Concurrent assessment of personal,indoor, and outdoor PM2.5 and PM1 levels and source contributions using novel low-cost sensing devices

The intensity, frequency, duration, and contribution of distinct PM_2.5 sources in Asian households have seldom been assessed; these are evaluated in this work with concurrent personal, indoor, and outdoor PM_2.5 and PM₁ monitoring using novel low-cost sensing (LCS) devices, AS-LUNG. GRIMM-comparable observations were acquired by the corrected AS-LUNG readings, with R² up to 0.998. Twenty-six non-smoking healthy adults were recruited in Taiwan in 2018 for 7-day personal, home indoor, and home outdoor PM monitoring. The results showed 5-min PM_2.5 and PM₁ exposures of 11.2 ± 10.9 and 10.5 ± 9.8 µg/m³, respectively. Cooking occurred most frequently; cooking with and without solid fuel contributed to high PM_2.5 increments of 76.5 and 183.8 µg/m³ (1 min), respectively. Incense burning had the highest mean PM_2.5 indoor/outdoor (1.44 ± 1.44) ratios at home and on average the highest 5-min PM_2.5 increments (15.0 µg/m³) to indoor levels, among all single sources. Certain events accounted for 14.0%-39.6% of subjects’ daily exposures. With the high resolution of AS-LUNG data and detailed time-activity diaries, the impacts of sources and ventilations were assessed in detail.     

Cooking‐related PM2.5 and acrolein measured in grocery stores and comparison with other retail types

We measured particulate matter (PM), acrolein, and other indoor air contaminants in eight visits to grocery stores in California. Retail stores of other types (hardware, furniture, and apparel) were also sampled on additional visits. Based on tracer gas decay data, most stores had adequate ventilation according to minimum ventilation rate standards. Grocery stores had significantly higher concentrations of acrolein, fine and ultrafine PM, compared to other retail stores, likely attributable to cooking. Indoor concentrations of PM_2.5 and acrolein exceeded health guidelines in all tested grocery stores. Acrolein emission rates to indoors in grocery stores had a mean estimate about 30 times higher than in other retail store types. About 80% of the indoor PM_2.5 measured in grocery stores was emitted indoors, compared to only 20% for the other retail store types. Calculations suggest a substantial increase in outdoor air ventilation rate by a factor of three from current level is needed to reduce indoor acrolein concentrations. Alternatively, acrolein emission to indoors needs to be reduced 70% by better capturing of cooking exhaust. To maintain indoor PM_2.5 below the California annual ambient standard of 12 μg/m³, grocery stores need to use air filters with an efficiency rating higher than the MERV 8 air filters commonly used today.     

Measured performance of filtration and ventilation systems for fine and ultrafine particles and ozone in an unoccupied modern California house

This study evaluated nine ventilation and filtration systems in an unoccupied 2006 house located 250 m downwind of the I‐80 freeway in Sacramento, California. Systems were evaluated for reducing indoor concentrations of outdoor particles in summer and fall/winter, ozone in summer, and particles from stir‐fry cooking. Air exchange rate was measured continuously. Energy use was estimated for year‐round operation in California. Exhaust ventilation without enhanced filtration provided indoor PM_2.5 that was 70% lower than outdoors. Supply ventilation with MERV13 filtration provided slightly less protection, whereas supply MERV16 filtration reduced PM_2.5 by 97‐98% relative to outdoors. Supply filtration systems used little energy but provided no benefits for indoor‐generated particles. Systems with MERV13‐16 filter in the recirculating heating and cooling unit (FAU) operating continuously or 20 min/h reduced PM_2.5 by 93‐98%. Across all systems, removal percentages were higher for ultrafine particles and lower for black carbon, relative to PM_2.5. Indoor ozone was 3‐4% of outdoors for all systems except an electronic air cleaner that produced ozone. Filtration via the FAU or portable filtration units lowered PM_2.5 by 25‐75% when operated over the hour following cooking. The energy for year‐round operation of FAU filtration with an efficient blower motor was estimated at 600 kWh/year.     

Household and behavioral determinants of indoor PM2.5 in a rural solid fuel burning Native American community

Indoor and outdoor concentrations of PM_2.5 were measured for 24 h during heating and non-heating seasons in a rural solid fuel burning Native American community. Household building characteristics were collected during the initial home sampling visit using technician walkthrough questionnaires, and behavioral factors were collected through questionnaires by interviewers. To identify seasonal behavioral factors and household characteristics associated with indoor PM_2.5, data were analyzed separately by heating and non-heating seasons using multivariable regression. Concentrations of PM_2.5 were significantly higher during the heating season (indoor: 36.2 μg/m³; outdoor: 22.1 μg/m³) compared with the non-heating season (indoor: 14.6 μg/m³; outdoor: 9.3 μg/m³). Heating season indoor PM_2.5 was strongly associated with heating fuel type, housing type, indoor pests, use of a climate control unit, number of interior doors, and indoor relative humidity. During the non-heating season, different behavioral and household characteristics were associated with indoor PM_2.5 concentrations (indoor smoking and/or burning incense, opening doors and windows, area of surrounding environment, building size and height, and outdoor PM_2.5). Homes heated with coal and/or wood, or a combination of coal and/or wood with electricity and/or natural gas had elevated indoor PM_2.5 concentrations that exceeded both the EPA ambient standard (35 μg/m³) and the WHO guideline (25 μg/m³).     

Modeling approaches and performance for estimating personal exposure to household air pollution: A case study in Kenya

This study assessed the performance of modeling approaches to estimate personal exposure in Kenyan homes where cooking fuel combustion contributes substantially to household air pollution (HAP). We measured emissions (PM_2.5, black carbon, CO); household air pollution (PM_2.5, CO); personal exposure (PM_2.5, CO); stove use; and behavioral, socioeconomic, and household environmental characteristics (eg, ventilation and kitchen volume). We then applied various modeling approaches: a single-zone model; indirect exposure models, which combine person-location and area-level measurements; and predictive statistical models, including standard linear regression and ensemble machine learning approaches based on a set of predictors such as fuel type, room volume, and others. The single-zone model was reasonably well-correlated with measured kitchen concentrations of PM_2.5 (R² = 0.45) and CO (R² = 0.45), but lacked precision. The best performing regression model used a combination of survey-based data and physical measurements (R² = 0.76) and a root mean-squared error of 85 µg/m³, and the survey-only-based regression model was able to predict PM2.5 exposures with an R² of 0.51. Of the machine learning algorithms evaluated, extreme gradient boosting performed best, with an R² of 0.57 and RMSE of 98 µg/m³.     

Real-time measurements of PM2.5 and ozone to assess the effectiveness of residential indoor air filtration in Shanghai homes

Portable air cleaners are increasingly used in polluted areas in an attempt to reduce human exposure; however, there has been limited work characterizing their effectiveness at reducing exposure. With this in mind, we recruited forty-three children with asthma from suburban Shanghai and deployed air cleaners (with HEPA and activated carbon filters) in their bedrooms. During both 2-week filtration and non-filtration periods, low-cost PM_2.5 and O₃ air monitors were used to measure pollutants indoors, outdoors, and for personal exposure. Indoor PM_2.5 concentrations were reduced substantially with the use of air cleaners, from 34 ± 17 to 10 ± 8 µg/m³, with roughly 80% of indoor PM_2.5 estimated to come from outdoor sources. Personal exposure to PM_2.5 was reduced from 40 ± 17 to 25 ± 14 µg/m³. The more modest reductions in personal exposure and high contribution of outdoor PM_2.5 to indoor concentrations highlight the need to reduce outdoor PM_2.5 and/or to clean indoor air in multiple locations. Indoor O₃ concentrations were generally low (mean = 8±4 ppb), and no significant difference was seen by filtration status. The concentrations of pollutants and the air cleaner effectiveness were highly variable over time and across homes, highlighting the usefulness of real-time air monitors for understanding individual exposure reduction strategies.     

Wood stove use and other determinants of personal and indoor exposures to particulate air pollution and ozone among elderly persons in a Northern Suburb

A six‐month winter‐spring study was conducted in a suburb of the northern European city of Kuopio, Finland, to identify and quantify factors determining daily personal exposure and home indoor levels of fine particulate matter (PM_2.5, diameter <2.5 µm) and its light absorption coefficient (PM_2.5abs), a proxy for combustion‐derived black carbon. Moreover, determinants of home indoor ozone (O₃) concentration were examined. Local central site outdoor, home indoor, and personal daily levels of pollutants were monitored in this suburb among 37 elderly residents. Outdoor concentrations of the pollutants were significant determinants of their levels in home indoor air and personal exposures. Natural ventilation in the detached and row houses increased personal exposure to PM_2.5, but not to PM_2.5abs, when compared with mechanical ventilation. Only cooking out of the recorded household activities increased indoor PM_2.5. The use of a wood stove room heater or wood‐fired sauna stove was associated with elevated concentrations of personal PM_2.5 and PM_2.5abs, and indoor PM_2.5abs. Candle burning increased daily indoor and personal PM_2.5abs, and it was also a determinant of indoor ozone level. In conclusion, relatively short‐lasting wood and candle burning of a few hours increased residents’ daily exposure to potentially hazardous, combustion‐derived carbonaceous particulate matter.     

Particle characterization in retail environments: concentrations,sources, and removal mechanisms

Particles in retail environments can have consequences for the occupational exposures of retail workers and customers, as well as the energy costs associated with ventilation and filtration. Little is known about particle characteristics in retail environments. We measured indoor and outdoor mass concentrations of PM₁₀ and PM_2.5, number concentrations of submicron particles (0.02–1 μm), size‐resolved 0.3–10 μm particles, as well as ventilation rates in 14 retail stores during 24 site visits in Pennsylvania and Texas. Overall, the results were generally suggestive of relatively clean environments when compared to investigations of other building types and ambient/occupational regulatory limits. PM₁₀ and PM_2.5 concentrations (mean ± s.d.) were 20 ± 14 and 11 ± 10 μg/m³, respectively, with indoor‐to‐outdoor ratios of 1.0 ± 0.7 and 0.88 ± 1.0. Mean submicron particle concentrations were 7220 ± 7500 particles/cm³ with an indoor‐to‐outdoor ratio of 1.18 ± 1.30. The median contribution to PM₁₀ and PM_2.5 concentrations from indoor sources (vs. outdoors) was 83% and 53%, respectively. There were no significant correlations between measured ventilation rates and particle concentrations of any size. When examining options to lower PM_2.5 concentrations below regulatory limits, the required changes to ventilation and filtration efficiency were site specific and depended on the indoor and outdoor concentration, emission rate, and infiltration level.     

Exposure to fine particulate matter in ten night clubs in Athens Greece: Studying the effect of ventilation, cigarette smoking and resuspension

The aim of the present work is to study the occupants' exposure to fine particulate concentrations in ten nightclubs (NCs) in Athens, Greece. Measurements of PM₁ and PM_2.5 were made in the outdoor and indoor environment of each NC. The average indoor PM₁ and PM_2.5 concentrations were found to be 181.77 μg m^− 3 and 454.08 μg m^− 3 respectively, while the corresponding outdoor values were 11.04 μg m^− 3 and 32.19 μg m^− 3. Ventilation and resuspension rates were estimated through consecutive numerical experiments with an indoor air quality model and were found to be remarkably lower than the minimum values recommended by national standards. The relative effects of the ventilation and smoking on the occupants' exposures were examined using multiple regression techniques. It was found that given the low ventilation rates, the effect of smoking as well as the occupancy is of the highest importance. Numerical evaluations showed that if the ventilation rates were at the minimum values set by national standards, then the indoor exposures would be reduced at the 70% of the present exposure values.     

A pilot study of traditional indoor biomass cooking and heating in rural Bhutan: gas and particle concentrations and emission rates

Although many studies have reported the health effects of biomass fuels in developing countries, relatively few have quantitatively characterized emissions from biomass stoves during cooking and heating. The aim of this pilot study was to characterize the emission characteristics of different biomass stoves in four rural houses in Bhutan during heating (metal chimney stove), rice cooking (traditional mud stove), fodder preparation (stone tripod stove), and liquor distillation (traditional mud stove). Three stage measurements (before, during, and after the activity had ceased) were conducted for PM_2.5, particle number (PN), CO, and CO₂. When stoves were operated, the pollutant concentrations were significantly elevated above background levels, by an average of 40 and 18 times for PM_2.5 and CO, respectively. Emission rates (mg/min) ranged from 1.07 × 10² (PM_2.5) and 3.50 × 10² (CO) for the stone tripod stove during fodder preparation to 6.20 × 10² (PM_2.5) and 2.22 × 10³ (CO) for the traditional mud stove during liquor distillation. Usable PN data were only available for one house, during heating using a metal chimney stove, which presented an emission rate of 3.24 × 10¹³ particles/min. Interventions to control household air pollution in Bhutan, in order to reduce the health risks associated with cooking and heating, are recommended.     

Fine and ultrafine particle exposures on 73 trips by car to 65 non‐smoking restaurants in the San Francisco Bay Area

A number of studies indicate cooking is a major source of exposure to particulate matter, but few studies have measured indoor air pollution in restaurants, where cooking predominates. We made 73 visits by car to 65 different non‐smoking restaurants in 10 Northern California towns while carrying portable continuous monitors that unobtrusively measured ultrafine (down to 10 nm) and fine (PM_2.5) particles to characterize indoor restaurant exposures, comparing them with exposures in the car. The mean ultrafine number concentrations in the restaurants on dinner visits averaging 1.4 h was 71 600 particles/cm³, or 4.3 times the mean concentration on car trips, and 12.3 times the mean background concentration in the residence. Restaurants that cooked dinner in the same room as the patrons had higher ultrafine concentrations than restaurants with separate kitchens. Restaurant PM_2.5 mass concentrations averaged 36.3 μg/m³, ranging from 1.5 to 454 μg/m³, but were relatively low on most visits: 43% of the indoor means were below 10 μg/m³ and 66% were below 20 μg/m³, with 5.5% above 100 μg/m³. Exposure to fine and ultrafine particles when visiting a restaurant exceeded the exposure a person received while traveling by car to and from the restaurant.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Developing a predictive model for fine particulate matter concentrations in low socio‐economic households in Durban,South Africa

In low‐resource settings, there is a need to develop models that can address contributions of household and outdoor sources to population exposures. The aim of the study was to model indoor PM_2.5 using household characteristics, activities, and outdoor sources. Households belonging to participants in the Mother and Child in the Environment (MACE) birth cohort, in Durban, South Africa, were randomly selected. A structured walk‐through identified variables likely to generate PM_2.5. MiniVol samplers were used to monitor PM_2.5 for a period of 24 hours, followed by a post‐activity questionnaire. Factor analysis was used as a variable reduction tool. Levels of PM_2.5 in the south were higher than in the north of the city (P < .05); crowding and dwelling type, household emissions (incense, candles, cooking), and household smoking practices were factors associated with an increase in PM_2.5 levels (P < .05), while room magnitude and natural ventilation factors were associated with a decrease in the PM_2.5 levels (P < .05). A reasonably robust PM_2.5 predictive model was obtained with model R² of 50%. Recognizing the challenges in characterizing exposure in environmental epidemiological studies, particularly in resource‐constrained settings, modeling provides an opportunity to reasonably estimate indoor pollutant levels in unmeasured homes.     

Household air pollution from wood burning in two reconstructed houses from the Danish Viking Age

During 13 winter weeks, an experimental archeology project was undertaken in two Danish reconstructed Viking Age houses with indoor open fireplaces. Volunteers inhabited the houses under living conditions similar to those of the Viking Age, including cooking and heating by wood fire. Carbon monoxide (CO) and particulate matter (PM_2.5) were measured at varying distances to the fireplace. Near the fireplaces CO (mean) was 16 ppm. PM_2.5 (mean) was 3.40 mg/m³, however, measured in one house only. The CO:PM mass ratio was found to increase from 6.4 to 22 when increasing the distance to the fire. Two persons carried CO sensors. Average personal exposure was 6.9 ppm, and from this, a personal PM_2.5 exposure of 0.41 mg/m³ was estimated. The levels found here were higher than reported from modern studies conducted in dwellings using biomass for cooking and heating. While this may be due to the Viking house design, the volunteer's lack of training in attending a fire maybe also played a role. Even so, when comparing to today's issues arising from the use of open fires, it must be assumed that also during the Viking Age, the exposure to woodsmoke was a contributing factor to health problems.     

Effects of energy retrofits on Indoor Air Quality in multifamily buildings

We assessed 45 multifamily buildings (240 apartments) from Finland and 20 (96 apartments) from Lithuania, out of which 37 buildings in Finland and 15 buildings in Lithuania underwent energy retrofits. Building characteristics, retrofit activities, and energy consumption data were collected, and Indoor Air Quality (IAQ) parameters, including carbon monoxide (CO), nitrogen dioxide (NO₂), formaldehyde (CH₂O), selected volatile organic compounds (benzene, toluene, ethylbenzene, and xylenes (BTEX), radon, and microbial content in settled dust were measured before and after the retrofits. After the retrofits, heating energy consumption decreased by an average of 24% and 49% in Finnish and Lithuanian buildings, respectively. After the retrofits of Finnish buildings, there was a significant increase in BTEX concentrations (estimated mean increase of 2.5 µg/m³), whereas significant reductions were seen in fungal (0.6‐log reduction in cells/m²/d) and bacterial (0.6‐log reduction in gram‐positive and 0.9‐log reduction in gram‐negative bacterial cells/m²/d) concentrations. In Lithuanian buildings, radon concentrations were significantly increased (estimated mean increase of 13.8 Bq/m³) after the retrofits. Mechanical ventilation was associated with significantly lower CH₂O concentrations in Finnish buildings. The results and recommendations presented in this paper can inform building retrofit studies and other programs and policies aimed to improve indoor environment and health.     

Personal exposure to PM2.5 in Chinese rural households in the Yangtze River Delta

High levels of PM_2.5 exposure and associated health risks are of great concern in rural China. For this study, we used portable PM_2.5 monitors for monitoring concentrations online, recorded personal time‐activity patterns, and analyzed the contribution from different microenvironments in rural areas of the Yangtze River Delta, China. The daily exposure levels of rural participants were 66 μg/m³ (SD 40) in winter and 65 μg/m³ (SD 16) in summer. Indoor exposure levels were usually higher than outdoor levels. The exposure levels during cooking in rural kitchens were 140 μg/m³ (SD 116) in winter and 121 μg/m³ (SD 70) in summer, the highest in all microenvironments. Winter and summer values were 252 μg/m³ (SD 103) and 204 μg/m³ (SD 105), respectively, for rural people using biomass for fuel, much higher than those for rural people using LPG and electricity. By combining PM_2.5concentrations and time spent in different microenvironments, we found that 92% (winter) and 85% (summer) of personal exposure to PM_2.5in rural areas was attributable to indoor microenvironments, of which kitchens accounted for 24% and 27%, respectively. Consequently, more effective policies and measures are needed to replace biomass fuel with LPG or electricity, which would benefit the health of the rural population in China.     

Quantifying fine particle emission events from time‐resolved measurements: Method description and application to 18 California low‐income apartments

PM_2.5 exposure is associated with significant health risk. Exposures in homes derive from both outdoor and indoor sources, with emissions occurring primarily in discrete events. Data on emission event magnitudes and schedules are needed to support simulation‐based studies of exposures and mitigations. This study applied an identification and characterization algorithm to quantify time‐resolved PM_2.5 emission events from data collected during 224 days of monitoring in 18 California apartments with low‐income residents. We identified and characterized 836 distinct events with median and mean values of 12 and 30 mg emitted mass, 16 and 23 minutes emission duration, 37 and 103 mg/h emission rates, and pseudo‐first–order decay rates of 1.3 and 2.0/h. Mean event‐averaged concentrations calculated using the determined event characteristics agreed to within 6% of measured values for 14 of the apartments. There were variations in event schedules and emitted mass across homes, with few events overnight and most emissions occurring during late afternoons and evenings. Event characteristics were similar during weekdays and weekends. Emitted mass was positively correlated with number of residents (Spearman coefficient, ρ=.10), bedrooms (ρ=.08), house volume (ρ=.29), and indoor‐outdoor CO₂ difference (ρ=.27). The event schedules can be used in probabilistic modeling of PM_2.5 in low‐income apartments.     

Size distribution and lung-deposited doses of particulate matter from household exposure to biomass smoke

Exposure to high concentrations of particulate matter (PM) is associated with a number of adverse health effects. However, it is unclear which aspects of PM are most hazardous, and a better understanding of particle sizes and personal exposure is needed. We characterized particle size distribution (PSD) from biomass-related pollution and assessed total and regional lung-deposited doses using multiple-path deposition modeling. Gravimetric measurements of kitchen and personal PM_2.5 (<2.5 µm in size) exposures were collected in 180 households in rural Puno, Peru. Direct-reading measurements of number concentrations were collected in a subset of 20 kitchens for particles 0.3-25 µm, and the continuous PSD was derived using a nonlinear least-squares method. Mean daily PM_2.5 kitchen concentration and personal exposure was 1205 ± 942 µg/m³ and 115 ± 167 µg/m³, respectively, and the mean mass concentration consisted of a primary accumulation mode at 0.21 µm and a secondary coarse mode at 3.17 µm. Mean daily lung-deposited surface area (LDSA) and LDSA during cooking were 1009.6 ± 1469.8 µm²/cm³ and 10,552.5 ± 8261.6 µm²/cm³, respectively. This study presents unique data regarding lung deposition of biomass smoke that could serve as a reference for future studies and provides a novel, more biologically relevant metric for exposure-response analysis compared to traditional size-based metrics.     

Controlled experiments measuring personal exposure to PM2.5 in close proximity to cigarette smoking

Few measurements of exposure to secondhand smoke (SHS) in close proximity to a smoker are available. Recent health studies have demonstrated an association between acute (<2 h) exposures to high concentrations of SHS and increased risk of cardiovascular and respiratory disease. We performed 15 experiments inside naturally ventilated homes and 16 in outdoor locations, each with 2–4 non‐smokers sitting near a cigarette smoker. The smoker's and non‐smokers' real‐time exposures to PM_2.5 from SHS were measured by using TSI SidePak monitors to sample their breathing zones. In 87% of the residential indoor experiments, the smoker received the highest average exposure to SHS, with PM_2.5 concentrations ranging from 50–630 μg/m³. During the active smoking period, individual non‐smokers sitting within approximately 1 m of a smoker had average SHS exposures ranging from negligible up to >160 μg/m³ of PM_2.5. The average incremental exposure of the non‐smokers was higher indoors (42 μg/m³, n = 35) than outdoors (29 μg/m³, n = 47), but the overall indoor and outdoor frequency distributions were similar. The 10‐s PM_2.5 averages during the smoking periods showed great variability, with multiple high concentrations of short duration (microplumes) both indoors and outdoors.     

Effects of types of ventilation system on indoor particle concentrations in residential buildings

The objective of this study was to quantify the influence of ventilation systems on indoor particle concentrations in residential buildings. Fifteen occupied, single‐family apartments were selected from three sites. The three sites have three different ventilation systems: unbalanced mechanical ventilation, balanced mechanical ventilation, and natural ventilation. Field measurements were conducted between April and June 2012, when outdoor air temperatures were comfortable. Number concentrations of particles, PM_2.5 and CO₂, were continuously measured both outdoors and indoors. In the apartments with natural ventilation, I/O ratios of particle number concentrations ranged from 0.56 to 0.72 for submicron particles, and from 0.25 to 0.60 for particles larger than 1.0 μm. The daily average indoor particle concentration decreased to 50% below the outdoor level for submicron particles and 25% below the outdoor level for fine particles, when the apartments were mechanically ventilated. The two mechanical ventilation systems reduced the I/O ratios by 26% for submicron particles and 65% for fine particles compared with the natural ventilation. These results showed that mechanical ventilation can reduce exposure to outdoor particles in residential buildings.