Source Strengths for Indoor Human Activities that Resuspend

Jan 31, 2004 - making a bed, dancing on a rug, dancing on a wood floor, vacuuming, and walking around and sitting on upholstered furniture. Although m...
0 downloads 0 Views 113KB Size
Download PDF
Environ. Sci. Technol. 2004, 38, 1759-1764

Source Strengths for Indoor Human Activities that Resuspend Particulate Matter ANDREA R. FERRO,* ROYAL J. KOPPERUD, AND LYNN M. HILDEMANN Department of Civil and Environmental Engineering, Terman Engineering Center, Stanford University, Stanford, California 94305-4020

A mathematical model was applied to continuous indoor and outdoor particulate matter (PM) measurements to estimate source strengths for a variety of prescribed human activities that resuspend house dust in the home. Activities included folding blankets, folding clothes, dry dusting, making a bed, dancing on a rug, dancing on a wood floor, vacuuming, and walking around and sitting on upholstered furniture. Although most of the resuspended particle mass from these activities was larger than 5 µm in diameter, the resuspension of PM2.5 and PM5 was substantial, with source strengths ranging from 0.03 to 0.5 mg min-1 for PM2.5 and from 0.1 to 1.4 mg min-1 for PM5. Source strengths for PM > 5 µm could not be quantified due to instrument limitations. The source strengths were found to be a function of the number of persons performing the activity, the vigor of the activity, the type of activity, and the type of flooring.

Introduction Outdoor particulate matter (PM) concentrations have been positively correlated with respiratory and cardiovascular disease (1-3). Summaries of human exposure studies have shown that personal exposure to PM is poorly correlated with outdoor air but highly correlated with indoor air, although the correlation with outdoor air improves for longitudinal studies for which individuals are monitored over longer time periods (4, 5). Because people spend most of their time indoors (6, 7), investigating indoor sources and their contribution to indoor PM levels improves our understanding of human exposure to PM. EPA’s 1990 Particle Total Exposure Assessment Methodology (PTEAM) study found that cigarette smoking and cooking were the largest identified sources of indoor air particles, while cleaning activities were a contributor to indoor PM of unknown significance (8). The PTEAM study also found that unknown indoor sources accounted for 14% of the indoor concentrations of PM2.5 and 26% of the indoor concentrations of PM10. Wallace (4) hypothesized that resuspension of household dust from human activity contributed to the unknown indoor sources. Indoor sources, including human activity, tend to generate short duration, high concentration particle events, which can result in indoor PM concentrations several orders of * Corresponding author phone: (315)268-7649; fax: (315)2687636; e-mail: [email protected]. Present address: Department of Civil and Environmental Engineering, Clarkson University, Potsdam, NY 13699-5710. 10.1021/es0263893 CCC: $27.50 Published on Web 01/31/2004

 2004 American Chemical Society

magnitude above background levels (9). To capture the temporal variability of indoor sources, continuous monitoring methods have recently been used in place of, or together with, traditional time-integrated sampling. Several studies have examined the effect of human activities that resuspend PM by collecting continuous particle size distribution data (9-12). Thatcher and Layton (10) found that even normal activities, such as walking and sitting, dramatically increased indoor concentrations of PM greater than 1 µm in a California residence. Using a multiple regression model, Abt et al. (11) found that cleaning (vacuuming, dusting, sweeping) and indoor work (walking around, field sampling, children playing) significantly increased indoor emission rates of particles 2-10 µm and 1-10 µm in diameter, respectively, in four Boston homes. Long et al. (9) conducted a follow-up study in 9 Boston-area homes that included some scripted activities to provide distinct indoor particle events for source characterization and apportionment. Long et al. (9) found that impact of indoor activities that resuspend particles, including dusting, vacuuming, and walking vigorously, was most pronounced for 2.5-10 µm particles. They estimated that dusting and vigorous walking contributed 23 (SD ) 23) and 12 (SD ) 9.1) µg m-3, respectively, to indoor PM2.5 concentrations. Similarly, Ferro (12) reported that dry dusting and one person walking activities contributed 32 and 15 µg m-3, respectively, to indoor PM2.5 concentrations in a California home. Indoor PM concentrations and personal exposures to PM from human activities are dependent on the air exchange rate, mixing volume, decay rate, and proximity to the source. However, source strengths (i.e., emission rates in mass per time) are not dependent on these factors. Thus, source strengths are generalizable and are used for modeling pollutant concentrations and human exposure in indoor microenvironments. Source strengths for a variety of pollutants from indoor sources, such as gas-fired ranges, kerosene-fired space heaters, wood-burning stoves, and environmental tobacco smoke (ETS), have been estimating using materials balance modeling (13-19). However, source strengths for indoor activities that resuspend particles have not been established. A few studies have characterized the emissions from human activities that resuspend PM. Using a steady-state materials balance model for indoor PM concentration, Thatcher and Layton (10) estimated resuspension rates of deposited PM from normal human activity that ranged from 10-6 h-1 for 0.3-0.5 µm particles to 10-4 h-1 for 10 µm particles. Based on these estimates, Schneider et al. (20) determined a mathematical relationship between size and resuspension rate from normal human activity, although both Schneider et al. (20) and Thatcher and Layton (10) quote other studies that found resuspension rates more than 100 times higher. Abt et al. (11) reported mean volumetric emission rates for cleaning and indoor work activities that increased with particle size from 0.02 µm3 cm-3 min-1 for 2-3 µm particles to more than 0.12 µm3 cm-3 min-1 for 6-10 µm particles. Because resuspension of particles from human activity is also dependent on dust loading and person-to-person variability, Kildeso et al. (21) developed a standardized method to measure potential resuspension of dust from carpets using a falling weight at a specified height. However, this method does not predict source strengths for actual human activities. This study provides a field survey of a variety of human activities in a real home. The goals of the study are to establish whether the activities resuspend enough particulate matter VOL. 38, NO. 6, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

1759

to contribute substantially to indoor PM levels and to provide initial estimates of their source strengths. Several of the activities have not been reported previously in the literature, including folding blankets, folding clothes, making a bed, and dancing. The remaining activities have been included in previous studies, although limited data exist to determine the source strengths of these activities. These activities include dusting, vacuuming, and walking around and sitting on furniture.

Experimental Methods Experiments were conducted for 5 consecutive days during April 2000 in a 75 year-old, single-family home with one occupant in Redwood City, CA. Personal, indoor and outdoor PM concentrations were measured using integrated PM2.5 and PM5 filter samplers side-by-side with real-time particle counters. The stationary indoor monitoring station (SIM) was located in the basement for the first day and in the living room on the first floor for the remaining 4 days. The stationary ambient monitoring station (SAM) was located in the backyard of the residence under a 10 m2 wooden structure with a roof, 2 sides fully open to the ambient air, and a large open window on a third side. Collocated instruments at the SIM and the SAM locations included the following: 2 PM2.5 cyclone samplers, 2 PM5 cyclone samplers, and a particle counter. For several hours on each of the first 3 days, prescribed human activities were performed in the general area of the SIM to resuspend deposited PM. Each activity period lasted 15 min and was followed by a 45-minute decay period with no activity. The activities included folding blankets, folding clothes, dry dusting, making a bed, dancing on a rug, dancing on a wood floor, vacuuming, and walking around and sitting on upholstered furniture. The walking and sitting activity was performed once by one person and once by two people. All other activities were performed by only one person. The residence consists of a first floor, finished basement and attic, and attached garage. The 83-m3 basement consists of one rectangular room with an 8-m3 open narrow staircase to the first floor. The first floor consists of a centrally located living room with a dining room, kitchen, and garage on one side, two bedrooms and a bathroom on the other side, and a bedroom in the back. The doors to the garage and two of the bedrooms were closed for the duration of the experiment. The third bedroom, where several activities took place, has a volume of 30 m3 and is connected to the living room by a short 4-m3 hallway. The other first floor rooms are connected by open doorways. The total measured volume for the first floor less the closed off areas is 206 m3. A 4-m3 open staircase connects the first floor and 65-m3 attic. The ceiling height is 2.3 m in the basement, 2.5 m on the first floor, and 2.1 m in the attic. The external doors and windows were closed, and no fan or air conditioning system was operating for the experimental period. The experiments were conducted during clear weather conditions with ambient daytime temperatures approximately 20 °C. The filter samples were collected downstream of California Department of Health Services Air and Industrial Hygiene Laboratory (AIHL) design cyclone samplers (22). The samplers were operated at flow rates of 21 and 11 L min-1 to collect PM2.5 and PM5, respectively. The particle counters used for the study were Met-One Model 237B laser particle counters (Grants Pass, OR) with common size ranges of 0.3-0.5, 0.51.0, 1.0-2.5, 2.5-5.0, and >5.0 µm. The particle counters collected counts over 3-min time periods at a flow rate of 2.8 L min-1. Following each set of activities, the particle counters were collocated for at least 45 min and count matched using the slope and the intercept from the linear regression of the collocation readings. The particle counter number concentrations were converted to volume concentrations assuming 1760

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 38, NO. 6, 2004

spherical particles, a geometric mean particle diameter Dp for each size range, and a particle density of 2.5 g cm-3. To more accurately represent the measured particle mass, the estimated mass concentrations were scaled to match the measured filter sample mass concentrations. Further details of the particle count matching and count to mass conversion are discussed in refs 23 and 12, respectively.

Source Strength Estimation A mass balance approach was used to estimate the source strengths from the human activities (e.g., refs 18 and 19). This method is derived from the mass balance equation for a time varying mass concentration Cin(t) (µg m-3) in an instantaneously mixed, incompressible volume of air v (m3). The mass balance, given in eq 1, states that the rate of change of Cin(t) is equal to the infiltration of the outdoor mass concentration Cout(t), attenuated by the penetration efficiency p (dimensionless) through the building envelope; the exfiltration and decay k (h-1) of Cin(t); and the generation from indoor sources S (µg h-1) divided by the mixing volume v. Because v is incompressible, the infiltration and the exfiltration have the same magnitude and are represented by the air exchange rate a in air changes per hour (ACH) with units of h-1.

dCin(t) S(t) ) apCout(t) - (a + k)Cin(t) + dt v

(1)

By integrating the mass balance equation from time t ) 0 to t ) T and dividing by T, where T is an arbitrary time greater than the source emission time ts, a solution is obtained in terms of the average outdoor concentration, the average indoor concentration, and the average source strength:

Cin(T) Cin(0) S(T) ) apCout(T) - (a + k)Cin(T) + T T v

(2)

Solving for the average source strength over time T gives

S(T) ) v

[

Cin(T) Cin(0) - apCout(T) + (a + k)Cin(T) T T

]

(3)

Since there are no indoor source emissions after time ts, the average source strength over time T is equal to the average source strength over time ts multiplied by the ratio of ts and T:

ts S(T) ) S(ts) T

(4)

Substituting eq 4 into eq 3, the average source strength over the source emission time ts is

[

]

T Cin(T) Cin(0) S(ts) ) v - apCout(T) + (a + k)Cin(T) ts T T (5) Values for the average concentrations of indoor and outdoor PM and the indoor concentration at times T and 0 were obtained from the real-time data. The methods for estimating a, v, p, and k are described below, and the estimated parameter values are given in Tables 1 and 2. Equation 5 was applied to each size range measured by the particle counters separately, and the source strengths for the applicable size ranges were summed for the PM2.5 and PM5 results. Air Exchange Rate a. To estimate the air exchange rate a, a 30-min pulse of sulfur hexafluoride (SF6) was released prior to the prescribed activities each day in the area where the activities would take place. The SF6 was released through

TABLE 1. Estimated Values for a and v by Experimental Day day

location

a (h-1)

v (m3)

1 2 3 4 5 mean

basement first floor first floor first floor first floor first floor

0.99 0.47 0.39 0.32 0.65 0.46 ( 0.14

86 240 310 220 280 260 ( 40

TABLE 2. Estimated Average Values for k by Experimental Size Range and Human Activity Location size range (µm)

basementa k (h-1)

first floor bedroomb k (h-1)

0.0 0.00f 0.3-0.5e 0.5-1.0 0.43 ( 0.12 0.04 ( 0.07 1.0-2.5 0.54 ( 0.25 0.06 ( 0.10 2.5-5.0 0.70 ( 0.26 0.05 ( 0.09 >5.0 1.0 ( 0.25 0.21 ( 0.18

first floor otherc k (h-1)

first floor alld k (h-1)

0.28g 0.21 ( 0.26 0.37 ( 0.17 0.48 ( 0.14 0.68 ( 0.15

0.14h 0.14 ( 0.21 0.24 ( 0.21 0.30 ( 0.26 0.48 ( 0.29

a SIM in basement; activities in basement 0-5 m from SIM (N ) 3). SIM in living room; activities in first floor bedroom approximately 10 m from SIM (N ) 3). c SIM in living room; activities in first floor living and dining rooms 0-5 m from SIM (N ) 4). d SIM in living room; all activities on first floor 0-10 m from SIM (N ) 7). e k values for 0.3-0.5 µm size range could only be calculated for vacuuming activities. f Calculated k value following vacuuming in bedroom. g Calculated k value following vacuuming in living room. h N ) 2. b

a flow controller at 200 cubic centimeters per minute and monitored with a Gilibrator volumetric flow meter (Gilian, West Cladwell, NJ). A Bruel and Kjaer Model 1302 multigas monitor (Decantar, GA) measured SF6 concentrations based on the principle of infrared photoacoustic spectroscopy. The multigas monitor was located approximately 4 m from the release point with an intake height of 1 m. Assuming uniform mixing, the slope of ln(SF6) concentration regressed over time provided an estimate of a in ACH. To obtain the optimal fit, the period from 1 h to 4 h (t)1.5 to t)4.5) after the source was shut off was used for the regression. This period was after the variability in the SF6 concentration diminished but before the concentrations approach the detection limit of the monitor. Although the air exchange rate can vary with time, a was reasonably constant for the period when the activities were performed from approximately t ) 1 to t ) 5 h. Because only one SF6 monitor was used for this study, the assumption of uniform mixing could not be directly tested. However, previous studies have found that the mixing time for a tracer gas in a room under quiescent conditions, with mixing induced only by natural convection, is approximately 0.5-1.5 h (23, 24-26). The mixing time for these studies is defined as the time required for the spatial coefficient of variation to become less than 10% (24) or the time required for the standard deviation of the pollutant concentrations at all locations to become less than 10% of the mean concentration (25). The mixing time decreases to several minutes when mixing induced by forced convection or solar radiation is added (24, 25). For this study, human activity contributed to the mechanical mixing and a reduction in the variability of the SF6 concentration was observed several minutes after the SF6 was shut off. Effective Mixing Volume v. In a real home with multiple rooms, multiple floors, closets, crawl spaces, and stairways, the effective mixing volume v is often not equal to the measured geometric volume. Therefore, v must be estimated. Because the SF6 emission rate was measured precisely, v was estimated by solving the source strength eq 5 for v, setting Cin(0), Cout, and k equal to zero, and inputting the remaining

values from the SF6 experimental data:

v)

()

ts S(ts) T Cin(T) + aCin(T) T

[

]

(6)

Penetration Efficiency p. The penetration efficiency p depends on the construction of the individual home as well as the velocity of the infiltrating air. Several studies have reported p by applying variations of the mass balance equation to indoor and outdoor particle concentration data. EPA’s PTEAM study (8) and Thatcher and Layton (10) found that p was equal to 1 for particles less than 10 µm in diameter. Other experimental studies have shown that p is dependent on particle size and can be much less than 1 (27-29). Theoretically, p has a maximum value for particle diameters between 0.1 and 1 µm, and p decreases as the particle diameter departs from this size range (30). Because p is difficult to predict for a specific building, and this study did not have sufficient data to calculate p directly, p was assumed to be equal to one for all size ranges. This simplification did not significantly affect the source strength calculations since the larger size classes that would be most impacted by reduced penetration efficiencies did not have a large outdoor contribution to the total indoor concentrations. Decay Rate k. The decay rate k for indoor particles accounts for all decay processes with the exception of exfiltration but is dominated by deposition onto the walls, floor, and furnishings. The decay rate k can be estimated using a method similar to what was used for estimating a. Solving the mass balance eq 1 gives

ln[Cin - RCout] ) -(a + k)t + ln[Co - RCout]

(7)

where Co is the modeled concentration at ts, and

R)

ap a+k

(8)

As described by eq 7, the slope m of the regression line of ln(Cin-aCout) versus t is equal to -(a+k). Therefore, k ) -(m+a), where a is estimated as described above. Subtracting Contributions from Previous Activities. The separation of activity periods from nonactivity periods allowed estimation of source strengths for each individual activity. As illustrated in Figure 1, the contributions from previous activities to the indoor PM concentration were modeled by extending the decay curve for the previous activity into the activity and decay period of the current activity. The indoor concentrations used in eq 5 to calculate the source strength are the measured indoor concentration less the modeled contribution from previous activities.

Results Particle Size Distributions. Figure 2 plots the estimated indoor particle volume concentration time series for a representative set of human activities in the absence of other indoor sources. Each activity period is characterized by an increase in PM, and each rest period is characterized by a decrease in PM. The final activity (E) plotted in Figure 2 is the monitor collocation period. Figure 2 shows that most of the indoor particle volume from the human activities is greater than 5 µm in diameter. In the 0.3-0.5 µm size range, no increases in PM were measured for walking around and sitting on furniture (A) or dusting (B), but PM increases were measured for the two vacuuming activities (C and D). In the 0.5-1.0 µm size range, all activities resulted in a measurable increase in PM. All prescribed human activities resuspended particles with a VOL. 38, NO. 6, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

1761

FIGURE 1. Subtraction of the previous activity’s modeled concentration decay from the measured PM concentration (µg m-3). This method allows the source strength to be estimated for a single activity without contributions from previous activities. Results are for 2.5-5 µm size range.

FIGURE 2. Indoor particle volume concentration (µm3 cm-3) versus time by size range on semilog plot. Each observation represents a 3-minute volume concentration. Activity periods represent (A) two persons walking around and sitting on furniture, (B) dry dusting, (C) vacuuming the living room, (D) vacuuming the bedroom, and (E) collocation period. similar particle size distribution. Together, the submicron particles accounted for less than 1% of the indoor total suspended particle (TSP) volume as estimated by the SIM for the 5-h experimental period. These results agree with Thatcher and Layton (10), who found that for normal human activities “particles larger than 5 µm show significant resuspension...particles smaller than 5 µm are not readily resuspended, and particles smaller than 1 µm show almost no resuspension, even with vigorous activity.” Parameter Values. Table 1 lists the estimated values for a and v by experimental day. The estimated v for the basement was 86 m3, which is similar to the measured geometric volume 1762

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 38, NO. 6, 2004

for the basement (83 m3) and open stairway to the first floor (8 m3). The estimated v for the first floor ranged from 220 m3 to 310 m3 with a mean of 260 ( 40 m3. The mean estimated v for the first floor is similar to the measured volume of the first floor (206 m3) and attic (65 m3). The range in v may be due to varying airflow and air stability in the home, causing the volume of well-mixed air to vary from day to day. Because the SF6 was released and measured in the same room as the SIM, and the SF6 release ended within 0.5 h of when the prescribed human activities began, the v estimated by the SF6 release was considered to be an accurate reflection of the effective mixing volume for the human activities.

FIGURE 3. Source strengths from human activities (mg min-1). BR ) first floor bedroom, FF ) first floor living room and dining room, BM ) basement; the “walk” activity consisted of continuous vigorous walking and sitting on furniture; the vacuum cleaner used for the vacuum activities was a Kenmore (Sears) canister model with a paper filtration bag. Table 2 lists the average estimated k values following activities in the basement, the first floor bedroom, the first floor living and dining room, and the first floor combined. With the exception of the first floor bedroom activities, the values presented in Table 2 are within the range of those from previous studies as summarized by Long et al. (27). The k values for the basement are higher than those for the first floor. This discrepancy may be due to differences in the surface-to-volume ratio, turbulent mixing patterns, and the types of surfaces, all of which affect the rate of particle deposition to surfaces (31). Three of the first floor activity periods took place in the bedroom approximately 10 m from the SIM, including making the bed/folding clothes, folding blankets, and vacuuming. The k estimates following these activities are much smaller with a larger relative standard deviation than those from the remainder of the first floor activities, which took place 0-5 m from the SIM. The lower k values for the activities in the bedroom are most likely due to a time delay for the particles to mix from the bedroom to the adjacent living room after the activity period, slowing the decay as measured by the SIM in the living room. The concentration measured by the SIM for these activity periods was likely reduced by this time delay, leading to an underestimation of the source strength via eq 5. This hypothesis is supported by a study in a separate residence under natural ventilation conditions where a tracer gas was released in one room, and the concentration was measured in this room as well as an adjacent room connected by a short hallway and an open door (23). The results of the tracer gas study showed that it took 0.5-1 h after the source was shut off for the concentrations in the two adjacent rooms to become equal. Both this study and a previous study in the same home reported a time lag for the pollutant to reach the monitor that corresponded with a pollutant transport rate of approximately 1 m min-1 across the room (23, 32). Source Strengths. Calculated source strengths for the human activities are given in Figure 3. The source strength of 1.7 mg min-1 from smoking a cigarette is included as a reference (19). Smoking cigarettes is one of the largest sources of indoor PM2.5; however, the composition of cigarette smoke is markedly different than that of house dust. As shown in Figure 3, source strengths from human activities can be large enough to significantly affect human exposure to PM2.5 and PM5. The source strengths estimated for the human activities ranged between 0.03 and 0.5 mg min-1 for PM2.5 and between 0.1 and 1.4 mg min-1 for PM5. Vacuuming resulted in the

maximum PM2.5 source strength, while two persons walking around and sitting on furniture resulted in the maximum PM5 source strength. The maximum PM2.5 and PM5 source strengths were 27% and 84%, respectively, of the source strength from smoking a cigarette. The source strength for two persons walking and sitting on furniture on the first floor was almost 3 times larger than one person walking and sitting on furniture on the first floor. Dancing on a rug in the basement had PM2.5 and PM5 source strengths 3 times larger than walking on the same rug. In addition, dancing on the rug resulted in PM2.5 and PM5 source strengths 7 and 9 times higher, respectively, than dancing on a wood floor in the same location. Vacuuming resulted in slightly higher PM5 source strengths than just walking and sitting on furniture. However, the ratio of PM2.5 to PM5 for vacuuming was much higher than for any other activity examined. The PM2.5 to PM5 ratios for vacuuming in the living room and bedroom were 0.5 and 0.6, respectively, while the mean ratio for the remainder of the activities was 0.3. This difference may be due to the vacuum cleaner motor emissions (33), the release of fine particles embedded in the area rugs by the action of the vacuum cleaner, and/or the inefficiency of the vacuum cleaner bag in filtering fine particles.

Discussion This study maintains the importance of including resuspension of house dust from human activities when investigating human exposure to PM. The estimated source strengths demonstrate that, although most of the resuspended mass is larger than 5 µm in diameter, the resuspension of PM2.5 and PM5 from human activities can be substantial. Additional field studies are required to determine the source strengths for PM larger than 5 µm as well as to determine the range of source strengths from human activities. Chamber studies are also recommended for better quantification of the source strengths. Personal exposures to the same prescribed activities were reported in Ferro et al. (12). The relative importance of each of the activities based on their source strengths is different than that based on the personal exposures. For example, one person walking in the basement resulted in a much higher human exposure but a lower source strength than one person walking on the first floor. The mixing volume in the basement is much smaller than that of the first floor, allowing concentrations to build up. However, the dust loading may be lower in the basement, resulting in a lower source strength. Also, personal exposures are subject to the personal cloud effect, where the exposure measured by a personal exposure monitor worn by a person (PEM) is higher than what is predicted by the indoor concentration measured by the SIM. Activities that took place in the first floor bedroom, specifically making the bed/folding clothes, folding blankets, and vacuuming, had 15-min PM5 PEM/SIM ratios of 3.9, 8.5, and 1.5, respectively, while the average 15-min PM5 PEM/SIM ratio for the remainder of the activities was 1.4 ( 0.5. Thus, folding blankets resulted in one of the highest personal exposures but the lowest source strength. These ratios indicate that the proximity to the source played a large role in the observed differences between indoor concentration and personal exposure. The reduced particle decay rate k following the three activities that took place in the first floor bedroom indicates that the particles were still transporting from the bedroom to the living room during the decay period. Therefore, the assumption of instantaneous mixing does not apply for the activities that took place in the first floor bedroom, and the concentration measured at the SIM is lower than it would have been if the first floor volume were instantaneously mixed. This means the source strength estimates for those activities should be viewed as lower-bound estimates. VOL. 38, NO. 6, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

1763

Correspondingly, source strengths for the remaining firstfloor activities, which took place closer to the SIM, may be overestimated. However, because these activities were centrally located on the first floor in much larger rooms than the bedroom, the effect of noninstantaneous mixing on the resulting source strengths is reduced. Source strengths from one set of experiments in one home do not predict the range of source strengths that would be found in the United States. Although source strengths are independent of outdoor concentrations, infiltration rate, mixing volume, or decay rate, they are dependent on vigor of activity, dust loading, type of flooring, and type of furnishings. Because vacuum cleaners have a large range of efficiencies and motor emissions (33), the source strength for vacuuming is also dependent on the type of vacuum cleaner used. Prescribed activities may be more deliberate than those performed naturally and, therefore, may resuspend more dust. Conversely, because the home used for this study is professionally cleaned once per week, contains no cloth-upholstered furnishings (with the exception of beds and pillows), and has wood floors partially covered by thin area rugs, these source strengths may represent the lower end of the range. Nonetheless, this study provides an estimate of the magnitude of source strengths from indoor human activities that resuspend deposited PM and shows that they represent a significant source contribution to the indoor environment. This work also presents a general methodology that can be used to measure source strengths in other indoor settings.

Acknowledgments This study was funded by the Stanford University Shah Family Fellowship and the Center for Indoor Air Research (CIAR). The authors thank Wayne Ott and Victor W. Chang for their advice and assistance.

Literature Cited (1) Vedal, S. J. Air Waste Manag. Assoc. 1997, 47, 551-581. (2) Samet, J. M.; Dominici, F.; Curriero, F. C.; Coursac, I.; Zerger, S. L. N. Eng. J. Med. 2000, 343, 1742-1749. (3) Peters, A.; Dockery, D. W.; Muller, J. E.; Mittleman, M. A. Circulation 2001, 103, 2810-2815. (4) Wallace, L. J. Air Waste Manag. Assoc. 1996, 46, 98-126. (5) Wallace, L. Aerosol Sci. Technol. 2000, 32, 15-25. (6) Robinson, J. P.; Thomas, J.; Behar, J. V. Time Spent in Activities, Locations, and Microenvironments: a California-National Comparison; EPA/600/4-91/006, U.S. EPA, Las Vegas, NV, 1991. (7) Smith, K. R. Annual Rev. Energy Environ. 1993, 18, 529-566. (8) O ¨ zkaynak, H.; Xue, J.; Weker, R.; Butler, D.; Koutrakis, P.; Spengler, J. The Particle Team (PTEAM) Study: Analysis of the Data, Final Report, Volume III; EPA/600/R-95/098; U.S. EPA, Research Triangle Park, 1996. (9) Long, C. M.; Suh, H. H.; Koutrakis, P. J. Air Waste Manag. Assoc. 2000, 50, 1236-1250. (10) Thatcher, T. L.; Layton, D. W. Atmos. Environ. 1995, 29, 14871497.

1764

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 38, NO. 6, 2004

(11) Abt, E.; Suh, H. H.; Catalano, P.; Koutrakis, P. Environ. Sci. Technol. 2000, 34, 3579-3587. (12) Ferro, A. R.; Kopperud, R. J.; Hildemann, L. M. J. Exp. Anal. Environ. Epidemiol. 2003, in press. (13) Traynor, G. W.; Anthon, D. W.; Hollowell, C. D. Atmos. Environ. 1982, 16, 2979-2987. (14) Traynor, G. W.; Allen, J. R.; Apte, M. G.; Girman, J. R.; Hollowell, C. D. Environ. Sci. Technol. 1983, 17, 369-371. (15) Traynor, G. W.; Apte, M. G.; Carruthers, A. R.; Dillworth, J. F.; Grimsrud, D. T.; Gundel, L. A. Environ. Sci. Technol. 1987, 21, 691-697. (16) Koutrakis, P.; Briggs, S. L. K.; Leaderer, B. P. Environ. Sci. Technol. 1992, 26, 521-527. (17) Ott, W.; Switzer, P.; Robinson, J. J. Air Waste Manag. Assoc. 1996, 46, 1120-1134. (18) Klepeis, N. E.; Ott, W. R.; Switzer, P. Environ. Sci. Technol. 1996, 30, 2813-2820. (19) Brauer, M.; Hirtle, R.; Lang, B.; Ott, W. J. Exp. Anal. Environ. Epidemiol. 2000, 10, 136-144. (20) Schneider, T.; Kildeso, J.; Breum, N. O. Building Environ. 1999, 34, 583-595. (21) Kildeso, J.; Vinzents, P.; Schneider, T. Textile Res. J. 1999, 69, 169-175. (22) John, W.; Reischl, G. J. Air Pollut. Control Assoc. 1980, 30, 872876. (23) Ferro, A. R. The Effects of Proximity, Compartments, and Resuspension on Personal Exposure to Indoor Particulate Matter, Ph.D. Thesis, Stanford University, Stanford, CA, 2002. (24) Baughman, A. V.; Gadgil, A. J.; Nazaroff, W. W. Indoor Air 1994, 4, 114-122. (25) Drescher, A. C.; Lobascio, C.; Gadgil, A. J.; Nazaroff, W. W. Indoor Air 1995, 5, 202-214. (26) Mage, D. T.; Ott, W. R. In Characterizing Sources of Indoor Air Pollution and Related Sink Effects; Tichenor, B. A., Ed.; American Society for Testing and Materials: West Conshohocken, PA, 1993; pp 263-278. (27) Long, C. M.; Suh, H. H.; Catalano, P. J.; Koutrakis, P. Environ. Sci. Technol. 2001, 35, 2089-2099. (28) Vette, A. F.; Rea, A. W.; Lawless, P. A.; Rodes, C. E.; Evans, G.; Highsmith, V. R.; Sheldon, L. Aerosol Sci. Technol. 2001, 34, 118-126. (29) Mosley, R. B.; Greenwell, D. J.; Sparks, L. E.; Guo, Z.; Tucker, W. G.; Fortmann, R.; Whitfield, C. Aerosol Sci. Technol. 2001, 34, 127-136. (30) Liu, D.-L.; Nazaroff, W. W. Atmos. Environ. 2001, 35, 44514462. (31) Nazaroff, W. W.; Gadgil, A. J.; Weschler, C. J. In Modeling of Indoor Air Quality and Exposure; Nagda, N. L., Ed.; American Society for Testing and Materials: Philadelphia, 1993. (32) Ott, W.; McBride, S.; Switzer, P. 2002. In Proceedings of the 9th International Conference on Indoor Air Quality and Climate; Levin, H., Ed.; Indoor Air 2002, Santa Cruz, CA, 229-234. (33) Lioy, P. J.; Wainman, T.; Zhang, J.; Goldsmith, S. J. Air Waste Manag. Assoc. 1999, 49, 200-206.

Received for review December 5, 2002. Revised manuscript received December 15, 2003. Accepted December 22, 2003. ES0263893