Indoor air quality assessment in child care and medical facilities in Korea

Indoor air quality assessment in child care and medicalfacilities in Korea

Ehsanul Kabir & K.-H. Kim & Jong Ryeul Sohn &

Bo Youn Kweon & Jong Hyun Shin

Received: 14 January 2011 /Accepted: 27 October 2011 /Published online: 16 November 2011# Springer Science+Business Media B.V. 2011

Abstract In order to characterize the status of indoorair pollution in some important facilities, a list of keycriteria pollutants [particulate matter (PM10), carbondioxide (CO2), carbon monoxide (CO), formaldehyde(HCHO), and bioaerosol] was measured from a totalof 91 randomly selected sites in 18 different cities,Korea (February 2006 to December 2009). The targetfacilities include 43 child care facilities, 38 medicalfacilities, 6 elementary schools, and 4 postnatal carecenters. The results showed that some air pollutants(e.g., CO and HCHO) did not exceed the recommen-ded guideline [e.g., the Korean indoor air standard(KIAS) values of 10 ppm and 100 ppb, respectively].However, concentration of PM10, CO2, and bioaerosoloccasionally exceeded their respective guidelines(e.g., seven, three, and two cases). Discrete season-alities were observed from indoor pollutants because

of varying ventilation practice (e.g., summer timedominance of PM10, HCHO, and bioaerosol or winterdominance of CO2 and CO). However, as theconcentrations of the indoor pollutants were scarcelyabove the recommended guideline level, more diver-sified approaches are desirable to diagnose the statusof indoor pollution and to provide a realistic strategyfor the improvement of IAQ.

Keywords Indoor air quality . PM10. CO2

. CO .

HCHO . Bioaerosol . Child care facility .Medicalfacility . Elementary school . Postnatal care center

Introduction

Air pollution, both indoor and outdoor, is oftenconsidered the major cause of environmental healthproblems. Even few years back, the problems associ-ated with outdoor air pollution have been wellpublicized due to the prominence of major pollutantsources (e.g., traffic, industrial, construction, combus-tion sources, etc.). However, in recent years, publicconcerns on indoor air quality (IAQ) have drawn agreat deal of attention, as the isolation of indoor fromoutdoor environment become phenomenal with thewidespread supply of tight-sealed buildings and theassociated sick building syndrome (SBS).

Environ Monit Assess (2012) 184:6395–6409DOI 10.1007/s10661-011-2428-5

E. Kabir :K.-H. Kim (*)Department of Environment & Energy, Sejong University,Seoul, South Koreae-mail: [email protected]

J. R. SohnDepartment of Environmental Health, Korea University,Seoul, South Korea

B. Y. Kweon : J. H. ShinGyeong-gi Do Institute of Health & Environment,324-1 Pajang-dong, Jangan-gu,Suwon, Gyeonggi-do 440-290, Republic of Korea

Airtight buildings have grown rapidly in order toconserve energy, to reduce the infiltration of outsideair, and to make circulation of inside air in occupiedzone (Anderson and Albert 1999). Although suchdevelopment was successful in certain respects (e.g.,economizing the energy cost), it was also hamperedby other factors like the degradation of air quality(Jones 1999). The extent of exposure to indoor airpollutants can be regulated by an interaction betweentheir indoor source strengths and the entrapped timein indoor environments. As people commonly stay inindoors for up to 22 h per day, individuals are at a riskof adverse health effects through their exposure over asustained period (Jonathan and Bernstein 2008).

Indoor air pollutants are commonly emittedfrom several indoor compartments, e.g., waxes,paints, furnishing, clothing, building materials, andpersonal sources (McKone 1999). Indoor environ-ment was hence favorable to emit a large quantity ofair pollutants including particulate matter (PM),formaldehyde (HCHO), bioaerosol, etc. (Morey andShattuck 1989). To date, the availability of variousconstruction techniques has been the main cause topromote the rapid consumption of synthetic buildingmaterials. In addition, poor management (e.g., delay-ing maintenance to save money) also led to increasesin indoor air pollution (IAP) from indoor sources andventilation systems.

If the heating, ventilation, and air conditioning(HVAC) system is not properly maintained, thecombined effects of such factors can worsen thesituation as the key sources of indoor pollution.Biological contamination can also proliferate in moistcomponents of the system throughout the building(Bholah et al. 2000). As most indoor air pollutantsdirectly affect the respiratory and cardiovascularsystems, certain parts of the population (like youngand elderly) can suffer from respiratory disease (orhyperresponders) more severely (Singh 1996). Airquality at these facilities is of special concern, aschildren can be affected more sensitively by changesin air quality due to their weaker resistance. However,indoor air problems are not always easily recogniz-able to take preventive measures (US EPA 1996).

The purpose of this study was to characterize theconcentrations of several key indoor pollutants in fourdifferent types of indoor facilities including [child carefacilities (CC), medical facilities (MF), elementaryschools (ES), and postnatal care centers (PC)]. To this

end, the concentrations of important indoor air pollu-tants were measured from the above-mentioned facili-ties and were used to evaluate the status of theirpollution. Diverse aspects of IAP are discussed basedon the results of our investigation conducted in severalcities of Gyeonggi province in Korea from February2006 to December 2009 (Fig. 1).

Method

Gyeonggi province is the most populous province inSouth Korea, as it fully surrounds the capital city ofSeoul in the western central region of the Peninsula. Thisprovince is located between 126° and 127° eastlongitude and 36° and 38° north latitude. Its climate iscontinental style with a severe differentiation in temper-ature between hot and humid summer and cold andsnowy winter. The annual temperature is between 11°Cand 13°C; it is known that the temperature in themountainous areas to the northeast is lower, while that inthe coastal areas to the southwest is higher. August is thehottest month with 20–26°C of average, and January isthe coldest month with −5 to 5°C of average. The sites ofIAQ sampling were randomly selected to include a totalof 91 indoor sites (43 CC, 38 MF, 6 ES, and 4 PC) in 18different cities within Gyeonggi province. These facil-ities were located both in the densely populatedresidential and commercial areas in the urban districtsthat are adjacent to heavy traffic roads. Ventilationsystems of these facilities, especially in CC and MF, aremaintained by central HVAC.

In this study, the IAP was investigated with respectto several key components including PM10 (particu-late matter with a diameter of less than 10 μm),carbon dioxide (CO2), carbon monoxide (CO), form-aldehyde (HCHO), and bioaerosol. The collection ofsamples was made from 1.1 m above the floor level ateach site. Temperature and relative humidity in thesefacilities were measured by a thermohygrometer(Testo 608-H1, Germany) and found in the range of20–28°C and 32–56%, respectively.

Details of the operating conditions along with thebasic information of quality assurance [e.g., precisionand method detection limit (MDL)] for all instrumentsused in this study are summarized in Table 1. Theparticle mass, determined by gravimetric method (con-tinuous weighing of particles deposited onto a filter), isused for the derivation of its mass concentration by

6396 Environ Monit Assess (2012) 184:6395–6409

considering the filter weights (before and after thesampling) along with the volume information of airdrawn through the filter. PM10 samples were collectedon a 0.5-μm pore, 47-mm Teflon filter (Advantec,MFS, Inc., Japan) via portable air samplers at a flowrate of 3 Lmin−1 (Microvol 1100; Ecotech, Australia).

N

2 km

Fig. 1 A geographical map of the cities selected for IAQanalyses (Gyeonggi province, Korea)

Tab

le1

The

operationalcond

ition

sandthebasicQA

inform

ationof

allinstrumentalsystem

sem

ploy

edin

thisstud

y

PM

10

CO2

CO

HCHO

Bioaerosol

Principle

Gravimetricmethod

Nondispersive

infrared

sensor

(NDIR)

NDIR

HPLCa

Impactb

Model

Microvol1100

API-360E

API-300E

Alliance

2695

MAS-100

Maker

Ecotech,Germany

Teledyne

API,CA,USA

Teledyne

API,CA,USA

Waters,MA,USA

MERCK,NJ,USA

Precision

(%)

0.50

±2±2

2.50

MDL

–0.1

0.4

0.8

–

Flow

rate

3Lmin

−1800cm

3min

−1800cm

3min

−11mLmin

−1100Lmin

−1

Sam

plingtim

e8h

1h

1h

–5min

aDetector—

photod

iode

arraydetector,Waters;

wavelength—

360nm

;column—

XTerra

RP18

,Waters,

4.6×15

0mm,5μm,13

7°A;mob

ileph

ase—

distilled

water

40%

+acetronitrile

60%;injectionvo

l.—10

μl;ov

entemperature—40

°CbForty-eight

hourscultu

ring

at35

°C

Environ Monit Assess (2012) 184:6395–6409 6397

The concentrations of CO2 and CO were measuredby the relationship between infrared (IR) energyabsorbed by a sample and that absorbed by areference (according to the Beer–Lambert law). Thisis accomplished by using a gas filter wheel whichalternately allows a high-energy IR light source topass through a chamber filled with CO2 or CO and achamber without them. HCHO was collected bypulling air through a 2,4-dinitrohydrazine (DNPH)-coated silica gel cartridge (Supelco, PA), with a flowrate of 0.8 Lmin−1 for 10 min. The DNPH–HCHOderivative eluted with acetonitrile was determined byhigh-performance liquid chromatography (Gilbert etal. 2008). For bioaerosol analysis, an MAS-100 airsampler (a multijet impactor plate with 400 holes;Merck, Germany) was used to collect samples at aflow rate of 100 Lmin−1 for 5 min. The resultingairstream is directed onto an agar surface in a standardpetri dish (diameter 90 mm). The impaction speed ofthe airborne microorganisms on to the agar surface isapproximately 11 ms−1 which corresponds to stage 5in the typical six-stage Andersen impactor (Merck1999). Casein soybean digest agar was used for totalbioaerosol determination. Before that, agar plateswere incubated at 35°C for 48 h. The results ofcolony-forming unit (CFU) were calculated andreported as CFU per cubic meter of sampled air.

Results and discussions

General status of indoor air pollution

Table 2 shows statistical summary of IAP levelsmeasured during the study period. The status of IAPis also displayed in a box plot diagram in Fig. 2. Themean (±SD) concentration values of PM10 in the twomajor types of indoor facilities were fairly compara-ble with 77.0±29.9 (CC) and 74.0±23.6 μg m−3

(MF). In contrast, those of PC and ES fell in arelatively wide range of 93.5±9.47 and 66.7±15.8 μg m−3, respectively. Among 7 out of 91individual data (e.g., one in PC, four in CC, and twoin MF), PM10 levels were recorded above the Koreanindoor air standard (KIAS) guideline (i.e., 100 μg m−3,KMOE 2005), although none of their mean valuesexceeded such guideline.

The concentrations of PM10 in the indoor environ-ment can be directly influenced by outdoor source

activities such as construction work, traffic condition,cooking activities in the nearby restaurants, etc. (Nyand Lee 2010; Wang et al. 2006; Kojima et al. 2010).However, in some indoor environments with specif-ically identified sources of pollution (e.g., smoking,fuel combustion for heating and/or cooking, etc),human-related activities at room (e.g. cleaning,walking, and working) can contribute to resuspensionof fine particles which lead to increases in particulatelevels (Chao and Wong 2002). As most of theseKorean facilities were built as airtight, the effect ofoutside environment is not noticeably large enough toalter the indoor PM10 concentrations (Baek et al.1997). Moreover, routine maintenance of HVACsystem and controls on other indoor sources (e.g.,smoking, fuel combustion for heating, etc.) helpedkeep the PM10 levels in a moderate level.

CO2 is not itself a pollutant under the mostcircumstances (Arens and Baughman 1996). Howev-er, as a key component of IAQ, CO2 concentrationsdirectly or indirectly reflect human activities, produc-tivity, and health symptoms (Daisey et al. 2003;Shendell et al. 2004). Throughout the study period,the mean CO2 concentrations in these target indoorfacilities fell in the range between 192 and 1,294 ppmin some relations with the airtightness of eachbuilding. Its mean values in two major sites wererecorded as 589±178 (CC) and 637±185 ppm (MF).As seen in the case of PM10, the CO2 results of thetwo other sites were also more variable with 582±72.3 (PC) and 702±174 ppm (ES). In only three cases(i.e., two in CC and one in MF), CO2 levels exceededthe guideline value (1,000 ppm) set to ensure enoughfresh air (KMOE 2005; ASHRAE 2004). Under mostcircumstances, the exceedance of this guideline issuspected to be caused by insufficiency of fresh airdue to poor ventilation.

Among the four facilities, the highest mean CO2

concentration was observed in ES. The closing ofwindows and doors during lecture hours may causeinefficient ventilation of CO2 under the overcrowdedclassroom conditions. As such, indoor environmentscan be influenced more sensitively by human occu-pancy than by the outdoor environments (Fromme etal. 2007). In a recent review, it was mentioned thatincreased indoor CO2 levels were positively associ-ated with one or more prevailing SBS symptoms(Dounis and Caraiscos 2009). SBS symptoms associ-ated with CO2 are identified to include headache,


Table 2 Statistical summary of indoor air pollutants measured across four seasons during the entire study period (February 2006 toDecember 2009)

Compound Unit Season Site type

All Child care facility(CC)

Medical facility(MF)

Elementary school(ES)

Postnatal carecenter (PC)

PM10 μg/m3 All 75.8±26.2 (75.6)a 77.0±29.9 (74.0) 74.0±23.6 (76.0) 66.7±15.8 (60.5) 93.5±9.47 (94.5)

15.9–171 (91)b 15.9–171 (43) 23.8–120 (38) 55.0–96.0 (6) 81.0–104 (4)

Spring 78.7±24.9 (77.2) 71.5±35.3 (70.7) 82.3±18.6 (81.2) –c –

15.9–122 (18) 15.9–122 (6) 59.0–120 (12)

Summer 72.9±22.3 (72.9) 73.9±23.2 (73.5) 70.3±22.0 (68.5) – 95.0d

25.0–105 (31) 28.0–105 (16) 25.0–96.8 (14)

Fall 80.9±29.6 (75.8) 93.6±32.1 (82.5) 70.8±27.6 (74.4) 66.7±15.8 (60.5) 104

24.9–171 (26) 56.9–171 (13) 24.9–116 (6) 55.0–96.0 (6)

Winter 66.3±27.6 (76.9) 60.5±26.2 (60.1) 66.9±32.7 (82.9) – 87.5±9.19 (87.5)

23.8–98.4 (16) 29.4–98.4 (8) 23.8–94.0 (6) 81.0–94.0 (2)

CO2 ppm All 616±178 (609) 589±178 (514) 637±185 (625) 701±174 (660) 582±72.3 (574)

192–1,294 (90) 377–1,068 (43) 192–1,294 (37) 510–945 (6) 510–670 (4)

Spring 614±167 (677) 674±167 (678) 584±170 (599) – –

414–941 (18) 414–941 (6) 192–816 (12)

Summer 598±177 (558) 547±135 (506) 667±211 (621) – 538

380–1,294 (30) 380–817 (16) 389–1,294 (13)

Fall 613±186 (535) 575±220 (471) 611±152 (564) 701±174 (660) 609

377–1,068 (26) 377–1,068 (13) 457–901 (6) 510–945 (6)

Winter 667±161 (660) 633±186 (616) 738±131 (673) – 590±113 (590)

415–1,031 (16) 415–1,031 (8) 656–993 (6) 509–670 (2)

CO ppm All 0.78±0.52 (0.55) 0.69±0.47 (0.50) 0.90±0.57 (0.80) 0.47±0.08 (0.45) 1.18±0.55 (1.05)

0.20–2.55 (90) 0.25–1.90 (43) 0.20–2.55 (37) 0.40–0.60 (6) 0.70–1.90 (4)

Spring 0.83±0.36 (0.85) 0.98±0.49 (1.00) 0.76±0.28 (0.85) – –

0.25–1.60 (18) 0.35–1.60 (6) 0.25–1.10 (12)

Summer 0.74±0.56 (0.55) 0.68±0.40 (0.50) 0.81±0.74 (0.60) – 0.70

0.20–2.55 (30) 0.30–1.40 (16) 0.20–2.55 (13)

Fall 0.73±0.54 (0.50) 0.63±0.48 (0.450) 0.97±0.69 (0.68) 0.47±0.08 (0.45) 1.30

0.30–2.25 (26) 0.30–1.80 (13) 0.40–2.25 (6) 0.40–0.60 (6)

Winter 0.94±0.63 (0.751) 0.59±0.55 (0.42) 1.27±0.52 (1.30) – 1.35±0.78 (1.35)

0.25–1.90 (16) 0.25–1.90 (8) 0.35–1.75 (6) 0.81–1.90 (2)

HCHO ppb All 19.9±13.4 (15.9) 18.4±8.72 (18.2) 24.3±18.8 (12.4) 12.4±0.05 (12.4) 14.7±3.46 (14.7)

3.85–69.6 (74) 3.85–40.8 (39) 4.55–69.6 (27) 12.3–12.4 (6) 12.2–17.1 (2)

Spring 17.0±9.68 (12.4) 20.5±13.1 (28.5) 15.1±7.45 (12.4) – –

3.85–34.6 (14) 3.85–31.1 (5) 11.2–34.6 (9)

Summer 27.4±15.5 (24.4) 21.8±8.54 (22.5) 35.2±19.7 (29.3) – –

9.90–69.6 (20) 9.90–40.8 (14) 14.5–69.6 (6)

Fall 16.3±7.40 (14.4) 18.2±6.95 (20.6) 16.5±10.9 (12.3) 12.4±0.05 (12.4) –

3.95–35.5 (24) 3.95–25.1 (12) 4.55–35.5 (6) 12.3–12.4 (6)

Winter 17.3±15.4 (12.9) 11.4±4.69 (12.9) 26.0±22.9 (13.5) – 14.7±3.46 (14.7)

3.85–64.1 (16) 3.85–18.1 (8) 8.55–64.1 (6) 12.2–17.1 (2)

Bioaerosol CFU/m3 All 345±279 (288) 418±283 (395) 231±198 (159) 620±317 (780) 55.5±39.3 (46.5)

1.00–1,222 (80) 1.00–1,222 (40) 2.00–740 (30) 210–900 (6) 19.0–110 (4)

Spring 306±222 (285) 381±258 (450) 250±187 (258) – –

2.00–705 (14) 2.00–705 (6) 21.0–570 (8)

Summer 320±21 (345) 397±202 (430) 250±206 (225) – 19.0


fatigue, eye symptoms, nasal symptoms, respiratory tractsymptom, and total symptom scores (Wang et al. 2008).

Carbon monoxide is an extremely toxic gas whichinterferes with the oxygen transport mechanism ofblood. It can cause cardiovascular disease andsymptoms such as headaches, nausea, fatigue, rapidbreathing, chest tightness, and impaired judgment(Modic 2003). The overall mean (±SD) concentrationof CO measured in this study was 0.784±0.518 ppm.Its concentrations in the two major sites were 0.69±0.47 ppm (CC) and 0.90±0.57 ppm (MF), while thoseof the other two were again widely variable to show0.47±0.08 ppm (ES) and 1.18±0.55 ppm (PC).Fortunately, CO concentrations in all cases weremuch lower than the indoor guidance level of CO(e.g., 10 ppm by KIAS, KMOE 2005). In indoorenvironment, CO is released as a result of incompletecombustion by gas cooking and/or space heating.Other important sources of CO in indoor areidentified to include both indoor sources (e.g.,tobacco smoking) and outdoor sources e.g., vehicleexhaust fumes entering the building (Georgoulis et al.2002; Kim et al. 2010; Baek et al. 1997).

Formaldehyde (HCHO) is a chemical ingredientused in many building materials, fabrics, cleaningfluids, and adhesives. The most common sources offormaldehyde emissions in buildings are plywood,particle board, carpets, and urea–formaldehyde foaminsulation which have been used frequently in moderninteriors (Gilbert et al. 2008). In this study, the meanconcentrations of HCHO measured in the two majorsites were 18.4±8.72 (CC) and 24.3±18.8 ppb (MF).In contrast, its values were much lower in the two

other sites to record 14.7±3.46 ppb (PC) and 12.4±0.05 ppb (ES). As such, none of the HCHO values inthis study were exceeding the guideline of KIAS (e.g.,100 ppb, KMOE 2005). Between four facilities, thehighest mean concentrations of HCHO (e.g.,24.3 ppb) were measured in MF. These relativelyhigh concentrations may be due to the emissions fromthe detergents and cleaning agents as these compo-nents are often used to keep the area germ free in MFs(Jones 1999).

Bioaerosols, especially bacterial and fungal origins,are another potential source of IAP, as they can causemore serious damages than the common contaminantswith the chemical nature. Harmful bioaerosol popula-tions, once built in the HVAC system or occupied incertain spaces of a building, may be produced episod-ically to cause or affect SBS (Cummings and Withers1998). Indeed, bioaerosol-related SBS can be moreenduring and recalcitrant to treatment than those withmultiple chemical exposures (Arens and Baughman1996). The mean concentrations (CFU per cubicmeter) of the total suspended bacteria measured inCC and MF were 418±283 and 231±198, respective-ly. In contrast, those in PS and ES were again variableenough to show 55.5±39.3 and 620±317, respective-ly. Only two out of 80 recorded cases (each one of CCand ES) were found above the recommended

Table 2 (continued)

Compound Unit Season Site type

All Child care facility(CC)

Medical facility(MF)

Elementary school(ES)

Postnatal carecenter (PC)

1.00–690 (28) 1.00–690 (15) 2.00–610 (12)

Fall 412±359 (220) 538±395 (550) 158±135 (115) 620±317 (780) 56.0

5.00–1,222 (24) 88.0–1,222 (11) 5.00–400 (5) 210–900 (6)

Winter 280±243 (192) 321±245 (242) 296±276 (135) – 73.5±51.6 (73.5)

28.2–798 (14) 28.2–798 (8) 104–740 (5) 37.3–110 (2)

aMean±SD (median)bMinimum–maximum (no. of data)c Data are not availabled No. of data is 1

Fig. 2 a–e Box plot of indoor air pollutant distributioninvestigated in this study: all data vs. four individual indoorfacility types (center lines in the boxes indicate the median,border of the boxes are the 25th and 75th percentiles, andvertical lines represent the range of values)

b


0

40

80

120

160

200

llACPSEFMCCSite type

(a) PM10

0

400

800

1200

1600


Con

cent

ratio

n (p

pm)

(b) CO2

0.0

0.5

1.0

1.5

2.0

2.5

3.0


Con

cent

ratio

n (p

pm)

(c) CO

0

20

40

60

80


Con

cent

ratio

n (µ

g/m

3 )C

once

ntra

tion

(µg/

m3 )

(d) HCHO

0

400

800

1200

1600


Con

cent

ratio

n (C

FU

/m3 )

(e) Bioaerosol


guideline value (e.g., 800 CFU m−3) for bioaerosol inKorea.

In this investigation, the highest mean concentra-tion of bioaerosol (e.g., 620 CFU m−3) was found inthe ES classrooms. One possible cause for thisobservation may be the higher occupancy and activityin the classrooms. This assertion is also supported bya number of previous studies in which indoor humanoccupancy was found to affect indoor microbiallevels, as settled spores were resuspended by humanactivities (e.g., walking and running in indoor sites);this effect is assumed to be more pronounced inyounger children (Jo and Seo 2005; Scheff et al.2000; Buttner and Stetzenbach 1993). Anotherpossible explanation is the environmental conditionssurrounding the classrooms, as plants and soil in theschool playgrounds can offer the important sources ofmicroorganisms (Li and Kendrick 1995; Hargreaveset al. 2003).

Seasonal variation of indoor air pollutants

Buildings are built to be energy efficient to hold heatduring the winter, while releasing the heat out duringthe summer. Sealing off the indoor from any freshoutside air can raise the concentrations of bothallergens and pollutants inside the building. Toevaluate the seasonality in the distribution of indoorair pollutants investigated in this study, the data foreach facility group and the whole data (without anydistraction) were compared after being divided intofour seasons: spring (March–May), summer (June–August), fall (September–November), and winter(December–February; Table 2). The occurrence pat-terns of the maximum seasonal mean concentrations,if assessed from the pooled data sets of all fourgroups, are distinguished greatly between pollutants(Fig. 3).

In our study, the highest mean concentration ofPM10 in the pooled data set was measured during fall(80.9 μg m−3). If the values are compared betweendifferent facilities, the highest mean and the maxi-mum PM10 levels for CC were seen in fall seasonwith the values of 93.6 and 171 μg m−3, respectively.In contrast, in case of MF, the largest seasonal mean(82.3 μg m−3) and maximum values (120 μg m−3)were seen during spring. The highest seasonal meanconcentration of CO2 for the pooled data group wasmeasured in winter with the value of 667 ppm. In case

of CC, the highest seasonal mean was observed inspring (674 ppm) followed by winter (633 ppm). Incontrast, in case of MF, the largest mean values wereseen during winter (738 ppm). Measurements of CO2

levels have been found to be elevated in many childcare centers in winter, as seen in this study. Likewise,the mean concentration of CO2 in CCs was found1,500 ppm in Norway (THF 1987), 1,400 ppm inDenmark (Pejtersen et al. 1991), and 1,500 ppm inCanada (Daneault et al. 1992) during winter. Themean concentration of CO2 in classrooms of Germanywas also recorded as 1,759 ppm in winter but droppednoticeably to 414 ppm in summer (Fromme et al.2007). The distinctive seasonal trend in indoor airpollution is most likely due to the different ventilationpractice across seasons and is reflected fairly sensi-tively by CO2 level changes. Due to frequentventilation in summer, the levels of indoor pollutionare affected more effectively by outdoor conditions.In contrast, its pattern for colder seasons (e.g., winter,spring) may be influenced more tightly by indooractivities unlike other seasons.

Carbon monoxide is one of the most hazardousindoor air pollutants given off by the combustion(IEH 1996). In indoor environment, it can beproduced by heating systems, wood-burning stoves,fireplaces, water heaters, dryers, and stoves. This isthe reason why CO levels are generally high in winterin indoor environment. In our study, its highest meanin CC (0.98 ppm) was measured in spring, while thatfor MF during winter (1.27 ppm). In one study at foururban hospitals in USA, the average CO level wasfound 2.2 ppm during winter and 0.88 ppm insummer (Allen and Wadden 1992).

In our study, the largest seasonal mean concentra-tion of HCHO in CC was measured in summer(20.5 ppb), while that of MF during spring (41 ppb).In contrast, its seasonal maximum values in both CCand MF peaked consistently in summer 40.8 and69.5 ppb, respectively. In a previous study in UK,enhancement in HCHO levels was also observedduring summer (e.g., 90 ppb) relative to winter (e.g.,70 ppb, Jones 1999). The level of formaldehydepollution is known to vary by several parameters suchas the age of the source, ventilation system, temper-ature, and humidity, while such variation is dynamicenough to exhibit patterns during the course of a dayor across seasons (Hayashi and Osawa 2008). Due tothe effect of temperature and relative humidity, indoor


50

60

70

80

90

100

110

120

retniWgnirpSremmuSllaF

Season

CC

MF

(a) PM10

450

500

550

600

650

700

750

800


Season

Con

cent

ratio

n (p

pm)

CC

MF

(b) CO2

0.0

0.5

1.0

1.5

2.0

retniWgnirpSremmuSllaFSeason

Con

cent

ratio

n (p

pm) CC

MF

(c) CO

10

20

30

40

50

retniWgnirpSremmuSllaFSeason

Con

cent

ratio

n (p

pb) CC

MF

(d) HCHO

0

75

150

225

300

375

450

525

600

675


Season

Con

cent

ratio

n (C

FU

/m3 )

CCMF

(e) Bioaerosol

Con

cent

ratio

n (µ

g/m

3 )


Fig. 3 a–e Seasonal patterns of each individual indoor air pollutant: comparison between different facilities

microbial concentrations were also found to increaseduring summer than winter (Yang et al. 2009; Jo andSeo 2005; Ren et al. 1999).

Unlike the general expectation, the seasonal meanand the maximum concentration of bioaerosol in CCtended to peak during fall with 538 and 1,222 CFUm−3,respectively. In MF, the seasonal mean and themaximum value of bioaerosol were found in winterwith their values of 296 and 740 CFU m−3, respec-tively. However, in one of previous study in Korea,microbial concentrations were significantly higher inthe summer than in the winter, regardless of sitewhether being indoor or outdoor (Jo and Seo 2005).In contrast, in another study covering homes andoffice rooms in upper Silesia industrial zone inPoland, no seasonal differences were observed in thebacterial concentrations (Pastuszka et al. 2000).

To check for the statistical significance in seasonalpatterns of diverse variables, we evaluated the differ-ences between the two largest seasonal values. In allcases, the differences in mean values between the twoseasons were not significant enough (((P>0.05),0.12–0.88); here, the P value denotes the probabilityof no correlation). The results thus suggest that theseasonal dominance of indoor pollutant concentra-tions is not necessarily significant processes in mostcases.

In order to learn more about the relationshipbetween indoor air pollutants, Pearson's correlationanalysis was conducted using the data from allfacilities as well as the two major facilities (CC andMF, Tables 3 and 4). In case of the pooled data setsfrom all facilities, 3 out of 10 matching pairs werecorrelated significantly (P<0.01). The cases of strongcorrelations are seen fairly abundantly between CO2,CO, and HCHO and also between CO and HCHO. Inthe CC, the strongest pairs (P<0.01) were observedbetween (1) HCHO and CO and (2) bioaerosol withPM10 and HCHO. Likewise, there was a strongcorrelation between CO2 and CO (P<0.05). On theother hand, significant correlations were observedbetween CO, PM10, and CO2 in MF. In one of theprevious studies made in urban dwellings in Uppsala,mid-Sweden, strong correlations were observedbetween CO2 and HCHO (Norback et al. 1995).Jiménez et al. (2000) also found an extremelysignificant correlation between HCHO and CO (r=0.99) in a wastewater treatment plant in Switzerland.Low ventilation or insufficient outdoor air supply

may cause the significant correlations between someparameters (such as CO2, CO, and HCHO).

Comparison of IAQ levels between different studies

IAQ has a significant impact on human health andcomfort. Poor IAQ can lead to discomfort, ill health,absenteeism, and low productivity. IAQ depends onthe different parameters such as the outdoor air, thebuilding location, number of people, the ventilationsystem in the building, etc. The health effects of IAQare dependent on the combined effects of severalfactors such as type of pollutants and their concen-tration levels, exposure duration, and individualsensitivity. Many studies have focused on the indoorair quality in child care centers, hospitals, schools,offices, and houses. In order to diagnose the presentstatus of indoor air pollution against those of differentfacilities, the data measured in this study are comparedwith some previous studies (Table 5). Table 6 listed theguidelines for criteria pollutant levels in indoor bydifferent international organizations.

In a previous study, the average PM10 concen-trations in four hospitals in Guangzhou city, Chinawere 128 μg m−3 (Wang et al. 2006) which is farhigher than our MF values (e.g., 74 μg m−3). Thisnotable difference can be explained by the fact thatthe Chinese hospitals were located in the denselypopulated areas in the urban districts and adjacent toheavy traffic road nearby. Moreover, poor ventilationsystem and high patient density may have contributedto higher PM10 concentrations in those hospitals.

However, in ES, the mean PM10 concentration valuesin three studies fell in a similar range (e.g., 66.7–77.9 μg m−3) except the Hong Kong study (e.g.,103 μg m−3). Among all the reported data sets ofCO2, the largest levels can be found from the data setsderived from 26 daily facilities in a midwesterncounty of the USA (1,142 ppm, Ferng and Lee2002). The CO2 values measured in Singapore(713 ppm) (Zuraimi and Tham 2008) and Finland(810 ppm, Ruotsalainen et al. 1993) were larger thanours by 21.1% and 37.5%, respectively. In the presentstudy, CO2 concentrations in ES were moderatelylower than four other ES in other countries. In anotherstudy made at nursery and elementary schools inGreece, CO2 levels were far beyond the Europeanstandards (e.g., 800 ppm, CEN 1999), especially atthe end of each lesson; the maximum values were


Tab

le3

Resultsof

correlationanalysisbetweenindo

orairpo

llutantsof

differentdata

grou

ps

All

Child

care

facility

Medical

facility

PM

10

CO2

CO

HCHO

Bioaerosol

PM

10

CO2

CO

HCHO

Bioaerosol

PM

10

CO2

CO

HCHO

Bioaerosol

Correlatio

nanalysis

PM

10

r1

11

P N91

4336

CO2

r0.02

10.25

1−0

.28

1

P0.85

0.09

0.10

N90

9043

4335

35

CO

r−0

.08

0.49

a1

0.08

0.33

b1

−0.36b

0.72

a1

P0.45

1.0E

-06

0.62

0.03

0.03

1.1E

-06

N90

9090

4343

4335

3535

HCHO

r0.06

0.35

a0.39

a1

0.06

0.24

0.53

a1

0.04

0.48

b0.31

1

P0.63

0.002

4.6E

-04

0.72

0.14

0.001

0.83

0.01

0.11

N74

7474

7439

3939

3927

2727

27

Bioaserosol

r0.18

0.19

0.066

0.014

10.41

a0.21

0.31

0.42

a1

−0.11

0.22

0.20

−0.07

1

P0.11

0.08

0.563

0.914

0.01

0.19

0.05

0.01

0.57

0.26

0.30

0.76

N80

8080

6780

4040

4036

4028

2828

2328

aCorrelatio

nissign

ificantat

theP≤0

.01level(twotailed)

bCorrelatio

nissign

ificantat

theP≤0

.05level(twotailed)


achieved near 4,000 ppm (Theodosiou and Ordoum-pozanis 2008). The concentrations of several keyparameters (CO, HCHO, and bioaerosol) measured inthis study were low relative to ones measured in otherES in Korea and Hong Kong (Yang et al. 2009; Leeand Chang 2000), as shown in Table 5. Especiallybioaerosol concentrations in these two studies werealmost two times higher than what were seen in ourstudy. In ES, HCHO is suspected to be released frompressed wood desks and shelving units (Lee andChang 2000). Godish (1996) reported that bioaerosolconcentration in classrooms depended on furnishingmaterials and moisture condition of the building.

Conclusion

Due to the gradual deterioration of air quality in urbanareas, people become increasingly aware of theimportance of good air quality as a safeguard to theirhealth. This study provides a detailed and compre-hensive IAQ investigation to diagnose the level ofindoor pollution in many indoor facilities in Korea.The measurements conducted in CC and MF alongwith two other facilities (e.g., ES and PC) were ableto derive the basic patterns of IAQ. None of thereadings for CO and HCHO exceeded the KIASguideline level. Only seven, three, and two cases werereported to exceed the KIAS guideline (PM10, CO2,and bioaerosol, respectively). The indoor air pollu-tants showed distinct seasonal variation. The extentof indoor pollution appears to be tightly associatedwith varying ventilation practice in different sea-sons. Some pollutants (e.g., PM10, HCHO, andbioaerosol) reportedly exhibited higher concentrationsin warmer seasons, while the others (e.g., CO2 andCO) tend to be measured higher in winter. Thesekinds of trends were also justified by some of theprevious studies.

Table 5 Comparison of indoor air pollutant data measured at different areas around the world

Facility PM10

(μg/m3)CO2

(ppm)CO(ppm)

HCHO(ppb)

Bioaerosol(CFU/m3)

No. ofdata

Period City Country Reference

Child care 77.0 589 0.692 18.4 418 91 Feb 2006 toDec 2009

Gyeonggiprovince

Korea This study

Facility – 713 1.1 – – 104 May to Aug 2007 Singapore Singapore Zuraimi andTham (2008)

(CC) – 810 – – – 30 Oct to Nov 1990 Espoo Finland Ruotsalainenet al. (1993)

– 1,142 – – – 26 March toApril 2001

Midwesterncountry

United States Ferng and Lee(2002)

– – – – 735 28 Feb to May 1995 Taipei Taiwan Li et al. (1996)

Medical 74.0 637 0.901 24.3 231 91 Feb 2006 toDec 2009

Gyeonggi province Korea This study

facility (MF) 128 – – – – 12 Aug 2004 toSep 2004

Guangzhou China Wang et al.(2006)

Elementaryschool(ES)

66.7 702 0.47 12.4 620 91 Feb 2006 toDec 2009

Gyeonggi province Korea This study

77.9 965 0.75 100 1,309 55 July to Dec 2004 Six metropolitanareas

Korea Yang et al. (2009)

71.7 890 – – – 92 May 2005 toJuly 2005

Munich andsurrounding area

Germany Fromme et al.(2007)

103 880 – 27 1,000 5 Nov 1997 toJan 1998

Hong Kong Hong Kong Lee and Chang(2000)

72.1 1,051 – – – 4 Feb 2006 toMarch 2006

Frankfurt Germany Heudorf et al.(2009)

Table 4 Summary of correlation analysis between indoor airpollutants for different data groups

Sample source Frequency at significance level

0.01 0.05

All 3 –

Child care facility 3 1

Medical facility 1 2

Maximum possible number of matching pairs=10


This study revealed that the indoor air pollutants inthe Korean facilities investigated in this research werein most cases noticeably lower than the KIASstandard. Although IAP is designated to constitutethe top five environmental health risks, it is a complexissue in terms of toxicology and health risk assess-ment (US EPA 2009). In addition, the compositionand concentrations of the different components inindoor air vary widely and are influenced by humanactivities. Because it is not feasible to regulate allpossible scenarios, prevention from possible healtheffects and protection of sensitive populations shouldbe best achieved by reducing exposure level. The goalof safe and healthy air should focus on the improve-ment of various factors such as ventilation, cleaningconditions, properties of buildings, cultural habits,climate, outdoor air, etc. More studies should hencebe undertaken to achieve the whole picture of theindoor pollutant distribution. Future research musthelp us fully acknowledge the complex nature of theindoor environment in order to provide a sound basisfor setting the proper standards.

Acknowledgment This work was supported by a NationalResearch Foundation of Korea grant funded by the Ministry ofEducation, Science and Technology (No. 2009–0093848).

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Indoor air quality assessment in child care and medical facilities in Korea

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