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Size-resolved source emission rates of indoor ultrafine particles considering coagulation Donghyun Rim, Jung-Il Choi, and Lance Arthur Wallace Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b00165 • Publication Date (Web): 14 May 2016 Downloaded from http://pubs.acs.org on June 5, 2016

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Environmental Science & Technology

Size-resolved source emission rates of indoor ultrafine particles considering coagulation Donghyun Rim 1, Jung-Il Choi2*, Lance A. Wallace3, 1

Department of Architectural Engineering, Pennsylvania State University, University Park, PA 16802 2

Department of Computational Science and Engineering, Yonsei University, Seoul 03722, Korea

3

Consultant, 428 Woodley Way, Santa Rosa, CA 95409

*

Corresponding author: Jung-Il Choi Yonsei University, Seoul 03772, Korea Email: [email protected] Abstract Indoor ultrafine particles (UFP, < 100 nm) released from combustion and consumer products lead to elevated human exposure to UFP. UFP emitted from the sources undergoes aerosol transformation processes such as coagulation and deposition. The coagulation effect can be significant during the source emission due to high concentration and high mobility of nano-size particles. However, few studies have estimated size-resolved UFP source emission strengths while considering coagulation in their theoretical and experimental research work. The primary objective of this study is to characterize UFP source strength by considering coagulation in addition to other indoor processes (i.e., deposition and ventilation) in a realistic setting. A secondary objective is to test a hypothesis that size-resolved UFP source emission rates are unimodal and log-normally distributed for three common indoor UFP sources: electric stove, natural gas burner, and paraffin wax candle. Experimental investigations were performed in a full-scale test building. Size- and time-resolved concentrations of UFP ranging from 2 nm to 100 nm were monitored using a Scanning Mobility Particle Sizer (SMPS). Based on the temporal evolution of particle size distribution during the source emission period, size-dependent source emission rate was determined using a material-balance modeling approach. The results indicate that for a given UFP source, the source strength varies with particle size and source type. The analytical model assuming log-normally distributed source emission rate could predict the temporal evolution of particle size distribution with reasonable accuracy for gas stove and candle. Including the effect of coagulation was found to increase the estimates of source strengths by up to a factor of 8. This result implies that previous studies on indoor UFP source strengths considering only deposition and ventilation might have largely underestimated the true values of UFP source strengths, especially for combustion due to natural gas stove and candle.

Keywords: nanoparticles, source strength, electric stove, gas stove, candle, log-normal distribution

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Introduction In the past decade, studies in literature show that ambient ultrafine particles (aerodynamic diameter < 100 nm) are associated with adverse health effects such as pulmonary inflammation, increased oxidative stress, and mitochondrial damage (1-4). With regard to toxicological effects of UFP, relatively high particle number concentration and large surface area allow greater proportion of the particles adsorbed or condensed in tissues and blood stream (5-7). High number concentrations of UFP have been reported to exist within residences due to prevalence of UFP emission sources in relatively smaller volume of enclosed buildings than outdoors. Major indoor UFP sources include combustion due to gas stove (8-10), cigarette smoking and incense (10-12), candle burning (10-12), and high temperature process that produce particles due to thermal desorption of molecules from heated surfaces (13-15) as well as chemical reactions between ozone and hydrocarbons (16), and operation of electrical motors and equipment (10, 17). Once emitted from an indoor source, the airborne particles undergo size transformation processes such as coagulation and deposition. Such processes play important roles in dynamic behavior of particle size distribution. Specially, when UFP number concentration is high due to source emission, coagulation is of primary importance in affecting the evolution of ultrafine particles. During the coagulation process, particles collide with one another or with larger particles, resulting in loss of smaller particles and gain of larger particles (17). This process shifts particle size distribution toward larger sizes, although the impact varies with source type, emission strength, and emission period. Coagulation is a second order process involving particle number


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concentrations, so as particle number increases due to UFP source emission, the impact of coagulation will be much higher. A number of studies in literature characterized source emission rates (8-15) for different types of indoor microenvironments. However, most previous studies have neglected coagulation effects and did not report information of size-resolved emission strength (11, 15-16). Such studies calculated only lump-sum source strength by taking into account particle losses due to particle deposition and air change rate, and the peak total concentration due to an emission source. Recently, some studies (19, 21-23) have revealed that the size-dependent coagulation effect can be important during periods with high particle number concentrations. Nonetheless, size-resolved UFP emission rates considering coagulation have seldom been previously reported for common indoor sources in full-scale buildings. To our knowledge, only one study (8) has reported sizeresolved UFP emission rates based on experiments in a realistic building. Given this background, the primary objective of this study is to characterize size-dependent emission rates of indoor UFP sources in a full-scale test building considering detailed coagulation process in addition to deposition and ventilation. A secondary objective is to test a hypothesis that size-resolved UFP source emission rates are unimodal and log-normally distributed. This study considers three major indoor UFP sources: 1) high surface temperature process associated with electric stovetop coil, 2) gas burner, and 3) paraffin wax candle. For each of the three major indoor UFP sources, this study elucidates the influence of coagulation involved in the source emission and particle decay period. It should be noted that the two combustion sources produce particles as long as fuel is available, whereas the particles from the electric stove are probably produced from an organic film coating the coils (17) and may be exhausted before the end of the heating period.



Methods Experiments were performed to examine the UFP emission and decay characteristics of the three common indoor UFP sources. Based on the experiment data, dynamic behavior of the UFP size distributions were analyzed using a material-balance modeling approach for a single well-mixed air volume. The subsequent sections describe the detailed information of 1) test building, 2) instrumentation and particle sampling protocol, and 3) analytical modeling approach. Test building Experiments were conducted within a full-scale residential test building. This 140-square-meter single-story manufactured house consists of three bedrooms, two bathrooms, and a combined family, kitchen, dining and living area. The house layout is shown in Supporting Information. The house has a forced air heating and cooling system located off the dining area, with the supply air distribution ductwork located in the belly space and a single return grille located in a panel of the HVAC system closet. The building was moderately furnished with tables and measurement equipment. During the UFP monitoring, all exterior doors and windows were closed and the house was occupied by only one researcher. In the tests with the gas stovetop and electric burners, the UFP source was activated in the kitchen with all interior doors open and the central mixing fan running in the house at a volumetric flow rate of 2000 m3/h. In this case, indoor air under equilibrium conditions was well mixed in the house with the tracer gas concentrations across all seven interior zones within 5% relative standard deviation (RSD). However, during the first few minutes with the kitchen source on, the air would not be wellmixed—at an equivalent 6 air changes per hour, 10 minutes would be required for the particle concentrations to reach 63% of an equilibrium level theoretically. The candle burning test was performed in the master bedroom with the room doors closed and the central fan off. Note that


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deposition rate varies with the fan-operating mode: when the fan is off, particles deposit only on indoor surfaces of the master bedroom, while with the fan operating particles additionally deposit on the furnace filter (low efficiency mechanical filter) and duct surfaces.

Instrumentation and test conditions UFP size and number concentrations were measured in the master bedroom for all tests using a Scanning Mobility Particle Sizer (SMPS Model 3936, TSI Inc.). The SMPS consisted of an electrostatic classifier, a nano-differential mobility analyzer (nano-DMA), and a water-based condensation particle counter (WCPC). An external pump employing a critical orifice was added to increase the aerosol flow through the WCPC from 0.6 to 1.5 L/min, allowing the lower bound of the particle size to be extended down to to 2 nm. Using this system, size-resolved particles with aerodynamic diameters ranging from 2 nm to 105 nm were monitored. The charging efficiency was increased using an enhanced radiation source (TSI 3077A neutralizer), especially for the smallest particles (2 nm). WCPC introduced water-saturated air flow to achieve condensational growth of nanoparticles in the sampled air before counting particles. The system monitored particles from 2 nm to 64 nm using an aerosol sampling flow rate of 1.5 L/min, and particles from 3 nm to 100 nm using a sampling flow rate of 0.6 L/min. For both cases, the ratio of sampling flow rate to sheath flow rate was 1:10. To ensure the quality of particle measurement, the sampling aerosol flow rates were checked on-site at least three times before every measurement using a gas flow calibrator and verified to agree within 2 %. Using this particle measurement system, time-varying concentrations of size-resolved UFP were monitored during the emission and decay periods for three major indoor sources: 1) electric stove, 2) gas stove, and 3) paraffin wax candles. The aerosol sampling rate was set to 120 s of size-



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resolved concentration measurement for 97 particle size categories followed by 30 s for the voltage to return to baseline. During each test, outdoor air change rate in the house was measured using an automated tracer gas monitoring system. Sulfur hexafluoride (SF6) was injected as a tracer gas into the house every 4 h, and a gas chromatograph with electron capture detector (GC-ECD) system monitored continuously the concentration decay of SF6 in seven major zones of the building (see Figure S1). For the seven zones, the air change rate was assessed for each zone as the best fit slope to a plot of the natural logarithm of the tracer gas concentration versus time based on ASTM E741 (24). The procedure for UFP source emission test was as follows: 1) 10 minutes of background concentration measurements, 2) 15-60 minutes of UFP source, and 3) subsequent 60 minutes UFP decay after the emission source was deactivated. Table 1 describes the test conditions including the duration of source emission, central fan running mode, and air change rates. Table 1. Experimental conditions Source tested

Test ID

Emission period (minutes)

Central forced fan operation mode

Avg. air change rate (SD) (h-1)

ELEC1

40

ON

0.17 (0.03)

ELEC2

40

ON

0.18 (0.04)

ELEC3

40

ON

0.20 (0.02)

ELEC4

40

ON

0.28 (0.02)

GAS1

20

ON

0.30 (0.02)

GAS2

20

ON

0.60 (0.08)

GAS3

20

ON

0.24 (0.02)

GAS4

15

ON

0.31 (0.04)

Electric Stove

Gas Stove*


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Paraffin Wax Candle

CAND1

60

OFF

0.12 (0.01)

CAND2

60

OFF

0.18 (0.03)

*

Gas flow rate was set to 4 L/min for GAS1, GAS2, and GAS, while the flow rate was 7 L/min for GAS 4.

In the tests with the gas stovetop and electric burners, the UFP source was activated in the kitchen while the central mixing fan was running in the house at the flow rate of approximately six house volume per hour. The candle burning test was carried out by burning a paraffin wax candle in the master bedroom with the central fan off and the room doors closed. To determine the importance of source emission period, duration of source emission varied from15 min to 60 min for some selected tests. During the whole test period, the data of time-varying indoor UFP concentration and air change rate were collected. The air changes rates observed for all tests ranged from 0.12 to 0.60 h-1.

Analytical modeling approach The dynamic behavior of the UFP size distributions were analyzed using an analytical materialbalance model that considered coagulation, deposition, and ventilation in a single and wellmixed air volume. The governing equation for the aerosol dynamics model that includes source emission is as follows: ̅

̅

̅

̅

Equation (1) where

[m-3] is the particle number concentration for particle volumes [m3] between at time t [s];

and

̅ and ̅ are volumes of two coagulating particles; v is the volume of

newly coagulated particle; β is the coagulation kernel (collision kernel); a is the air change rate



[h-1]; and k is the particle deposition rate [h-1]; between

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is source emission rate for a particle sizes

at time t [h-1 is an involved volume (the whole house or master

and

bedroom) [m3]. The first two terms on the right hand side in Equation (1) represent the particle gain and loss due to coagulation in which two particles collide and stick together. The third term accounts for the particle loss due to deposition and ventilation that are defined as a function of particle size. Particle deposition for the fan operating condition was based on regression of 31 different 3-day datasets from the same test house (19) (Figure 1). On the other hand, particle deposition with the central fan off condition was derived from the Lai–Nazaroff model (23), using a friction velocity of 3 cm/s (Figure 1). The last term represents the particle gain due to source emission. For a given source, the total number of particles released from the source per unit time was considered is log normally

as stable. We hypothesized that the steady source emission rate, distributed in size and used the following equation:

where

01

!

"√$% &' ()

*+,

&' &' ) / !. &' () -

/2

34 3

is a total number of particles released per unit time [h-1];

volume and 65 is standard deviation for a log-normal distribution.

5 5

Equation (2) is a geometric mean and 65 were estimated

based on particle size distributions at the initial 10 min of source emission. A discrete delta function is defined as 2

34 3

78

34

8

34

3 , which distinguishes the

source emission period. Here 3 is the emission period, 34 is a time delay, and 8 Heaviside function. Note that 8

if 9 : and 8

is a

: otherwise. Kovisto et al. (22)

showed similar pattern in log-normal distribution between source emission rates and particle size distributions due to pulse and continuous injections in a laboratory chamber. We evaluated the uncertainty associated with the log-normal distribution parameters based on the change in particle size distribution during the initial 10 min of source emission. We compared two types of the source emission strength ( ). The first is an optimized emission rate that minimizes the difference in total number concentration between the measurement and model prediction based on Equation (1). In this case, coagulation was considered and sizeresolved source emission rates were determined by the least square sum fitting of Equation (1) to the measurement data. The second approach was based on a conventional method that did not


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consider coagulation, but only considered deposition (k) and air change rate (a) along with the involved air volume (V), and total UFP concentration (N) at time t (17): 1; 1
50,000 cm-3) of nanoparticles (< 20 nm) released from the sources. Previous studies also


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observed the coagulation effects for ultrafine particles originated from gas stove (8, 15, 17), but only one study (8) estimated the size-resolved source emission rate for just two size categories ( 10 nm) considering the coagulation. Figure 4 shows size-resolved emission rates calculated based on the coagulation model for three tests (ELEC4, GAS1, and CAND2). The size-resolved emission rates are unimodal and lognormally distributed in a particle size range from 2 nm to 20 nm. The total particle emission rate (Se in equation 2) is the highest with the gas stove (GAS1) followed by candle (CAND2) and electric stove (ELEC4). The geometric mean particle sizes are 4.6 nm for GAS1, 3.9 nm for CAND2, and 5.0 nm for ELEC4. The discrepancy between the coagulation model and the conventional model is the largest for the candle, mainly due to a long emission period (60 min) These results in Figure 4 demonstrate that conventional model underestimate the size-resoled source emission rate. Also note that the majority of the primary particles originated from indoor combustion or high surface temperature process are smaller than 10 nm. Future studies that analyze emission strengths of such indoor UFP sources should include monitoring of particles < 10 nm.



Figure 4. Size-resolved source emission rates based on the coagulation model and the conventional model: (A) Electric Stove (ELEC4); (B) Gas Stove (GAS1); and (C) Candle (CAND2). Error bars represents uncertainty associated with variations of the model parameters: air change rate, deposition rate, and log-normal distribution parameters. Note that y-axis scale varies with the UFP source type. Table 2 provides a more detailed description of best-fit log-normal distribution parameters for size-resolved source emissions, best Hamaker constant for coagulation model, and source emission strength (Se) estimated by our coagulation model and the conventional model. The geometric mean of the log-normal distribution ranged from 5 to 6 nm for the electric stove from 5 to 8 nm for the gas stove, and from 3 to4 nm for the candle.


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The coagulation model with an assumption of log-normally distributed source emission revealed UFP source strengths of 1.8 – 2.8×1012 min-1 for the electric stove. This range agrees with the estimates by Afshari et al. (16) and Rim et al. (19) that did not consider coagulation and reported emission strength ranging from 0.5 to 3.4×1012 min-1. However, the only previous study including a full accounting of coagulation (8) found an upper range of 14 × 1012 min-1, about 5 times the value found here. This can be explained by our use of a 40-minute heating period, which probably exceeded the time during which particles were being desorbed from the stovetop coil surface. If that time was on the order of 8-10 minutes, then our estimate of the emission rate could be 4-5 times too low. The coagulation model revealed UFP source strengths of 2.9 –76×1012 min-1 for gas stove and 0.70 –2.75×1012 min-1 for candle. These ranges are notably higher than those reported by previous studies (8, 13-14, 19) that did not consider coagulation over the emission period. Although they monitored particles down to 2 nm, the previous studies reported UFP emission rates of 1.9–17×1012 min-1 for gas stove and 0.06 - 0.80 ×1012 min-1 for candle. Such ranges are similar to the estimates from the conventional model in this study. The difference in source strength between the coagulation model and conventional model in this study is found to be up to a factor of 6 for the gas stove and 8 for the candle. This large discrepancy suggests significant effect of coagulation on the estimation of UFP source strength for combustion due to gas stove and candle.



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Table 2. Summary of log-normal source emission rate estimates

Source tested

Electric Stove

Gas Stove Paraffin Wax Candle

Log-normal distribution Test ID

Best Hamaker Constant (KBT)

Source Strength, Se – (×1012 min-1)

150

Coagulation model (SD) 2.81 (0.12)

Conventional model (SD) 1.44 (0.05)

Difference factor 1.96

1.72 (0.15)

20

1.86 (0.11)

1.12 (0.04)

1.66

5.84 (0.13)

1.74 (0.16)

200

2.02 (0.09)

1.14 (0.04)

1.78

ELEC4

4.97 (0.18)

1.43 (0.04)

100

1.80 (0.10)

1.01 (0.03)

1.79

GAS1

4.65 (0.66)

1.55 (0.10)

20

16.3 (1.11)

7.10 (0.10)

2.29

GAS2

8.04 (0.39)

1.64 (0.13)

20

3.83 (0.09)

2.56 (0.04)

1.49

GAS3

5.50 (0.27)

1.52 (0.10)

20

3.09 (0.19)

1.99 (0.03)

1.55

GAS4

5.88 (0.44)

1.35 (0.05)

20

74.7 (1.69)

12.8 (0.15)

5.85

CAND1

3.10 (0.35)

1.43 (0.29)

100

0.68 (0.07)

0.14 (0.001)

5.02

CAND2

3.86 (0.18)

1.38 (0.03)

100

2.75 (0.05)

0.35 (0.007)

7.96

ELEC1

GMD (SD) (nm) 5.54 (0.28)

Dispersion (SD) (-) 1.60 (0.10)

ELEC2

5.84 (0.16)

ELEC3

Figures 5A-5C show the particle size distribution at the end of the source emission period. The figures provide the errors associated with the coagulation model and the conventional model. In the figures, the dots indicate measurements, while the lines represent model predictions by 1) the coagulation model and 2) conventional model. The model predictions are based on the timemarching calculation of particle size distribution over the emission period with a time step of 1 second. The error bars represent the uncertainty associated with deposition rates, air change ranges, and log-normal particle size distribution parameters. According to the figures, the coagulation model could predict the UFP size distribution at the end of the emission period with reasonable accuracy, while the conventional model fails to predict size- resolved UFP concentrations regardless of varying emission periods for different sources. The figures also suggest that the coagulation model with log-normally distributed emission yields reasonable estimates of particle size dynamics in a full-scale test building. However, the conventional model


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with an assumption of log-normal distribution underestimates the particle peak concentration by factors of up to 3 as well as the geometric mean of the distribution. This discrepancy is mainly attributed to the simplified modeling approach that neglects coagulation effects over the source emission period. The higher the particle concentration due to source emission, the more remarkable discrepancy is observed between measurement and conventional model (Fig. 5C). Specially, in the case of candle (Fig. 5C), the emission was longer than other sources, accordingly a strong coagulation effect occurred in the particle dynamics until the end of the emission period when particle size distribution evolved into a bimodal distribution.



Figure 5. Comparisons of size-resolved particle distributions at the end of source emission between measurements and model predictions: (a) Electric Stove (ELEC4); (b) Gas Stove (GAS1); and (c) Candle (CAND2). Error bars represents uncertainty associated with the log-normal distribution parameters. Note that y-axis scale varies with the UFP source type.


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Testing of Log-normal distribution of size-resolved source emission rates Figure 6 compares the modeled log-normal size distribution (x-axis) of source emission rates with the measured particle size distribution (y-axis) for initial 10-min of emission period using cumulative distribution function (CDF). The CDF simply shows the integrated fraction of particles for a given particle size range. If the CDFs perfectly match between model and measurement, then the geometric mean and standard deviation of log-normal size distribution are the same for the model and experiment. According to Figure 5, size-resolved emissions associated with the electric stove are not necessarily log-normally distributed, while the sizeresolved emissions for gas stove and candle are very close to log-normal distributions. This result is perhaps not surprising because the particles released from hot surface temperature process strongly depend on available organic and inorganic compounds sorbed on the heated burner surfaces, and their equilibrium partitioning between the surface and air at different temperature (16-17). The emission time of 40 min for the electric stove could be also longer than the time to desorb the compounds on the hot surface. On the other hand, gas stove and candle produce particles steadily at relatively constant rates compared to the hot temperature process. Therefore, the assumption of steady and log-normal size-resolved UFP emission seems to work well for combustion due to gas stove and candle (Figures 6B and 6C). It may also work well for a hot surface temperature process such as the electric stove provided the heating period is chosen to match the period of desorption of organics from the stovetop coil (Figure 6A).



Figure 6. Comparisons of particle distributions for initial 10 minutes of source emission: (A) Electric Stove (ELEC4); (B) Gas Stove (GAS1); and (C) Candle (CAND2). Error bars represents experimental uncertainty from four different scans of particle size distribution.

This study provided new experimental information of size-resolved source emission strength for common indoor UFP sources. The source emission rates reported in this study provide detailed size-resolved source strengths associated with combustion and high temperature process in a realistic indoor environment. The study results also support the assumption that the size-resolved source emission rates for natural gas stove and candle are log-normally distributed; however, deviation from the log-normal distribution can exist for electric stoves. A few limitations of this study should be noted. The assumption of perfect mixing throughout the entire house is not valid during the few minutes of the initial emission, although we adjusted the time-delay of concentration increase for the electric stove test. Considering that UFP emission rate due to the electric stove varies with the amount of substrates on the stovetop coil over time, more electric stove tests should be performed further with varying emission periods (5-60 min). The present study did not analyze variations in UFP emission rates across different cooking styles. Variations in the cooling style, food, oil, and pan type and operating conditions (i.e., gas flow rate, and surface temperature) could alter the size distribution and size-resolved emission rates of UFP. The primary goal of our study is to provide baseline size-resolved source


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emission strengths of naked gas and electric burners. Future studies can examine further how the size-resolved emission rate is altered depending on the cooling type, food, oil, and pan type. The study results of the candle tests are limited to only paraffin wax candles. Future studies can examine further how size-dependent emission rates vary with candle type, chemical composition, shape, flame size, and burning mode (steady burning, unsteady burning and smoldering). Such parameters can significantly influence particle emission rates of candle (13-14). Future studies are also warranted to examine characterize the size-resolved UFP emissions owing to hot surface temperature processes used for consumer products or office machines (i.e., hair dryer, antimosquito products, 3D printers, cooking pans, etc). Acknowledgement This work was supported by National Research Foundation of Korea (NRF) grants funded by the Korea government (MSIP) (NRF-2011-0014558). The authors thank to Ms. Haeeun Han for her help with rendering the TOC art. References (1) Weichenthal, S., Dufresne, A., & Infante>Rivard, C. (2007). Indoor ultrafine particles and childhood asthma: exploring a potential public health concern. Indoor air, 17(2), 81-91. (2) Donaldson, Ken, et al. "The pulmonary toxicology of ultrafine particles." Journal of aerosol medicine 15.2 (2002): 213-220. (3) Li, N., Sioutas, C., Cho, A., Schmitz, D., Misra, C., Sempf, J., & Nel, A. (2003). Ultrafine particulate pollutants induce oxidative stress and mitochondrial damage. Environmental health perspectives, 111(4), 455. (4) G. Oberdörster et al., Environ. Health Perspect. 113, 823 (2005). (5) Verma, A., & Stellacci, F. (2010). Effect of surface properties on nanoparticle–cell interactions. Small, 6(1), 12-21. (6) Nel, A., Xia, T., Mädler, L., & Li, N. (2006). Toxic potential of materials at the nanolevel. Science, 311(5761), 622-627. (7) Bakand, S., Hayes, A., & Dechsakulthorn, F. (2012). Nanoparticles: a review of particle toxicology following inhalation exposure. Inhalation Toxicology, 24(2), 125-135. (8) Wallace, L., Wang, F., Howard-Reed, C., & Persily, A. (2008). Contribution of gas and electric stoves to residential ultrafine particle concentrations between 2 and 64 nm: size distributions and emission and coagulation rates. Environmental science & technology, 42(23), 8641-8647.



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Size-Resolved Source Emission Rates of Indoor ... - ACS Publications

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