not have cooled spaces. The calculated building heat demand is 7.0 kW (51.5 W/m² of heated usable area). The energy source for space heating and domestic hot water is an air-to-water heat pump. The heated residential space is equipped with a hybrid ventilation system operating in a change-over mode, where the mode is selected manually. During the measurement period, the actual capacities of the MVHR system were 250 m³/h (supply) and 230 m³/h (exhaust), which gave a calculated air exchange rate in the building of 0.5 h⁻¹.The actual heat recovery efficiency was approximately 75%. The building was subjected to a Blower Door Test with a result of n₅₀ = 1.85 h⁻¹.

Air exchange in the building during NV operation is managed through manual partial or full opening of windows and automatic activation of natural ventilation ducts following the shutdown of the AHU. When designing the building, the future occupants considered their intended use of windows and outdoor spaces—during warm periods, all household members spend a lot of time outdoors and keep the building envelope highly ventilated (with windows and patio doors often fully open). The external conditions support this behavior—during warm and transitional periods (from spring to autumn), the outdoor air is relatively free of pollutants since the building is located in a rural area, far from busy roads and industrial facilities. That surrounding area is not used for livestock farming. In contrast, during the winter months, due to the use of fossil fuels in neighboring buildings, the air is perceived by the occupants as heavily polluted, prompting them to “seal” the building.

The building is occupied by three people—two working adults and a preschool child. Occasionally, guests stay in the house, including an elderly person every 2–3 months for about 2 weeks. One adult works from home most of the time and takes care of the child. During the three-year period covered by this study, no changes were introduced in terms of building characteristics, household composition, lifestyle, health, or occupancy patterns, which makes this research unique. This article focuses on the master bedroom (MB) of the building, for which the highest amount of measurement data was collected. The MB is also the room with the most stable occupancy pattern, as its occupation is the least dependent on external and internal factors. This stability provides a reliable basis for evaluating the impact of ventilation strategies on indoor environmental conditions. While the analysis is limited to a single room, the MB serves as a representative space for broader insights, as it reflects typical conditions of regularly occupied rooms in residential buildings, allowing for cautious generalization of the findings to similar spaces.

3.3. Local Climate

The research site is located within a region of Poland classified as the temperate oceanic climate zone (Cfb) (Figure 1). It is characterized by cool summers and mild winters, with a relatively narrow annual temperature range. According to a Typical Meteorological Year (TMY) in Wroclaw, evaluated based on data including the years 2001–2020 [18], the average annual temperature is $9.7 °\mathrm{C}$. The coldest month is January, with a monthly average external temperature equal to $-1.7 °\mathrm{C}$. The highest monthly average temperature is $18.8 °\mathrm{C}$, which occurs in August (Figure 2). According to the TMY, westerly winds dominate in Wrocław, and their average annual speed is approx. 3 m/s (Figure 3).

3.4. Research Methods

To explore the causal relationship between the specific ventilation strategy and indoor air parameters, a longitudinal in-depth case study approach was adopted, focused on one occupied, low-energy house. This was possible due to a change in ventilation system from natural to hybrid halfway through the three years of monitoring, while keeping constant all other relevant contextual parameters.

Data collection involved in-depth user feedback, an audit of the building fabric and the installed heating and ventilation systems, and monitoring of indoor and outdoor air parameters. The user feedback involved understanding the occupancy patterns, inhabitant roles within the household in terms of ventilation practices, and their understanding of ventilation and expectations towards air quality. The audit of the building fabric and systems was based on repeated site visits, involving a walk-through, photo survey, and performance surveys, e.g., the Blower Door Test. Indoor and outdoor air parameters were monitored across three consecutive years in an occupied detached house.

3.5. Measurements

The analysis focused on indoor air parameters in the bedroom over the seasons when heating is most likely to be used. This was defined as seven-month periods, from September 1st to March 31st, in the years 2020–2023. In 2020 and 2021, NV was used. On 27 January 2022, MVHR was first activated (Figure 4). The abbreviation “NV + MVHR” is used to denote the period during which natural ventilation (NV) or mechanical ventilation with heat recovery (MVHR) was employed in a change-over mode, meaning that one type of ventilation was active at any given time. This change-over strategy is one of the recognized approaches within hybrid ventilation systems. Throughout the manuscript, the term “hybrid ventilation” is used as a general category, with the specific system examined in the case study representing a subset of this broader classification. The airflow ventilating the bedroom during the MVHR period was approximately 30 m³/h and remained unchanged by the occupants.

The bedroom was equipped with an Efento magnetic window reed switch that registered opening cycles. The device recorded information about the window position in a 5 min time step (information about the window-opening status in successive 5 min periods, not the actual time of opening). The device did not record window-unsealing cycles.

In February and the first half of March 2022, air exchange was carried out using the MVHR system, and the periods of window opening registered by the installed magnetic reed switch usually lasted 1–2 cycles (mainly several minutes of airing after the night and before bed). In the second half of March 2022, longer periods of window opening were observed, indicating the commencement of NV use (a total of 122 cycles in March, including 90% after 15 March). Similarly, longer periods of window opening were recorded in September 2022 (2687 cycles, including 96% before September 16) and October 2022 (476 cycles, unevenly distributed throughout the period). In March 2023, apart from one day, there were no periods of longer window opening (a total of 66 cycles, of which 51 were on March 22). Residents therefore mainly used mechanical ventilation, and the time of switching to the natural mode was not possible to determine. The switch from NV to MVHR was determined by the building occupants, and according to interviews, the trigger was either the outside temperature or outside air pollution.

The measurements of indoor air parameters were averaged to hourly values for analysis purposes. This decision was made to ensure consistency across all datasets, as both the meteorological station data and calculations of thermal comfort provided results at 1 h intervals. Aligning all data to a common time step allowed for a coherent comparison and integration of indoor and outdoor conditions throughout the analysis.

Table 1. Parameters of the measurement equipment used in this study.

Equipment	Data Logger HOBO MX 1102	ELT Sensor S-300-3 V Sensirion SHT25	ATMOS 14 (Outdoor)
Measuring range	$\mathrm{Temperature}: 0-50 °\mathrm{C}$ $\mathrm{RH}: 1-90\mathrm{\%}$ CO2$:0-5000 \mathrm{p}\mathrm{p}\mathrm{m}$	$\mathrm{Temperature}: (-40)-125 °\mathrm{C}$ $\mathrm{RH}: 1-80\mathrm{\%}$ CO2: $0-5000 \mathrm{p}\mathrm{p}\mathrm{m}$	$\mathrm{Temperature}: (-40)-80 °\mathrm{C}$ $\mathrm{RH}: 1-100\mathrm{\%}$
Accuracy	$\mathrm{Temperature}: \pm 0.21 °\mathrm{C}$ from $0 °\mathrm{C}$ to $50 °\mathrm{C}$ $\mathrm{RH}: \pm 2\mathrm{\%}$ from $20\mathrm{\%}$ to $80\mathrm{\%}$ typically to a maximum of $\pm 4.5\mathrm{\%}$ including hysteresis at $25 °\mathrm{C}$; below 20% and above 80% $\pm 6\mathrm{\%}$ typically CO2$:\pm 50 \mathrm{p}\mathrm{p}\mathrm{m}\pm 5\mathrm{\%}$ of reading at $25 °\mathrm{C}$, $\mathrm{R}\mathrm{H}<90\mathrm{\%}$, non-condensing, 1013 mbar	$\mathrm{Temperature}: \pm 0.2 °\mathrm{C}$ from $10 °\mathrm{C}$ to $60 °\mathrm{C}$ $\mathrm{RH}: \pm 1.8\mathrm{\%}$ from $20\mathrm{\%}$ to $90\mathrm{\%}$, typically to a maximum of $\pm 2.0\mathrm{\%}$ including hysteresis at $25 °\mathrm{C}$; below 20% and above 90% $\pm 3\mathrm{\%}$ typically CO2: $\pm 20 \mathrm{p}\mathrm{p}\mathrm{m}\pm 3\mathrm{\%}$ of reading at $25 °\mathrm{C}$, $\mathrm{R}\mathrm{H}<90\mathrm{\%}$, non-condensing	$\mathrm{Temperature}: \pm 0.2 °\mathrm{C}$ $\mathrm{RH}: \pm 1.5\mathrm{\%}$ from $0\mathrm{\%}$ to $80\mathrm{\%}$ (exception $\pm 2\mathrm{\%}$ for RH 80% and temperature $0 °\mathrm{C}$, above 90% $\pm 2\mathrm{\%}$)
Resolution	Temperature: $0.024 °\mathrm{C}$ w $25 °\mathrm{C}$ RH: 0.01% CO2$:1 \mathrm{p}\mathrm{p}\mathrm{m}$	Temperature: 0.01 °C RH: 0.04% CO2$:1 \mathrm{p}\mathrm{p}\mathrm{m}$	Temperature: 0.1 °C RH: 0.1%
Sampling interval	15 min	1 min	1 min, average for 1 h

presents the specifications of the measurement equipment used, and Figure 5 shows the locations of the devices in the analyzed room. The distance between the occupied space and the measuring devices was 1.3 m. Sensor calibration took place before the start of each research period.

3.6. Thermal Comfort and Indoor Air Quality Criteria

The ACM was used to conduct an analysis of thermal comfort conditions. The adaptive approach to the thermal comfort of residents was selected as both NV and MVHR operations were analyzed in this study. According to the literature, occupants tend to have different degrees of toleration of changes in indoor air temperature, depending on the ventilation system used [19]; therefore, a broader range of acceptable indoor temperatures was required to compare the ventilation systems. The model also assumes that indoor temperature preferences are flexible and influenced by individual preferences [20] and that previous days’ temperatures influence users’ thermal comfort perceptions. Including the impact of previous days’ temperatures could allow for a better estimation of the influence of different outdoor temperatures during the examined seasons. The acceptable ranges of ACM operative temperature are presented in Table 2 [21]: The formula for calculating the optimal operative temperature can be found in both European and American standards [21,22]. The Adaptive Comfort Model (ACM) is commonly used for modeling thermal comfort conditions in buildings with NV and hybrid ventilation systems [19,23,24,25,26,27]. The PMV model, on the contrary, is used widely in buildings with MV and air conditioning systems [26,27,28] and assumes that the human body is in a constant state and the environment is stable, with no significant changes over time. The human body’s response is predictable and based primarily on the heat balance. With frequent window opening and interzonal airflows occurring in the analyzed MB, the PMV model would have been inadequate for the case study. Also, the research [25,28,29,30,31] suggests that applying the PMV model in MM buildings tends to overestimate the thermal sensations of occupants, especially during periods of high outdoor temperatures.

The equations used in calculations of thermal comfort categories are presented below.

Running mean temperature (RMT):

$$t_{rmt}=\left(1-\alpha \right)\cdot t_{e,d-1}+\alpha \cdot t_{e,d-2},\mathrm{℃}$$

(1)

where

• $t_{rmt}$—daily external mean temperature for the considered day, $\mathrm{℃}$;
• $t_{e,d-1}$—daily external mean temperature one day before, $\mathrm{℃}$;
• $t_{e,d-2}$—daily external mean temperature two days before, $\mathrm{℃}$;
• $\alpha$—constant between 0 and 1, where according to EN 16798-1:2019, the recommended value is 0.8.

Optimal operative temperature:

$$t_c=0.33\cdot t_{rmt}+18.8,°$$

(2)

where

• $t_c$—optimal operative temperature, $°$C.

Table 2. The operative temperature ranges for the thermal environment categories [21].

Category	$\mathbf{Temperature} \mathbf{Range}, \mathbf{℃}$
Category I	$t_{uo}^I=0.33\cdot t_{rmt}+18.8+2,\mathrm{℃}$
	$t_{lo}^I=0.33\cdot t_{rmt}+18.8-3,\mathrm{℃}$
Category II	$t_{uo}^{II}=0.33\cdot t_{rmt}+18.8+3,\mathrm{℃}$
	$t_{lo}^{II}=0.33\cdot t_{rmt}+18.8-4,\mathrm{℃}$
Category III	$t_{uo}^{III}=0.33\cdot t_{rmt}+18.8+4,\mathrm{℃}$
	$t_{lo}^{III}=0.33\cdot t_{rmt}+18.8-5,\mathrm{℃}$

Table 2. The operative temperature ranges for the thermal environment categories [21].

Category	$\mathbf{Temperature} \mathbf{Range}, \mathbf{℃}$
Category I	$t_{uo}^I=0.33\cdot t_{rmt}+18.8+2,\mathrm{℃}$
	$t_{lo}^I=0.33\cdot t_{rmt}+18.8-3,\mathrm{℃}$
Category II	$t_{uo}^{II}=0.33\cdot t_{rmt}+18.8+3,\mathrm{℃}$
	$t_{lo}^{II}=0.33\cdot t_{rmt}+18.8-4,\mathrm{℃}$
Category III	$t_{uo}^{III}=0.33\cdot t_{rmt}+18.8+4,\mathrm{℃}$
	$t_{lo}^{III}=0.33\cdot t_{rmt}+18.8-5,\mathrm{℃}$

where

• $t_{uo}$—upper limit of operative temperature, $\mathrm{℃}$;
• $t_{lo}$—lower limit of operative temperature, $\mathrm{℃}$.

The EN 16798-1:2019 standard describes design criteria for relative humidity in occupied zones [21]. These criteria are recommended if humidification or dehumidification systems are installed, which is usually not the case in residential buildings. However, the design criteria presented in the standard were used to create relative humidity ranges for the assessment of the performance of the analyzed ventilation system (

Table 3. The relative humidity ranges [21].

Category	Relative Humidity Range, %
Category I	30 % ≤ RH ≤ 50 %
Category II	25 % ≤ RH < 30 % 50 % < RH ≤ 60 %
Category III	20 % ≤ RH < 25% 60 % < RH ≤ 70%

). Based on EN 16798-1:2019, the ranges of carbon dioxide concentration were also created (

Table 4. The carbon dioxide concentration increase ranges in the bedroom [21].

Category	Ranges for Carbon Dioxide Concentration Increase in Bedroom, ppm
Category I	ΔCO2 ≤ 380 ppm
Category II	380 ppm < ΔCO2 ≤ 550 ppm
Category III	550 ppm < ΔCO2 ≤ 950 ppm
Category > III	ΔCO2 > 950 ppm

). The increase in carbon dioxide concentration is given relative to the assumed average atmospheric CO₂ concentration of 420 ppm.

4. Analysis and Results

4.1. Outdoor Air Parameters

Fluctuations of outdoor air temperature impact the ventilation rates, heating and cooling systems’ efficiency, and infiltration of outdoor air, all of which affect indoor temperature, humidity, and pollutant levels. Additionally, seasonal variations in outdoor temperature influence residents’ behavior in shaping the indoor environment [11,32]. To understand the influence of external conditions on the performance of ventilation systems in the three research periods, outdoor air temperature was analyzed. The presented results were further considered for a comparison of indoor air quality between the researched seasons.

The coldest of the analyzed periods was the 2020–2021 heating season, when the mean outdoor temperature was 0.5 °C lower than the TMY and 0.8 °C lower than the warmest season of 2022–2023 (

Table 5. Monthly mean external temperatures—monitored on-site vs. TMY. Description: yellow—only natural ventilation in the building; green—both natural and mechanical ventilation in the building, manual switching in change-over mode enabled.

Month	$2020–2021,$ °C	$2021–2022,$ °C	$2022–2023,$ °C	TMY 2001–2020, °C
September	14.7	14.8	12.9	13.5
October	10.3	9.2	11.2	11.4
November	5.5	4.8	4.3	4.6
December	1.5	−0.1	1.0	1.9
January	−1.0	1.4	3.1	−1.7
February	−0.8	3.9	2.1	2.7
March	3.8	4.2	5.1	5.2
Average	4.9	5.5	5.7	5.4

). For January and February, on-site mean monthly temperatures between the three years varied by between 4.1 °C and 4.7 °C, respectively. The average monthly temperature in January 2023 was 3.1 °C, which is 4.8 °C higher than the TMY value. In February 2021, the average monthly temperature was −0.8 °C, lower than the TMY value by 3.5 °C. In the remaining months, the difference between the highest and the lowest mean outdoor temperatures on-site was no more than 2 °C, with the differences in comparison to TMY values not exceeding 2.2 °C.

Even for months with a similar monthly mean, the daily temperature amplitudes and profiles varied (Figure 6). The variability of these values over time held the potential to create differences in the indoor air parameters across the analyzed measurement periods; however, a decrease in variability is evident when comparing the on-site measurements and the TMY. A difference of 9.9 °C in January’s daily mean temperatures was established based on on-site measurements, while for the TMY data, a difference of 18.8 °C could be expected (

Table 6. Minimum and maximum daily mean temperature at the research site. Description: yellow—only natural ventilation in the building; green—both natural and mechanical ventilation in the building, manual switching in change-over mode enabled.

Month	2020–2021		2021–2022		2022–2023		TMY 2001–2020
	$\mathbf{max}.$ °C	$\mathbf{min}.$ °C	$\mathbf{max}.$ °C	$\mathbf{min}.$ °C	$\mathbf{max}.$ °C	$\mathbf{min}.$ °C	$\mathbf{max}.$ °C	$\mathbf{min}.$ °C
September	21.3	8.8	18.5	8.8	18.1	7.9	27.3	2.8
October	18.5	5.6	17.8	4.0	15.1	6.0	24.3	3.5
November	12.6	−2.2	10.2	−0.5	11.3	−3.9	17.6	−5.4
December	9.1	−4.0	10.3	−10.5	9.7	−8.1	11.4	−8.0
January	5.5	−11.6	10.2	−4.3	12.4	−1.7	8.8	−20.5
February	8.6	−9.3	7.8	−0.7	8.6	−3.9	12.1	−5.2
March	14.3	−3.2	9.9	−0.3	11.8	−0.7	17.0	−4.6

).

4.2. Indoor Air Parameters

The timeframes for indoor air parameters’ analysis were narrowed down to the occupancy hours. It was established through an interview that the MB is used from approximately 23:00 to 7:00, while during the day, the room remains unoccupied, with the door mostly closed. The habit of closing the bedroom door for the day is motivated by the preference to keep two cats out of the room. The room is designated as a bedroom for two people, but very often (several times a week, at least for part of the night), a preschool-age child also sleeps in the room. The door to the MB is always left open at night. The analysis of the 2021–2022 heating season is separate for the NV and hybrid ventilation periods for clarity.

4.3. Adaptive Thermal Comfort

Across the analyzed autumn–winter periods, high thermal comfort conditions were maintained, mostly within category I of adaptive thermal comfort (Figure 7). The gradual decrease in the operative temperatures between the consecutive years, down from 22–24 °C in the 2020–2021 seasons through 21–23 °C in 2021–2022 to 19–21 °C in 2022–2023, was due to adjustments made to the heating curve on the heat pump to better match the users’ preferences. When the change-over mode of hybrid ventilation operation was enabled (27 January 2022), with an RMT < 5 °C, the secondary heater in the MVHR ventilation unit remained off. In such mode, the heating of supply air occurs only in the rotary heat exchanger, and thus the effect depends on the thermal efficiency of the heat exchanger and the temperature and flow rates of the outdoor and exhaust air. At low outdoor temperatures, the temperature of the air supplied to the room decreases, which can lead to cooling of the space, especially during the day when the doors to the room remain closed and internal heat gains are limited (no users, room oriented to the north and west, and low solar gains due to shaded location of windows). However, as the comparison of external parameters indicates (Table 5 and Table 6), the 2022–2023 seasons were not colder overall than the previous years, while February–March 2022 was clearly milder than in 2021. Measurements did not reveal the daytime cooling effect in the MB that could be expected, suggesting that the secondary heater in the MVHR was not needed. The heating curve modification at the start of the heating season resulted in operative temperatures falling into category II for 11% of the 2022–2023 season.

4.4. Relative Humidity

In the 2020–2021 season, RH values ≤ 40% did not occur, unlike in the other periods. An analysis of meteorological data did not reveal differences in outdoor air parameters that could offer an explanation. The house was used in a similar way, by the same residents, so a significant change in internal moisture gains between seasons was unlikely. Considering the highest indoor temperature in the 2020–2021 season (Figure 7a), lower RH values were to be expected. The interdependencies of the humid air parameters suggest that with a decrease in air temperature, the building’s relative humidity will increase (for an unchanged moisture content). However, Figure 8 shows the opposite effect—in the seasons of 2021–2022 and 2022–2023, relative humidity decreased. An analysis of air parameters in the Mollier diagram (Figure 9) indicates that the moisture content in the naturally ventilated bedroom reached higher values than during the NV + MVHR period, suggesting an increase in the efficiency of air exchange in the room in the latter case.

Significant differences were noted in the time of occurrence of the indoor environment category for the periods analyzed (

Table 7. The percentage of time in each indoor environment category in terms of relative humidity in the MB during occupation hours.

Category	NV IX.2020–III.2021	NV IX.2021–I.2022	NV + MVHR II–III.2022	NV + MVHR IX.2022–III.2023	NV (Total)	NV + MVHR (Total)
	% of MB Occupancy Hours (23:00–7:00)/[h]
Cat. I	34%/507	71%/951	77%/443	68%/1267	51%/1458	70%/1710
Cat. II	49%/743	23%/302	19%/111	28%/519	37%/1045	26%/630
Cat. III	17%/252	6%/79	4%/22	4%/74	12%/331	4%/96
Cat. > III	0%/0	0%/0	0%/0	0%/0	0%/0	0%/0

). The longest time of occurrence of category I (70% of the time) was recorded for the periods of availability of both the NV and MVHR systems. This is a value greater by almost 20% compared to the period of use of the NV system alone. At the same time, for the NV period, an 11% longer time of category II and an 8% longer time of category III were noted. However, no exceedance of category III was recorded for any of the analyzed periods, indicating low moisture-related risks for both ventilation systems as used in the studied MB.

4.5. CO₂ Concentration

As an effective indicator of the efficiency of air exchange, CO₂ was used as a tracer gas [33,34]. The level of CO₂ concentration in the room is shown in Figure 10.

Significant differences in the maximum CO₂ concentrations and the frequency of each indoor environment category (

Table 8. The percentage of time in each indoor environment category in terms of the increase in carbon dioxide concentration in the MB during occupancy hours (baseline CO₂ = 420 ppm in the atmosphere).

Category	NV IX.2020–III.2021	NV IX. 2021–I.2022	NV + MVHR II–III. 2022	NV + MVHR IX.2022–III.2023	NV	NV + MVHR
	% of MB Occupancy Hours (23:00–7:00)/[h]
Cat. I	10%/151	25%/336	18%/101	37%/678	17%/487	32%/779
Cat. II	13%/196	29%/390	58%/332	45%/844	21%/586	48%/1176
Cat. III	61%/922	42%/565	25%/143	18%/333	52%/1487	20%/476
Cat. > III	16%/233	3%/41	0% /0	0%/0	10%/274	0%/0

) were noted, depending on the ventilation system used. In the 2020–2021 season, when only NV was employed, the percentages of time spent in categories I, II, and III were 10%, 13%, and 61%, respectively. There was also an exceedance of the category III carbon dioxide concentration in the MB for 16% of the analyzed occupancy timeframes. Interestingly, in the following season, during NV operation, the internal conditions in terms of CO₂ concentration improved, with over twice as many hours in category I than across the previous season. This was despite the NV use in the coldest month of the 2021–2022 heating season, i.e., December. In February and March 2022, when the MVHR was launched, the CO₂ concentrations in categories I, II, and III were 18%, 58%, and 25%, respectively. As expected, the use of the MVHR system effectively reduced the CO₂ levels in the MB and no exceedances of category III were observed (Table 8, Figure 10b). In the 2022–2023 measurement period, during NV and MVHR availability periods, categories I and II of the CO₂ concentration were maintained for over 82% of the time, and there was no exceedance of category III. When considering the results together for different ventilation strategies, more distinct differences can be seen. Categories I and II were maintained for only 38% of the time for the NV strategy and as much as 80% of the time for the NV + MVHR strategy. At the same time, the incidence of category III decreased by over 1000 h for the hybrid strategy, and category >III did not occur. This indicates a successful strategy by the occupants in ventilating the building during periods when the hybrid system operated in the natural mode and highlights the high effectiveness of MVHR in preventing excessive CO₂ increase during low outdoor temperatures.

4.6. Monthly Comparisons

Figure 11, Figure 12 and Figure 13 show the indoor air parameters in all months of the research.

In September 2020, the mean temperature in the MB was high at 23.9 °C (Figure 11), in line with high outdoor air temperatures, i.e., the monthly outdoor mean was 14.7 °C and the highest daily mean was 21.3 °C—this was the highest value among the analyzed months in the years 2020–2023. In the 2021–2022 season, the monthly average temperature ranged from 21.5 °C to 22.2 °C. On January 27, 2022, the MVHR system was first activated, though this change is not clearly reflected in the indoor temperatures recorded in the MB. The beginning of the 2022–2023 measurement period was characterized by an average monthly indoor temperature of 21.6 °C in September and October, largely due to favorable outdoor conditions (with average outdoor temperatures of 12.9 °C in September and 11.2 °C in October). For the remaining time of the analyzed period, the average monthly temperature ranged from 20.1 °C to 20.8 °C. During the measurement periods when MVHR was in use, smaller temperature amplitudes were observed compared to when NV was used.

In the 2020–2021 period, average monthly relative humidity values ranged from 47.6% to 64.2%, which was the widest range obtained across the analyzed seasons (Figure 12). The activation of MVHR in the 2021–2022 period is reflected in the relative humidity levels in individual months. In the months when MVHR was operating, lower relative humidity values were achieved, both in comparison to the preceding months and to the entire previous measurement season. In February and March 2022, the average outdoor temperatures were 3.9 °C and 4.2°C, respectively. Compared to the previous year, the average monthly temperatures were higher (−0.8 °C in February and 3.8 °C in March 2021), yet the relative humidity values were lower when using MVHR compared to NV. Relative humidity values below 30% recorded in February and March could be attributed to the activation and regulation of the ventilation unit. In the 2022–2023 seasons, the hybrid system was fully switched to the MVHR mode in November (Figure 4), and the change in the operating mode is reflected by a noticeable difference in the range of recorded relative humidity between October and November. In October, when both NV and MVHR were used, the average relative humidity was 56.0%, with the first quartile value at 54.6%. In November, these values dropped to 48.5% and 44.1%, respectively. The decrease in humidity during the winter period is directly linked to the constant use of the MVHR system. Noticeable differences in indoor relative humidity depending on the ventilation system used (mechanical/hybrid/natural) have been confirmed in previous research [35].

In September 2020, a significant difference in CO₂ concentration ranges was observed compared to other months of the analyzed measurement period (Figure 12). This difference was likely due to the windows being left open overnight. Lower CO₂ concentrations in the MB in September were also recorded in the 2021–2022 and 2022–2023 seasons, with the average monthly temperature for September across all measurement periods ranging from 12.9 °C to 14.8 °C. For the winter months (December to March), when NV was used, the average CO₂ concentrations ranged from 893 to 1155 ppm (excluding March 2021). During constant-MVHR and MVHR-availability periods (Figure 4), lower average CO₂ concentrations were achieved, ranging from 797 to 926 ppm. The use of MVHR during the winter months contributed to lower average CO₂ concentrations recorded in the MB. In March 2021 significantly higher CO₂ concentrations were observed, exceeding 2000 ppm for about 14 days, which according to residents’ feedback, coincided with the presence of guests in another bedroom vis-a-vis the MB. In an interview, the residents did not rule out the possibility that during this period, the MB door might have been partially closed. In such case, a gradual increase in CO₂ concentration begins in the late-night hours, around 23:00–00:00, rising hour by hour and typically reaching a peak at around 5:00–7:00. When the occupants leave the room or ventilate it, a significant decrease in CO₂ concentration occurs between 8:00 and 10:00. During the day, CO₂ concentrations in the MB remain at levels consistent with the other months when analyzed in 2021.

4.7. Selected Daily Cycles

Figure 14a illustrates the variability of measured parameters in the MB over the course of a week. A specific week was chosen for this representation due to a significant drop in outdoor air temperature during that period. On September 15–16, the outdoor temperature fluctuated between 11 and 30 °C, and on September 17, it cooled down to below 20 °C during the day and below 5 °C at night. This had a direct impact on the occupants’ behavior and resulted in changes in indoor air parameters. When the outdoor temperature at night exceeded 10 °C, the residents left the MB window open, which led to a relatively small increase in CO₂ concentration (Δ CO₂ = 100–150 ppm) during occupancy. Leaving the windows open at night also allowed for utilizing the cooling potential of the outdoor air to naturally lower the indoor temperature. During the night of September 15 to 16, the use of night cooling reduced the indoor air temperature from 29 °C to 24 °C. When the outdoor temperature is low, the occupants tend to leave the windows only slightly open (unsealed), which results in a CO₂ concentration increase up to 700–800 ppm during the night. Closing the windows also affects the change in relative humidity within the room. With open windows, the relative humidity in the room is largely influenced by the external conditions. However, when the windows are closed, a gradual increase in relative humidity is observed during room occupancy.

Figure 14b illustrates the variability of measured parameters in the MB over two days of use. Narrowing the time range allowed for a more detailed examination of diurnal changes in indoor air parameters and helped to determine the occupants’ role in shaping the quality of the indoor environment in the NV mode. The graph depicts changes in indoor air parameters during one night with an open window and another night with a closed window. With the window open, a slight decrease in indoor temperature was recorded during the night, whereas with the window closed, the room temperature increased by approximately 2.5 °C. The window was closed by the occupant at around 00:00, which resulted in a sharp increase in carbon dioxide concentration (∆CO₂) and an overall increase in indoor temperature during the night. With the appearance of a second occupant in the room (between 1:00 and 2:00), a reduction in CO₂ concentration to about 500 ppm above the outdoor air CO₂ level was observed, caused by door opening and mixing of air from the corridor. A subsequent rise in CO₂ concentration (to approximately ∆CO₂ = 800 ppm) suggests the simultaneous presence of two people in the room. The CO₂ concentration continued to increase until 6:00, at which time one of the occupants left the room. Between 6:00 and 9:00, only one person remained in the room. After 9:00, the room remained unoccupied, and the CO₂ concentration decreased to levels similar to the outdoor air CO₂ concentration. Then, at around 16:00, it is likely that the window was opened, as a significant drop in indoor temperature was recorded over a six-hour period (ΔT = 4 °C), followed by an increase in temperature when the window was slightly closed again around 22:00, suggesting that the room was ventilated before nighttime. Although the occupants noted that the described use of the room slightly deviates from their standard routine (the second person usually leaves the room earlier than 9:00), it nonetheless accurately reflects the general behavior pattern of the residents.

4.8. Air Exchange Rates

To provide a more in-depth interpretation of the ventilation efficiency for distinct strategies, the air exchange rate (ACH) (3) was calculated using CO₂ emitted by the occupants as a tracer gas. The ACH value was based on the bedroom’s volume (49.7 m³). VCO₂ (4) represents the total volume of air exchanged in the room, including interzonal airflow. During the MVHR period, system efficiency measurements indicated a mechanical airflow of 30 m³/h, resulting in an air exchange rate of 0.6 h⁻¹. According to residents’ feedback, the bedroom door is kept open during the night, allowing for air exchange between rooms in the building. There are no other people living in the house apart from those who slept in the bedroom, so there was no significant CO₂ emission outside the bedroom during the night. In addition, the window, except for periods of below 0 °C, was always in the unsealed mode or ajar, which caused undetermined airflows that also contributed to the reduction in CO₂ concentration.

$$ACH={\displaystyle \frac{{VCO}_2}{Vol}},\hspace{1em}\hspace{1em}{h}^{-1}$$

(3)

VCO₂—total ventilation air volume, m³/h;

Vol—volume of the room, m³.

$${VCO}_2={\displaystyle \frac{K_{CO2}}{\Delta s_{CO2}}}={\displaystyle \frac{K_{CO2}}{s_2-s_1}},\hspace{1em}\hspace{1em}{\displaystyle \frac{m^3}{s}}$$

(4)

K_CO2—carbon dioxide emission in the room, g/h;

s₁—initial carbon dioxide concentration in the air introduced into the room, mg/m³;

s₂—maximum recorded carbon dioxide concentration in the room, mg/m³.

For the calculation of the K_CO2, it was assumed that there were two adults in the room (100% attendance) and one child (50% attendance). The CO₂ emissions in the bedroom were estimated as 0.01 l/s based on the ages and weights of the inhabitants and an assumed metabolic rate of 0.95 [36]. This study did not involve measurements of the CO₂ concentration in outdoor air. To estimate the ACH, measurement results recorded inside the building were analyzed. The initial CO₂ concentration in the ventilation air was assumed based on the minimum result recorded in the room, which was 420 ppm. The maximum CO₂ concentration was defined as the highest value recorded in the morning, when all persons were most likely in the room at rest. Days when no significant increase in CO₂ concentration was observed compared to the assumed initial value were excluded from the calculations. The calculation results for the adopted assumptions are shown in Figure 15, and

Table 9. Sensitivity analysis for CO₂ emission results in relation to background CO₂ concentration and occupancy levels.

		CO2 Emission
		NV			NV + MVHR
Initial CO2	400 ppm	87.7%	97.5%	107.2%	86.4%	96.0%	105.6%
	420 ppm	90.0%	100.0%	110.0%	90.0%	100.0%	110.0%
	450 ppm	93.6%	104.0%	114.5%	96.0%	106.7%	117.3%

presents the change in the results obtained from the sensitivity analysis. The sensitivity analysis considered possible changes in internal CO₂ emissions and changes in atmospheric background CO₂ concentrations. The analysis revealed a greater sensitivity of the results to input data regarding the internal CO₂ source.

Figure 15a shows the distribution of obtained ACH for the NV and NV + MVHR periods. A large diversification of the obtained results was observed for both ventilation strategies. The lowest ACH value for NV is less than 0.3 h⁻¹, while the highest is close to 10 h⁻¹. A similar maximum value was obtained for the hybrid strategy. These results are obtained during the period when the windows in the room (and probably in other places in the building) are open, which is confirmed by the reed switcher data. The minimum ACH value is about three times higher for the NV + MVHR strategy, and the median and mean value are 45% and 42% higher, respectively.

For the collected data, it was checked what trigger caused the bedroom window to open. For this purpose, a simple correlation analysis of the ACH index with the values of the outside temperature (Tout), inside temperature (Tin), and inside humidity (RHin) was performed. A comparison was performed for the average values throughout the whole night (23:00–7:00) and for the beginning of the night, defined as the moment when the occupants entered the bedroom (23:00–1:00). The results are presented in

Table 10. Correlation coefficients among the main study variables.

Variable	Correlation Coefficient
	ACH During NV, h−1	ACH During NV + MVHR, h−1
Tout av.23-7	0.353	0.357
Tout av.23-1	0.365	0.355
Tin av.23-7	−0.124	0.015
Tin av.23-1	−0.003	0.124
RHin av.23-7	0.092	0.169
RHin av.23-1	0.138	0.185

. The highest values of the correlation coefficient were obtained for the outside temperature. A graph ACH = f(tout av.23-7) was prepared for this variable. According to the obtained results, the residents opened the windows mainly in the period when the average outside temperature at night reached a minimum value of approx. 7–8 °C (Figure 15b). The results also indicate the significant importance of interzonal air exchange. In additional analyses, no influence of internal temperature on window opening was found. The lowest results obtained for NV indicate that despite the doors being left open at night, during the period of high building sealing, the air exchange rate may be insufficient to ensure a high quality of the internal environment. At the same time, the results obtained for NV + MVHR show that the actual ACH results are significantly different from the design ACH, resulting from mechanical airflows (from 50% higher to several times higher than the design value when the window is not opened).

4.9. Summary of Statistical Analysis Results

To statistically compare the results obtained from measurements and calculations, a two-sample t-test for the mean was conducted. A null hypothesis H0₁ (5) was formulated, assuming no difference in results between the NV and NV + MVHR periods:

H0₁: μ._NV = μ._{NV + MVHR}

(5)

The comparison was performed for relative humidity, carbon dioxide concentration, and air exchange rate. Indoor temperature was excluded from the analysis due to adjustments made to the heating curve during the study period. Homogeneity of variances was tested using Levene’s test. The t-test was then performed according to Equations (6) and (7), and the calculated t-values (t_calc) were compared to the critical t-values (t_crit). The significance level was set at α = 0.05. A summary of the results is presented in

Table 11. Summary of the statistical analysis of the collected data.

Parameter	Sample Size		Levene’s Test p-Value		2-Sample t-Test		Result
	1 (NV)	2 (NV + MVHR)			tcrit	tcalc
RH	2503	1656	0.001	heterogeneous	1.961	50.533	H01 rejected
CO2	2503	1656	<0.001	heterogeneous	1.961	23.523	H01 rejected
ACH	308	255	0.577	homogeneous	1.964	−6.086	H01 rejected

. Based on the analysis, the influence of the applied ventilation system on the observed outcomes was confirmed.

$$t_{calc}={\displaystyle \frac{\overline{X_1}-\overline{X_2}}{\sqrt{(\frac{s_1^2}{n_1}+\frac{s_2^2}{n_2})}}}\hspace{1em}\hspace{1em}\hspace{1em}forheterogeneousvariances$$

(6)

$$t_{calc}={\displaystyle \frac{\overline{X_1}-\overline{X_2}}{\sqrt{s^2·(\frac{1}{n_1}+\frac{1}{n_2})}}}\hspace{1em}\hspace{1em}\hspace{1em}forhomogeneousvariances$$

(7)

$\overline{X_i}$—arithmetic mean of the results in the sample;

si—standard deviation;

n_i—sample size.

Calculations were also performed for hypothesis H0₂ (8), excluding natural ventilation results from the NV + MVHR season. The results were consistent and led to the rejection of the hypothesis.

H0₂: μ._NV = μ._MVHR

(8)

5. Energy Demand

This study examined the impact of the ventilation type on the indoor temperature, relative humidity, and CO₂ concentration. However, it did not focus on analyzing energy consumption, which is a key aspect in the context of hybrid ventilation systems. During the design phase of the ventilation systems in their home, the residents considered both operational costs (final energy demand) and environmental impact (primary energy demand). The planned solution aimed to improve indoor environmental quality while also minimizing energy use.

Table 12. Annual energy needs associated with ventilation heat losses, including operation of the MVHR.

	MVHR	NV	NV + MVHR (8 °C)	NV + MVHR (12 °C)
Final energy, kWh/m2	6.6	16.8	8.9	7.6
Primary energy, kWh/m2	23.3	41.9	25.5	23.5

presents a comparison of annual energy needs associated with the operation of the ventilation systems, calculated for a Typical Meteorological Year (TMY) [16]. For the mechanical ventilation system, actual operating parameters were assumed: airflow rate of MVHR = 250 m³/h, heat recovery efficiency η = 75%, no pre-heater, and the auxiliary heater turned off. For natural ventilation, the airflow rate was determined according to the national building energy performance methodology [37] and set at NV = 152 m³/h. The overall efficiency of the heating system supplying energy for air heating was calculated based on the following methodology: η = 2.08 (generation: 3.0; distribution: 0.96; regulation: 0.76; accumulation: 0.95). The non-renewable primary energy factor for electricity in Poland was adopted as w = 2.5. Energy consumption was estimated based on the measured power consumption of the MVHR unit (p = 52 W). For hybrid operation, the results are presented for two scenarios: a switching-point temperature estimated from measurements (8 °C) and an assumed value (12 °C) as supported in the literature [38].

According to the results, the ventilation operation practiced by the residents leads to an approximately 35% higher final energy demand and around a 10% higher primary energy demand compared to the full-time MVHR strategy. Changing the switching-point temperature to 12 °C would increase the final energy demand by 15%, with nearly no change in primary energy demand. Operating the system solely in the natural ventilation mode would result in nearly a 90% higher final energy demand and 65% higher primary energy demand compared to the resident-practiced hybrid mode.

These calculations represent only a rough estimate of the energy demand associated with ventilation operation. They do not account for the benefits of natural ventilation during summer, when passive night cooling enables the release of heat accumulated during the day and improves thermal conditions indoors, as demonstrated in scientific studies [38,39]. These aspects will be addressed in future stages of the research. An additional benefit of using natural ventilation, as reported by the residents, was the perceived biophilic comfort—a sense of psychological and physical well-being associated with a direct connection to the outdoor environment.

6. Discussion

Based on a stable home–user environment, the results of this unique longitudinal study contribute to the literature on the link between the ventilation strategy and the indoor air quality in bedrooms in the heating season. Well-informed residents were recruited, who understand the ventilation options in place and are committed to maintaining a good indoor air quality, which distinguishes this study from other field studies, where users’ understanding of ventilation strategies is either not considered [40,41,42] or the underperformance of ventilation is partly explained by the insufficient awareness or skills of the residents [7]. Here, the results showcase the best-case scenario of the in-use heating season performance for the two distinct ventilation strategies, i.e., natural or hybrid ventilation in an air-tight, low-energy, detached house. This study provides insight into the impact of the key factor specific to bedroom ventilation: all decisions on opening or closing the windows and doors are made before going to sleep, and after that, no changes are introduced for several hours. The analysis of natural ventilation in bedrooms, which relies on windows’ operation, allows us to capture the residents’ dilemma of balancing sufficient air exchange and heating energy considerations when outdoor temperatures are low. Here, air change rate analysis suggests that the windows remained open throughout the nights when the nighttime outdoor temperature was higher than 7–8 °C. This is a relatively low threshold compared to findings in previous studies focused on housing, e.g., 12 °C in the northwest US or 11.4 °C in the UK [43]. This suggests a higher concern of the residents in this study about sufficient air exchange than about energy conservation in a well-insulated and effectively heated house. The monitoring of bedroom indoor air parameters over three consecutive autumn–winter seasons showed their strong relationship with the ventilation strategy adopted. Compared to relying on NV only, a more effective ventilation strategy in terms of carbon dioxide concentration in bedroom is MVHR combined with periodic use of the NV system. In the coldest periods of the heating season when leaving windows open is being avoided, MVHR working in the background secures overall improved indoor air parameters. However, the impact of hybrid ventilation on RH is more ambiguous. Significantly higher RH values were recorded during NV operation. During NV + MVHR operation, an increase in the frequency of RH below 40% was observed, and there was a reduction in the number of hours when RH exceeded 60%. Relative humidity in the range of 40–60% is considered the most beneficial for human health and well-being. Scientific studies indicate that a RH below 40% is a factor conducive to the spread of pathogens by weakening the defense mechanisms of the respiratory tract [44,45,46]. It also dries out interior elements such as carpets and furniture and can lead to the resuspension of dust particles, which irritate the respiratory tract. On the other hand, too high of an RH value promotes the growth of fungi, molds, and mites, which also has negative effects on human health [47,48]. The decrease in RH value during MVHR operation may be more significant in buildings equipped with plate heat exchangers, which we propose because the rotary heat exchanger used in this case study was found to partially recover moisture in the winter season [49].

The interzonal airflows in the building, affecting the spatial variability of pollutant concentrations, have been shown to have relevance in terms of enhancing the positive impact of MVHR in the coldest periods of the heating season [50]. Numerous publications have shown that leaving doors open during sleep can significantly reduce the CO₂ concentration [51,52], and leaving windows open can increase the airflow by several times [53], which was confirmed in this study. However, the presented results indicate that leaving the doors open without simultaneously ensuring additional air exchange (mechanical ventilation or building leakage) may prove to be insufficient, even despite relatively low CO₂ emissions in relation to the volume of the entire building, as airflows between rooms are limited. In case of air-tight building envelopes and spaces that do not have exhaust points for natural ventilation, which is typical for new-built energy-efficient housing in Poland, it is necessary to involve residents in the process of active regulation of the internal environment through window opening or unsealing. The ACH values and CO₂ concentrations obtained in this study compare favorably to those reported in other publications [54], even during the period of using NV. This can be explained by the residents’ high level of understanding of the role of ventilation and their active and conscious cooperation with the building infrastructure.

7. Conclusions

The following conclusions can be made from this autumn–winter longitudinal study focused on comparing indoor air parameters of a master bedroom, depending on the ventilation strategy adopted by skilled residents in an air-tight, energy-efficient house located in a rural setting in southwest Poland. The strategies explored are natural ventilation or hybrid ventilation systems operating in a change-over mode.

During the occupancy hours, the differences in air quality categories observed can be linked to the type of ventilation used. Compared to relying on NV only, a more effective ventilation strategy in terms of carbon dioxide concentration in the bedroom is MVHR combined with the periodic use of NV. The air exchange rate for the NV strategy was on average 38% lower than for the mixed-mode ventilation strategy.

The large variance in CO₂ concentration observed for the NV strategy and the variability of ACH values throughout this study indicate an evident influence of residents, modifying the airtightness of the building through window opening or unsealing or leaving the doors open. Also, it was determined that the behavior and interactions of the residents with the indoor environment are particularly critical in the case of hybrid ventilation systems operating in a change-over mode, where key operational parameters—such as the decision to switch between NV and MVHR modes, ensuring adequate air exchange during periods of natural ventilation—are dependent on user behavior. The effectiveness of such a system is therefore closely linked to occupant awareness and correct system management. The results also indicate the need for further research into the importance of interzonal airflows.

No clear influence of the ventilation strategy on the internal temperature was observed. The indoor temperature was driven by the inhabitants’ preferences, and the building was capable of consistently maintaining the adjusted indoor temperature, proving the overall high standard of the building fabric and systems.

Despite the high level of knowledge and involvement of residents, periods of a lower indoor environmental quality were not avoided, especially during the period of NV use, which indicates the contribution of other drivers of the NV strategy. Residents highlighted the outside temperature and air pollution as factors determining the opening of windows. The analysis of window opening indicated that the activation of the mechanical system showed a connection with the outdoor temperature. The longest opening periods were recorded up to mid-September 2022. During this period, the outside temperature did not drop below 7 °C. Later on, a drastic decrease in the frequency of window opening was observed (approx. 2570 cycles in the first half of September, approx. 107 cycles in the second half of September). During this period, the outside temperature periodically reached values below 4 °C. Numerous research results indicate outdoor noise, air pollution, and safety concerns as relevant factors influencing the effectiveness of natural ventilation in buildings [55,56,57,58]. Due to the building’s location in a quiet environment and the first-floor bedroom location, the residents indicated neither noise nor safety as factors limiting their window-opening behavior [42,43,44].

8. Limitations

This study presents a comparison of the energy demands associated with the operation of different ventilation systems, based on the known specifications and parameters of the installed equipment, as direct measurement data were unavailable. The calculations were carried out using Typical Meteorological Year (TMY) data and should be regarded as indicative values rather than representations of actual, real-time system performance. The analysis is limited to the master bedroom (MB), selected due to its stable and regular occupancy pattern. The MB serves as a representative space for drawing broader insights applicable to similar residential rooms. However, the findings cannot be directly generalized to spaces with different functions, occupancy profiles, or internal heat and moisture gains—such as kitchens, bathrooms, laundry rooms, etc.

This study also does not include interzonal airflow measurements, which could further inform the understanding of ventilation effectiveness across the entire dwelling. Additionally, the absence of on-site monitoring of outdoor air pollution prevented the evaluation of its potential influence on the occupants’ ventilation behavior.

Another limitation comes from the residents’ professional background in HVAC and architecture, which may lead to a higher-than-average awareness and optimized use of the ventilation system. This introduces a positive bias and may limit the generalizability of the results. Nonetheless, the authors believe that this study offers valuable practical insights that can inform future research and support the development of guidelines for implementing hybrid ventilation strategies in non-expert households.