A Study on Indoor Air Quality in Traditional Earthen Residences of Western Hunan: Field Survey and Passive Mitigation Strategies

Abstract

In the western Hunan region, the fire pit serves as the primary space for heating, receiving guests, and sacrificial ceremonies. However, the prolonged use of wood as the main fuel for the fire pit poses a significant threat to indoor air quality and the health of residents. This study conducts field monitoring and evaluation of indoor air quality in traditional earthen residences in Western Hunan during winter. It employs software simulation to analyze the concentration of indoor pollutants in typical earthen dwellings. Three passive mitigation strategies—adjusting window size, installing interior partitions, and setting up passive smoke exhaust systems—are proposed, and their effectiveness is validated through simulation. The results indicate that the best air circulation performance occurs when the window sill height is between 0.9 and 1.5 m, and the window sill length is between 1.5 and 2.1 m. Installing partitions increases the average concentration of indoor pollutants in the fire pit and master bedroom areas by 2.33 and 3.05 times, respectively. Installing smoke exhaust systems above the fireplace can decrease indoor pollutant concentrations by more than 70%. The findings provide effective strategies for controlling health risks caused by indoor pollutants in winter without affecting local residents’ living habits and traditional customs.

1. Introduction

People spend on average approximately 87% of their time in indoor environments [1]. Meanwhile, about 2.1 billion people worldwide—nearly one third of the global population—still rely on open fires or inefficient stoves for cooking. These stoves primarily burn kerosene, biomass fuels (such as wood, animal dung, and crop residues), or coal, resulting in severe household air pollution [2]. According to estimates by the World Health Organization, household air pollution caused approximately 3.2 million deaths annually in 2020, including about 237,000 deaths among children under five years of age. When both indoor and ambient air pollution are considered together, their combined impact leads to approximately 6.7 million premature deaths each year worldwide [2]. Therefore, indoor air quality (IAQ) has become one of the key environmental factors affecting global public health. In rural China, the combustion of solid fuels such as wood and coal in households is a major source of indoor air pollution. The use of these fuels for cooking and heating has been shown to significantly increase health risks [3,4]. In economically underdeveloped, cold, and humid winter regions of Western Hunan, residents commonly use open biomass combustion in a fire pit for heating, cooking, and religious rituals. In daily life, cooking with biomass in the kitchen is a widespread practice. However, long-term exposure to high concentrations of pollutants generated by the use of fire pit has been associated with a high incidence of respiratory and cardiovascular diseases. Health risks are particularly pronounced for women with prolonged exposure, elderly individuals with declining physiological functions, and children with underdeveloped defense mechanisms. Although China and its local governments have implemented policies such as the Healthy China Action (2019–2030) [5] to improve indoor air quality, the IAQ of traditional dwellings still requires systematic investigation [6].

A large body of research has demonstrated that indoor air pollutants in buildings—including PM_2.5, PM₁₀, volatile organic compounds (VOCs), formaldehyde, and CO₂—have significant impacts on the respiratory system, cardiovascular system, and immune function [7,8,9,10]. These pollutants originate not only from the outdoor environment but are also closely related to indoor building materials, finishing materials, heating methods, and ventilation conditions [11]. With regard to building materials, previous studies have shown that certain materials possess adsorption and diffusion capacities, which may reduce pollutant concentrations under low ventilation rates [12]. However, in humid environments, these materials may also absorb moisture and promote the growth of mold and microorganisms, thereby deteriorating indoor environmental health [13]. In modern buildings with improved energy efficiency and enhanced airtightness, low ventilation rates often lead to the accumulation of indoor pollutants. By contrast, the natural ventilation strategies commonly found in traditional dwellings can, to some extent, improve indoor air quality [14]. Increasing natural ventilation and air exchange rates has been shown to effectively dilute indoor pollutant concentrations [15].

In rural areas of China, the combustion of solid fuels such as wood and coal during cooking and heating remains the primary source of indoor air pollutants [16,17]. Studies indicate that the use of solid fuels significantly elevates indoor pollutant concentrations and increases health risks, particularly for elderly people, women, and children [16,18,19]. During the winter heating season, PM_2.5 concentrations in rural areas are generally high, resulting in more severe pollution exposure and more pronounced adverse health effects [20]. Moreover, traditional rural dwellings often lack effective ventilation systems, which further exacerbates the accumulation of indoor pollutants. Improving ventilation conditions and heating methods is therefore considered a key strategy for mitigating indoor pollution exposure during winter [21]. To reduce indoor air pollution, the promotion of clean stoves has become an important research focus. The use of high-efficiency clean stoves can significantly reduce PM_2.5 concentrations and associated health risks [22,23]. However, the widespread adoption of clean stoves in rural areas faces economic, cultural, and technical challenges [24,25].

Existing studies on indoor air quality in residential dwellings are mainly based on field measurements. Without disrupting residents’ daily activities, researchers typically monitor temperature, humidity, CO₂, PM_2.5, PM₁₀, formaldehyde, and total volatile organic compounds (TVOCs) in key living spaces such as bedrooms, central room and kitchen. Outdoor environmental conditions and occupant activities are recorded simultaneously to reflect the IAQ performance of naturally ventilated dwellings [26,27,28,29,30,31]. In addition, tracer gas methods are widely used to quantitatively assess residential ventilation performance. Techniques such as the SF₆ decay method or calculations based on occupants’ exhaled CO₂ are commonly employed to determine air change rates, thereby revealing actual ventilation levels under natural and infiltration ventilation conditions [32,33]. To compensate for the limitations of objective assessments, questionnaire surveys and subjective evaluation methods have been applied to analyze occupants’ perceptions of air quality and indoor environments, by combining residents’ subjective evaluations of air freshness, odor, thermal comfort, and health symptoms with measured data, researchers have explored the relationships between IAQ, residential satisfaction, and acceptance [34,35]. The results indicate that socioeconomic background and long-term adaptive behaviors significantly influence occupants’ tolerance of air quality, with low-income groups or populations accustomed to long-term natural ventilation exhibiting higher adaptability [36]. However, because subjective evaluations are strongly influenced by psychological and social factors, their conclusions need to be validated against objective monitoring results [35]. With the advancement of research, numerical simulation and modeling approaches have increasingly been applied to studies of residential IAQ. Computational fluid dynamics (CFD) simulations and coupled energy–air quality models [37,38,39,40] have been used to analyze airflow patterns and pollutant distributions under different building forms, ventilation strategies, and occupant behaviors, thereby evaluating the potential impacts of design and retrofit measures on IAQ [41,42].

Overall, domestic and international research on indoor air quality has primarily focused on modern buildings and public spaces, such as schools, office buildings, and hospitals [43,44,45]. Existing studies on traditional Chinese dwellings have mainly addressed spatial layout and cultural characteristics, architectural conservation, thermal environment, and thermal comfort, while research specifically targeting indoor air quality in traditional dwellings remains relatively limited [46,47,48,49]. In Western Hunan in particular, existing research has primarily focused on the daylighting performance of traditional dwellings, fire risk assessments, and analyses of factors affecting the health of the elderly. However, systematic studies on the characteristics of winter indoor air pollution and the diffusion patterns of pollutants in traditional earthen dwellings in Western Hunan remain scarce [50,51].

Western Hunan Province preserves a large number of traditional dwellings constructed primarily from earthen and wood. In these dwellings, the fire pit serves as the core living space, functioning not only as a source of heating but also as a place for social interaction and family gatherings. In addition, the fire pit plays an important role in ritual activities, and many ethnic minorities in this region continue to maintain these traditional customs and lifestyles [52,53,54,55]. As residents spend long periods of time in such indoor environments, it is essential to quantify indoor pollutant concentrations and propose effective mitigation measures.

Therefore, we select representative traditional earthen dwellings in Western Hunan as sample sites to monitor winter indoor air quality, focusing on PM_2.5, PM₁₀, and formaldehyde (HCHO). Furthermore, PyroSim software 2021.3.0901 is employed to simulate indoor pollutant dispersion, and passive mitigation strategies are proposed to improve indoor air quality and reduce health risks associated with indoor pollutants in traditional dwellings. An investigation of the IAQ characteristics of these dwellings not only provides valuable insights for modern green building design but also offers important references for the development of sustainable living environments.

2. Materials and Methods

2.1. Study Objects

2.1.1. Traditional Earthen Dwellings in Western Hunan

Traditional earthen dwellings are widely distributed in Xiangxi Autonomous Prefecture and exhibit distinct characteristics shaped by local environmental conditions. At present, Baojing County, Huayuan County, and Fenghuang County are among the regions where such dwellings are best preserved. In Fenghuang County, more than 14,900 earthen and adobe dwellings are still in existence, with a total floor area exceeding 1.3 million m². Among these, seven villages—namely Shujia Village, Laodong Village, Laojiazai Village, Liangdeng Village, Zhushan Village, Sumahe Village in Laershan Town, and Luotuoshan Village—retain large, contiguous clusters of traditional earthen dwellings. These villages account for 31.8% of the listed traditional villages in the region. For this reason, the present investigation was mainly conducted in Fenghuang County (Figure 1). The selection of surveyed samples was based on the following criteria:

• The selected earthen villages were included in the national list of Chinese Traditional Villages or were characterized by relatively underdeveloped infrastructure;
• The selected dwellings were mainly made of raw earth or combined with rubble and wood;
• The traditional architectural appearance of the selected dwellings was well preserved;
• The selected dwellings had not undergone renovation or extension within the past 20 years;
• The selected dwellings were currently occupied and in regular use.

The three villages finally selected for detailed investigation were Zhushan Village (with a permanent population of 1095), which was founded in the Ming Dynasty and listed as the third batch of “Characteristic Villages of Ethnic Minorities in China”, and Guniu village (with a permanent population of 947) and Suode village (with a permanent population of 788), which have relatively backward infrastructure.

2.1.2. Basic Characteristics of the Respondents

In Zhushan Village, approximately 99.8% of the population belongs to the Miao ethnic group, and the village is commonly referred to as the Zhushan Miao Village. Out-migration for entrepreneurship or wage employment constitutes the primary source of household income. As a result, the permanent residents of the village are predominantly elderly people and children. Daily agricultural activities mainly involve the cultivation of traditional crops such as rice and maize, as well as flue-cured tobacco and the locally known “Lazy Man Pear” as an economic crop. In terms of daily clothing, children generally wear modern apparel, whereas elderly residents—particularly women—often wear traditional Miao ethnic costumes (Figure 2). The situations in Gunniu Village and Suode Village are similar to that of Zhushan Village. The resident sample investigated in this study consisted of permanent village inhabitants. The selection criteria were as follows: more than 60% of the respondents were over 60 years of age, more than 70% were over 65 years of age, and the duration of residence exceeded 10 months per year. Individuals staying temporarily for purposes such as visiting relatives, tourism, or short-term residence were excluded.

Most respondents were found to live in multi-generational households, with traditional earthen dwellings serving as their primary long-term living spaces. Daily production and living activities were closely integrated with the dwelling spaces. The majority of respondents carried out agricultural cultivation and poultry breeding in the immediate surroundings of their houses. In addition, the habitual use of an indoor fire pit was widely maintained. The fire pit functioned as the core space for daily heating, cooking, and boiling water, as well as for certain folk activities such as ritual practices, and large quantities of firewood were commonly stored indoors (Figure 3).

2.2. Field Investigation

2.2.1. Subjective Survey

A subjective investigation of indoor air quality was conducted among residents living in traditional earthen dwellings in Western Hunan. The subjective evaluation was carried out through on-site interviews and questionnaire surveys. The interview framework was developed based on the indoor air quality survey design proposed by Zhang et al. [56], with additional modifications made to account for the specific environmental characteristics of earthen dwellings in the Xiangxi region. The survey covered residents’ daily living habits, their level of awareness of air pollutants, and the types of energy used in daily activities, which are shown in

Table 1. Content of the questionnaire research.

Comment	Question
Basic information	Age, gender, ethnicity, occupation, income, number of permanent residents
Fire pit conditions	Usage, Location
Cooking and heating energy source	Electricity, biogas, natural gas, solar energy
Open window behavior	Open windows all day, open windows occasionally, never open windows
Air purifier use	Never, barely use, often use, daily use

. Questionnaire distribution was conducted on a random basis. Meanwhile, to address the language communication difficulties faced by some elderly people, such as having a strong dialect accent and being not good at speaking Mandarin, this survey was conducted accompanied by the village head or local students from Xiangxi. In addition, before the research was initiated, in-depth exchanges had been conducted with the village party secretary, village director, or director of the village women’s federation, among others. Elderly people with brain-related diseases were temporarily not considered in the sample. Meanwhile, the survey content had been approved by the village director and others. A total of 150 questionnaires were obtained, of which 138 were valid. The period is from December to January 2021.

2.2.2. Objective Monitoring

The monitored residences were determined based on on-site evaluations by the research team and discussions with the residents to ensure that these residences are representative and do not affect the daily lives of the residents. All these residences were built in the Qing Dynasty and are still in normal use at present, and the main residents are elderly people who live there permanently. Typical earthen dwellings in Suode Village and Guniu village in Xiangxi area were selected for on-site measurements using the AZ-77,597 CO₂ analyzer and the BR-SMART128S air quality instrument [57], including PM_2.5 concentration, PM₁₀ concentration and HCHO concentration. The monitoring parameters were determined based on Tastan’s research and adapted to the specific conditions of Xiangxi earthen dwellings [58]. Monitoring was conducted in December 2021. In addition, according to the “Standards for indoor air quality” [59], five monitoring points have been set up in rooms with an area of 50 to 100 square meters, including the main room and bedrooms. Three monitoring points were set up in rooms with an area of less than 50 square meters, including the secondary bedroom, bathroom, kitchen and storage room. The sampling points in this study were evenly distributed along the diagonals or pentagons of each room. The instrument is placed at a measurement point approximately 1.1 m above the ground. The pollutant concentration is recorded every 3 min, and the average value of each monitoring point is taken as the pollutant concentration of the room. None of the rooms where the voters lived used air purifiers. Before the monitoring, the residents carried out their daily cleaning as usual. Meanwhile, during the monitoring process, all the south-facing windows were open and the residents were engaged in their daily activities. The parameters of the monitoring instrument are shown in

Table 2. Indoor Air Quality Monitoring Instruments and Parameters.

Instrument	Measurement Content	Accuracy	Range	Resolution
BR-SMART128S Air Quality Instrument	PM2.5, PM10	±20 μg/m3	0–999 μg/m3	1 μg/m3
	HCHO	±0.03 mg/m3	0–3.000 mg/m3	0.001 mg/m3

. The monitoring points of each room are shown in Figure 4. According to the Code for design of residential building for the aged (GB50340-2016) [60], and in combination with the impact of particulate matter concentration on indoor air quality and human respiration, the concentration of indoor pollutants is evaluated and analyzed by assigning values.

2.2.3. Data Analysis

The evaluation of indoor air quality in traditional earthen dwellings in Western Hunan was conducted in accordance with relevant Chinese indoor air quality standards. Specifically, the assessment was based on the Code for design of residential building for the aged (GB 50340–2016) [60], the Ambient Air Quality Standard (GB 3095–2012) [61], and the Indoor Air Quality Standard [59]. In combination with the known effects of particulate matter concentrations on indoor air quality and human respiratory health, an index-based evaluation and analysis of indoor pollutant concentrations were performed. For the quantitative assessment, reference values were assigned to each pollutant concentration. The evaluation thresholds were set at 100 μg/m³ for PM_2.5, 150 μg/m³ for PM₁₀, and 100 μg/m³ for formaldehyde (HCHO), as summarized in

Table 3. Indoor Air Quality Standards.

Pollutant	PM2.5	PM10	HCHO
Average value standard	100 μg/m3	150 μg/m3	100 μg/m3

[62]. Based on these reference values, the measured indoor pollutant concentrations were compared against the corresponding standards to assess indoor air quality levels. In addition, by integrating existing indoor air quality standards with the selected reference concentration values and their associated impacts on human health, the concentration ranges of each pollutant were classified into graded levels. Each concentration interval was assigned a corresponding rating value to facilitate comparative analysis, as shown in

Table 4. Recommended Assignment Values for Indoor Air Quality Standards.

PM2.5	PM10	HCHO	Evaluation Level	Assigning Value
0–35 μg/m3	0–40 μg/m3	0–40 μg/m3	Best	X1 = 5
35–75 μg/m3	40–70 μg/m3	40–80 μg/m3	Better	X1 = 4
75–115 μg/m3	70–150 μg/m3	80–100 μg/m3	Normal	X1 = 3
115–150 μg/m3	150–200 μg/m3	100–150 μg/m3	Worse	X1 = 2
150 μg/m3 or higher	200 μg/m3 or higher	150 μg/m3 or higher	Worst	X1 = 1

[56].

2.3. Indoor Pollutant Dispersion Simulation

2.3.1. Simulation Method

A typical traditional earthen dwelling located in Zhushan Village, Fenghuang County, Western Hunan, was selected for indoor pollutant dispersion simulation using PyroSim software. The building has a planar layout consisting of three main bays subdivided into five smaller functional areas. The depth of the building corresponds to five structural columns. The overall building width is 13 m, and the depth is 8.6 m. The height from the ground level to the eaves is 7.3 m. This dwelling form and scale are representative of traditional residential buildings in the Xiangxi region. The building is a single-story structure, comprising bedrooms, a fire pit area, a central room, a kitchen, and a storage room.

2.3.2. Model Development and Parameter Selection

The dimensions of the simulation model were consistent with the actual measured data, and the indoor furniture was arranged in accordance with the real residential layout (Figure 5). Based on the simulated dwelling configuration, the computational domain was set to 16.75 m × 13.5 m × 8.5 m, with a total volume of 1922.0625 m³. According to the PyroSim user manual [63], the grid size was set to 0.1496 m × 0.15 m × 0.1496 m, resulting in a total of 574,560 grids. In combination with the maximum heat release rate of the fire pit source, the grid configuration was verified using the grid resolution formula recommended in the PyroSim user manual. The ratio of the characteristic fire diameter to the grid size satisfied the manual requirements, ensuring that the simulation results were consistent with those obtained from grid independence tests.

$${\mathrm{D}}^{\ast }={\left({\displaystyle \frac{\mathrm{Q}}{{\mathsf{\rho }}_0{\mathrm{c}}_{\mathrm{p}}{\mathrm{T}}_0\sqrt{\mathrm{g}}}}\right)}^{{\displaystyle \frac{2}{5}}}$$

(1)

where D* is the fire source feature diameter, Q is the heat release rate of the fire source, taken as 2000 kW; ρ₀ is the air density, taken as 1.205 kg/m³; c_p is the specific heat capacity of air, taken as 1.004 kJ/(kg k); T₀ is the ambient temperature, taken as the annual average temperature of the Tujia region (i.e., 293.15 k); and g is the acceleration of gravity, taken as 9.8 m/s² [64,65].

$${\mathsf{\delta }}_{\mathrm{x}}=\sqrt[3]{\mathrm{x} \times \mathrm{y} \times \mathrm{z}}$$

(2)

where δ_x is the grid size, and x, y, and z are the dimensions of the X, Y, and Z coordinate axes of the unit grid, respectively.

With respect to wind speed parameters, historical wind direction data for Hunan Province from 2011 to 2022 were determined based on statistical records from the China Meteorological Administration, which showed that northeasterly winds accounted for 52.07% of the observations. Accordingly, the wind condition in the simulation was set as a northeasterly wind with a velocity of 1.5 m/s (Figure 6).

For fire source configuration, the fire scale and heat release rate of the fire source were determined based on the maximum heat release rate standards for various venues specified in the Technical Standard for Smoke Control and Ventilation Systems in Buildings (GB51251-2017) [66], as well as the relevant combustion simulation settings for residential buildings by Zhang et al. [67]. The most closely matching fire scenario was selected, establishing the maximum simulated heat release rate of the fire source at 6 MW. Material parameters: The primary combustible material is fir wood, with a heat release rate of 160 kW/m², a burn-up time of 58 s, and an ignition temperature of 260 °C [68]. Ground bluestone slabs and roof tiles are both designated as flame-retardant materials. Based on relevant research and historical weather data, the annual average temperature in the Xiangxi region ranges from 16 to 18 °C. The air temperature for the scenario was uniformly set at 17 °C, and the simulation duration was set to 400 s. The simulation model, monitoring points, and slice settings are illustrated in Figure 7.

2.4. Improvement Measures

2.4.1. Facade Configuration: Window Smoke Ventilation

Windows represent the primary means of indoor air exchange in traditional dwellings. The rational design of window size and position is considered one of the effective measures for mitigating indoor air pollution. Based on a previous survey and analysis of doors and windows in earthen dwellings in the Xiangxi region, the window height ranges from 300 to 1850 mm, while the window width ranges from 200 to 2300 mm. The median values of window height and width are 1000 mm and 1100 mm, respectively, and the corresponding mean values are 974.8951 mm and 1041.74825 mm. In combination with the window size specifications stipulated in the Steel Doors and Windows Standard (GB/T 20909–2007), the basic window opening dimensions range from 600 mm to 2100 mm, with 300 mm adopted as the basic modular increment. In residential buildings, the typical window height is generally 1.5 m. Based on the control variable method, the influence of window configuration on indoor air quality was investigated by modifying a single variable at a time—such as the horizontal position of the window sill, the vertical position of the window sill, the horizontal dimension of the window, and the vertical dimension of the window—using simulations conducted with the Fire Dynamics Simulator (FDS).

The configurations of window and window sill conditions were determined according to the predominant window size ranges observed in local dwellings and the most commonly used window sizes in Chinese residential buildings. Seven scenarios were defined for the vertical position of the window, set at 0.6 m, 0.9 m, 1.2 m, 1.5 m, 1.8 m, 2.1 m, and 2.4 m. Seven scenarios were also defined for the horizontal position of the window, set at −0.9 m, −0.6 m, −0.3 m, 0, 0.3 m, 0.6 m, and 0.9 m. For the horizontal window dimension, twelve scenarios were considered, with widths of 0.3 m, 0.6 m, 0.9 m, 1.2 m, 1.5 m, 1.8 m, 2.1 m, 2.4 m, 2.7 m, 3.0 m, 3.3 m, and 3.6 m. For the vertical window dimension, eight scenarios were defined, with heights of 0.3 m, 0.6 m, 0.9 m, 1.2 m, 1.5 m, 1.8 m, 2.1 m, and 2.4 m. The procedures for model development and software parameter settings were identical to those described in Section 2.3.2 (Figure 8).

2.4.2. Floor Plan: Separate Flue Gas

Field investigations indicate that indoor pollutants in earthen dwellings in Western Hunan are mainly generated by the use of wood-fueled open flames in the fire pit. During fire pit operation, flue gas spreads from the fire pit to other indoor areas, resulting in air pollution in adjacent spaces. The presence or absence of internal partition walls influences both the pathways and the rate of flue-gas dispersion. To examine the extent to which internal partitions affect pollutant levels in different functional areas during the use of fire pit, simulations were conducted based on the prototype described in Section 2.3.2. In accordance with the evolutionary patterns and existing forms of traditional residential plans in Western Hunan, two scenarios were defined—with and without internal partition walls—and the dispersion of indoor pollutants during fire pit operation was simulated and comparatively analyzed (Figure 9).

2.4.3. Passive Equipment: Accelerated Smoke Exhaust

Passive smoke collectors are an effective measure to enhance indoor smoke exhaust efficiency. They accelerate the diffusion rate of indoor air pollutants to the outdoors using the principle of thermal pressure ventilation without altering the existing layout, facade form, or other architectural features of traditional dwellings. This reduces indoor air residence time, making it a minimal-intervention smoke exhaust solution. To validate the effectiveness of passive smoke collectors in traditional earthen dwellings of Western Hunan, two dwelling configurations—with internal partition walls and without internal partition walls, as selected in Section 2.4.2—were adopted., passive smoke collectors were installed at the fire pit location in both cases. The FDS6.7.6_SMV6.7.16.was employed to simulate and compare pollutant dispersion within both sample interiors. Model parameters were configd identically to those in Section 2.3.2 (Figure 10).

3. Results

3.1. Indoor Air Quality Evaluation

3.1.1. Subjective Evaluation

The results are shown in Figure 11. The data indicate that 85.5% of the respondents are over 45 years old, while only 7.97% fall between the ages of 30 and 45. The age distribution aligns with the expected sample structure. In terms of gender distribution, males outnumber females by 2.9%, with a small difference between the sexes. Among the respondents, 88.4% are of Miao ethnicity, and 78.99% are farmers. More than half of the participants have an annual income of around 50,000 yuan, and over half live in households with two people. The majority of residents are Miao elderly people living in earthen dwellings, with relatively low economic status and a balanced gender distribution.

Among the elderly population in the traditional earthen dwellings of Xiangxi, the main daily activities include rest and sleep, cooking and eating, religious rituals, socializing and communication, among others. According to the survey results, rest and sleep account for 42% of the elderly’ s daily time, while cooking and eating occupy 12%. Additionally, socializing and communication, exercise and physical activity, and recreational activities together account for 35% of the time (Figure 12). This suggests that the elderly make extensive use of the existing living space for social and daily activities, including agricultural work and household chores. These activities demonstrate that the elderly fully utilize the available space and its functions, leading to a relatively active lifestyle. Furthermore, women engage in more social visits, walking, traveling, and dancing than men, although the overall difference is not significant.

Residents’ satisfaction with indoor air quality is 79%. Most residents believe that there are no pollutants inside or outside their dwellings, which indicates that the majority of residents have a limited understanding of air pollution. They may not be aware of the potential impact of indoor energy sources such as firewood on air quality.

Traditional earthen dwellings in Western Hunan primarily rely on wood as their main energy source, with 93.5% of residents using wood daily for cooking, heating, and water boiling in kitchens and around fire pits. 90.3% of respondents retain the practice of using fire pits, primarily located in kitchens and bedrooms. In some newly built or renovated dwellings, fire pits are also installed in outdoor annexes. Biogas systems were frequently used during initial construction, with over 90% of households having used them. However, regular cleaning and maintenance often required able-bodied adults, leading to eventual abandonment. Natural gas ranks as the third most common energy source after electricity and wood, used by 35.5% of respondents. Solar energy and air conditioning remain less prevalent, utilized by only 11.7% and 3.4% respectively. The use of open flames in indoor fire pits and kitchens often increases indoor smoke concentrations (e.g., CO₂, CO). However, 68% of respondents believed indoor fire use does not cause indoor air pollution. Concurrently, residents frequently open windows for ventilation. Nearly all respondents indicated they open doors and windows daily to enhance indoor airflow, with 87% keeping windows open all day during summer (Figure 13).

3.1.2. Objective Monitoring Results

PM_2.5

The monitoring results of indoor PM_2.5 concentrations during the use of fire pit in winter in traditional earthen dwellings in Xiangxi are as follows (Table S1): In Guniu Village, the PM_2.5 concentrations in all functional indoor spaces are significantly higher than in areas without the use of fire pit. The average concentration in the fire pit area is the highest, at 755.36 μg/m³, followed by the master bedroom (722.74 μg/m³). The concentrations in the central room and kitchen are relatively close, at 460.85 μg/m³ and 409.44 μg/m³, respectively. In Suode Village, the indoor air quality is also significantly affected by the use of fire pit. The average concentrations in the fire pit, master bedroom, and central room are 740.55 μg/m³, 654.72 μg/m³, and 480.50 μg/m³, respectively. The maximum concentrations in these areas reached the maximum range of the instrument, 999 μg/m³. The fire pit area is the region with the highest indoor PM_2.5 concentration, and other areas are clearly impacted by pollutants generated from the use of fire pit.

The analysis of indoor PM_2.5 monitoring results in winter for earthen dwellings in Xiangxi is shown in Figure 14. During the use of indoor fire pits, the PM_2.5 concentrations in all areas of both Guniu Village and Suode Village significantly exceed the standard range. In Guniu Village, the highest concentration is in the fire pit area, followed by the master bedroom, central room, and kitchen. The situation in Suode Village is similar to that in Guniu Village, with the master bedroom and central room also being significantly affected by the smoke from the fire pit. The evaluation score for all areas is 1, indicating a very poor indoor PM_2.5 air environment. Compared to traditional earthen dwellings, modern dwellings generally maintain lower levels of air pollution. The use of fire pit is the key factor in increasing PM_2.5 concentrations in traditional earthen dwellings, while modern dwellings typically do not rely on fire pits for heating and cooking, resulting in lower indoor air pollution.

PM₁₀

The monitoring results of indoor PM₁₀ concentrations during the use of fire pit in winter in traditional earthen dwellings in Xiangxi are as follows (Table S2): In Guniu Village, the average concentrations in the fire pit, master bedroom, central room, and bedroom are 804.03 μg/m³, 730.62 μg/m³, 651.91 μg/m³, and 521.26 μg/m³, respectively. The fire pit area has the highest indoor PM₁₀ concentration, followed by the master bedroom, central room, and bedroom. In Suode Village, the average concentrations in the fire pit, central room, and master bedroom are 736.15 μg/m³, 541.93 μg/m³, and 717.68 μg/m³, respectively. The fire pit is also the area with the highest indoor PM₁₀ concentration, with the master bedroom, located closest to it, coming second. The maximum concentrations in all monitored areas reached 999 μg/m³, similar to the PM_2.5 levels, indicating that the use of fire pit significantly impacts indoor PM₁₀ concentrations.

The analysis of the winter indoor PM₁₀ monitoring results for earthen dwellings in Xiangxi is shown in Figure 15. Similar to the PM_2.5 situation, during the use of indoor fire pit in winter, the fire pit area is the most severely affected area. The average concentrations in all monitored areas of both Suode Village and Guniu Village exceed the specified range by a wide margin. The concentration evaluation scores for all areas are 1, indicating a very poor indoor PM₁₀ air environment. In the modern dwellings surveyed, the overall PM₁₀ concentration is below the standard value of 150 µg/m³, clearly due to the traditional earthen dwellings.

HCHO

The monitoring results of indoor HCHO concentrations during the use of fire pit in winter in traditional earthen dwellings in Xiangxi are as follows: In Guniu Village, the concentration ranges for the fire pit, master bedroom, central room, and bedroom are 0 to 0.182 mg/m³, 0 to 0.002 mg/m³, 0 to 0.147 mg/m³, and 0 to 0.12 mg/m³, with average concentrations of 0, 0.005 mg/m³, 0.007 mg/m³, and 0.004 mg/m³, respectively. In Suode Village, the concentration ranges for the master bedroom, fire pit, and central room are 0 to 0.002 mg/m³, 0 to 0.005 mg/m³, and 0, with average concentrations of 0.0038 mg/m³, 0.000581 mg/m³, and 0, respectively.

The analysis of the winter indoor HCHO monitoring results for earthen dwellings in Xiangxi is shown in Figure 16. The average HCHO concentrations in the rooms of both Guniu Village and Suode Village are well below the specified range of 0.1 mg/m³. The use of firewood indoors does not contribute to an increase in indoor HCHO pollutants, and the overall HCHO evaluation is positive, with a score of 4. The survey found that the residents of earthen dwellings are predominantly elderly individuals and children. Most of the dwellings have not undergone recent renovations, and the furniture and items were purchased years ago. Additionally, the dwellings are located in a forested environment, with no factories nearby generating pollutants. The fresh natural surroundings and green indoor items create a healthy indoor HCHO environment.

3.2. Simulation Results of Indoor Pollutant Diffusion

3.2.1. Facade Form

Window Vertical Position: Window Smoke Exhaust

The vertical position of the windows ranges from 0.6 to 2.4 m. As the window sill height changes, the CO concentrations in different indoor areas exhibit varying trends (Figure 17). As the window sill height increases vertically, the CO concentration in the master bedroom shows an upward trend. At heights of 1.5 m and 2.4 m, the changes over time are similar, with average concentrations of 13.71 ppm and 13.59 ppm, respectively. The CO concentrations in the central room, fire pit area, secondary bedroom, and kitchen show a significant decrease as the window sill height increases. The higher the window sill, the less pronounced the decrease. Except for the fire pit area, where the average concentration is relatively high, the average concentrations in the other areas are similar to that of the master bedroom.

The vertical position of the windows ranges from 0.6 to 2.4 m. As the window sill height gradually increases, the CO concentration at the master bedroom measurement point also increases. The most severe pollution in the master bedroom occurs at window sill heights of 1.8 m and 2.1 m. The central room, secondary bedroom, and kitchen all show a decreasing trend, with the best conditions for the central room being at heights of 0.6 m and 1.2 m, with reductions of 43.85% and 35.50%, respectively. The impact of changes in window sill height on the secondary bedroom is similar to that of the kitchen, with the most significant effect occurring in the 0.6 to 1.5 m vertical range, and minimal changes observed in the 1.5 to 2.4 m range. The CO concentration in the fire pit area shows little variation, with only slight reductions at 1.2 m and 1.5 m (Figure 18).

Window Sill Height Levels

At seven window sill height levels: −0.9 m, −0.6 m, −0.3 m, 0 m, 0.3 m, 0.6 m, 0.9 m (Figure 19), CO concentrations in all areas except the fire pit remained essentially zero within 0–100 s, then rose rapidly thereafter. As the window sill height shifted from the center to the left, the indoor air in the bedroom, central room, fire pit area, secondary bedroom, and kitchen showed no significant impact from the window sill height, with no noticeable decrease in CO concentrations at the monitoring points. Conversely, CO concentrations at the fire pit monitoring point showed a clear decreasing trend as the window’s horizontal position shifted to the right. However, the reduction was similar across operating conditions ranging from 0.3 to 0.9 m. The optimal operating condition for CO concentration in the fire pit area was 0.9 m, with an average concentration of 22.49 ppm and a maximum concentration of 94.8 ppm.

As the window sill shifts horizontally from the central position toward the left, the CO concentrations at all monitoring points show an overall increasing trend. The condition at −0.9 m is particularly significant: the CO concentration at the fire pit monitoring point increases sharply by 87.31%, while the concentration at the central room monitoring point decreases by 53.78%; changes in the other areas are relatively moderate.

When the window sill shifts from the central position toward the right, the CO concentrations at all monitoring points generally decrease. Overall, changes in the window horizontal position have a limited impact on pollutant concentrations in the different indoor areas. When the window sill is shifted 0.9 m to the left, the indoor pollution level in the fire pit area is the worst, while the central room shows the lowest pollutant concentration, with little difference observed in the other areas (Figure 20).

Horizontal Window Dimensions

Under different window horizontal size conditions, the temporal variations of indoor CO concentrations in each area show that, as the window horizontal size increases, indoor CO concentrations exhibit an overall decreasing trend (Figure 21). After 100 s of the use of fire pit, the CO concentrations at all monitoring points begin to rise. When the window size ranges from 0.3 to 1.8 m, the reduction in CO concentrations is most pronounced in all areas. Under the 1.8 m condition, the average CO concentrations in the bedroom, central room, fire pit area, secondary bedroom, and kitchen are 13.28 ppm, 9.15 ppm, 15.21 ppm, 20.17 ppm, and 21.20 ppm, respectively.

When the window size increases to the range of 2.1 to 3.6 m, the decreasing trend of CO concentrations over time at each monitoring point becomes less pronounced. This indicates that appropriately increasing the window horizontal size can reduce the residence time of air pollutants generated during the use of fire pit indoors, thereby improving indoor air quality.

When the window horizontal size ranges from 0.3 to 3.6 m, the CO concentrations in all indoor areas show an overall decreasing trend. However, when the window size increases beyond 2.7 m, the magnitude of the reduction in CO concentrations at the monitoring points in each indoor area no longer increases (Figure 22). The bedroom and fire pit areas exhibit similar overall trends in response to changes in window horizontal size, with reductions of 54.45% and 55.80% observed under the 0.9 m and 3.0 m conditions, respectively. The decreasing trends in CO concentrations at the monitoring points in the central room, secondary bedroom, and kitchen are similar to those observed in the bedroom and fire pit areas.

Window Vertical Dimension

Under different window vertical size conditions, the indoor CO concentrations in all areas show a decreasing trend over time. During the first 0–100 s, the CO concentration remains close to zero; after 100 s, as the fire pit continues to be used, the concentration begins to increase (Figure 23). When the window vertical size increases from 0.3 m to 1.2 m, the CO concentrations in all areas decrease progressively, with a pronounced effect. As the size further increases to 1.5–2.4 m, the concentrations continue to decrease; however, the magnitude of the reduction is not significant.

According to the simulation results, under eight operating conditions with window vertical sizes ranging from 0.3 to 2.4 m, the indoor CO concentrations in all areas show an overall decreasing trend (Figure 24). The bedroom, central room, fire pit area, and kitchen exhibit similar variation patterns. Under the conditions of 0.3–1.5 m, the reductions are most pronounced; as the window size continues to increase, the magnitude of the decrease in CO concentration at the monitoring points becomes less evident. Within the range of 0.9–1.5 m, the use of fire pit has the greatest impact on the secondary bedroom area. When the window size increases beyond this range, the CO concentration in the secondary bedroom continues to decrease, but the reduction is relatively small.

Summary

During the indoor use of fire pit, the effects of window size and position on CO concentrations in different functional areas under varying operating conditions are analyzed, as shown in Figure 25. As the window sill vertical position increases, the overall trend of CO concentrations in all indoor areas is a decrease; however, when the height increases beyond the range of 1.5–1.8 m, the changes become less pronounced. When the window sill shifts horizontally to the left or right, the impact on most functional areas is limited, except for the fire pit area. This is related to the relative position between the fire pit and the window sill. Overall, the window sill horizontal position has a limited effect on pollutant concentrations in indoor areas.

Changes in window horizontal size have a consistent effect on pollutant concentrations across all functional areas: as the size increases, the concentrations decrease significantly. However, when the window size exceeds 2.1–2.4 m, the magnitude of the reduction diminishes and the trend becomes more gradual. The influence of window vertical size on pollutant concentrations in all indoor areas is similar to that of window horizontal size. Larger window sizes correspond to lower indoor concentrations; likewise, when the window vertical size increases to 1.5–1.8 m, further increases result in smaller reductions in indoor pollutant concentrations.

As the primary pathway for indoor pollutants to be discharged outdoors, windows not only influence the emission rate of indoor pollutants through their size and position, but also affect the facade characteristics of dwellings. Preliminary field investigations indicate that, in earthen dwellings in Xiangxi, the average window width is 975 mm and the average height is 1042 mm. For a single window, the window area ranges from 0.75 m² to 3.6 m², with an average value of 1.1 m². At the scale of a single dwelling, the total window area ranges from 1.1 m² to 14.2 m², with an average of 3.55 m². Overall, window sizes are generally small, which is not only unfavorable for indoor daylighting but also limits the rate at which indoor pollutants are discharged outdoors.

With respect to pollutant dispersion to the outside, the window sill horizontal position has little influence on pollutant concentrations; therefore, the selection of the horizontal position can be determined primarily based on facade design considerations. In terms of window sill vertical position, the commonly observed sill height in earthen dwellings in Xiangxi is approximately 1.2 m, which falls within a reasonable range with respect to its impact on pollutant concentrations in different indoor functional areas. Regarding window horizontal and vertical dimensions, it is advisable to moderately increase the sizes within feasible limits. The recommended horizontal size is 1.5–2.1 m, and the recommended vertical size is 1.5–2.1 m.

3.2.2. Plan Layout

No Partition Walls

Figure S1 shows smoke dispersion in various functional zones within an interior space without partition walls. Figure S2 illustrates the dispersion of smoke particles in the various functional zones and at a height of 0.75 m. The smoke particle dispersion across functional zones and at the 0.75 m height plane is shown in Figure 26. The smoke particle dispersion patterns across functional zones indicate that at 25 s, particles are confined to perimeter walls of the central room and master bedroom. By 65 s, particles have spread to walls in the central room, kitchen, and secondary bedroom. At 150 s, dispersion extends throughout the entire dwelling.

Figure 27 shows the temporal variation of CO concentrations in functional zones during indoor fire use under the no-partition condition. From 0 to 100 s, smoke concentrations in all rooms remained near zero, representing the initial phase of the use of fire pit. As combustion progressed, the curve rose rapidly after 100 s, with the fire pit exhibiting the most significant increase and trend. Concentration peaked at 73.47 ppm at 200 s, then stabilized with fluctuations for the remainder of the period. The monitoring points in the master bedroom, secondary bedroom, and kitchen exhibit similar temporal trends. Compared to the fire pit, their concentrations peaked at approximately 46 ppm around 300 s, fluctuating between 300 and 400 s. The living room curve showed the slowest change, with the smallest trend and amplitude, reaching a maximum of about 26 ppm at 380 s.

The smoke concentration distribution across monitoring points under open-plan conditions is shown in Figure 28. The most prevalent concentration at each monitoring point was close to zero. Meanwhile, concentrations between 27 and 54 ppm were relatively evenly distributed around the fire pit. The most common concentration in the master bedroom was approximately 22 ppm, with concentrations gradually decreasing on either side. In the central room, fewer concentration values were recorded as concentrations increased. The secondary bedroom and master bedroom showed similar distribution patterns, while the kitchen and fire pit exhibited comparable distributions. Furthermore, the fire pit area exhibited the most severe pollution, with a maximum concentration of 72.90 ppm—roughly double the maximum concentration in the central room (35.40 ppm). Its average concentration was also the highest at 24.17 ppm, approximately 3.5 times that of the central room. The master bedroom had the second-highest pollutant concentration, while the guest bedroom and kitchen were comparable, with average values of 17.34 ppm, 16.28 ppm, and 18.69 ppm respectively.

With Partition Walls

Figure S3 shows the diffusion of CO concentrations in various functional zones under conditions where partition walls are present indoors. Figure 29 illustrates smoke particle dispersion across functional zones and at the 0.75 m height plane under conditions with interior partition walls. Between 0 and 25 s, smoke particles spread from the fire pit to surrounding walls; between 25 and 50 s, they permeated the entire fire pit area but did not extend to other rooms; Between 65 and 95 s, particles spread outdoors, into the central room, and the master bedroom through doors and windows, with the highest particle concentrations near walls in these areas. By 200 s, concentrations peaked in the central room and master bedroom, covering the entire floor plan. Only minimal smoke remained in the kitchen, and no particle dispersion occurred in the secondary bedroom. Partition walls significantly suppressed the spread of fire pit smoke to other rooms, particularly in the kitchen and secondary bedroom.

Figure 30 illustrates the temporal evolution of CO concentrations across functional zones during indoor fire use with partition walls. The fire pit and master bedroom exhibited the most pronounced curve changes: the fire pit curve gradually rose after 50 s, peaking at approximately 95.87 ppm around 375 s before fluctuating thereafter. The concentration in the master bedroom begins to increase only after 100 s, rising continuously between 100 and 400 s to reach a peak of 105.81 ppm. The curves for the central room, secondary bedroom, and kitchen remain largely flat throughout the simulation period, showing no significant increase, with maximum values below 18 ppm. The presence of partition walls significantly restricts the spread of air pollutants generated during the use of fire pit to other rooms in the interior.

The distribution of smoke concentrations at monitoring points with partition walls is shown in Figure 31, with the fire pit pollutant concentration gradually increasing at 80 ppm and then decreasing between 80 and 160 ppm. The concentration in the central room gradually decreased as the overall concentration increased. The main bedroom showed relatively uniform concentration distribution, indicating it was most significantly affected by fire pit pollutants. Concentrations in the kitchen and secondary bedroom remained essentially at 0. The fire pit exhibits the highest average concentration (56.16 ppm), closely followed by the master bedroom. Concentrations in the central room, kitchen, and secondary bedroom all remain below 3 ppm.

Figure 32 compares smoke concentrations at monitoring points with and without partition walls. With partition walls, the average fire pit pollutant concentration was 2.33 times higher than without walls, while the master bedroom’s average was 3.05 times higher. Partition walls reduce the impact of fire pit-generated pollutants on the kitchen and secondary bedroom but cause pollutants to accumulate in the fire pit and bedroom areas. Without interior partitions, pollutants generated by the fire pit diffuse outward, resulting in increased pollution in the kitchen, central room, and secondary bedroom. However, this setup prevents the concentration of pollutants solely in the fire pit area. Without altering ventilation factors like door and window openings, adding interior partition walls alone would make the fire pit the most polluted area indoors. This would hinder residents’ winter activities near the fire pit, such as heating, cooking, and social gatherings.

3.2.3. Passive Devices: Accelerated Smoke Evacuation

Smoke Evacuation in Non-Partitioned Structures

The diffusion of CO concentrations in various functional areas of residential units without partition walls under conditions where exhaust ventilation equipment is in operation is shown in Figure S4. Figure 33 illustrates smoke particle dispersion across functional zones in non-partitioned dwellings equipped with smoke evacuation devices. Results indicate that within 0–50 s, no smoke particles spread from the fire pit to other areas. At 100 s, only a small number of smoke particles appeared in the fire pit area. By 150 s, smoke particles had spread from the fire pit to the entire master bedroom area and parts of the central room near the walls, with relatively low particle concentrations. Between 200 and 300 s, smoke particles gradually spread to the central room, kitchen, and secondary bedroom areas. After 300 s, particles dispersed throughout the entire interior. The smoke particle concentrations in the secondary bedroom, central room, and kitchen areas remained moderate, with portions of the floor still visible.

Figure 34 illustrates the temporal variation of smoke concentration at monitoring points within partitionless dwellings equipped with exhaust ventilation. The fire pit monitoring point exhibited the most pronounced temporal trend, showing rapid fluctuations and gradual increases between 130 and 380 s, peaking at approximately 520.73 ppm. The curve for the master bedroom also began increasing around 130 s, though with lower fluctuation amplitude than the fire pit. The curves for the living room, kitchen, and secondary bedroom exhibited similar fluctuation patterns: all began a slow increase around 220 s, reached their maximum values by 300 s, and maintained stable trends thereafter with no significant further concentration growth.

Figure 35 illustrates smoke concentration comparisons across monitoring points in partition-free dwellings under conditions with and without smoke extraction equipment. Following installation of passive smoke collectors, air pollution issues caused by indoor hearth fires showed significant improvement, with both maximum and average concentrations at all monitoring points substantially reduced. Compared to uninstalled conditions, the installation of passive smoke collectors reduced concentrations in the fire pit, bedroom, central room, kitchen, and secondary bedroom by 78.38%, 77.75%, 96.18%, 92.35%, and 93.36%, respectively.

Partitioned Walls—Equipment Exhaust

Figure 36 illustrates CO concentration diffusion patterns across functional zones in partitioned dwellings under smoke extraction equipment operation. Between 0 and 50 s, smoke remained confined within the passive collector ductwork. After 100 s, minor diffusion occurred above the fire pit. From 100 to 150 s, substantial smoke volumes were vented outdoors via ducts, while smoke concentration above the fire pit gradually increased to low levels, appearing light green. At 200 s, smoke spreads to the master bedroom and the central room. By 250 s, the fire pit smoke turns orange-red and persists until the end, while the master bedroom color shifts from light green to orange-yellow. Particle dispersion results show: at 0 s, smoke overflowed along the pipe to the fire pit near the wall of the master bedroom; at 150 s, smoke filled the fire pit area and began spreading toward the master bedroom; at 200 s, smoke particles were present but sparse throughout the master bedroom; after 250 s, smoke particle distribution stabilized at the fire pit, while particle concentrations in the bedroom and central room increased and began diffusing outdoors. The diffusion of CO concentrations in various functional areas of residential units separated by partition walls under conditions where exhaust ventilation equipment is in operation is shown in Figure S5.

Figure 37 illustrates the temporal variation in smoke concentration at various monitoring points within partitioned residential structures equipped with exhaust systems. The fire pit exhibits the most pronounced temporal concentration changes, with levels gradually increasing around 120 s and peaking at approximately 537.45 ppm around 295 s, followed by stable fluctuations thereafter. Next was the concentration change in the master bedroom, which gradually increased at 200 s and showed a steady growth trend between 200 and 400 s. The curves for the hall, kitchen, and bedroom monitoring points were close to the X-axis, remaining near zero throughout the simulation period. Installing smoke exhaust equipment in dwellings with partition walls can significantly mitigate the pollutant impact of the use of fire pit on areas outside the master bedroom.

Figure 38 illustrates the comparison of smoke concentration at various monitoring points in residential dwellings with interior partition walls, both with and without smoke extraction equipment. For dwellings with partition walls, the existing walls partially block smoke diffusion from the fire pit into these spaces. Consequently, installing passive smoke collectors resulted in only marginal improvements in concentration levels in the central room, kitchen, and secondary bedroom. However, concentrations in the fire pit and master bedroom areas decreased after installation, with average reductions of 69.15% and 83.69%, respectively.

Figure 39 illustrates smoke concentration comparisons at various measurement points in dwellings with and without partition walls under conditions with indoor smoke exhaust equipment. The presence of partition walls significantly blocked the spread of smoke generated by the fire pit to other indoor areas. Consequently, installing a passive smoke collector in the fire pit area resulted in higher concentrations in that zone compared to dwellings without exhaust equipment. Additionally, since the main bedroom connects to the fire pit area through an opening, smoke from the fire pit spreads into the main bedroom through this opening, resulting in higher concentrations there compared to the absence of a partition wall. Furthermore, the partition wall prevents smoke from spreading to the central room, kitchen, and secondary bedroom areas, leading to lower concentrations in these spaces compared to the absence of a partition wall. Under the indoor smoke exhaust system scenario, the average smoke concentrations in the fire pit and master bedroom of the dwelling without partition walls decreased by 69.84% and 55.24%, respectively, compared to the dwelling with partition walls.

4. Passive Strategies for Improving Air Quality

4.1. Impact of Window Parameters on Indoor Air Quality

Section 3.2.1 examines the impact of alterations to residential facade forms on indoor air quality in primary living areas, covering four aspects: window vertical position, window sill horizontal position, window horizontal dimensions, and window vertical dimensions. ① Regarding window vertical position: Satisfaction peaked at 0.6–1.5 m sill height, exceeding 50%. Beyond this range, satisfaction significantly declined below 40% between 1.5 and 2.1 m. Satisfaction showed a significant correlation with sill height, with 0.6–1.5 m being the optimal range. ② Regarding horizontal window sill position: When centered toward the right, light uniformity significantly outperforms the left side. Within the range of −1.5 to −0.6 m, closer horizontal positioning to the center improves indoor light uniformity. However, within 0.5 to 1.8 m, uniformity is less affected by horizontal position. with positions shifted up to 0.6 m to either side considered ideal. ③ Horizontal window dimensions: Indoor light uniformity shows a significant increasing trend with horizontal dimensions between 0.3 and 2.1 m. Beyond 2.1 m, uniformity first decreases then increases, reaching its peak at 3.6 m. ④ Regarding vertical window dimensions, indoor illumination uniformity increases with vertical height, reaching a peak at 1.8 m before gradually declining. Considering indoor illuminance, satisfaction, and uniformity comprehensively, a minimum vertical height of 1200 mm ensures favorable daylighting conditions in residential interiors.

4.2. Impact of Interior Floor Plans on Indoor Air Quality

Section 3.2.2 discussed how residential floor plans affect smoke compartmentalization, examining scenarios with and without interior partition walls. Without enlarging door or window openings, the presence of partition walls resulted in an average fire pit pollutant concentration 2.33 times higher than in unpartitioned spaces. While the master bedroom’s average pollutant concentration was 3.05 times higher than in layouts without partitions. However, partitions effectively reduced the impact of fire pit-generated pollutants on the central room, kitchen, and secondary bedroom. When modifying layouts, optimizing smoke exhaust pathways is also recommended to lower pollutant levels at the fore pit and in the master bedroom.

To address the issue of pollutant accumulation in the master bedroom under partitioned wall conditions, the following measures can be implemented from the perspective of passive building design: First, install openable windows on the exterior walls of the master bedroom to enhance natural ventilation and indoor-outdoor air exchange, thereby reducing the residence time of pollutants indoors; Second, install vents or air shafts between the master bedroom and the hearth to establish a controlled airflow path, thereby reducing the uncontrolled penetration and accumulation of pollutants from the hearth into the master bedroom; third, integrate a passive smoke collector to enhance localized smoke capture and upward exhaust capacity in the hearth area, thereby reducing the flux of pollutants entering the master bedroom.

4.3. Impact of Passive Smoke Collectors on Indoor Air Quality

Section 3.2.3 discussed the smoke dispersion effectiveness of devices installed in residential interiors. After installing passive smoke collectors in an existing dwelling, smoke levels in the fire pit, master bedroom, central room, kitchen, and secondary bedroom decreased by 78.38%, 77.75%, 96.18%, 92.35%, and 93.36%, respectively, compared to uninstalled areas. In the dwelling without partition walls, the average smoke levels in the fire pit and master bedroom decreased by 69.84% and 55.24%, respectively, compared to dwellings with partition walls when equipped with smoke extraction devices.

5. Discussion

In recent years, with the advancement of rural revitalization and the preservation of traditional settlements in ethnic regions, the earthen dwellings of Western Hunan—a traditional architectural type with distinct regional and cultural characteristics—continue to be extensively used by Tujia and Miao residents. Most of these dwellings are built in mountainous terrain, featuring earthen walls, wooden beam structures, and interior spaces organized around a fire pit. Due to their natural building materials and ventilation designs reliant on natural conditions, traditional earthen dwellings offer certain advantages in thermal comfort and ecological adaptation. However, under modern living conditions, indoor air quality issues have become increasingly prominent. Field research indicates that 85.5% of surveyed residents are middle-aged or elderly, with daily activities predominantly occurring indoors. Furthermore, 93.5% of residents rely on wood as fuel for cooking, heating, and water boiling in kitchens. The combustion of wood releases substantial particulate matter and carbon dioxide, which accumulate within indoor spaces, significantly increasing exposure risks. Prolonged exposure to high-concentration pollutants readily impacts the respiratory and cardiovascular health of vulnerable populations like the elderly and children. This study examines traditional earthen dwellings in Xiangxi, employing field surveys, objective monitoring, and numerical simulation to systematically analyze the current state of indoor air quality and its influencing factors. It proposes three passive strategies to enhance indoor air quality in these dwellings. Testing results indicate widespread indoor air pollution in traditional earthen dwellings across Xiangxi, particularly during winter fire pit combustion periods. In the fire pit area of Guniu Village, average PM_2.5 and PM₁₀ concentrations reached 755.36 μg/m³ and 804.03 μg/m³, respectively. While the average concentrations in the fire-heating areas of Suoduo Village reached 740.55 μg/m³ and 736.15 μg/m³. These pollutant levels exceeded the national indoor air quality standards. Although formaldehyde concentrations in Guniou and Suoduo villages complied with national standards, residents’ prolonged exposure to high concentrations of particulate and gaseous pollutants poses significant health risks.

To enhance indoor air quality in traditional earthen dwellings of Western Hunan, this study proposes three passive improvement strategies and validates their effectiveness through FDS numerical simulation. First, in optimizing facade design, smoke exhaust efficiency was improved by adjusting window dimensions and height. Optimal indoor air uniformity was achieved with sill heights between 0.6 and 1.5 m, horizontal sill positions at 1.5 to −0.6 m, and horizontal window dimensions of 2.1 m. Vertical window heights exceeding 1.2 m provided favorable natural lighting conditions. Second, regarding residential spatial layout, installing interior partition walls increased average pollutant concentrations in the fire pit and master bedroom by 2.33 times and 3.05 times, respectively, compared to configurations without partitions. Finally, for passive smoke exhaust devices, installing passive smoke collectors above the fire pit significantly improved indoor air quality.

This study provides scientific evidence and theoretical support for improving indoor air quality in traditional dwellings of Western Hunan. It establishes an air quality monitoring and simulation system tailored for earthen architecture, reveals the interactive mechanism between the fire pit combustion behavior and building morphology, and proposes a low-cost, electricity-independent retrofitting approach based on passive smoke extraction and ventilation. While respecting traditional architectural aesthetics, it achieves health improvements, embodying the synergy between cultural continuity and environmental well-being. This provides actionable technical references for traditional village conservation, rural revitalization, and habitat enhancement in ethnic regions. However, the study has certain limitations: limited regional representativeness of monitoring samples; numerical simulations that did not fully account for dynamic factors such as seasonal wind direction changes and resident usage behaviors; lack of long-term operational validation for passive devices; and absence of comprehensive evaluation of other health indicators like energy efficiency and thermal comfort. Future research should conduct dynamic monitoring of multi-source pollution across multiple time periods under year-round climatic conditions. By integrating field measurements with simulation optimization, a comprehensive health evaluation system tailored for traditional dwellings in Western Hunan can be established, thereby providing more comprehensive scientific basis for the sustainable renewal of traditional architecture.

6. Conclusions

This study focused on traditional earthen dwellings in the Xiangxi region of Hunan Province. By combining field surveys, indoor air quality monitoring, and FDS numerical simulation methods, the study investigated the current state of indoor air pollution, pollutant dispersion patterns, and passive improvement strategies in these dwellings during winter when fire pits are in use. The main conclusions are as follows:

• Indoor air pollution in traditional rammed-earth dwellings in Western Hunan is a significant issue. During the winter fire pit usage period, PM2.5 and PM10 concentrations significantly exceeded the limits set by the “Indoor Air Quality Standard” (GB/T 18883-2002), while HCHO concentrations remained generally low. This indicates that particulate matter generated by wood combustion is the primary source of indoor air pollution.
• According to software simulation results, after smoke accumulates at high concentrations in the hearth area, it diffuses along indoor airflow toward the master bedroom and the main living room. Partition walls can, to some extent, block the spread of pollutants toward the kitchen and the secondary bedroom; however, they simultaneously enhance the retention of pollutants in the hearth and master bedroom areas. The average pollutant concentrations in the hearth and master bedroom were 2.33 times and 3.05 times higher, respectively, compared to conditions without partition walls, indicating that spatial partitioning has a dual effect on pollutant diffusion.
• Reasonably optimizing the height, location, and dimensions of windows helps enhance indoor air circulation and smoke exhaust capacity while improving the indoor lighting environment. The study indicates that appropriately increasing ventilation openings and optimizing airflow organization can effectively alleviate the problem of pollutant accumulation inside traditional dwellings.
• Installing a passive smoke collector above the hearth significantly reduces indoor pollutant concentrations and minimizes the spread of pollutants to adjacent spaces. The results indicate that through optimized passive ventilation and smoke extraction strategies, the healthiness of the indoor environment in traditional dwellings can be improved while preserving the architectural characteristics and lifestyle of these structures.

This study established air quality monitoring and simulation analysis methods applicable to traditional earthen dwellings in Western Hunan, providing a theoretical basis and technical reference for low-intervention health-oriented renovations of traditional dwellings in ethnic minority regions. The research indicates that, without relying on mechanical equipment or high-energy-consumption systems, optimizing building ventilation organization and smoke exhaust methods can effectively reduce residents’ risk of pollution exposure, holding practical significance for the preservation of traditional villages and the improvement of the human living environment.

This study has certain limitations. It has not fully considered the impact of different age groups, residential behaviors, and seasonal variations on pollution exposure. Furthermore, the passive improvement strategies proposed in this paper have primarily been validated through numerical simulations and lack long-term practical engineering applications and on-site operational testing. Future research could further integrate multi-seasonal dynamic monitoring, resident behavioral characteristics, and actual renovation case studies to conduct more in-depth research on strategies for optimizing the indoor air environment in traditional dwellings.