An Overview: PM2.5 Concentration Levels in Urban Residential Buildings during the Past Two Decades

Received: May 1, 2022
Revised: July 22, 2022
Accepted: August 3, 2022

 Copyright The Author's institutions. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited. 

Cite this article:

Liu, Y., Dong, J., Ma, H., Jiang, Y., Zheng, W., Luo, X. (2022). An Overview: PM_2.5 Concentration Levels in Urban Residential Buildings during the Past Two Decades. Aerosol Air Qual. Res. 22, 220174. https://doi.org/10.4209/aaqr.220174

HIGHLIGHTS

• Household PM_2.5 concentrations across different countries were collected.
• Influence factors of indoor PM_2.5 concentrations were explicated.
• Mean daily indoor PM_2.5 concentrations ranged from 6.6 µg m^–3 to 493.0 µg m^–3.
• Indoor PM_2.5 concentrations in developing countries were much higher.

Keywords: PM2.5, Concentration, Residential building, Indoor activity, Ventilation, Ambient environment

1 INTRODUCTION

Urban residents spend most of their time in indoor environments. Investigations of people’s activity patterns have indicated that more than half of the time in a day is spent in residential buildings (Kornartit et al., 2010; de Kluizenaar et al., 2017). The National Human Activity Pattern Survey of the United States reported that on average, people spend 16.6 h per day in average in residential buildings (Klepeis et al., 2001). Baxter et al. (2013) observed that people spend 16.98 to 18.05 h per day in residential buildings in New Jersey, the United States. The Canadian Human Activity Pattern Survey indicated that adult Canadians spend 15.83 to 16.0 h per day in homes (Leech et al., 2002; Matz et al., 2014, 2015). According to one exposure assessment study, children spend 16.1 to 17.35 h per day at home in Windsor, Ontario (Van Ryswyk et al., 2014). Moreover, reports indicate that on average, people spend 13.95 h per day at home in seven European cities (Schweizer et al., 2007). In Germany, Belgium and Denmark, people spend approximately 15.7 (Brasche and Bischof, 2005), 15.84 (Dons et al., 2011) and 17.3 h (Bekö et al., 2015) per day at home, respectively. These figures clearly indicate that people spend considerable time in residential buildings. Therefore, special attention should be paid to residential indoor environments.

Air pollution is a key factor influencing residential environments. Among all forms of air pollutants, particle matter (PM) has received the most extensive research attention because of its adverse effects on health (Stranger et al., 2007; Han et al., 2010; Wu et al., 2018; Zhu et al., 2018). In particular, fine particle matter (PM_2.5, aerodynamic diameter less than 2.5 µm) causes severe morbidity and mortality because it is easily absorbed by the lungs and distributed throughout the human body (Hofmann, 2011; Achilleos et al., 2017; Li et al., 2017). Toxicological and epidemiological studies have indicated that PM_2.5 concentrations in various environments are strongly associated with several adverse health outcomes such as respiratory and cardiovascular diseases (Wallace et al., 2003; Anderson et al., 2012; Wyzga and Rohr, 2015; Sun et al., 2019). Regarding urban outdoor environments, Cakmak et al. (2018) analysed the association between exposure to ambient PM_2.5 and disease-related mortality across Canada; their research indicated that an increase of 10 µg m^–3 in long-term PM_2.5 exposure resulted in a hazard ratio of 1.26 for lung cancer mortality. You et al. (2017) evaluated PM exposure and element deposition distributions in the human respiratory system by using data collected alongside a highway in Singapore. Perrone et al. (2013) assessed the chemical composition of PM by using data collected from Italian urban sites. Furthermore, Zwozdziak et al. (2017) estimated the inhaled dose of ambient PM in an urban area of southern Poland, and they reported the PM deposition fractions. Martuzevicius et al. (2008) estimated traffic-induced PM_2.5 concentrations near major highways in Cincinnati, the United States. Chen et al. (2017) determined the chemical components of regional PM_2.5 and the corresponding source contributors in Guangzhou, China. Regarding urban indoor environments, Bai et al. (2020) assessed the health risks of polycyclic aromatic hydrocarbons (PAHs) attached in PM_2.5 in an office environment. Chen et al. (2018) also investigated the associations between PM_2.5 and asthmatic or allergic diseases in Chinese preschool children. In South Asia, exposure to indoor PM emissions from anthropogenic activities engenders considerable health risks (Junaid et al., 2018). Zhao et al. (2019) collected samples of PAHs from cooking emissions for health risk assessment in residential settings. Although numerous studies have reported the effects of outdoor PM, indoor particles have only recently started attracting research attention (Han et al., 2015, 2016; Butler and Madhavan, 2017; Tang and Wang, 2018; Huang et al., 2018). Therefore, addressing the problem of indoor PM_2.5 is crucial.

Building envelopes separate residents from the outdoor environment, leading to an accumulation of indoor particles. Previous reviews have demonstrated that PM_2.5 pervades in indoor environments. Diaz Lozano Patino and Siegel (2018) conducted a review of indoor environment air quality in European and American buildings, and observed that smoking led to high concentrations of PM_2.5. Morawska et al. (2017) reviewed the exposure pathways of airborne particles of outdoor origin in home, school, office and aged care facility environments. Other scholars have also conducted reviews of air pollutants in office environments (Wolkoff, 2013; Al Horr et al., 2016; Nezis et al., 2019). However, these reviews have neither summarized PM_2.5 concentrations nor identified the influential factors in urban residences. Additionally, people spend considerable time in residential buildings, especially in the living room. Hence, a thorough investigation of PM_2.5 concentrations in living rooms is necessary for effective indoor air quality control. Accordingly, we present a review of PM_2.5 concentrations in urban residential buildings, particularly studies predominantly focusing on the living room. Detailed analyses of the factors influencing PM_2.5 concentrations are also presented.

 
2 METHODS

 
2.1 Search Strategy

In this review, we included studies on PM_2.5 concentrations in the living rooms of urban home environments over the past two decades. The following search terms were used: “indoor environment” OR “indoor air quality”, “indoor PM_2.5” OR “indoor fine particulate matter” OR “indoor particles”, and “urban dwellings” OR “urban residential buildings” OR “urban homes”. The inclusion criteria were as follows: 1) being searchable on the Web of Science Core Collection, 2) being published up to 2020, 3) being written in English, and 4) reporting on PM_2.5 concentrations in the living rooms of urban homes. Studies reporting on specific health outcomes, source apportionment, or the chemical species or composition of particles were excluded.

 
2.2 Literature Collection

Data from the selected studies were organized into tables and figures presenting PM_2.5 concentrations. Fig. 1 illustrates the number of studies selected in this review. In the graph showing the number of publications each year, an increase in the volume of research on this topic can be observed.

Fig. 1. Reference amount in this review.

 
3 RESULTS AND DISCUSSION

 
3.1 Indoor PM_2.5 Measurements

We found that indoor PM_2.5 monitoring is predominantly performed with mobile sampling instruments. Professional devices and low cost sensors are widely used in indoor environment measurements. Professional and accurate instruments are available for real-time monitoring. Particle number concentrations are measured using optical particle counter. Particle size distribution can be monitored by scanning mobility particle sizers. Particle mass concentrations are monitored by tapered element oscillating microbalance, continuous aerosol mass monitor, nephelometer and nanoparticle surface monitor. Moreover, due to the advantage of small dimension and low power demand, use of low cost sensors in indoor PM_2.5 monitoring is continuously increasing. The accuracy of low cost sensors can be improved by proper calibration techniques (Gozzi et al., 2016).

 
3.2 PM_2.5 Concentrations

We collected PM_2.5 concentrations from published articles to provide a review of PM_2.5 concentrations in households. As listed in Table S1, most studies reporting household PM_2.5 concentrations were conducted in Asia and in Europe, and some studies were conducted in North America and in Africa. The earliest studies that reported PM_2.5 measurements in living environments were conducted in North America and in Europe. Later studies were conducted in Asia, and few were conducted in Africa. Factors influencing PM_2.5 concentrations were as follows: 1) continent and country, 2) indoor activities, 3) ventilation type and air cleaner (AC) use, 4) building type and performance, 5) and ambient environment and season.

 
3.2.1 Mean PM_2.5 concentration

We reviewed the mean daily household PM_2.5 concentrations measured by the included studies in different regions. Fig. 2 illustrates box plots of the mean daily PM_2.5 concentrations worldwide. In Europe, the mean daily PM_2.5 concentrations ranged from 6.0 µg m^–3 in Colchester, the United Kingdom (Nasir and Colbeck, 2013), to 46.0 µg m^–3 in Rome, Italy (Romagnoli et al., 2016). 

Fig. 2. Box plot of mean daily PM_2.5 concentration worldwide. 

In North America, indoor PM_2.5 concentrations varied from 6.5 µg m^–3 in Edmonton, Canada (Kearney et al., 2014) to 45.4 µg m^–3 in California, the United States (Sawant et al., 2004). In Asia, indoor PM_2.5 concentrations ranged from 11.7 µg m^–3 in Harbin, China (Liu et al., 2020b) to 207.3 µg m^–3 in Wuhan, China (Yin et al., 2017). In Africa, indoor PM_2.5 concentrations ranged from 45.0 µg m^–3 in Alexandria, Egypt (Abdel-Salam, 2015) to 74.0 µg m^–3 in Accra, Ghana (Zhou et al., 2014). Typically, the mean daily PM_2.5 concentrations measured in Asia were higher than those measured in Europe and North America. Similar concentrations were observed among European and North American countries. The mean daily PM_2.5 concentrations measured in Europe, North America, Asia and Africa were 18.7, 17.3, 68.6 and 60.1 µg m^–3, respectively.

We also reviewed the mean PM_2.5 concentrations measured using different monitoring intervals, namely 1-, 3-, 5-, 6-, 10-, 15- and 30-min intervals. The mean PM_2.5 concentrations measured using 30-min intervals ranged from 10.0 µg m^–3 in Bologna, Italy (Zauli Sajani et al., 2015) to 64.9 µg m^–3 in the Yangtze River Delta of China (Wang et al., 2016). The mean PM_2.5 concentrations measured using 10-min intervals were 8.7 µg m^–3 in Switzerland (Meier et al., 2015) up to 107.7 µg m^–3 along a roadside in Nablus, Pakistan (Jodeh et al., 2017). Regarding shorter monitoring intervals, the mean PM_2.5 concentrations measured using 1-min intervals were 8.4 µg m^–3 in Edinburgh and Lothian, the United Kingdom (Steinle et al., 2015); 28.6 µg m^–3 in winter in Seoul, Korea (Hwang and Lee, 2018); and 69.7 µg m^–3 along a roadside in Hong Kong, China (Cao et al., 2005). In addition, mean PM_2.5 concentrations measured using short intervals were considerably higher in some Asian countries, particularly in environments involving smokers and during heating season. Remarkably, the highest mean PM_2.5 concentration measured in 1-min sampling intervals was 572.0 µg m^–3 under conditions of severe outdoor air pollution in Tianjin, China (Zhou et al., 2016).

 
3.2.2 Maximum PM_2.5 concentration

We reviewed the maximum daily PM_2.5 concentrations measured by the included studies in different regions worldwide, with our review revealing remarkable differences in the maximum daily PM_2.5 concentrations among different sampling sites. In North America, the maximum daily PM_2.5 concentration was 74.9 µg m^–3 in Boston, the United States (Baxter et al., 2007). In Europe, the maximum daily PM_2.5 concentration was 109.9 µg m^–3 in Colchester, the United Kingdom (Nasir and Colbeck, 2013). However, the maximum daily PM_2.5 concentrations measured in Africa and Asia were considerably higher; the concentration was 218.0 µg m^–3 in Durban, South Africa (Gumede and Savage, 2017) and 368.0 µg m^–3 in Lanzhou, China (Li et al., 2016). Higher PM_2.5 concentrations were observed in some Asian and African countries under conditions of severe ambient air pollution (Zhou et al., 2016; Li et al., 2016; Gumede and Savage, 2017). This observation was likely influenced by high PM_2.5 concentrations in the outdoor environment. As displayed in Fig. 3, the maximum daily PM_2.5 concentrations were higher in Asia and Africa than in Europe and North America.

Fig. 3. Box plot of maximum daily PM_2.5 concentration worldwide.

Notably, a monitoring campaign conducted in France reported a maximum PM_2.5 concentration of 568.0 µg m^–3 (Langer et al., 2016). This high concentration was attributed to indoor smoking. In most regions, relatively high maximum PM_2.5 concentrations were observed in the vicinity of particle emission sources despite the use of short sampling intervals. For example, in Prague, Czech Republic, the maximum PM_2.5 concentration measured using a 5-min interval reached 2,282.0 µg m^–3 (Braniš and Kolomazníková, 2010). In Tianjin, China, the maximum PM_2.5 concentration measured using a 1-min interval was 1,370.0 µg m^–3 (Zhou et al., 2016); this was measured in an environment involving group smoking. This extremely high PM_2.5 concentration was primarily caused by considerable indoor activities over the short sampling period.

 
3.3 Factors Influencing PM_2.5 Concentrations

The PM_2.5 concentrations measured by the included studies are listed in Table S1. As mentioned, factors influencing PM_2.5 concentrations were indoor activities, ventilation type and AC use, household type, ambient environment, and season. The effects of these factors on PM_2.5 concentrations are discussed in the following sections.

 
3.3.1 Indoor activities

Because tobacco smoking often occurs in the living room, it is an indoor activity that considerably elevates PM_2.5 concentrations (Janssen et al., 2000; Lai et al., 2004; Minguillón et al., 2012; Canha et al., 2019). PM_2.5 concentrations measured in smoking households were compared with those measured in non-smoking ones, as illustrated in Fig. 4. In general, the mean daily PM_2.5 concentration observed in smoking households (36.7 µg m^–3) was higher than that observed in non-smoking ones (15.0 µg m^–3) by 2.5-fold. In smoking households, the daily PM_2.5 concentrations ranged from 16.0 to 109.0 µg m^–3 (Nasir and Colbeck, 2013). In Helsinki, Finland, the mean PM_2.5 concentrations in households of active smokers (31.1 µg m^–3) were higher than those in households of non-smokers (9.9 µg m^–3) by more than threefold (Koistinen et al., 2001). The mean PM_2.5 concentrations observed in some Asian countries were considerably higher than those observed in other countries. In a Chinese household, the mean PM_2.5 concentration measured within 1 min was 549.0 µg m^–3; when the household involved smoking, the maximum PM_2.5 concentration reached 1,317.0 µg m^–3 (Zhou et al., 2016). These results indicate that during this period, the maximum PM_2.5 concentration was higher than the mean PM_2.5 concentration by more than twofold. In conclusion, cigarette smoking causes a significant increase in PM_2.5 concentrations in the living room, particularly peak PM_2.5 concentrations measured using a short sampling interval.

Fig. 4. Mean daily PM_2.5 concentration in non-smoking and smoking households.

Domestic cooking is another major source of particles in residential environments. Our included studies extensively reported high concentrations of cooking-generated PM_2.5 in Europe (Abdullahi et al., 2013; Kosonen et al., 2006), North America (Olson and Burke, 2006) and Asia (Cao et al., 2017; Wang et al., 2020; Liu et al., 2020a). These studies indicated that the influence of cooking-generated particles was not limited to the kitchen but instead spread to other sections of the living environment; this is because opening kitchen and interior doors leads to PM_2.5 diffusion throughout the living environment. A study performed a field measurement of PM_2.5 concentration during cooking in an apartment in Korea and indicated that the PM_2.5 concentration in the living room was higher than that in background areas by more than 12-fold (Kim et al., 2018). In addition, a monitoring campaign conducted in a Chinese style residence reported that cooking led to a peak PM_2.5 concentration of 365.0 µg m^–3 in the living room, whereas the PM_2.5 concentration in background areas was 15.0 µg m^–3 (Liu et al., 2020b). In a Korean residence with an open kitchen, the PM_2.5 concentration in the living room could reach up to 1,000.0 µg m^–3 (Kang et al., 2019). Furthermore, Zhao and Zhao (2020) conducted PM_2.5 measurements in a household with an open kitchen design and reported that cooking in the kitchen led to PM_2.5 concentrations ranging between 282.0 µg m^–3 and 1,187.0 µg m^–3 in the living room. These findings demonstrate that cooking in a household’s kitchen elevates PM_2.5 concentrations in the living room, especially in households with open kitchens.

 
3.3.2 Ventilation type and AC use

The most common types of ventilation in residential buildings are natural/normal ventilation (NV) with or without an AC and mechanical ventilation (MV) with an air filtration unit. We reviewed PM_2.5 concentrations measured in Chinese households with these types of ventilation, as presented in Fig. 5. In Harbin, China, the mean daily and maximum daily PM_2.5 concentrations measured in households with NV in winter were 88.0 and 261.0 µg m^–3, respectively. However, the mean daily and maximum daily PM_2.5 concentrations measured in households with an AC in winter were 51.0 and 131.0 µg m^–3, respectively (Xue et al., 2020). Therefore, the use of an AC reduced the mean daily and maximum daily PM_2.5 concentrations in this region by 42.0% and 49.8%, respectively. In addition, in Beijing, China, the use of an AC reduced the mean daily PM_2.5 concentration from 87.0 to 63.0 µg m^–3 and reduced the maximum daily PM_2.5 concentration from 223.0 to 116.0 µg m^–3 (Deng et al., 2017). Therefore, the mean and maximum PM_2.5 concentrations were reduced by 27.6% and 48.0%, respectively. Moreover, studies conducting measurements in the Yangtze River Delta region by using a 30-min interval revealed that the mean and maximum PM_2.5 concentrations were 26.0 and 63.0 µg m^–3, respectively, in households using both MV and an AC. Nevertheless, in households using only NV, the mean and maximum PM_2.5 concentrations were up to 64.9 and 165.0 µg m^–3, respectively (Wang et al., 2016). Therefore, seethe use of both MV and an AC reduced the mean and maximum PM_2.5 concentrations by 60.0% and 61.8%, respectively.

Fig. 5. PM_2.5 concentration in Chinese households with natural/normal ventilation (NV), mechanical ventilation (MV) and use of AC.

 
3.3.3 Building type and performance

We reviewed the mean PM_2.5 concentrations measured in different building types and building performance levels, as displayed in Fig. 6. For different building types in European countries, single-room residences in Colchester, the United Kingdom, had the lowest mean daily PM_2.5 concentration (6.0 µg m^–3) (Nasir and Colbeck, 2013), followed by single-family houses in France (8.7 µg m^–3) (Derbez et al., 2018), multifamily apartment buildings in Finland (9.0 µg m^–3) (Du et al., 2015), and retrofitted multifamily apartment buildings in France (14.6 µg m^–3) (Derbez et al., 2014a, 2014b). Multifamily houses in France had a higher mean daily PM_2.5 concentration (32.0 µg m^–3) than did other building types (Derbez et al., 2018). These results thus demonstrate that multifamily apartment buildings had higher mean PM_2.5 concentrations than did single room residences. Notably, higher indoor PM_2.5 concentrations were reported in winter than that in summer for most regions. One possible reason is that higher ambient PM_2.5 concentrations in winter contributed to higher indoor concentrations (Jung et al., 2011).

Fig. 6. PM_2.5 concentration in different building types and performance.

We noted remarkable differences in PM_2.5 concentration between Chinese households. Specifically, measurement conducted during heating season in Harbin revealed that the mean daily PM_2.5 concentration was 51.0 µg m^–3 in conventional households and 38.0 µg m^–3 in passive households (Xue et al., 2020). A measurement campaign of PM_2.5 concentration in different building types revealed that the concentration in conventional households was higher than those observed in passive households by 1.79-folds (Wang et al., 2018). Furthermore, the mean PM_2.5 concentrations in energy-saving and passive residential buildings were lower than those in conventional households. The low concentration was predominately attributed to the good building performance.

 
3.3.4 Ambient environment and season

Ambient environmental factors that affect PM_2.5 concentrations include roadside conditions outside the household (proximity to a roadside with vehicular traffic, proximity to an urban area with no vehicular traffic, or proximity to industrial facilities) (Meng et al., 2005; Molnar et al., 2007; Lim et al., 2012; Schembari et al., 2013; Huang et al., 2015; Ji et al., 2018; Xiao et al., 2018; Zhou et al., 2018; Jeong et al., 2019; Oliveira et al., 2019; Ścibor et al., 2019), weather conditions (clear or hazy conditions), and climate zone and season (Chao and Wong, 2002; Cao et al., 2012; Garcia et al., 2016; Fang et al., 2020). Household mean PM_2.5 concentrations under different ambient conditions are illustrated in Fig. 7. In typical residences without substantial outdoor pollution, the mean daily household PM_2.5 concentration was 56.2 µg m^–3. However, in residences located along roadsides with high traffic volumes or located in proximity to industrial facilities, the mean daily PM_2.5 concentrations were 73.5 and 73.4 µg m^–3, respectively (Huang et al., 2007). These results thus indicate that the mean daily PM_2.5 concentration in residences close to vehicular traffic and industrial facilities increased by 30.6%. In Nablus, Pakistan, the mean daily PM_2.5 concentration was 84.2 µg m^–3 in households located in urban areas and 107.7 µg m^–3 in households located along roadsides (Jodeh et al., 2017). These results demonstrate that compared with the mean PM_2.5 concentration in households located in urban areas, the mean PM_2.5 concentration in households located along roadsides increased by 27.9%. A similar trend was also observed in Hong Kong, China (Cao et al., 2005) and Agra, India (Massey et al., 2012), where the mean PM_2.5 concentration was higher in households located along roadsides than in those located in urban areas with no vehicular traffic. The higher household PM_2.5 concentrations were attributed to the elevated concentrations in the ambient environment.

Fig. 7. Household mean PM_2.5 concentration under different ambient conditions.

Weather conditions also considerably influence household PM_2.5 concentrations. During days involving severe haze pollution, high indoor PM_2.5 concentrations can be explained by the severe outdoor PM_2.5 pollution. Zhou et al. (2016) conducted indoor and outdoor measurements in households with slightly open windows during periods of severe particle pollution in the ambient environment by using a sampling time of 1 min; they observed that the mean indoor and outdoor PM_2.5 concentrations were 572.0 and 723.0 µg m^–3, respectively. When windows and doors were adequately sealed, the mean indoor PM_2.5 concentration could still reach up to 246.0 µg m^–3,

with the mean outdoor PM_2.5 concentration ranging from 254.0 to 403.0 µg m^–3. In addition, they reported that under conditions of low wind speed, the mean indoor and outdoor PM_2.5 concentrations were 290.0 and 580.0 µg m^–3, respectively; however, under conditions of high wind speed, the mean indoor and outdoor PM_2.5 concentrations were 65.0 and 33.0 µg m^–3, respectively.

Concentrations varied with seasons. The mean daily PM_2.5 concentrations in different seasons in the various regions are presented in Fig. 8. In Bologna, Italy, the mean daily household PM_2.5 concentrations in spring, summer, and winter were 6.6, 8.4, and 15.1 µg m^–3, respectively, and the mean daily outdoor PM_2.5 concentrations were 10.8, 13.7, and 31 µg m^–3, respectively (Zauli Sajani et al., 2015). In Rome, Italy, the mean daily PM_2.5 concentrations in indoor and outdoor environments were 27.3 and 12.8 µg m^–3, respectively, in summer and 31.4 and 32.8 µg m^–3, respectively, in winter (Perrino et al., 2016). By contrast, higher PM_2.5 concentrations were reported in some Asian countries, particularly in winter. Specifically, in Lanzhou, China, the mean daily PM_2.5 concentrations in indoor and outdoor environments were 119.0 and 328.0 µg m^–3, respectively, in winter and 80.0 and 80.0 µg m^–3, respectively, in summer (Li et al., 2016). The remarkable increases in both indoor and outdoor PM_2.5 concentrations in winter were attributed to heating. In residences along roadsides in Agra, India, the peak mean PM_2.5 concentration in winter was 207.0 µg m^–3 in indoor environments and 212.0 µg m^–3 in outdoor environments. However, in summer, the mean PM_2.5 concentration in household was 119.0 µg m^–3 (Massey et al., 2012). These results demonstrate that in most households in Asian countries, the mean indoor PM_2.5 concentration in winter was higher than that in summer by approximately twofold. The increase in PM_2.5 concentration in winter can be attributed to indoor space heating and increased ambient concentrations. Except for the studies by Kearney et al. (2014) and Pekey et al. (2010), the other studies included in this review reported consistently higher PM_2.5 concentrations in winter than in summer in the various regions.

Fig. 8. Household mean PM_2.5 concentration in various seasons.

As illustrated in Fig. 8, the mean indoor and outdoor PM_2.5 concentrations in Shanghai, China, were 69.9 and 77.1 µg m^–3 in the cold season, respectively, 46.1 and 39.8 µg m^–3 in the transitional season, respectively, 32.3 and 31.6 µg m^–3 in the hot season, respectively. Similar household indoor and outdoor PM_2.5 concentrations were observed during different seasons in the hot summer climate zone. The mean PM_2.5 concentrations measured by Dai et al. (2018) in households in different climate zones in China are indicated by the box plot in Fig. 9. The PM_2.5 concentrations differed considerably among the seasons across the climate zones. Specifically, the mean PM_2.5 concentration in winter was considerably higher than those in the other seasons. The household PM_2.5 concentrations ranged from 75.0 µg m^–3 in the mild zone to 163.0 µg m^–3 in the cold zone in winter. By contrast, the mean PM_2.5 concentrations ranged from 32 µg m^–3 in the mild zone to 56 µg m^–3 in the cold zone (Dai et al., 2018). Notably, higher PM_2.5 concentrations were observed in the cold climate zone across the various seasons. The mean PM_2.5 concentration was 24.8 µg m^–3 in the severe cold climate zone, 43.0 µg m^–3 in the cold climate zone, 35.5 µg m^–3 in the hot-summer and cold-winter climate zone, 13.5 µg m^–3 in the mild zone and 27.0 µg m^–3 in the hot-summer and warm-winter climate zone. The highest mean PM_2.5 concentration was observed in the cold climate zone, whereas the lowest was observed in the mild climate zone.

Fig. 9. Box plot of household daily PM_2.5 concentration in various climate zones in China (Box from up to down refers to maximum, mean and minimum value).

 
4 CONCLUSIONS

We present a review of studies on PM_2.5 concentrations in urban residential buildings. We reviewed PM_2.5 concentrations that were measured using 1- to 30-min intervals in various regions worldwide. The findings indicate that PM_2.5 concentrations across the world varied considerably. The mean daily PM_2.5 concentrations in Asia and Africa were higher than those in Europe and North America by more than threefold. Similar concentrations were observed between European and North American countries. In some Asian countries, the PM_2.5 concentrations measured using intervals of several minutes were up to > 1,000 µg m^–3. In regions with considerable particle pollution, the use of different sampling intervals is likely to engender variations in the measured concentrations. For example, the use of long sampling intervals during periods of high concentration could lead to biased measurements of average concentrations. Therefore, we recommend the use of uniform sampling intervals across different monitoring campaigns to facilitate comparisons future studies.

On the basis of the findings of the included studies, we can conclude that different indoor activities, ventilation type and AC use, building type and building performance, ambient environment, and seasons can explain the large discrepancies in indoor PM_2.5 concentrations between countries and regions. The main indoor particle sources that lead to large PM_2.5 concentration variations in residential environments are smoking and cooking. The mean daily PM_2.5 concentration in smoking households was higher than that in non-smoking households by 2.5-fold. Smoking led to a significant PM_2.5 concentration increase in the living rooms within short periods. Regarding measurements conducted for Chinese households with different ventilation types, the mean PM_2.5 concentrations were much lower in households with MV and ACs than in those with NV. The use of ACs could reduce the mean daily PM_2.5 concentration and mean maximum PM_2.5 concentration by 27.6%–60.0% and by 48.0%–61.8%, respectively.

We also observed differences in PM_2.5 concentrations among different building types and building performance levels. The mean PM_2.5 concentration in multifamily apartment buildings was higher than that in single-room residences in Europe. In China, the mean PM_2.5 concentration in passive households was lower than that in conventional residential buildings. Severe outdoor particle pollution could increase indoor PM_2.5 concentrations. The mean indoor PM_2.5 concentration in winter was higher than that in summer by approximately twofold for most households in Asian and African countries. Regarding the measurements made in the different climate zones of China, nearly identical indoor and outdoor household PM_2.5 concentrations were reported for different seasons in the hot summer climate zone. The mean household PM_2.5 concentration in the cold zone was higher than that in the mild zone by more than threefold.

 
ACKNOWLEDGEMENTS

This work was funded by the National Natural Science Foundation of China (No. 51978193, 51808275 and 52068021), the Jiangxi Provincial Natural Science Foundation (No. 20202BABL204060) and the Scientific Research Project of Education Department of Jiangxi Province (No. GJJ190301). This manuscript was edited by Wallace Academic Editing.