AIVC 11680

I11daor Air 1998; 8: 140--152 Printed in Denmark. All rigl1ts reserved

ISSN 0905-6947

Development of New Volatile Organic Compound (VOC Exposure Metrics and their Relationship to "Sick Building Syndrome" Symptoms

J. TEN BRINKE1'4'5, S. SELVIN2, AT. HoocsoN1, W. J. FrsK1, M. J. MENDELL3, C. P. KosHLAND4 AND J. M. DAISEY1*

enced by office workers in Eu rope and the Un Abstract Occupants of office buildings are exposed to low concen­ States. SBS is defined by the World Health Organ trations of complex mixtures of volatile organic compounds tion as a complex of subchronic symptoms that Ol (VOCs) that encompass a number of chemical classes and a broad while occupants are irt a building and generally range of irritancies. "Sick building syndrome" (SBS) is suspected crease when they l e . The symptoms include i to be related to these exposures. Using data from 22 office areas eav in tation of the eyes, nose, or throat, headache, fatif 12 California buildings, seven VOC exposure metrics were de­ veloped and their ability to predict self-reported SBS irritant symp­ dry or itchy skin, and difficulty breathing or d toms of office workers was tested. The VOC metrics were each tightness. SBS is most evident in the extreme case� evaluated in a multivariate logistic regression analysis model ad­ which the building occupants experience u nusually justed for other risk factors or confounders. Total VOCs and most vere, frequent, or widespread symptoms. Surv y� of the other metrics were not statistically significant predictors of office buildings conducted in the U .S. and in Eun symptoms crude or adjusted analyses. Two metrics were de­ in suggest that 20% or more of occupants in buildi veloped using principal components (PC) analysis on subsets of without known problems frequently experience � the 39 VOCs. The Irritancy /PC metric was the most statistically significant predictor of adjusted Lrritant ymptoms. The irritant po­ symptoms (Hedge et al., 1989; Norback and Torg t ncies of individual compounds, highly correlated nature.of in­ 1990; Skov et al., 1990; Mendell, 1991; Zweers et door VO mi tures; and probable presence of potent, but unmeas­ 1992; Mendell et al., 1996). ured, VOCs were arioi1sly factored into thi metric. These results, There are several reasons for suspecting that vola which for the first time show a li11k between low level voe e, - organic compounds (VOes) are a factor in SBS syn posures from specific types of indoor sources to SBS symptoms, re­ toms. Industrial exposures to voes cause the kinds quire confirmation using data sets from other buildings. symptoms observed for SBS. However, indust1 workers are typically exposed to only one or a f1 Key words Volatile organic compounds (VOC); Sick building syndrome (SBS); Total volatile organic compounds (T VOC); voes at very high concentrations. In office buildin. Office buildings; Indoor sources. workers are typically exposed to perhaps a hundr or more voes, each at a concentration that is abou Received 19 fai111nry 1998, Acapted for p11b/irntio11 17 April 1998. © l11door Air 11998) hundred- to a thousand-fold lower than the conCl trations known to cause such symptoms. For this n son, it has been suggested that the total concentrati

of all VOes (TVOe) is a causativ factor in SBS sym Introduction toms. eoncenh·ations of TVOC in office buildings < There is now a large body of evidence that "sick build­ typically about 0.5 mg/m3, although in some buildin ing syndrome" (SRS) symptoms are widely experi- TVOe reaches levels of 2-10 mg/m3. Studies in e

11"rloor £11viroir111e11/ Dcpnrl111t•11/, E1wiroi1111e11tnl Energy Ti:c/1110/ogit•s Division, Li1wrc11n• Berkeley NntiQ1tnl Lnborntory, B.•rkdi:y, CA 9472 486-7491, Fax: LlS".', T1tl: (510) (510) 486-7202, E-mail: i111dais1ty ct/bl.gov, 2Dt1p11rt111e11t of Bio ·tntislics, Sdwol of P11bli1: Hm///i, U11iwrsily a11d Hra//11, OH, Cnlifomia, Berkdey, CA, USA, 3Jud11stryn ide Studi<•s Brn11cl1, Natio1111/ /11stitu/I!for Ocrn11a/io11al Safety Ci11ci1111nli, US "Dep11rt111e11t of E11viro11111t111/11I H1taltlt Scie11ce�, School t>f P11b/ic Ht•a//h, University of G1/ifomi11, Bt!l'ke/t!y, CA, USA, 5Dt1p11rt111e11/ of ApJ'lt Social St11di1ts 1111d Social Ri!s<1arc!1, Lllth>crsity of Oxford, Oxfurif, UK, ...A11//10r lo whom i:om:spo11de11cc s/1011/d VI' addrl!sst•d. j

Development of New VOC Metrics and their Relationship to "Sick Building Syndrome" Symptoms

vironmental chambers with simple mixtures of voes between work-related symptoms and various metrics at high total concentrations (5-25 mg/m3) suggest that of voe exposure while controlling for other factors exposures to high concentrations can induce SBS known to affect symptom reporting. 5ymptoms (Molhave et al., 1986; Kjaergaard et al., 1989). Studies in buildings have not generally been able to find relations between measured VOCs and SBS Approach svmptoms, except at high concentrations. However, Study Description SBS symptoms are reported even for buildings with As part of Phase 1 of the California Healthy Building \ow TVOC concentrations. There have been just a few Study (CHBS) (Daisey et al., 1990; Mendell, 1991; Fisk sh1dies in which relationships between low-level voe et al., 1993; Mendell et al., 1996), concentrations of exposures and SBS symptoms were reported. Norback TVOC and of 39 individual VOCs were measured in and Torgen (1990) reported associations between 12 office buildings in the San Francisco Bay Area in TVOC and airway (nasal), general and eye symptoms northern California. Self-administered questionnaires at total hydrocarbon levels of 130 µg m -3; however, (Mendell, 1991) were returned by participants (n=880, TVOC measurements were made 6 months to 4 years 85% response rate) with information on personal, after questionnaire data were gathered. Hodgson et al. psychological, job and workspace factors, as well as (1991) reported associations between voe concen­ SBS symptoms. trations and central nervous symptoms, but the re­ City and county office buildings (excluding jails, lationship was weak when compared with associations hospitals, police stations and fire stations) were chosen between work stress and complaints. Sundell et al. from within San Francisco, Alameda, and Contra Costa (1993) reported negative correlations between TVOC counties. Smoking within all city and county buildings concentrations and symptom prevalences for 29 office was prohibited except in specific areas, none of which buildings in northern Sweden with low TVOC concen­ were included in this study. The selection criteria were: trations. They also found that the TVOC concentrations 1) more than 900 square meters of currently occupied were generally lower in the room air than in the supply office space; 2) at least 45 full-time and at least 10 cleri­ or intake air. The authors suggested that these results cal workers; 3) no unusual pollutant sources; 4) no on­ might be related to chemical reactions of some of the going renovations; and 5) one of three ventilation TVOCs to form more irritating VOCs, such as form­ types: naturally ventilated (NV), mechanically venti­ aldehyde. lated with operable windows and no air conditioning In the work reported here, it was hypothesized that (MV), and mechanically ventilated with sealed win­ there is an association between reported SBS symp­ dows and air conditioning (AC). Ten of the buildings '/. toms and exposures to voes at low concentrations but were located in a moderate climate zone and two of that better exposure metrics than TVOC are needed. the AC buildings were located in a hot climate zone.1 The term "exposure metric" refers to the measurement One of the AC buildings in the moderate climate was and mathematical expression of the potential or actual a classic problem building with a long history of occu­ if agent (or combination of agents) that causes an adverse pant complaints, causes of which had never been 11 health effect. clearly identified. All eligible buildings to which access v In this study, a number of different exposure metrics was granted were included. Workers within selected were developed and tested for the mixtures of voes study spaces of each building were invited to partici­ :l commonly found in indoor air using data collected in pate in the study. Spaces were chosen to be as similar the California Healthy Buildings Study (Fisk et al., across buildings as possible. Open office spaces with 1993). In developing exposure metrics for VOCs, it was cubicles were chosen where possible; in some cases ad­ hypothesized that the variability of the biological po­ joining offices were included. The buildings were 1 tencies of VOCs should be taken into account. Because studied between June and September, 1990. some of the VOCs are highly correlated due to com­ Self-administered questionnaires were used to col­ mon sources, the study also considered how to reduce lect information on the frequency of 15 health symp­ the number of voes to a smaller number of factors toms during the previous week and the previous year, that could be related to sources. The study focused on the SBS symptoms of irritancy which involve stimula­ 1 The climate in the San Francisco Bay area varies substantially tion of the trigeminal nervous system. For this pur­ over relatively short distnnces. During the summer, the average pose, a relative irritancy scale for the voes was first daily maximum temperature varies from 69°F in San Francisco to developed. Multivariate logistic regression analysis 86°F in Contra Costa county to the east. There is essentially no was then used to assess the correlation relationships summer rain and generally moderi:lle <60%) ( relative humidity.

141

. ·. ·. . ,. ' ...... �. < ! _... ·- • •• • �- __ - .. ··;�,;:�.. ·. -�,.\4!,:!..1_� .... .:; "" Brinke, Selvin, Hodgson, Fisk, Mendell, Koshland and Daisey and on demographic, psycho-social, and job-related and two metrics derived using principal compor parameters (Daisey et al., 1990; Mendell et al., 1996) in (PC) analysis of the measured VOCs. For the Chem the week after the VOC measurements were made. For Class metric, concentrations of VOCs within ead this investigation of voe metrics, symptoms reported five chemical classes were summed and regression for the previous week were used. efficients were fit for each class in the metric as par Indoor locations of voe samples were chosen to the multivariate logistic regression model used to represent exposures of the individuals in the selected late SBS symptoms and the metrics (described belo study space(s), e.g., samples were placed at breathing Principal component analysis, which converts hig zone level for a seated person (1.4 m above the floor) correlated variables to a reduced number of lineari; in the center of the study spaces. The VOCs were col­ sums of the individual V0Cs, Or principal compOnE lected on multisorbent samplers for 8-h work day (PC), was used to develop two metrics. Correla periods and were analyzed for TVOC using a flame­ VOCs tend to group on a single PC because cert ionization detector and for individual compounds groups of voes increase or decrease in concentrat using a capillary gas chromatograph-mass spec­ together because they have a common source ty trometer (Hodgson et al., 1991). Some VOCs originate from more than a single sou

The data for the current investigation of the relation­ type and are then associated with more than one 1 ships between occupant symptoms and various met­ Thus, this methodology can apportion the voe amc rics of exposure to voes are a subset of those from the its sources. The PCs may also trace the presence original survey. Since not all individuals were located other compounds that are probably present but are i within reasonable proximity to voe sampling loca­ sampled and analyzed with the usual voe method tions, the final joint voe and symptom database con­ The PC metrics were obtained by principal com1 tained 517 individuals located in 12 buildings with 22 nent analysis of different subsets of the 39 voes. voe samples. principle, all available voes could be used in the pr cipal component analysis. For the CHBS data set, ho Development of Exposure Metrics ever, there were only 22 cases (sites) for which a co In order to take the voe irritant potencies differences plete set of VOC measurements and SBS sympto into account, a relative irritancy scale for the voes was were available. To obtain more robust PC solutio first developed. As there is limited irritancy data for Smaller subsets of 10 Or ll out of the 39 V0Cs W( controlled human exposures to voes, the irritancy used in the analysis (Henry et al., 1984). The subs scale was based on the mouse bioassay developed by Alarie (1966). The mouse bioassay determines the RD50, the concentration of airborne irritant, which causes a 50% decrease in the breathing rate in exposed Table 1 Ordered relative irritancy scale fur 22 VOCs measured mice. The bioassay has been used to test many individ­ the California Healthy Buildings Study ual VOCs and the results are highly correlated with Compound Chemical Class Relative Irritanc thresholds set to protect humans (Alarie, 1981). Miss­ Referenced to Toluene ing data for some voes was estimated from corre­ lations between the RD50 values of the bioassay and Styrene Aromatic 7.9 Ethylacetate Ester 7.6 vapor pressures, by chemical class (Ten Brinke, 1995). n-Butyl acetate Ester 6.2 Since relative irritancy was of interest, the RD50 of each 1,2,3-Trimethylbenzene Aromatic 4.1 VOC of interest was referenced to the RD50 for toluene. n-Hexanal Aldehyde 4.0 n-Pentanal Aldehyde 3.9 The relative irritancy of the most irritating VOCs is 1,2,4-Trimethylbenzene Aromatic 3.6 presented in Table 1. There is more than a factor of 100 m/p-Xylene Aromatic 3.4 1,3,5 -Trimethy !benzene Aromatic 3.16 difference between the most and least irritating voe 2-Ethyltoluene Aromatic 3.15 in this table. o-Xylene Aromatic 3.08 3/4-E thyltoluene The exposure metrics which were investigated are Aromatic 2.9 Ethylbcnzene Aromatic 1.7 summarized in Table 2. These included TVOC; 1:VOC, 2-Butoxyethanol Alcohol 1.6 Toluene Aromatic the sum of the voes i di idually quantiiied by gas 1 (reference) n v Benzene Aromatic 0.46 chrnmatography-mass spectrometry (GC-MS); t(Ir; 2-Propanol Aromatic 0.40 *VOC;), the sum of the VOCs with each weighted by n-Heptane Alkane 0.26 n-Octane Alkane 0.25 its relative irritancy; 2:(0r;*VOC1), the sum of the VOCs Ethanol Alcohol 0.17 with each weighted by its odor threshold (Devos et al., 2-Propanone (acetone) Ketone 0.09 1990) relative to toluene; the Chemical Class metric; n-Nonane Alkane O.Q7

142 � ..:

. .

Development of New VOC Metrics and their Relationship to "Sick Building Syndrome" Symptoms

VOC exposure metrics �nt Table 2 c 1 al Metric symbol Description Exposure metric as used in regression equationa of rvoc Mass sum of VOCs measured with flame ionization Pr· TVOC co­ detector o ' f I:VOCi Sum of individual VOCs quantified by GC/MS Ps · I(VOC)i * ,re­ !:(lr*VOC)i Sum of irritancy-weighted individual compounds. Pi I(lri *VOCi) N). Irritancy weighting based on irritancy relative to toluene where Iri =relative irrita11cy weighting factor for voci illy (Table 1) > Sum of odor-weighted individual compounds. Odor r .ed �(Or*VOC i fo* E(O i *VOCi) weighting based on odor relative to tolueneb where Ori=relative odor weighting factor for VOC, Chemical class Concentrations of individual compounds summed into Pi (Aromatic)+p i ied five chemical classes: Aromatics, Alkanes, Terpenes, (Alkane) + Pk(Terpene) + P1(Chlorina ted) + Pm (Oxidized) �iJ1 Chlorinated, and Oxidized Hydrocarbons where: (Chemical Class)=Sum of concentrations of the VOCs in on each class, and pi, pi, pk, Pt and fim are 11111/tiple regression be. coefficientsfrom logistic regression a11alyses

;ce AF /CP source voes preselected based on prior source identification Ps.1 Ps(4) ·c. vector and source strengths, using the 1/0 ratio; principal component vector 4, P5(4), produced by PCN and ng identified as due to Air Fresheners and Cleaning of Products is used as exposure metric .lot lrritancy /PC voes preselected based on relative irritancy scale and p3 P(3)+p4 P(4) prior source identification; sum of two of the principal components produced by PCA, P(3) & P(4), used as r°­ exposure metric .I n • Ws are regression coefficients from the logistical regression equations :n- b Odor thresholds, taken from Devos et al. (1990), were ordered relative to toluene using the same method as described for irritancy; however, the results are not shown. The CHBS VOCs were well below odor thresholds, i.e., no odor(s) dominated. As an odor N· threshold ordered scale may not be valid due to low exposure levels and the non-additivity of odor thresholds, the ordered scale h- was not reported; however, it was used in an exploratory manner c Principle components analysis (l

were selected on the basis of potential sources and highest or lowest indoor I outdoor (I/O) concentration source strength and relative irritancy of the voes. ratios in eight or more of the 12 study buildings were An important underlying assumption of the current selected. VOCs with high I/0 ratios, predominantly analysis is that each voe exposure metric provides indoor sources, and their tentatively identified sources in some measure of the irritant potency of voe mixtures. included dichloromethane, trichloroethylene, 1,1,1- This assumption is weakest for TVOC and the LVOCi trichloroethane (cleaning and degreasing products); variants. A reasonable hypothesis is that an irritant- or ethanol, 2-propanol, 2-propanone (bioeffluents and odor-weighted sum of voes might be useful in a building materials); n-dodecane, n-pentanal, n-hexa­ model of sensory irritant symptom prediction. The nal, limonene (air fresheners, building materials and chemical class metric is intermediate between the cleaning products). Conversely, VOCs with low I/O ra­ TVOC and irritant-weighted metrics. The principal tios have strong outdoor sources; these included: ben­ component analysis is based on the assumption that zene, m&p-xylene, a-xylene, 2-ethyltoluene, 3&4-ethyl­ emissions from different types of sources have differ­ toluene, 1,2,4-trimethylbenzene, 1,3,5-trimethylben­ ent relative irritancies, and that there could be direct zene, n-pentane, 3-methylhexane (motor vehicle relationships to SBS irritant symptoms. The results of emissions); tetrachloroethylene (dry cleaning); n-de­ the analysis will indicate that this hypothesis has some cane and n-nonane (Other). A subset of 11 VOCs was merit, provided that the appropriate irritant voes are selected that included compounds from all of the tenta­ included in the analysis, as seen in the predictive tively identified sources: trichloroethylene, ethanol, n­ power of the Irritancy/PC metric. dodecane, n-hexanal, limonene, benzene, 1,2,4-trime­ In the principle components analysis, the initial em­ th y !benzene, 1,3, 5-trimethy !b enzene, tetrachloroethy­ phasis was on identifying voe sources that were com­ lene, n-decane, and n-nonane. mon across the buildings and voes were selected for Four vectors were obtained from the PC analysis of inclusion in the analysis using a criterion of potential VOCs selected based on source strengths. These were source strength, as described previously (Daisey et al., identified as: Ps(l), motor vehicle emissions; Ps(2), dry 1994; Ten Brinke, 1995). That is, the VOCs with the cleaning emissions; Ps(3), bioeffluents and building

143 Brinke, Selvin, Hodgson, Fisk, Mendell, Koshland and Daisey

materials; and P5(4), room air fresheners/deodorizers Wallace, 1986; Wallace et al., 1987; Wallace, 1989; We and cleaning products, where the "S" subscript indi­ off et al., 1993). cates that the voes were selected based on source strengths. Only the sources represented by the fourth Irritant Symptom Prevalences principal component were found to be useful in symp­ Work-related irritant symptom prevalences from tom prediction, and for brevity, only this metric, desig­ questionnaire data were used as dependent variable� nated the AF/CP Source Vector, is presented and dis­ multiple logistic regression analyses. These are st cussed here. The most highly loaded voe on this vec­ marized in Table 4. A symptom was considered we tor was limonene, which is used widely in cleaning related if it was reported as being experienced wit products (Lebret et al., 1986; Wallace, 1986), followed the office building, but improving on days not in the by n-decane and n-nonane, which are major compo­ fice. Binary symptom outcomes (yes/no) were based nents of air fresheners and deoderizers (Tichenor, 1989; whether individuals experienced a work-related syr Levin, 1989). tom three or more days in the last week, with qt For the Irritancy /PC metric, a different subset of 10 tionnaire administration timed so that "last week" ' VOCs were selected for PC analysis based on relative the week of VOC sampling. Specific work-related syr irritancy (Table 1) and on the four sources of the VOCs toms were obtained from individual symptom qt

identified in previous analyses. For example, five of tions: dry, irritated or itching eyes (eye); dry or itchy 5 the 10 most irritating voes were from the group of (skin); dry or irritated throat (throat); chest tightr voes previously identified as coming from motor ve­ (chest); difficulty breathing; runny nose; stuffy n1 hicle emissions. In order to allow inclusion of VOCs sleepiness; fatigue; headache. Subjects were also q1 from other sources, only three of the five were in­ ied regarding three symptoms believed not to be pa1 cluded, i.e., 1,2,4-trimethylbenzene, m&p-xylene and the SBS syndrome (earache, shoulder pain or numbn a-xylene. Table 3 presents the loadings of the selected toothache), in order to estimate symptom over VOCs on each of the principal components of the Irri­ porting. However, prevalences of earache and tootha tancy/PC exposure metric. The loadings are corre­ were generally too low for analysis. Only shoulder F lations of the VOCs with the PC vectors. The greater or numbness was retained. Three composite symp the value of the loading, the greater the correlation variables were developed based on at leasl one posi with a given PC. The source identifications of the vec­ report of any of the specified individual work-relc tors were based on the most highly correlated VOCs symptoms. The irritant symptom variable was C• for each of the vectors, indoor-outdoor concentration posed of eye, skin, or throat symptoms. The irrit< ratios, and information from the literature on the mucus membrane variable was composed of eye, thr sources of the these VOCs (Berglund et al., 1989; runny nose, or stuffy nose symptoms. The overall \. Clausen et al., 1990; Daisey et al., 1994; Hodgson and able was composed of general systemic symptoms ( t Wooley, 1991; Hodgson et al., 1993; Lebret et al., 1986; chest, difficulty breathing, runny nose, stuffy n Levin, 1989; Plehn, 1990; Sheldon and Pellizzari, 1994; sleepiness, fatigue, or headache).

Table 3 Results of principal component analysis on VOCs selected for irritancy and sources

Compounds Principal components Communality

1 2 3 4

Styrene 0.03 0.042 0.81 -0.D15 0.83 Ethyl acetate -0.32 0.46 0.12 -0.25 0.91 Butyl acetate 0.29 0.098 0.079 0.29 0.45 1,2,4-Trimethylbenzene 0.42 0.29 0.065 -0.23 0.89 m/p-Xylene 0.42 0.27 -0.10 -0.29 0.96 a-Xylene 0.42 0.29 -0.11 -0.24 0.98 Hexanal -0.34 0.46 0.13 -0.062 0.89 Pentanal -0.40 0.33 -0.27 -0.14 0.97 2-Butoxyethanol 0.069 0.33 -0.36 0.564 0.74 2-Propanol 0.069 0.34 0.27 0.563 0.68 Variance (%) 42 17 12 11 Overall 84%

Probable Source Identity: Motor Building Carpets and Cleaning vehicle materials building products & emissions materials waterbased paint

144 j

Development of New VOC Metrics and their Relationship to "Sick Building Syndrome" Symptoms

Definitions of symptoms (individual and composite) used as dependent variables I k- fable 4 Symptom Abbreviations Symptoms

Individual symptoms: Eye Dry, irritated, or itching eyes Skin Dry or itchy skin he Throat Dry or irritated throat ) in Chest tightness Chest tightness Difficulty breathing Difficulty breathing m­ Runny nose Runny nose rk­ Stuffy nose Stuffy nose in Sleepiness Sleepiness Fatigue Fatigue of­ Headache Headache on Shoulder Shoulder pain or numbness Composite symptoms: Irritant Reporting at least one of the following: eyes, skin, throat Irritated mocous membrane Reporting at least one of the following: eyes, runny nose, stuffy nose, throat Overall Reporting at least one of the following: chest, difficulty breathing, runny nose, stuffy nose, sleep, fatigue, headache

es- 1kin ess

se; er- Logistic Regression Analytic Methods model. The final models contained all terms for demo­

t of Multivariate logistic regressions (Stata version 3.1) graphic variables, potential indicators of source of ex­ ess, were used to assess the relationships between work- posures to voes, ventilation type, temperature, rela­ ) re- related symptoms and various metrics of voe ex- tive humidity, and ensitiv ubpopulations (asth­ che posure. The odds ratio (OR) was used as the measure matics, individuals with allergies, ever smokers, afrl of effect for both crude analyses (not adjusted for other problem building status). voe metrics were tested in om potential risk factors or confounders) and adjusted models adjusted for these factors. ive analyses (adjusted for other potential risk factors or ted confounders). Crude and adjusted ORs were estimated

m- for 10 individual work-related (dependent) variables, Results ted one non-SBS symptom variable, and three composite Most of the tested metrics shown in Table 2 were not at, variables. Chi-square comparisons of models with and effective in predicting the SBS irritancy symptoms in xi- without voe exposure metrics were used to evaluate the logistic regression m de!, including the most com­ ght the influence of each of the seven exposure metrics on mon VOC exposure metric, TVOC. The VOC metric

s •, individual and composite symptoms. Additionally, re­ that took into account irritant potency, but did not ad­ gression coefficients per unit increase of the indepen­ just for the highly correlated nature of the data set or dent variable were used to assess the importance of the for the presence of voes that were not measured, was independent variables. also not a statistically significant predictor of irritant Additional variables were included in the full model symptoms. The AF /eP Source Vector metric was use­ based on their ability to confound or obscure relation­ ful in a model with data from all available buildings, ships between VOC exposures and SBS symptoms which included spaces where TVOe levels were elev­ (Table 5). Categorical independent variables were rep­ ated (>2 mg m-3) due to the presence of liquid-process resented by dichotomous indicator variables for each photocopiers. None f the adjusted metrics were useful level; the reference levels were not included in the in the prediction of shoulder pain or numbness (the symptom that repi:esented over-reporting). Logistic re­ gression estimates of the impact of earache and tooth­ Table 5 Other independent variables included in the logistic re­ ach would not converge, due to the low number of ,l;ression models ymptoms rep rted. Other Independent Variables, Grouped by Type Crude ORs (not shown) for th AF/CP Source Vec­ Gender, age, race, education, job classification tor metric, which w re based only on the cleaning Time using copy machine, new paint nearby products source vector from the sources PC analysis, Ventilation type Temperature, relative humidity were low (1.32= OR !51.5) but significant (Os excluded Asthmatics, individuals with allergies, ever smokers, 1.0) for all but th ch st symptom. However, adjusted problem building status ORs for the AF /CP Source Vector metric were not stat-

145

r •:' • � ,;,-• , • I • ''r�i - . � Brinke, Selvin, Hodgson, Fisk, Mendell, Koshland and Daisey

Table 6 Irritancy/PC and AF/CP source vector metrics in an adjusted model: Chi-square comparisons of maximum log-likelil estimations, with and without metrics

Symptom Irritancy/PC AF/CP source vector

2 P< 2 P< N x N x Eye 12 0.003 403 1.7 0.19 403 Skin 9.2 O.Ql 395 2.3 0.13 395 Throat 5.1 0.08 395 2.3 0.13 395 Irritant 13 0.002 416 1.7 0.19 416 Chest Tightness 2.2 0.33 350 0.2 0.65 350 Difficulty Breathing 0.4 0.82 373 0.0 0.83 373 Runny Nose 4.3 0.12 404 1.8 0.18 404 Stuffy Nose 6.6 0.04 395 6.3 O.Dl 395 Sleepiness 11 0.01 386 3.5 0.06 386 Fatigue 2.5 0.28 403 0.0 0.87 403 Headache 2.2 0.34 399 0.1 0.83 399 Overall 11 0.004 425 1.5 0.22 425 Irritated Mocous Membrane 14 0.001 419 5.1 0.02 419 Shoulder 3.1 0.21 392 0.3 0.55 392

Table 7 Crude and adjusted ORs for slalblically significant vectors of the irritancy metric

Symptom Cleaning products & water-based paints vector, P(4) Carpet/building materials vector, P('.' Crude Adjusted Crude Adjusted

OR 95% CI OR 95% CI OR 95% CI OR 95%·

Eye 1.3 1.0-1.7 1.7 1.1-2.7 1.2 1.0-1.5 1.6 1.1-2 Skin 1.6 1.1-2.2 2.2 1.3-3.7 1.2 0.9-1.5 1.2 0.7-2 Throat 1.3 1.0-1.8 1.8 1.1-3.1 0.9 0.7-1.l 0.9 0.6-1 Irritant 1.3 1.0-1.6 1.8 1.2-2.7 1.1 0.9-1.3 1.4 l.G-1 Chest tightness 1.6 1.0-2.6 1.8 0.8-4.0 0.9 0.6-1.3 0.9 0.4-1 Difficulty breathing 1.'i 1.0-2.3 1.2 0.5-2.7 0.9 0.7-1.3 1.2 0.5-2 Runny nose 1.5 1.0-2.0 1.6 0.9-2.8 1.0 0.8-1.3 1.3 0.8-::' Stuffy nose 1.5 1.1-2.0 1.7 1.1-2.8 0.9 0.8-1.2 1.3 0.8-2 Sleepiness 1.6 1.2-2.1 1.6 1.0-2.4 1.1 0.9-1.4 1.5 1.0-::' Fatigue 1.2 0.9-1.5 1.3 0.9-2.0 1.0 0.8-1.2 1.1 0 . 8-1 Headache 1.4 1.0-2.0 1.4 0.8-2.3 1.1 0.8-1.4 L2 0.8-1 Overall 1.7 13-2.2 1.8 1.2-2.7 1.1 0.9-1.3 1.1 0.8-1 Irritated mucous membrane 1.4 1.1-1.7 1.8 1.2-2.7 1.1 0.9-1.3 1.4 1.0-1 Shoulder 1.1 0.8-1.6 1.7 0.9-3.2 1.0 0.7-1.3 0.9 0.6-1

istically significant, except for the stuffy nose (OR= sons for the Irritancy/PC and AF /CP Source Vee 1.6), sleepiness (OR=l.4) and the composite irritated metrics in an adjusted model. Symptoms for which mucous membrane (OR=l.4) symptoms. Irritancy/PC metrics showed significant correlatil

Incontrast, the Irritancy/PC exposure metric was an (P<0.05) included: eye, skin, irritant, stuffy m effective and statistically significant predictor of several sleepiness, overall, and irritated mucous membrane SBS irritant symptoms, including skin irritation. Ini­ contrast, the AF/CP Source Vector metric was sign tially, all four vectors were tested against irritant symp­ cant for only two symptoms, stuffy nose and irrita toms. The carpet/building materials and cleaning prod­ mucous membrane (P<0.05). ucts & water-based paints emissions vectors (Table 3) The Irritancy/PC exposure metric was composed were found to be more influential than the other Lhe twu the two principal components representing the m principal components in symptom prediction, i.e., the irritating voes emitted from carpets and building n sources represented by the first (motor vehicle emis­ terials, and from cleaning products and water-ba:­ sions) and second principal component (building ma­ paints, P(3) and P(4), respectively, in Table 3. Tablt terials emissions) were not irritating as measured by compares the crude and adjusted ORs and 95% car their ability to be useful in symptom prediction. Thus, dence intervals (95% CI) for the two separate vectc the Irritancy/PC exposure metric was defined as the P(3) and P(4), of the Irritancy/PC metric. Crude C sum of principal components three and four. for the cleaning products and water-based pai1 Table 6 presents the results of Chi-square compari- source vector, P(4), were statistically significant for

146 J

Development of New VOC Metrics and their Relationship to "Sick Building Syndrome" Symptoms

)Od jrritant variables, but not for headache, fatigue and the (95% CI 1.1-2.7), 2.2 (95% CI 1.3-3.7), 1.8 (95% CI 1.2- 11on-SBS symptoms (shoulder pain and numbness). 2.7) and 1.8 (95% CI 1.2-2.7) for eye, skin, irritant, and crude ORs for the carpet/building materials source irritated mucous membrane symptoms, respectively. vector, P(3), were near 1.0 and were not statistically Adjusted ORs for the carpet/building materials vector, significant (95% Cis did not include 1.0). P(3), were somewhat lower but statistically significant Adjusted ORs for P(4) are also presented in Table 7. for the eye, irritant and irritated mucous membrane, {!1 general, the adjusted ORs were slightly larger than and sleepiness symptoms. crude ORs. Elevated and statistically significant (95% The association of the adjusted Irritancy/PC metric Cls excluded 1.0) ORs were calculated for the follow­ with skin symptoms was noteworthy. The large and ing symptoms: eye (OR=l.7); skin (OR=2.2); throat statistically significant chi-square change in the model (OR=l.8); irritant (OR=l.8); stuffy nose (OR=l.7); of skin irritation due to removal of the Irritancy /PC sleepiness (OR=l.6); overall (OR=l.8); and irritated metric (OR=9.2, P<0.01, see Table 6) is likely to be mucous membrane (OR=l.8) symptoms. Adjusted dominated by the cleaning products & water-based ORs for the carpet/building materials source were less paints source vector (OR=2.2, 95% CI 1.3-3.7), since significant; after adjustment, only the eye, irritant, the adjusted OR for the carpet/building materials sleepiness, and irritated mucous membrane symptoms source vector, P(3), was small and non-significant had elevated statistically significant ORs. Thus, of (OR=l.2, 95% CI 0.7-2.0). these two vectors, P(4) was more important in symp­ The P(4) vector was identified as being related to tom prediction. emissions from cleaning products & water-based paints. Many cleaning products used in buildings con­ tain 2-butoxyethanol and a metabolite of this com­ ·r Discussion pound has been found in urine samples collected from

.j. ln this study, a number of new metrics of voe ex­ building cleaners (Vincent et al., 1990). Irritant symp­ J posure were developed and tested with respect to their toms (eye, nose and throat) and headaches due to occu­ + ability to predict self-reported SBS irritancy symptoms. pational exposures of water-based paints and cleaning 1 ) Chi-square comparisons of models with and without products containing 2-butoxyethanol and other glycol voe exposure metrics were used to evaluate the influ­ ethers have been reported in a comprehensive review ence of seven different exposure metrics on individual of toxicological studies (Hansen et al., 1987). Water­ and composite symptoms. Only two of the seven ex­ based paints contain both glycol ethers, such as 2-bu­ posure metrics, the Irritancy/PC and the AF /CP toxyethanol, as well as 2-propanol (Hodgson and Source Vector metrics, were statistically significant in Wooley, 1991; Sheldon and Pellizzari, 1994). Thus, the models of symptom prediction (Table 6). The Irri­ relationships observed here between the cleaning tancy /PC metric had more statistically significant pre­ products & water-based paints PC exposure metric and dictive power than the AF/CP Source Vector metric. the prevalences of irritant symptoms in office workers The Chi-square comparison of the maximum likelihood seem reasonable. estimations with and without the Irritancy/PC metric In addition to finding eye and skin irritation from were most statistically significant for the eye, skin and occupational exposures to water-based paints contain­

the two composite irritant symptoms. For example, x2 ing glycol ethers, Wieslander et al. (1994) found that was 12 (P<0.003) for the eye irritation symptom. For the number of years of exposure to water-based paints the AF /CP Source Vector exposure metric, only the was related to a decrease in forced expiratory volume. symptoms of stuffy nose and the composite irritated In the CHBS, the P(4) vector gave a relatively high ad­ mucous membrane symptoms were statistically signifi­ justed OR for chest tightness (OR=l.8), although the cant. relationship did not reach statistical significance (CI o f 95% 0.8-4.0). I !st The Irritancy/PC Exposure Metric Johanson and Boman (1991) reported that dermal

· 'a- Although both vectors of the Irritancy /PC metric have uptake of 2-butoxyethanol accounted for 75% (45-85%) ?d predictive power for the irritant symptoms, the ad­ of the total uptake during whole body exposure to 2- 7 justed ORs for the individual vectors indicated that the butoxyethanol vapor in a chamber experiment. The h- cleaning products & water-based paints source vector, dermal exposure route is also important for other gly­ is, P(4), accounts for a significant proportion of the ob-. col ethers and acetates present in cleaning products & �s served association of irritant symptoms with this met­ water-based paints (Hansen et al., 1987). The dermal ts ric (Table 7). Adjusted ORs for the P(4) vector were uptake reported for painters and cleaners and subjects ill substantially elevated and statistically significant: 1.7 exposed in environmental chambers are consistent

147

. . . � -- - � - - ,,� ·�·· Brinke, Selvin, Hodgson, Fisk, Mendell, Koshland and Daisey with the findings of an association between skin irri­ 11 and 71 strongly influenced the observed relations tation symptoms and the P(4) vector in the California between the skin irritant symptom and the Irritanc office workers, although exposures of the office PC metric. Thus, the VOCs traced by the Irritancy / workers to 2-butoxyethanol and related emissions metric may be actually associated with the prevale from cleaning products & water-based paints were of skin symptom, or the symptoms may have be probably considerably lower than the exposures of the caused by some confounding factor. Since the ove painters and cleaners. prevalence of skin symptom was relatively 1 The concentration of 2-butoxyethanol, the most (13.4%), these findings suggest little over-reporting highly "loaded" VOC in the P(4) vector, was also in­ the skin symptom. vestigated as an exposure metric and found that, al­ though useful for predicting the throat symptom (x2= Influence of High TVOC Concentrations 4, P<0.03; OR=l.1, 95% CI 1.0-1.2), 2-butoxyethanol There is some evidence from these analyses that VC alone was not a statistically significant predictor of any from liquid-process photocopiers contribute to syn of the symptoms of irritancy. This suggests that other toms of mucosa! irritation:. Elevated TVOC conei voes associated with emissions from cleaning prod­ trations were measured in two buildings with liq1 ucts & water-based paints and traced by the P(4) vector process photocopiers. TVOC levels in these buildir are an important determinant of the irritant symptoms. were 2 to 7 mg m - 3, compared to a median value

To investigate the potential influence of various 0.5 mg Ill.-3 measured in the other buildings, wl­ building sites on the relationships between the irri­ these high TVOC values were excluded. Fifty-sev tation symptoms and the Irritancy/PC metric, the cru­ subjects were located at these locations; 42 and 15 in de prevalences of eye and skin irritation symptoms viduals were located in building 4 (sites 41, 42) a were plotted versus the values of the P(4) vector at building 5 (site 53), respectively. each building and site location. As shown in Figures 1 The gas chromatograms of the air samples frc and 2, the crude prevalences of these two symptoms these sites were dominated by a mixture of C10-C11 i: versus the P(4) vector are suggestive of increased paraffinic hydrocarbons characteristic of emissic prevalences with increased values of this vector. Both from these photocopiers. In chamber experiments w plots show high levels of the cleaning products & 63 healthy subjects exposed to n-decane (C10), sign water-based paints vector in sites 11 and 71. A total of cant decreases in tear film stability were observed w 29 individuals were located in spaces 11 (n=ll) and 71 exposures of 6 to 20 mg m -3 over 6 hours (Kjaergaa

(n=18). The chi-square comparison between full and et al., 1989). High TVOC concentrations found in t nested models with all sites (N=395) was 9.2 (P<0.01). CHBS approached and overlapped with the concE For the skin irritancy symptom, upon removal of the trations observed to cause eye irritation in the chaml: individuals located in two sites with high vectors (n= study, although the alkanes were not identical. 29), the chi-square comparison was 2.8 (P<0.24). This The influence of high TVOC concentrations on t indicates that the elevated values for the cleaning Irritancy/PC and AF/CP Source Vector metrics w products & water-based paints vector found in spaces evaluated by removing individuals with high TVC

60

n 50 ..- - 0 -� 40 21• Q) 82 CJ • c: .I ll Q) iU 30 > • 12 71 Q) 2 • • 102 • .. 4 ..41 72 c.. 20 • � .a • • 61 w 33 10 81 lit ii Fig 1 Prevalence of eye symJ tom (%) versus value of \'ectc 0 P(4), for cleaning products water-based paints, at eac -3 -2 -1 0 2 3 site. Building and site Joe. P(4) Vector tions are indicated

148 � - .� -,.- - . -�- -

� •' � J

Development of New VOC Metrics and their Relationship to "Sick Building Syndrome" Symptoms

fig- 2 Prevalence of skin symp- 30 l ) versus value of vect r 1 : % 7 jp 10m ( • YI p(�), cleaning products - for & rft. 22 12 c ased paints, at ench site. 25 • 1,,ater-b - • ilding and site locations are Q) 21 Ce 5o (,) indicated c: n 20 - � • 111 co 72 I > Q)..... ' V I 15 - Lil c.. • 103 • II l)f 41 • I c: • 61 82 ::i2 10 5 L CJ) 33 JI

5 - • 81 1i

.... o +-,...... ,.�-.-. -...--....-'lllt--+'l-=r•l"1'-..---..-r---.---rm1 1-rm-�--....-��r-r���---1 -3 -2 -1 0 1 2 3 id P(4) Vector l"'S•)f n I n exposures. Even with high TVOC exposures excluded, Further, these results are from a single study and re­ 1- the Irritancy/PC metric was statistically significant in quire further investigation and confirmation in other id the prediction of irritancy symptoms. Relative to an sets of buildings. analysis with all cases, exclusion of these 57 obser­ Due to the limited number of cases, subsets of voes m vations at high TVOC sites (11% of the cases) slightly had to be selected for analysis and development of >- decreased but did not eliminate the predictive ability VOC exposure metrics. The selection criteria used here :s of the adjusted Irritancy/PC metric. For example, with emphasized source strength and irritancy and thus 'h data from all buildings, significance values were limited the number of source types that could be exam­ ' i- P<0.003, P<0.002, P<0.004 for eye, irritant, and irri­ ined. With a larger data set and fewer restrictions on h tated mucous membrane symptoms, respectively. After the VOes to include in the PC analysis, it should be d excluding the high TVOC exposures, the correspond­ possible to identify additional sources of voes that ,e ing symptoms remained significant at P<0.03, P<0.01, contribute to SBS symptoms. and P<0.001. By comparison, the ability of the AF/CP Two potentially important sensory irritants, ozone !r Source Vector metric to predict SBS symptoms de­ and formaldehyde, were not measured in the CHBS. creased (e.g., the P-value for the stuffy nose symptom Ozone is a strong irritant, and is one of the six pol­ e was P<0.01 with all data, compared to P<0.07 with lutants for which there are National Ambient Air Qual­ .s data from the high TVOC spaces excluded). ity Standards (NAAQSs). During the period of sa'm-· piing for the California buildings, the ambient ozone Limitations of the Study values were very low (0.014-0.048 ppm; Bay Area Air There are several limitations to this study that must be Quality Management District, 1994), although poten­ noted. First, the VOC sample size in this study was tial indoor sources of ozone, such as photocopiers, relatively small (22 sites in 12 buildings). Due to were known to be present in the eHBS buildings. limited numbers and spacing of voe measurement Formaldehyde is commonly found indoors, and the sites, exposures could have been misclassified. Ex­ irritant effects of the compound have been well docu­ posure assessment using personal voe monitors could mented; eye and respiratory tract irritation generally allow for better assessment of the relationship between occur at levels of about 0.12 mg m-3 (0.1 ppm) (World VOC exposure and symptom occurrence. Additionally, Health Organization, 1989). An attempt was made to although the symptom database included 517 individ­ sample formaldehyde in the CHBS buildings; however, uals, there were a small number of sites with elevated problems occurred with the sampling system and the risk factors. For example, 29 individuals were located measurements were judged unreliable. Polluted urban in 2 sites (11, 71) where the cleaning products & water­ air concentrations of formaldehyde are typically an or­ based paints vector was elevated. Similarly, 57 individ­ der of magnitude below the concentrations known to uals were located in 3 sites (41, 42, 53) with high TVOC cause irritant symptoms (Seinfeld, 1986). However, in­ concentrations. Observed associations may have been door levels of formaldehyde may have been elevated due to confounding of other, unmeasured parameters. enough to cause or contribute to irritant eye and skin

149 Brinke, Selvin, Hodgson, Fisk, Mendell, Koshland and Daisey symptoms, although reported measurements for non­ symptom prevalence; however, as has been discus problem office buildings are generally quite low (Turk above, the TVOC metric does not take into account et al., 1987). ferences in the irritant effects of different voe n The lack of indoor measurements of formaldehyde, tures. After adjusting for ventilation type in the curr ozone, or other potentially irritating pollutants may study, the Irritancy/PC exposure metric and its t have been partially compensated for by the ability of vectors were found to be significantly associated "' the principal component analysis to identify sources of symptoms of irritancy. a group of compounds through a single or few tracers. The CHBS buildings were chosen to be represei Formaldehyde has been found in tobacco smoke, auto­ tive of typical office buildings; however, selection mobile emissions, materials used in buildings and quirements may have excluded potential source5 home furnishings, and in consumer and medicinal VOCs. For example, buildings were excluded if ti products (World Health Organization, 1989). As the contained unusual pollutant sources (e.g., bookbi. buildings chosen were non-smoking, and two form­ ing, lacquering). Buildings with on-going renovah aldehyde sources (automobile emissions and building were excluded and a non-smoking policy is in ef materials) were identified in the principal component for all CHBS buildings. Unusual pollutant sour. analysis, some impact of the formaldehyde may have renovations, and/or smoking are all potential sorn been taken into account by the use of principal compo­ of VOCs. For example, renovations have been foum nent analysis. be almost continual in office buildings, with appn Exposures to airborne fungi and bacteria were not mately 30% of an average office building's inte1 included in this analysis, although there is evidence space completely rebuilt each year (Brooks and Da· that these agents may contribute to SBS symptoms. 1992). Therefore, it is possible that selection criteria Measurements of bacteria and fungi were made about eluding buildings with potential sources of voes n one month after all of the other measurements were have biased the results downwards. Further stud\ made in these buildings (Fisk et al., 1993). Concen­ include a wider range of buildings may find stron trations of bacteria and fungi at that time were all be­ relationships between symptoms and voe expos low the concentrations that have been suggested as metrics. levels of concern (Morey, 1984; Rao et al. 1996). How­ ever, the sampling methods for these bioaerosols are limited to about 15 min and thus, do not provide a Conclusions reliable estimate of workday exposures. In this study, seven VOC exposure metrics were im

"Sick Building Syndrome" is generally believed to tigated with respect to their ability to predict S• be a multifactorial problem that includes various reported SBS irritant symptoms in office workers. M chemical, physical, psychological and biological fac­ were not statistically significant predictors in logisti tors. The analyses presented here adjusted for many regressions models. The Irritancy /PC exposure met: potential confounding factors (e.g., gender, race, job, which took into account the irritancy of the voes Cl new paint nearby, ventilation type, temperature, rela­ their intercorrelations, was a statistically signific. tive humidity, sensitive subpopulations, ever smokers, predictor of irritant symptoms. The results obtained problem building status). However, other potential this study also indicated that emissions from cleani sources of bias were not included in the model as they products & water-based paints could account for so were found to be insignificant (building age). Several of the SBS symptoms observed in office workers in : other factors could not be included due to measure­ California Healthy Buildings Study. ment limitations. For example, too few cases were re­ The most commonly used VOC exposure meti ported for "time using carbonless copy paper". TVOC, was not a statistically significant predictor There have been some earlier studies that suggested SBS symptoms. In general, TVOC levels were low that SBS symptoms might be related to mechanical the CHBS buildings. However, high TVOC conCl ventilation systems, either in etiology (Molhave and trations, due to the presence of liquid-process pho Thorsen, 1991) or via the transport of voes through­ copiers (2 to 7 mg m-3), were observed for three si out buildings. In an earlier analysis, Mendell et al. and were within the range of TVOC levels reported (1996) found elevated symptom prevalence in the cause symptoms in chamber experiments. The analr CHBS buildings with mechanical ventilation systems, demonstrated that high TVOC levels at some sites relative to the buildings with natural ventilation. Both fluenced both the Irritancy /PC and AF/CP Sow this earlier study and the current analysis found no Vector metrics in an adjusted model; removal of t statistically significant associations between TVOC and cases with high TVOC levels slightly reduced t

150 ? ! ' t . I

Development of New VOC Metrics and their Relationship to "Sick Building Syndrome" Symptoms

ower of the Irritancy/PC metric, and reduced the (ed.) Proceedings of Indoor Air '90, Ottawa, Canada Mort­ sect p gage and Housing Corporation, Vo l. 3, pp. 557-562. tical significance of the AF I CP Source Vector met­ :iif. statis Daisey, J.M., Fisk, W.J., Hodgson, AT., Mendell, M.J., Faulker, 1ix­ ric to predict irritancy symptoms to below the 90% D., Nematollahi, M. and Macher J.M. (1990) The California J vel. healthy building pilot stlldy. I. Study design nnd protocol, Re­ ent e These results are from a single study and require port LBL-29851, Berkeley, CA, Lawrence Berkely Labora­ wo tory. !ith I further investigation and confirmation in other sets of Daisey, J.M., Hodgson, A.T., Fisk, W.J., Mendell, M.J. and Ten I buildings. The CHBS buildings were chosen to be rep­ Brinke, J. (1994) "Volatile organic compounds in twelve California office buildings: Classes, concentrations and l resentative of the typical office environment. However, ta - sources", Atmospheric Environment, 28(22): 3557-3562. selection requirements specifically excluded buildings re­ 1 Devos, M., Patte, F., Rouault, J., Laffort, P. and Van Gernert, with unusual pollutant sources, or ongoing reno­ L.J. (1990) Stmrdnrdized Hw11m1 Olefnclory Ox­ o f , Tl1resilolds, ford, IRL Press Oxford University Pre s. ey vations. Therefore, the results from the current study at Fisk, W.J., Mendell LJ., Daisey, J.r 1., Faulkner, Hodgson, ggest that for a wider range of pollutant exposures, , D., ild- su A.T., Nematollahi, M. and Mad1er J.M. (1993) "Phase 1 of 1 stronger correlations might be observed between irri­ the California Healthy Building Study", Indoor Air, 3, 246- ·ns 254. fCt tant symptoms and voe exposure metrics based on Hansen, Ml<., Larsen, M. and Cohr, K.-H. (1987) "Water­ irritancy and principal component analysis. re·, borne paints: A review of their chemistry and toxicology The new methodology developed here to obtain an es and the results of determinations made during their exposure metrics for a complex mixture of voes has use", Scnmii1111uin11 foumal of Work, E11viro11111ent, a11d 473-485. 1:� Jinked low level voe exposures from specific types of Hen/th, 13, Hedge, A., Burge, P.S., Robertson, AS., Wilson, S. and Harris­ ior indoor sources to SBS symptoms for the first time. This Bass, J. (1989) "Work-related illness in offices: A proposed I . methodology, when applied to other buildings and model of the 'Sick Building Syndrome'", Environment Inter- IS, larger data sets, may be a useful tool in helping to de­ 1111tion11l, 15, 143-15 . x- Henry, R.C., Lewis, C.H., Hopke, P. K. and Williamson, H.J. termine some of the causes of SBS symptoms, and ulti­ (1984) "Review of receptor model fundamentals", Atmos­ mately contribute to solutions to this problem. pheric Environment., 18, 1507-1515. 1:� , Hodgson A.T., Daisey, J.M. and Grot, R.A. (1991) "Sources r <1nd source strength of volatile organic compounds in a ·re new office building'', Journal of the Air and Waste Manage­ Acknowledgments ment Associntio11, 41, 1461-1468. This work was supported by the Assistant Secretary Hodgson, A.T. and Wooley, J.D. (1991) Assessment of i11door conce11.trnfio11s, indoor sources n11d source e111issio11s of selected for Energy Efficiency and Renewable Energy, Office of uo/atile orgm zic co111po1111d, Report LBL-30908, Berkeley, CA, Building Systems, and by the Directory, Office of En­ Lawrence Berkeley Laboratory. Hodg on, A.T., Wooley, J.D. and Dais y, J.M. (1993) "Emis­ s­ ergy Research, Office of Health and Environmental Re­ sions of volatile o g nic compounds from new carpets lf­ search, Human Health and Assessments Division, U.S. r a measured in a large-scale en on en a /011n111l Department of Energy under Contract No. DE-AC03- ir m t l chamber", st of /he Air n11d Wn ste Mm111ge111ent Associntion, 43, 316-324. al 76SF00098. Hodgson, M.J., Frohlinger, J., Permar, E., Tidwell, C., Tr aven, N.D., Olenchock, S.A. and Karph, M. (1991) "Symptoms c, and microenvironmental measures in nonproblem build­ d ings", Journal of Occ11pntionnl Medicine, 33, 527-533. nt References Johanson, G. and Boman, A. (1991) "Percutaneous absorption in Alarie, Y. (1966) "Irritating properties of airborne materials to of 2-butoxyethanol vapour in human subject", British the upper respiratory tract", Archives of E11viro11111e11ta/ Journal of Ind11strinl Medicine, 48, 788-792. g Health, 13, 433-449. Kjaergaard, S., Molhave, L. and Pedersen, 0.F. (1989) "Hu­ le Alarie, Y. (1981) "Dose-response analysis in animal studies: man reactions to indoor air pollutants: n-decane", Environ­ Prediction of human responses", E11viro11me11tal Hen/th Per­ ment Intemntionnl, 15, 473-482. e spectives, 42, 9-13. Lebret, E., van de We il, J.H., Bos, H.P., Noij, D. and Boleij, American Conference f Governmental Industrial. Hygienists J.S.M. (1986) "Volatile organic compounds in Dutch ic, (1992) Th res.hold limil vnl11es fo r cl1e111icnl s11bs/a11ces n11d plzysi­ homes", Environment [nternationnl, 12, 323-332.

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