ABSTRACT
The present study investigated indoor and outdoor concentrations of two particulate matter size fractions (PM10 and PM2.5) and CO2 in 20 urban homes ventilated naturally and located in one congested residential and commercial area in the city of Alexandria, Egypt. The results indicate that the daily mean PM2.5 concentrations measured in the ambient air, living rooms, and kitchens of all sampling sites exceeded the WHO guideline by 100%, 65%, and 95%, respectively. The daily mean outdoor and indoor PM10 levels in all sampling sites were found to exceed the WHO guideline by 100% and 80%, respectively. The indoor PM10 and PM2.5 concentrations were significantly correlated with their corresponding outdoor levels, as natural ventilation through opening doors and windows allowed direct transfer of outdoor airborne particles into the indoor air. Most of the kitchens investigated had higher indoor concentrations of PM2.5 and CO2 than in living rooms. The elevated levels of PM2.5 and CO2 in domestic kitchens were probably related to inadequate ventilation. The current study attempted to understand the sources and the various indoor and outdoor factors that affect indoor PM10, PM2.5 and CO2 concentrations. Several domestic activities, such as smoking, cooking, and cleaning, were found to constitute important sources of indoor air pollution. The indoor pollution caused by PM2.5 was also found to be more serious in the domestic kitchens than in the living rooms and the results suggest that exposure to PM2.5 is high and highlights the need for more effective control measures.
Implications: Indoor air pollution is a complex problem that involves many determinant factors. Understanding the relationships and the influence of various indoor and outdoor factors on indoor air quality is very important to prioritize control measures and mitigation action plans. There is currently a lack of research studies in Egypt to investigate determinant factors controlling indoor air quality for urban homes. The present study characterizes the indoor and outdoor concentrations of PM10, PM2.5, and CO2 in residential buildings in Alexandria city. The study also determines the indoor and outdoor factors which influence the indoor PM and CO2 concentrations as well as it evaluates the potential indoor sources in the selected homes. This research will help in the development of future indoor air quality standards for Egypt.
Introduction
Exposure to particulate matter (PM) including PM10 (particles with aerodynamic diameter <10 μm) and PM2.5 (particles with aerodynamic diameter <2.5 μm) is considered of great risk to human health in both outdoor and indoor air (Ghio, Carraway, and Madden Citation2012; Pope et al. Citation2002; Samet and Krewski Citation2007). Considerable fraction of exposure to PM occurs indoors as this is where people spend most of their times (about 90% or even more) (Klepeis et al. Citation2001; World Health Organization [WHO] Citation2010). Vulnerable populations such as the children and the elderly can spend entire days indoors (Schweizer Citation2007). Indoor particles are a mixture of particles that could originate from indoor sources, infiltrated from outdoors, and/or formed indoors through chemical reactions of gas-phase precursors. Outdoor sources considerably affect indoor PM concentrations particularly when infiltration rates of outdoor particles are high (Jones et al. Citation2000). Ventilation, either natural or mechanical, can also bring outdoor particles into the indoor environment and this can pose a great risk particularly during periods of high ambient PM concentrations. As the infiltration rates of outdoor particles are size-dependent, fine particles have higher infiltration rate values than coarse particles (Wallace Citation1996). PM2.5 represents the fine PM fraction which often contains hazardous substances and is mainly released by combustion processes such as outdoor traffic emissions and/or indoor combustion-related activities including smoking and cooking using gas stoves (Chao, Tung, and Burnett Citation1998; Jones et al. Citation2000). PM2.5 can also penetrate deeply into the respiratory tract and is significantly related to respiratory and cardiovascular diseases (Pope and Dockery Citation2006; Pope, Ezzati, and Dockery Citation2009; WHO, Citation2006). Other indoor activities including cleaning using vacuuming or sweeping can significantly increase PM10 concentrations in domestic households through re-suspension of large particles from indoor surfaces (Chao and Cheng Citation2002; Lewis et al. Citation2018).
Indoor carbon dioxide (CO2) is generally produced by combustion processes and human respiration. Therefore, occupant density and combustion-related indoor activities are important factors of indoor CO2 concentrations (Abdel-Salam Citation2015). Furthermore, ventilation efficiency is another crucial factor which largely affects indoor CO2 concentrations as it shows how the outdoor air is adequate to dilute indoor air pollutants. Increasing air tightness to reduce both energy consumption and the effect of outdoor air pollution can increase indoor CO2 concentrations (Colton et al. Citation2014; Gall et al. Citation2016). The American National Standards Institute/The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ANSI/ASHRAE) Standard 62.1 (Citation2013) recommends sufficient building ventilation rates in order to keep indoor CO2 levels less than 700 ppm above outdoor CO2 concentrations for occupant satisfaction and comfort. Poor ventilation and high occupancy combined with smoking and/or cooking are responsible for elevated indoor CO2 levels exceeding 1000 ppm (Boor et al. Citation2017; Persily and de Jonge Citation2017). On average, CO2 levels in different indoor environments including homes and schools typically range from 600 ppm to 1000 ppm (Erdmann, Steiner, and Apte Citation2002; Fisk Citation2017). Adverse health effects may occur as a result of exposure to CO2 concentrations as low as 1000 ppm and more (Satish et al. Citation2012; Zhang et al. Citation2017).
In developing countries, air quality in indoor environments has been studied much less extensively than that in the outdoor air. There exists a significant need to conduct more indoor air quality (IAQ) research in urban areas in Egypt in order to enhance the knowledge and skills in this area. The current study was carried out in Alexandria City which is considered the second largest city in Egypt and it extends about 32 km along the north Mediterranean Sea coast of the country. The city is one of the most densely populated cities in Egypt which accommodates about 5.2 million people on an area of 2,679 km2. Generally, most residential areas in the city are situated close to heavy traffic roads and therefore both outdoor and indoor air quality were largely affected by traffic emissions (Abdel-Salam Citation2013). Vehicle emissions are considered a major source of PM in urban areas (Abu-Allaban et al., Citation2007; Artíñano et al. Citation2004). Airborne particles are released by motor vehicles through pipe exhaust, road dust re-suspension, and products of abrasion processes (Gertler, Gillies, and Pierson Citation2000). In Alexandria, residential areas are usually high-rise multistory flat-type buildings surrounding heavy traffic roads. Poor dispersion of emitted vehicular exhausts may lead to high air pollution exposure with the potential health risks in such highly populated areas (WHO, Citation2005; Zhang and Batterman Citation2013). IAQ data in Egypt are very limited although IAQ has become a critical issue to public health. This prevents policymakers to have an accurate assessment of the problem and to develop national IAQ standards in Egypt. Recently, IAQ particularly at local residences has been attracting a growing attention in Egypt. Two previous studies were carried out in a number of homes located in two different residential and commercial urban areas in Alexandria during the summer season of 2009 and the spring time of 2010 according to Abdelsalam (Citation2013, Citation2015), respectively. These studies recommended more future research in this field to compare their results with other relevant future studies, to identify additional determinants of indoor PM and CO2 concentrations, and to emphasize the importance of establishing national IAQ standards. Therefore, the current study aims to characterize the indoor and outdoor concentrations of PM10, PM2.5, and CO2 at a number of naturally ventilated urban homes in the city of Alexandria. Also, it aims to determine the various indoor and outdoor factors which influence the indoor PM and CO2 levels and to evaluate the potential indoor sources in the selected domestic households. In this research, additional indoor measurements of PM and CO2 were performed in the domestic kitchens to indicate the effect of cooking on indoor PM and CO2 concentrations.
Experimental methods
The current study was conducted from end of October till end of December 2018 at 20 selected homes located in a highly populated and congested residential and commercial urban area known as Smouha (31°13′01″N, 29°56′41″E) in the eastern part of Alexandria and almost 2.5 km from the north coast. The study area is classified as mixed residential and commercial as it contains a mixture of residential buildings and commercial shops (Nabil and Abd Eldayem Citation2015; Raman and Roy Citation2019). PM10, PM2.5 and CO2 were measured for 24 h both indoor and outdoor simultaneously at each residence on 2–3 occasions followed by calculation of mean values. Indoor air sampling was carried out both in the living rooms and kitchens, whereas outdoor air sampling was conducted only in the balconies of the living rooms. The selected homes are all private flats situated in the first floor of different multistory flat-type residential buildings with varying distances from major traffic roads. All homes were occupied during air sampling and no pets were found. The living rooms of all sampling sites were ventilated naturally through opening windows/doors and their floors, either tile or wooden, were all covered with carpets. The kitchens of all studied homes were supplied with natural gas for cooking using gas stoves and were ventilated either by using exhaust fans/hoods or through opening windows. Brief information about the sampling sites and description of indoor activities and mean ventilation rates in the monitored homes is shown in and , respectively.
Table 1. Main characteristics of the sampling sites
Table 2. Description of indoor activities and mean ventilation rates in the sampling sites
One pair of the Marple PM10 and PM2.5 environmental monitor samplers (Personal Environmental Monitor [PEM – model 200]; MSP Co., Minneapolis, MN, USA) was used for separating PM10 and PM2.5 fractions from the air, respectively (Marple et al. Citation1987). The PM10 and PM2.5 samplers were placed in the living room and the balcony of each sampling site and were run for 24 h at a flow rate of 10 L/min to collect simultaneous indoor and outdoor PM10 and PM2.5 samples. A calibrated rotameter (Model 320–100, SKC Inc., PA, USA) was used to monitor the airflow rates at the start and end of each sampling period. The PM10 and PM2.5 samples were collected on 37 mm diameter polytetrafluoroethylene [PTFE] membrane after-filters with a 2 μm pore size. All used filters including both air-exposed and blank filters were conditioned before weighing for 24 h in a controlled room at a constant temperature and relative humidity of about 20°C and 50%, respectively. All filters were then weighed for at least three times before and after sampling using a high-precision microbalance (Mettler-Toledo AG245; Mettler-Toledo Inc., Columbus, OH) with 10 µg readability and mean values were then calculated. Moreover, the indoor and outdoor CO2 concentrations were monitored for 24 h by using portable Q-Trak monitors (model 8551; TSI Inc., Shoreview MN, USA) based on the mechanism of non-disperse infrared detection. The data logging interval was 1 min. The Q-Trak monitors were calibrated by the manufacturer using standard CO2 gas of known concentrations. Also, zero checking of the Q-Trak monitors was conducted before each field monitoring. Further, parallel indoor PM2.5 and CO2 measurements were also conducted for 24 h in the kitchens of all homes under investigation, in order to cover the times of preparation of all meals and snacks, using an additional Marple PM2.5 sampler and a Q-Trak monitor, respectively. Air measurements in the kitchens were taken place at the same time as measurements conducted in the living rooms and balconies. The sampling position of all indoor instruments was almost close to the center of the living rooms and kitchens at about 1.5 m above the floor and about 1 m away from any potential source of air pollution. Indoor and outdoor sampling and monitoring processes were performed with great care to obtain accurate measurements as well as to avoid any contamination or loss of the measured pollutants. Before the sampling process, parallel testing of paired air samplers was carried out in the laboratory for the verification and correction, if needed, of the calibration factors.
Air exchange rate (AER), which is the rate at which ambient fresh air replaces indoor air, was also measured in the living rooms of all sampling sites by the tracer gas decay method. The tracer gas used in this method should be easily detected at low levels and also should not be available in the background air. Therefore, the nontoxic and odorless sulfur hexafluoride (SF6) was used as a tracer gas and dosed up to 10 ppm in the middle of the living rooms and at a height of about 1.6 m. The gas was then left to decay and the rate of decay was used to calculate the AER. The decay rate of the SF6 was measured by the photo-acoustic multi-gas monitor (Innova 1412i; LumaSense Technologies Inc., Santa Clara, CA, USA). The method was applied at the beginning and end of the measurement periods followed by calculation of mean values.
Statistical analysis
Statistical analyses were performed by SPSS package for Windows (version 20.0, SPSS Inc., NY, USA), using two-tailed tests and a significance level at p < .05. The normality of data was evaluated using the Shapiro–Wilk test, before applying the statistical tests. Correlations among measured air pollutants were analyzed using the Pearson bivariate correlation coefficient (r). Similarly, correlations of indoor PM and CO2 concentrations with various outdoor and indoor influential factors were also evaluated. Differences between mean indoor PM2.5 and CO2 concentrations measured in kitchens ventilated only naturally and those measured in kitchens supplied with exhaust fans or hoods were calculated and the t-test was used to determine the statistical significance.
Results and discussion
Indoor/outdoor relationships of PM10, PM2.5, and CO2 concentrations
The daily mean indoor and outdoor PM10, PM2.5, and CO2 concentrations in all selected homes were measured and shown in , , and respectively. Variations in daily mean concentrations of both PM fractions and carbon dioxide for each home along the measurement period were calculated and presented on each figure as error bars. shows the mean outdoor and indoor concentrations of PM10, PM2.5, and CO2 measured at the 20 selected homes. Indoor concentrations of all measured pollutants vary according to both outdoor concentrations and indoor activities. On average, PM2.5 concentrations accounted for 47.2 ± 10.9% and 51.8 ± 17.3% of the PM10 concentrations both outdoor and indoor, respectively. Moreover, indoor PM10 and PM2.5 concentrations in all living rooms of the studied residences were found to be significantly correlated (r = 0.65, p < .01). Significant, but weaker, correlation was also found between outdoor PM10 and PM2.5 concentrations (r = 0.50, p < .05). This is probably due to their releases from similar emission sources.
Table 3. Concentrations of air pollutants measured in 20 homes both outdoors and indoors
Environmental authorities in Egypt have not issued any indoor air quality standards yet. Therefore, the World Health Organization (WHO) PM10 and PM2.5 guidelines for an averaging time of 24 h have been used (50 µg/m3 for PM10 and 25 µg/m3 for PM2.5). The daily mean outdoor PM10 concentrations exceeded the WHO guideline in all sampling sites, whereas the daily mean indoor PM10 concentrations were found to exceed the WHO guideline by only 80%. For indoor PM2.5, the daily mean concentrations of living rooms and kitchens in all sampling sites exceeded the WHO guideline by 65% and 95%, respectively. For outdoor PM2.5, the daily mean concentrations were found to exceed the WHO guideline in all sampling sites due to the proximity of residences to main roads of high traffic densities and commercial activities. The outdoor and indoor (both living rooms and kitchens) CO2 levels were also compared to the ANSI/ASHRAE Standard 62.1 and no exceedances were found for either indoor or outdoor CO2 concentrations.
Figure 1. Daily mean outdoor and living room concentrations of PM10 in 20 selected homes
Figure 2. Daily mean outdoor, living room, and kitchen concentrations of PM2.5 in 20 selected homes
Figure 3. Daily mean outdoor, living room, and kitchen concentrations of CO2 in 20 selected homes
A statistically significant correlation was found between indoor and outdoor PM10 levels (r = 0.51, p < .05). A more significant correlation was also found between indoor (living rooms) and outdoor PM2.5 concentrations (r = 0.61, p < .01). This implies that indoor PM10 and PM2.5 concentrations are influenced by their corresponding outdoor levels through opening doors and windows during natural ventilation and the infiltration of outdoor air into the homes (El-Hougeiri and El Fadel Citation2004). However, no significant correlation was found between indoor (kitchens) and outdoor PM2.5 concentrations. This means that PM2.5 levels measured in kitchens are more affected by indoors sources, primarily cooking, than outdoor concentrations. Similarly, no significant correlation was found between CO2 levels in living rooms or kitchens and the outdoor CO2 levels, which confirms that indoor activities largely influence indoor CO2 concentrations.
The presence of major roads of high traffic densities could influence IAQ in nearby naturally ventilated households (Chang Citation2002; Perez et al. Citation2010). Significant correlations were found between the distance from major roads and both outdoor and indoor PM10 concentrations (r = – 0.63, p < .01 and r = – 0.60, p < .01, respectively). Also, the distance from major traffic roads was found to correlate significantly with outdoor PM2.5 levels (r = – 0.70, p < .01) and indoor PM2.5 levels in both living rooms (r = – 0.65, p < .01) and kitchens (r = – 0.45, p < .05). For CO2, no significant correlation was found between the distance from nearby major roads and CO2 concentrations either indoors or outdoors. Furthermore, the correlation between home age and the concentrations of all measured parameters was insignificant. This is probably because most of the buildings in which the sampling sites exist were constructed recently with no obvious cracks in the building structures (Yang et al. Citation2009).
The indoor to outdoor (I/O) ratio is an indicator used for evaluating the strength of indoor emission sources or as an indicator to assess the difference between indoor and outdoor levels (Huang et al. Citation2007). The mean I/O ratios were calculated to PM10, PM2.5, and CO2. shows I/O ratios of the measured parameters for all selected households. For PM10, mean I/O ratio for all sampling sites was found to be 0.64 ± 0.15 (range 0.47–0.96; median: 0.58). Mean I/O ratios for PM2.5 in living rooms and kitchens were found to be 0.71 ± 0.25 (range: 0.42–1.29; median: 0.63) and 1.48 ± 0.76 (range: 0.59–3.10; median: 1.30), respectively. The mean I/O ratios of PM2.5 were found to be higher than that of the PM10 because of the higher emissions of the fine PM fraction from various indoor combustion sources and also the higher infiltration of outdoor PM2.5 into the indoor environments as they have a smaller size (Chao, Wong, and Cheng Citation2002; Hoek et al. Citation2008). Furthermore, PM10 have higher deposition velocities than PM2.5 and can easily deposit on doors and window frames during penetration from outdoors to indoor environments and this may reduce their indoor levels (Thatcher and Layton Citation1995). Also, the indoor suspended PM10 can deposit on various indoor surfaces (e.g. floor, furniture, etc.). I/O ratios of PM2.5 for living rooms were found to have values more than 1 in only three homes (home 6, 13, and 17) and in 13 kitchens of all selected homes (See ). Generally, I/O ratios with values higher than 1 are attributed to the existence of significant indoor emission sources such as smoking and cooking, as will be discussed later. For CO2, the mean I/O ratio for living rooms was 1.38 ± 0.26 (range: 1.03–1.86; median: 1.35) and that for the kitchens was 1.59 ± 0.36 (range: 1.05–2.63; median: 1.51).
Table 4. I/O ratios of PM10, PM2.5, and CO2 in all selected homes
In comparison with previous studies conducted in residential buildings in Alexandria, Abdelsalam, (Citation2013) found that the mean indoor PM2.5 and PM10 concentrations in 17 homes were 53.5 ± 15.2 μg/m3 (range: 25–76 μg/m3) and 77.2 ± 15.1 μg/m3 (range: 46.1–99.0 μg/m3), respectively. The mean I/O ratios of the observed sites were 0.84 ± 0.27 (range: 0.43–1.45; median: 0.81) and 0.65 ± 0.18 (range: 0.40–1.07; median: 0.65) for PM2.5 and PM10, respectively. Abdel-Salam (Citation2015) reported that the mean indoor PM2.5 and CO2 concentrations in 15 homes were 45.5 ± 11.1 (range: 25.3–65.0 μg/m3) and 583 ± 87 ppm (range: 473–730 ppm), respectively. The mean I/O ratios for PM2.5 and CO2 of all selected homes were 0.99 ± 0.26 (range: 0.73–1.65; median: 0.87) and 1.41 ± 0.15 (range: 1.13–1.66; median: 1.37), respectively. The I/O mass concentration ratios can largely vary due to many factors including building structure and design, location, and various indoor activities (Massey et al. Citation2012). The indoor concentrations of PM10, PM2.5, and CO2 measured in the present study were lower than those found in the previous studies, probably due to lower contributions from outdoor and indoor sources.
Air exchange rates (AERs) were measured in living rooms of all homes under investigation (See ) to assess how indoor air is replenished with entering outdoor air. AER, also known as ventilation rate, is highly related to ventilation time which varies from one household to another. AER was used to understand the variations in the I/O ratios for all measured pollutants. shows how AERs influence I/O ratios of PM10, PM2.5, and CO2 in the living rooms, as AERs were only measured in the living rooms of all selected households. The mean AER in all residences was 2.5 ± 0.9 h−1 (range: 1.1–4.2 h−1; median: 2.0 h−1). The reduced ambient temperature during the sampling period led to low ventilation times and AERs in many homes under investigation. Homes with higher I/O ratios for PM10, PM2.5, and CO2 had low AERs (less than 2 h−1) as their levels tend to build up in the indoor environments, such as homes 6, 13, 17, and 19. The results also indicate that lower I/O ratios of the measured pollutants corresponded to high AERs (more than 3 h−1), such as homes 1, 4, 7, 12, and 20.
Figure 4. Variations in the I/O ratios of PM10, PM2.5, and CO2 in relation to AERs measured in 20 selected homes
Effect of indoor factors
Indoor emission sources and human activities in different indoor environments greatly influence indoor concentrations of air pollutants and IAQ in general. Smoking in living rooms and cooking in kitchens are important combustion sources for particulate matter and CO2 in indoor environments. In the current study, smoking was seen in only seven homes with mean I/O ratios 0.74 ± 0.14 (range: 0.57–0.96), 1.02 ± 0.25 (range: 0.73–1.29), and 1.59 ± 0.20 (range: 1.31–1.86) for PM10, PM2.5, and CO2, respectively. In homes where occupants smoke including homes 2, 6, 10, 13, 16, 17, and 19, the mean indoor concentrations of PM10, PM2.5, and CO2 measured in the living rooms were higher than those recorded in homes with no smokers by 23%, 91%, and 32%, respectively. Significant correlation was found between smoking and mean indoor levels of PM10 (r = 0.52, p < .05), PM2.5 (r = 0.82, p < .01), and CO2 (r = 0.74, p < .01), which confirms the significant contribution of smoking to their indoor levels. Recent studies have shown the significant influence of smokers on the PM concentrations in residences (e.g. Faria et al. Citation2020; Langer et al. Citation2016). Also, cooking was another important indoor combustion source and a regular activity frequently undertaken in the kitchens of all selected residences using gas stoves about 3–4 times every day. During the periods of air sampling, the daily mean concentrations of PM2.5 and CO2 in the domestic kitchens of all residences were 104% and 16% higher than those measured in the living rooms. Most of the domestic kitchens investigated had higher indoor concentrations of PM2.5 and CO2 than in living rooms. This is due to insufficient ventilation in these kitchens as well as their small volumes which enhanced the influence of emissions from cooking activity. However, significant correlation was found between mean levels of PM2.5 in kitchens and both mean levels of PM10 (r = 0.54, p < .05) and PM2.5 (r = 0.81, p < .01) measured in living rooms. Similarly, a significant correlation was observed between mean levels of CO2 in living rooms and those recorded in kitchens (r = 0.72, p < .01). This confirms the strong association and contribution of cooking in kitchens to PM and CO2 concentrations in living rooms. Inadequate ventilation in domestic kitchens can lead to the accumulation of combustion-generated products including PM2.5 and CO2 in these kitchens during cooking (Willers et al. Citation2006). In the present study, important information was recorded about kitchen sizes as well as type and use of ventilation provisions in each kitchen of the sampling homes (See and ). Significant correlation was found between kitchen sizes and mean concentrations of PM2.5 (r = – 0.59, p < .01) and CO2 (r = – 0.65, p < .01) measured in the kitchen environments. Elevated concentrations of PM2.5 and CO2 were found in kitchens not supplied with exhaust fans or smoke hoods of homes 2, 6, 13, and 17 with a mean value of 135.3 ± 26.5 µg/m3 (range: 104.0–167.0 µg/m3) and 885.0 ± 149.3 ppm (range: 730.0–1080.0 ppm), respectively. These kitchens were poorly ventilated as indicated by their relatively higher indoor levels of CO2. All other domestic kitchens (n = 16) were ventilated by exhaust fans or smoke hoods during cooking times and indoor levels of PM2.5 and CO2 were largely reduced in these kitchens with a mean value of 54.2 ± 19.3 µg/m3 (range: 20.0–90.0 µg/m3) and 583.8 ± 71.5 ppm (range: 430.0–690.0 ppm), respectively. Significantly higher mean PM2.5 (p < .018) and CO2 (p < .004) concentrations were found in kitchens ventilated only naturally through opening windows than in those supplied with exhaust fans or hoods. Unfortunately, opening windows was not as effective as using exhaust fans or hoods in these domestic kitchens because windows were only kept open during cooking or for very limited periods as open windows could cause cold and discomfort for inhabitants.
Household cleaning, including sweeping and vacuuming, is another indoor activity associated with increased levels of particulate matter (Ji Citation2020; Knibbs et al. Citation2012). Indoor cleaning may cause resuspension of previously settled dust particles on the floor and furniture surfaces (Corsi, Siegel, and Chiang Citation2008). Frequent cleaning (i.e., shorter periods between cleaning activities) largely decreases the deposited dust on different indoor surfaces and its resuspension through human’s movement into the indoor air (Lewis et al. Citation2018). In the present study, mean indoor concentrations of PM10 and PM2.5 were calculated in living rooms of six daily cleaned homes (homes 1, 2, 5, 9, 10, and 12) and found equal to 51.8 ± 11.4 µg/m3 (range: 39.0–64.0 µg/m3) and 29.3 ± 15.2 ppm (range: 13.0–49.0 ppm), respectively. In the other less frequently cleaned homes, PM10 and PM2.5 had mean indoor concentrations equal to 71.4 ± 13.9 µg/m3 (range: 50.0–97.0 µg/m3) and 36.6 ± 15.5 ppm (range: 19.0–71.0 ppm), respectively. The mean indoor levels of PM10 and PM2.5 measured in less frequently cleaned homes were higher than those recorded in daily cleaned homes by 38% and 25%, respectively.
Other internal factors, such as volume of living room and number of occupants, within homes can affect the indoor particulate matter and CO2 concentrations. Volume of living rooms was found to be significantly correlated with indoor levels of PM10 (r = – 0.46, p < .05), PM2.5 (r = – 0.51, p < .05), and CO2 (r = – 0.67, p < .01). As humans exhale CO2 during the process of respiration, number of occupants in indoor environments is expected to influence indoor CO2 concentrations. Furthermore, human occupancy and walking activity are other indoor factors that could increase indoor levels of airborne particulate matter through resuspension of previously deposited particles (Qian, Peccia, and Ferro Citation2014; Rosati, Thornburg, and Rodes Citation2008). Indeed, significant correlation was found between number of occupants and mean indoor concentrations of CO2 (r = 0.63, p < .01). Moreover, higher CO2 levels were found in small size living rooms combined with high occupancy as in homes 6, 10, 13, and 17. In comparison, significant but weak correlations were observed between number of occupants and mean indoor levels of PM10 (r = 0.49, p < .05) and PM2.5 (r = 0.45, p < .05). This is probably attributed to the more frequent cleaning in most highly occupied homes as this largely removes previously settled particles from different indoor surfaces. However, high PM10 and PM2.5 concentrations recorded in the living rooms of homes 6, 13, and 17 were associated with high occupancy combined with less frequent cleaning and perhaps also due to the existence of smokers in these homes.
Conclusion
In the present study, indoor and outdoor concentrations of PM10, PM2.5, and CO2 were measured simultaneously in 20 naturally ventilated urban homes. The study was performed in one large residential and commercial area in Alexandria, Egypt, during the autumn season. Good correlation was found between mean indoor PM10 and PM2.5 concentrations measured in the living areas and their corresponding outdoor concentrations, whereas no association was found between indoor and outdoor CO2 levels. Also, higher indoor concentrations of PM2.5 and CO2 were recorded in the kitchen environments than in living rooms. This was possibly linked to inadequate ventilation and cooking activity in small size kitchens. Furthermore, indoor PM2.5 and CO2 concentrations measured in living rooms were strongly associated with those measured in domestic kitchens. Therefore, increasing ventilation and using efficient mechanical systems, such as exhaust fans and smoke hoods, in the kitchen environments can play key roles in reducing the indoor levels of PM and CO2 both in kitchens and living rooms. Domestic activities such as smoking and cooking were found to constitute important indoor combustion sources of indoor PM and CO2. The highest PM and CO2 concentrations were found in living rooms of homes with smokers, where the highest I/O ratios occurred. Cleaning is another indoor routine activity which is recommended to be performed more frequently to remove settled particles on floors, carpets, and furniture surfaces and this can effectively reduce the potential of re-suspension from human’s movement. Outdoor factors such as outdoor PM levels and distance to major traffic roads were also found to affect indoor PM10 and PM2.5 concentrations. AERs measured in the living areas of all surveyed homes were found to influence I/O ratios of PM10, PM2.5, and CO2. The current study also showed that the effect of several routine domestic activities, such as smoking, cooking, and cleaning, on indoor levels of PM and CO2 was comparatively more apparent than that of outdoor sources. In addition to the effect of ventilation rate, mean indoor levels of CO2 varied largely as a result of the combined effect of room occupancy and room size. Good characterization of the sources that affect indoor levels of air pollution and the establishment of IAQ standards in Egypt is of major importance for improving IAQ and reducing the associated health risks.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Mahmoud M. M. Abdel-Salam
Mahmoud M. M. Abdel-Salam is an Associate Professor in the Department of Environmental Sciences, Faculty of Science, Alexandria University, Alexandria, Egypt.
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