Table 2.

Overview of the characteristics of the studies included (in alphabetical order of the first author of each study).

Author/Reference	Country	Study Type/Design	Number of Participants and Their Characteristics	Methods of Indoor Pollution Assessments and Collection Time	Pollutant Analysis (Including Indoor-Outdoor)	Method of Health Effect Measurement	Results
Adgate, J. L., et al., (2004) [15]	USA	Prospective cohort	Children from 2 inner city schools	Organic vapor monitors, 1999, 2000.	VOCs		Home had largest and the school and outdoor environments had the smallest influence on personal exposure to VOCs.
Adgate, J. L., et al., (2004) another article [16]	USA	Prospective cohort	Children from 284 house holds	Organic vapor monitors, 1997	VOCs		Personal exposure was strongly associated with home indoor environment after controlling for important covariates.
Batterman, S., et al., (2005) [17]	USA	Prospective cohort	4 single family home environments	Four speed HEPA filter unit	PM, VOCs		Air filters can significantly lower PM concentrations in smoker’s homes if air exchange rates are limited.
Byun, H., et al., (2010) [18]	Korea	Prospective cohort	50 children	Organic vapour monitors, 2008	VOCs		Parental education, year of home construction and type of housing were correlated with personal VOC exposure.
Broich, A. V., et al., (2012) [19]	Germany	Prospective cohort	16 participants	Optical aerosol spectrometer and a small video camera, 2010.	UFP, PM10, PM2.5		Smoking and cooking were the main indoor sources for PM and the personal exposure significantly exceed the outdoor particulate matter concentrations.
Buonanno, G., et al., (2012) [20]	Italy	Prospective cohort	103 children	Hand-held UFP counters equipped with GPS Tracking, 2011, 2012.	UFP		Most of the children exposure take place at home during cooking/eating time at home and time spent in traffic jams.
Buonanno, G., et al., (2013) [21]	Italy	Prospective cohort	103 children	Black carbon monitor, hand-held UFP counters equipped with GPS tracking, 2011, 2012.	UFP and Black carbon (BC)		High levels typically detected in urban traffic microenvironments. Cooking and using transportation were the main daily exposure.
Baumgartner, J., et al., (2014) [22]	China	Prospective cohort study	280 women	Chemical and optical methods	UFP, PM2.5, black carbon	Blood pressure	Black carbon from combustion is more strongly associated with blood pressure than PM mass, and that BC’s health effects may be larger among women living near a highway due to greater exposure to vehicle emissions.
Branco, P., et al., (2014) [23]	Portugal	Cross-sectional	3 nurseries	TSI DustTrak DRX 8534 particle monitor, 2013.	PM1, PM2.5, PM10		Indoor sources (re-suspension phenomena due to children’s activities, cleaning, and cooking) were the main contributors to indoor PM concentrations, but poor ventilation of classrooms affected indoor air quality by increasing the PM accumulation.
Beko, G., et al., (2015) [24]	Denmark	Cross-sectional study	60 non-smoking residents	NanoTracer, 2013.	UFP		The home accounted for 50% of the daily personal exposure. Indoor areas other than home or vehicles contributed 40%. The highest median UFP concentration was obtained during passive transport (vehicles).
Cortez-Lugo, M., et al., (2008) [25]	USA	Prospective cohort	38 asthma children and COPD adults	MiniVol sampler, personal pumps, 2000	PM2.5 and PM10	Effects of PM exposure to lung function in asthma and COPD	Consistent decrements in MMEF in children with asthma who were not receiving medications.
Cortez-Lugo, M., et al., (2015) [26]	Mexico	Prospective cohort	29 adults with COPD	Personal pumps, 2000.	PM2.5	Lung function and respiratory symptoms	Exposure to PM2.5 was associated with reductions in peak expiratory flow (PEF) and increased respiratory symptoms in adults with COPD.
Cipolla, M., et al., (2016) [27]	Italy	Prospective cohort	74 students	Perkin Elmer Italia S.p.A, 2006.	VOCs	Rates of school absenteeism	The VOC levels were significantly higher in the industrial areas causing absence from school due to sore throat, cough, and cold. O-Xylene is associated with respiratory symptoms.
Cleary, E., et al., (2017) [28]	USA	Cross-sectional	2 cities	E Q-Trak Indoor Air Quality Monitor, Formaldehyde Multimode Monitor, e P-Trak Ultrafine Particle Counter, 2017.	VOCs, PM, CO	Asthma symptoms	Average CO concentrations were high, which is potentially associated with increased asthma symptoms.
Cheung, P. K., et al., (2019) [29]	Hong Kong	Prospective cohort	Seven subdivided units	Portable Aeroqual monitors, 2018.	CO, CO2, PM10, PM2.5 and VOC.		Mean PM10 and PM2.5 concentrations during cooking were higher than the pre-cooking levels but cooking did not increase CO, CO2, and VOC concentrations.
Cunha-Lopes, I., et al., (2019) [30]	Portugal	Prospective cohort	9 children	SKC five-stage Sioutas Cascade Impactor, 2018.	PM1, BC, UFP		High peak BC levels in underground parking lots, during charcoal grills, and candles were burning.
Curto, A., et al., (2019) [31]	Mozambique	Prospective cohort	202 women	A high-volume sampler, 2014, 2015	UFP and Black carbon		Main determinants of mean and peak personal exposure to BC were lighting source, kitchen type, ambient EC levels, and temperature.
Delfino, R. J., et al., (2006) [32]	USA	Prospective cohort	48 asthmatic children	Personal PM2.5 monitor, Harvard impactor. 2003,2004.	PM2.5, NO2, Elemental carbon		The strongest positive associations were between FENO and 2-day average pollutant concentrations. Strong associations were found for ambient elemental carbon and weak associations for ambient NO2.
Diapouli, E., et al., (2007) [33]	Greece	Cross-sectional	7 primary schools	Portable Condensation Particle Counter, cold period of 2003, 2004	UFP		The highest mean indoor concentrations were found in a small carpet-covered library and a teachers’ office. The highest outdoor concentrations were affected by heavy traffic. Indoor-to-outdoor concentration (I/O) ratios were below 1.
Diapouli, E., et al., (2008) [34]	Greece	Cross-sectional	7 primary schools	Harvard PEMs, 2003, 2004	UFP, PM2.5, PM10		Very high I/O ratios were observed when intense activities took place.
Fang, L., et al., (2019) [35]	China	A double-blind, randomized crossover trial	20 asthma patients	Low-cost pump packages. 2017.	VOCs		Levels of formaldehyde, acetaldehyde, and toluene were highest in the bedrooms. Air cleaners in houses lead to significant reductions in VOC concentrations indoors, but the associated health risks are still of concern.
Faria, T., et al., (2020) [36]	Portugal	Prospective cohort	5 schools, 40 homes, and 4 transportation modes.	Medium volume samplers, light scattering laser photometer. 2017, 2018.	UFP, PM2.5, PM10	Health effects due to developing immune, respiratory, central nervous, digestive and reproductive systems	Indoor environment is the main contributors to personal exposure to PM.
Gokhale, S., et al., (2008) [37]	Germany	Prospective cohort	7 adults	Organic vapour monitor, 2005	VOCs		The largest contribution of VOCs to the personal exposure is from homes, followed by outdoors, and the offices.
Goyal, R. and M. Khare (2009) [38]	India	Prospective cohort	A three–storied naturally ventilated school	Environmental dust monitor, IAQ monitor, 2006,2007	PM1, PM10, PM2.5		PM concentrations in classroom exceeds the permissible limits and indoor/outdoor levels for all sizes of particulates are greater than 1 and influence of ventilation rate and of traffic was found.
Guo, H., et al., (2010) [39]	Australia	Cross-sectional	A primary school	Two scanning mobility particle sizers, 2006	UFP, PM2.5		Early morning and late afternoon peaks of number of particles and PM2.5 were observed at traffic rush hours and the temporal variations of those related to human activities such as cigarette smoking and the operation of a mower. The indoor air pollution is affected by the outdoor and influenced by indoor sources, such as cooking, cleaning, and floor polishing activities as well.
Gao, Y., et al., (2014) [40]	China	1:1 matched case control study	105 children with acute leukemia	Diffusive sampler, 2008–2011	VOCs, NO2	Association between indoor air pollutants and childhood acute leukemia	High concentrations of NO2 and almost half of VOCs were associated with the increased risk of childhood AL.
Garcia-Hernandez, C., et al., (2019) [41]		Systemic review			UFP		The levels of UFP were correlated with heavy traffic or cooking and cleaning activities.
Habil, M. and A. Taneja (2011) [42]	India	Cross-sectional	4 schools	Grimm aerosol dust Monitor, 2007, 2008	PM1, PM10, PM2.5		The average indoor/outdoor ratios were >1 and there was poor correlation.
Hoang, T., et al., (2017) [43]	USA	Cross-sectional	34 early childhood education environments	Q- TRAK™ IAQ Monitors, SKC AirChek 2000 pumps, VOC sampler, 2010, 2011.	VOCs		VOCs found in cleaning and personal care products had the highest indoor concentrations.
Jansen, K. L., et al., (2005) [44]	USA	Prospective cohort	16 asthma or COPD patients	PM2.5 and PM10 Harvard Impactor, Marple Personal Environmental Monitors for PM10, 2002, 2003	PM2.5, PM10	FeNO, spirometry, exhaled breath condensate, pulse oximetry, heart rate, blood pressure, symptom, and medication use	An increase in outdoor, indoor, and personal black carbon was associated with increases in FENO but no significant association was found in spirometry, blood pressure, pulse rate, or SaO2.
Jeong, H. and D. Park (2017) [45]	Korea	Prospective cohort	44 children	Micro-aethalometer, 2015, 2016.	UFP and Black carbon		Diesel vehicles, subway, cooking, and smoking increase BC exposure.
Jeong, H. and D. Park (2018) [46]	Korea	Prospective cohort	40 children	Microaethalometer AE-51, 2015, 2016	black carbon		Transportation and cooking led to frequent peak levels.
Kearney, J., et al., (2011) [47]	Canada	Prospective cohort	45 homes of non-smoking adults and 49 homes of asthmatic children	Portable condensation particle counter, 2005,2006	UFP	.	Outdoor levels generally exceeded indoor levels, but indoor concentrations were higher around 5–7 pm, suggesting a strong influence of cooking. Large indoor peaks and low infiltration of ambient PM resulted in the indoor sources contributing more than infiltrated UFP.
Kalimeri, K. K., et al., (2016) [48]	Greece	Prospective cohort	3 public primary school	Radiello passive samplers, Gammadata RAPIDOS samplers, 2011, 2012	VOCs, NO2, Ozone	Possible health risks at school as measured by lifetime cancer risk	Emissions from building materials have a significant contribution to the indoor air quality. The estimated average lifetime cancer risks for benzene, formaldehyde and trichloroethylene were very low.
Liu, Y. W., et al., (2020) [49]	China	Prospective cohort	13 children	Personal sampling pump, 2018, 2019	UFP, PAHs	Lifetime cancer risk	Coal combustion and gasoline were main sources during heating and non-heating seasons. There was significant increase in PAHs and the incremental lifetime cancer risk in the heating season.
Massolo, L., et al., (2010) [50]	Argentina	Prospective cohort	93 school and houses, 33 outdoor areas	Passive 3 M monitor, 2000–2002	VOCs		Most VOCs predominantly originated indoors in urban, semirural, and residential areas, whereas an important outdoor influence in the industrial area was observed.
Mainka, A. and B. Kozielska (2016) [51]	Poland	Prospective cohort	48 children	Perkin Elmer stainless steel tube samplers. 2013, 2014.	VOCs (BTEX)	The health risk as measured by cancer risk	Elevated levels of o-xylene and ethylbenzene were found in all monitored classrooms during the winter season. Outdoor concentrations were lower than indoors. Chronic health effects associated with carcinogenic benzene or non-carcinogenic BTEX were high.
Mazaheri, M., et al., (2014) [52]	Australia	Cross-sectional	137 children	Philips Aerasense Nanotracers (NTs), 2010–2012	UFP		Outdoor activities, eating/cooking at home, and commuting were the three activities causing the highest exposure. Children’s exposure during school hours was more strongly influenced by urban background particles than traffic near the school.
Mazaheri, M., et al., (2019) [53]	China	Prospective cohort	24 children	Philips Aerasense NanoTracers, 2016.	UFP		Indoor exposure was significantly higher than outdoor exposure which was due to smoking and the use of mosquito repellent.
Martins, V., et al., (2020) [54]	Portugal	Cross sectional study	4 homes and 4 schools	Personal Cascade Impactor Sampler. 2017–2018.	UFP		PM chemical composition depended on transport mode. Fe was the component of metro PM, derived from abrasion of rail -wheel -brake interfaces. Zn and Cu in cars and buses PM were related with brake and tyre wear particles.
Martins, V., et al., (2021) [55]	Portugal	Cross sectional study	Assigned bicycle, bus, car and metro route in Lisbon	Personal environmental monitor. 2018	UFP		Black carbon concentrations when travelling by car was higher than in the other transport modes due to the closer proximity to exhaust emissions. Personal exposure to PM2.5 is higher in cycling than car due to higher inhalation rate and longer journey time.
Phillips, M. L., et al., (2005) [56]	USA	Prospective cohort	39 participants	Personal sampling pump	VOCs		Personal and indoor concentrations were higher than outdoor concentrations, indicating that indoor exposures were dominated by indoor sources.
Paunescu, A. C., et al., (2017) [57]	Paris	Prospective cohort	96 children	MicroAeth®AE51, DiSCmini®, 2014, 2015.	UFP and Black carbon		BC exposure was high during trips (principally metro/train and bus), while UFP exposure was high during indoor activities (mainly eating at restaurants).
Pacitto, A., et al., (2020) [58]	Italy	Prospective cohort	60 children	Handheld diffusion charger particle counter, 2018–2019	UFP		Non-school indoor environment causes most children’s exposure.
Raaschou-Nielsen, O., et al., (1997) [59]	Denmark	Cross-sectional	98 children	Diffusive VOC samplers, 1995	VOCs		The front-door concentrations were significantly higher in Copenhagen than in rural areas, but the personal exposures were only slightly higher.
Rojas-Bracho, L., et al., (2000) [60]	USA	Prospective Cohort	18 COPD patients	Modified PM2.5 and PM10 personal exposure monitor and a single personal pump, 1996, 1997	PM2.5, PM10		The strength of the personal-outdoor association for PM2.5, was strongly related to that for indoor and outdoor levels.
Rojas-Bracho, L., et al., (2004) [61]	USA	Prospective cohort	18 COPD patients	Modified personal exposure monitor, 1996, 1997	PM2.5, PM10		The relationship between personal PM2.5 exposures and the corresponding ambient concentrations was influenced by home air exchange rates.
Rufo, J. C., et al., (2015) [62]	Portugal	Cross-sectional	10 public primary schools	Portable condensation particle counters, 2014	UFP		The average indoor UFP number concentrations were not significantly different from outdoor concentrations. The levels of carbon dioxide were negatively correlated with indoor UFP concentrations. Occupational density was significantly and positively correlated with UFP concentrations.
Shendell, D. G., et al., (2004) [63]	USA	Prospective cohort	7 schools	Organic vapour monitor and DNSH passive aldehydes and ketone sampler, 2001	VOCs		The main sources of aldehydes in classrooms were likely interior finish materials and furnishings made of particleboard without lamination. The four most common VOCs measured were toluene, m-/p-xylene, alpha-pinene, and delta-limonene.
Sexton, K., et al., (2005) [64]	USA	Prospective cohort	150 children	Passive sampler, bloods, and urine sample, 2000, 2001	VOCs		There were strong statistical associations between measured blood VOC concentrations in siblings in the same household.
Sohn, H. and K. Lee (2010) [65]	Korea	Prospective cohort	2 vehicles	Portable aerosol spectrometers	UFP, PM2.5		A single cigarette being smoked could exceed the US EPA NAAQS of PM under realistic window opening conditions.
Soppa, V. J., et al., (2014) [66]	Germany	randomized cross-over controlled exposure study	55 healthy volunteers	Fast Mobility Particle Sizer, Aerodynamic Particle Sizer, Nanoparticle Surface Area Monitor	PM1, PM10, PM2.5	Respiratory health as measured by lung function	High levels of indoor fine particles from certain sources may be associated with small decreases in lung function in healthy adults.
Slezakova, K., et al., (2019) [67]	Portugal	Cross-sectional	20 public primary schools	Portable condensation particle counters. 2014, 2015.	UFP		Outdoor emissions contributed to indoor UFP. Canteens had the highest UFP levels. Cooking on school grounds caused elevated UFP in the classrooms. Lowest UFP were found in libraries mostly due to the limited occupancies.
Trenga, C. A., et al., (2006) [68]	USA	Prospective cohort	57 elderly, 17 children	Harvard impactor, personal monitor. 1999–2001.	PM2.5, PM10	Lung function changes to daily indoor, outdoor, and personal PM	Maximal midexpiratory flow (MMEF) was decreased in children with asthma who were not receiving medications. The effects were observed even though PM exposures were low for an urban area.
Tran, T. D., et al., (2020) [69]	Vietnam	Cross-sectional	10 nursery schools	Adjustable mini air Samplers, 2017, 2018	BTEX	Health risk as measured by life-time cancer risk	Outdoor BTEX originated from the common sources, which consisted mainly of automobile traffic. Indoor and outdoor concentrations of BTEX influenced lifetime cancer risk.
Vu, D. C., et al., (2019) [70]	USA	Cross-sectional	Children from four facilities of Head Start programs	Air pump. 2014.	VOCs	Human health risks associated with the targeted VOCs as measured by cancer risk	Sources of VOCs included vehicle-related emission, solvent-related emission, building materials, personal care products and household products. Potential carcinogenic compounds were benzene, ethylbenzene, naphthalene, 1,4-dichlorobenzene, tetrachloroethylene and trichloroethylene.
Vardoulakis, S., et al., (2020) [6]		Systemic review			VOC, PM2.5, NO2.		Household characteristics and occupant activities are essential in indoor exposure, especially cigarette smoking for PM2.5, gas appliances for NO2, and household products for VOCs and PAHs. Home location near high-traffic-density roads, redecoration, and small house size contribute to high indoor air pollution. High indoor particulate matter, NO2 and VOC levels were associated with respiratory symptoms, particularly asthma symptoms in children.
Weisel, C. P., et al., (2005) [71]	USA	Prospective cohort	100 non-smoking adult and children	Organic vapour monitor, personal environmental monitors	VOCs		The range of distribution for the VOCs, carbonyls, PM2.5, and air exchange rates, are consistent with values reported previously in the literature.
Weichenthal, S., et al., (2008) [72]		Review		Passive sampler	VOCs, UFP, NO2	Relationship between indoor nitrogen dioxide or VOC exposure and childhood asthma or related symptoms	VOC exposure have been more consistent in demonstrating a significant relationship with asthma or related symptoms.
Wangchuk, T., et al., (2015) [73]	Bhutan	Cross-sectional	82 children	Philips Aerasense NanoTracers, 2013.	UFP, VOCs, NO2		The highest UFP exposure resulted from cooking/eating, contributing to 64% of the daily exposure, resulting from firewood combustion in houses using traditional mud cookstoves.
Xia, X., et al., (2020) [74]	Hong Kong	Prospective cohort	20 COPD patients and 20 healthy participants	MicroPEM™ sensor. 2017–2018.	PM2.5	Effects on oxygen saturations in COPD and healthy participants	Short-term exposure to PM2.5 results in acute declines of SpO2 in 0–3 h, and then became insignificant at 0–12 h.
Yang, F. H., et al., (2019) [75]	Hong Kong	Prospective cohort	73 urban residents	Personal exposure kit. 2015–2016.	UFP, PM2.5, PM10		PM2.5 concentrations were lowest in office, whereas highest in outdoor activities.
Zhu, Y. F., et al., (2005) [76]	USA	Prospective cohort	4 two-bedroom apartments	Scanning mobility particle sizer, common switching manifold, 2003, 2004	UFP		Indoor to outdoor ratios for ultrafine particle number concentrations depended strongly on particle size and indoor ventilation mechanisms.
Zamora, M. L., et al., (2018) [77]	USA	Prospective cohort	17 pregnant women	Personal Environmental Monitor, 2015	PM2.5, black carbon, and nicotine		Cooking activities contributed significantly to the total PM2.5.
Zhang, L. J., et al., (2018) [78]	China	Prospective cohort	57 children	TSI DUST TRAKTM DRX sampler, real-time laser diode photometers, 2013.	PM2.5		Children personal exposure was mainly associated with ambient air conditions, height of the classroom, and transportation mode to school.
Zhou, Y., et al., (2020) [79]	China	Prospective cohort	26 students	Portable MicroAeth BC Monitor, Miniature Diffusion Size Classifier. 2016.	UFP and Black carbon		Average level of BC was higher in outdoor than the household and transport. Average level of UFP was higher in indoor than transport.
Zhou, H. C., et al., (2020) [80]	China	Prospective cohort	67 non-smoking healthy retirees	Micro-aethalometer AE51. 2018, 2019.	UFP and Black carbon		Ambient BC concentration, ambient temperature, humidity, education level and air purifier significantly impact personal BC exposure.
Zusman, M., et al., (2020) [81]	USA	Prospective cohort	2982 healthy smokers and non-smokers, COPD patients.	Ogawa passive samplers, Harvard Personal Environmental Monitor. 2014–2016.	PM2.5, NO2, NOx		Models using socioeconomic, meteorological, behavioral, residential, and ambient-pollutant concentration data obtained from questionnaires, direct observations, and measurements can facilitate exposure characterization of research cohorts with much less effort and expense than the monitoring of all participants.