The Role of Condensation and Coagulation in Aerosol Monitoring

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The role of condensation and coagulation in aerosol monitoring

A. KELLER AND H.C. SIEGMANN

Laboratory for Combustion Aerosols and Suspended Particles, Swiss Federal Institute of Technology (ETH), CH—8093 Zu¨rich, Switzerland

We derive general-purpose mathematical model for pollution concentration studies. The model is based on the aerosol general dynamic equation (GDE).It accounts for aerosol processes like coagulation and growth by deposition and is therefore suited for suspended-particle monitoring. Our model is validated by controlled experiments done using standard aerosol monitoring devices that measure PM10, particle cross section, particle-bound polycyclic aromatic hydrocarbons (PPAHs) and number concentration, showing an excellent agreement with the experimental data in a 77-m3 room with a time sequence of cigarettes smoked. As an example of an application, we calculated the mean PPAH emission rate in environmental tobacco smoke (ETS) for a ‘‘smolder- smoked’’ cigarette and found it to be 8 ng/s for a total emission of 5.28 g per cigarette. The results show that real aerosol dynamics should be taken into account when monitoring suspended particles. Journal of Exposure Analysis and Environmental Epidemiology (2001) 11, 441–448.

Keywords: aerosol monitoring, environmental tobacco smoke, indoor air pollution, PAH, particles, RSP.

Introduction therefore, it just accounts for the indoor–outdoor air exchange rate, deposition and other properties, which There has been a growing interest in monitoring human involve first-order processes in a mass balance differential exposure to aerosol nanoparticles in the last few years. The equation. Nevertheless, when using sensors that measure reason for this is the increasing amount of evidence that links properties other than aerosol mass, as is the case with the nanoparticles with a wide range of public health problems number concentration, cross section, photoionization, or that go from allergic diseases (Bo¨mmel et al., 2000) to the light scattering, or when measuring aerosol mass indirectly shortening of life expectancy by as much as several years (i.e., when using most portable sensors) second-order (Leuenberg et al., 1995; Godleski et al., 1996). Therefore, it terms, such as the aerosol coagulation, must be considered. is important to develop accurate models for human exposure A comparison between the mass balance model and our to these particles in everyday life that take into account model that includes an additional second-order term will be several particle properties and not only the total particle mass. presented.1 The use of the new term will be validated with For instance, substances like the polycyclic aromatic hydro- our experimental data, obtained from aerosol devices that carbons (PAHs) absorbed on the surface of particles may work with different principles, and as an application induce cancer in humans (Denissenko et al., 1996). example the total PPAH emission of a cigarette will be It has been previously shown that a mass balance model calculated. It will also be shown that the comparison of used in combination with portable aerosol sensors is suitable different sensors reveals more information on physical and for estimations of indoor particulate concentrations and chemical properties of the aerosol. cigarette emission rates (Ott et al., 1992; Klepeis et al., 1996; Brauer et al., 2000). More specifically, such a method has been used to estimate the indoor particle-bound Methods polycyclic aromatic hydrocarbon (PPAH) concentration coming from traffic (Dubowsky et al., 1999), environ- Indoor Measurements mental tobacco smoke (ETS; Ott et al., 1994) and other We performed a series of experiments to determine the indoor combustion sources. The method is designed to be amount of PPAHs generated from ETS under controlled used when measuring aerosol mass with a piezoelectric conditions. The experimental setup was based on the one balance or when monitoring ambient gas concentration and, suggested for chamber measurements by Ott et al. (1992) and Brauer et al. (2000). Four cigarettes were lighted simultaneously by a smoking machine (Filtrona model 1. Address all correspondence to: A. Keller, Solid State Physics HPF-G3, ETH Hoenggerberg, CH-8093 Zu¨rich, Switzerland. Tel.: +41-1-633- 2597. Fax: +41-1-633-1080. E-mail: [email protected] 1For detailed assumptions and experimental validation of the mass balance Received 10 August 2001. method, refer to Ott et al. (1992). Keller and Siegmann Condensation and coagulation in aerosol monitoring

302) but then left to burn by themselves (‘‘smolder- sample of PAHs with the integrated signal obtained from the smoked’’). Afterwards they were put out by dousing them PPAH sensors. into water. Commercially available filter cigarettes were used. The experiments were done inside a 77-m3 room with Diffusion Charging two ventilators placed inside to ensure a fast mixture of the An Ecochem DC 2000 CE diffusion charging sensor was cigarette smoke. also used in the indoor experiments. This sensor works by In another set of experiments, we sampled the aerosol in producing positively charged ions by a glow discharge the mainstream smoke by setting the smoking machine to formed in the neighborhood of a thin wire. The ions are burn the cigarettes, performing puffs every 60 s. The repelled by the wire, which is at positive potential and travel mainstream smoke was collected into filters, while side- to the space containing the particles. During this process, the stream smoke was released into the room; the filters were ions have a probability of attaching to a particle. If this then analyzed to determine the amount of PAHs in them by happens, the particle carries the charge. The gas containing means of a commercial gas chromatography mass spec- the particles is then sampled in a filter where the current trography (GC-MS) analysis. flowing from the filter to ground potential is measured. For On average, each cigarette burned for about 8 min when particles with a diameter below 100 nm, the probability of smoked by the machine and 11 min when left to smolder. one ion hitting the surface and sticking to it is proportional to the cross section of the particle. Hence, this instrument PPAH measures the active surface of small particles (i.e., the A portable PPAH sensor (EcoChem PAS 2000 CE) was exposed fraction of the surface, also called ‘‘Fuchs used to measure the PPAH concentration during the surface’’) without being sensitive to the chemistry (Qian experiments. The photoelectric aerosol sensor (PAS) uses et al., 2000). an excimer lamp to expose the aerosol flow to UV radiation with an energy h below the threshold for ionization of the PM10 gas molecules but above the photoelectric threshold of the We used a TSI Dusttrak (model 8520), which is a portable, particles (i.e., photoelectrons are emitted from the particle). battery-operated instrument that measures the scattering of The emitted photoelectric current is determined by collect- infrared light coming from a GaAs-laser diode at an angle ing the positively charged particles in a filter and looking at of 908. It has an impactor at the sample entrance that the current flowing to ground potential. The wavelength of removes all particles above 10 m, and gives a value of the excimer lamp is chosen in such a way that the mass per cubic meter. It is factory calibrated to relate the photoelectric yield is mainly governed by the yield coming intensity of the scattered light to the particle mass from aerosol particles, which have PAH molecules adsorbed concentration of a standard aerosol sample (A1 test dust, on their surface (Kasper et al., 1999). The resulting previously know as ‘‘Arizona dust’’), which exhibits a wide photoelectric current establishes in fact a signal, which is size distribution. proportional to the mass concentration of PPAHs (Burtsch- er and Siegmann, 1994). Number Concentration To estimate the number concentration of aerosol particles, a Calibration of PPAH Sensors continuous-flow ultrafine condensation particle counter The Ecochem PAS 2000 CE sensors are sold with (TSI CPC model 3025A) was used. The CPC is a device calibration for combustion aerosols from traffic. Since these specially designed for detection of particles with a size sensors do not measure PAH mass directly, a new smaller than the wavelength of visible light (down to 3 nm). calibration has to be done when changing the aerosol Particles that enter the measurement device serve as source. In our case, the calibration was done for particles condensation nuclei for oversaturated butanol vapor and emitted from the combustion of the test cigarettes. grow. The butanol-covered particles are then big enough to In the same room used for the indoor measurements (a be counted by means of light scattering. well-ventilated and well-mixed 77-m3 room), the test cigarettes were burned using the smolder method. Four to six cigarettes were burned simultaneously (average burning Results and discussion time 11 min), waiting between 30 and 60 min before the next set of cigarettes was burned to avoid a saturation of the Population Balance Equation sensors. A total of 70 cigarettes were burned in a 13-h Ott et al. (1992) have shown that the indoor mass period. During this time, two PAS 2000 CE and a DC 2000 concentration of pollutants can be well described by CE sensors acquired data every 10 s. Additionally, a filter means of the mass balance model. Nevertheless, this was sampling the aerosol in the room at a flow rate of 0.84 model is not well suited to describe other aerosol m3/h to do a GC-MS analysis and compare the collected properties. Moreover, since most of the portable aerosol

442 Journal of Exposure Analysis and Environmental Epidemiology (2001) 11(6) Condensation and coagulation in aerosol monitoring Keller and Siegmann sensors used to monitor aerosol mass actually rely on the changes in number concentration (k=0), particle cross other physical properties, they should be used together section (k=2/3), mass and volume (k=1) and light with a model derived from the general dynamic equation scattering (2/3k2), among others. Additionally, such (GDE, see, e.g., Friedlander, 2000), which correctly an equation can even be used in the case of aerosols describes the aerosol dynamics. In this section, we shall composed of agglomerates with fractal dimension D f by Df introduce the definition of moment of the size distribution taking into account the power law relationship v / dp . M k, list the relevant moments for our experiments, and use the population balance equation derived by Keller and Time Series Model Siegmann (2001) to construct a time series model that Consider a well-mixed room of volume V, an indoor aerosol can be used for aerosol monitoring. concentration with size distribution n(v,t ), an indoor source producing aerosol at a rate g(v,t), and an outdoor aerosol concentration x (v,t ) entering the room at a rate ! (air flow Size Distribution Moments 0 rate). Keller and Siegmann (2001) showed that for an The kth moment of the size distribution function is defined aerosol presenting a narrow size distribution, which is the as (Friedlander, 2000) case of the aerosol produced in our indoor measurements, Z1 the population balance equation for the kth moment can be k Mk ðtÞ¼ v nðv; tÞdv; ð1Þ written as 0 @ ! g ðtÞ 1 ðM Þ¼ ½x ðtÞÀM þ k À M À K M 2; ð7Þ where n(v,t ) is the particle size distribution (number of @t k V 0;k k V k k 2 k k particles per unit volume) at time t, v is the particle volume k k where g k (t)=v g(t,v) and x 0,k (t)=v x 0(v,t) are the and k is an arbitrary real number. The zeroth moment, contributions from the indoor source and outdoor concen- Z1 tration, respectively, to the kth moment, and v is the average particle volume. The first-order change rate coefficient is M0ðtÞ¼ nðv; tÞdv ¼ NðtÞ; ð2Þ k defined as 0 d kI is the total concentration of particles and the first moment is k À ; ð8Þ the total volume of the particles per unit volume of gas: V v Z1 where d is the rate of particle loss due to diffusion to the walls, and I is the single-particle growth rate by M ðtÞ¼ vnðv; tÞdv ¼ ðtÞ; ð3Þ 1 condensation, and the second-order change rate coefficient 0 K k is defined as where is the volume fraction material in the fluid. k Other physical properties can be expressed by different 2 À 2 Kk K; ð9Þ moments. Since for very small particles the light scattering v k follows the Rayleigh model, the intensity of the scattered where K is the average coagulation coefficient. 6 light is proportional to d p and the total Rayleigh scattering We can see immediately the similarity between Equation can be written as 7 and the mass balance equation. The first term on the right- b / M ðsmall particlesÞ: ð4Þ hand side of the equation is the change in the kth moment scat 2 due to air exchange, the second is the indoor source On the other extreme, the scattering intensity in the optical contribution, and the third is the change in moment due to 2 range corresponds to I/d p, and its total intensity can be sinks (diffusion losses) and sources (condensation or written as particle nucleation) inside the chamber. We also notice that the coagulation contributes as a quadratic term for the bscat / M2=3 ðlarge particlesÞ: ð5Þ moments k6¼1. This would yield an error if we try to describe properties other than mass and volume by using the Similarly, if we assume that the surface of a particle is mass balance model. 2 3 S/dp and its volume v/d p, then the total aerosol surface By analyzing the value of the coefficients K k and k for per unit volume gas A is given by the moments related to our sensors, we see that in the case of the zeroth moment (number concentration) K 0 =K is the A / M2=3: ð6Þ actual coagulation coefficient and 0 =d/V is reduced to the particle loss by diffusion since condensation has no Therefore, a population balance equation written in terms influence in number concentration. For k=1, M 1 represents of the GDE for different moments M k can be used to study total mass or volume, and K 1 =0. Finally, for moments

Journal of Exposure Analysis and Environmental Epidemiology (2001) 11(6) 443 Keller and Siegmann Condensation and coagulation in aerosol monitoring

M k >1, as in the case of Rayleigh scattering (k=2), the exponential. This is especially important for our example of coagulation would have a positive contribution to the total source strength determination, where we analyze the decay moment since K k <0. and calculate the values for F and K k to estimate the If, for simplicity, we assume a constant outdoor concentration in the room at the time when the source was concentration x 0,k (t)=x 0,k and an indoor source with extinguished. It also plays an important role when constant strength over time g k (t)=g k we can solve measuring in places where the air is not mixed fast because Equation 7 as we would have to wait for the moment when a stable condition is reached. Mk ðtÞ¼ ÀÁÀÁÀÁIndoor Measurements Results K M t G ! ! ÀGðtÀt1Þ ! k k ð 1Þþ þ k þV G þ k þ V e þ G À k þ V K M ðt ÞÀGþ þ! Figure 1 presents the aerosol concentration, produced by hik k 1 k V ! ; Kk Mk ðt1ÞþGþ k þ lighting four cigarettes together, as measured by the TSI V ÀGðtÀt1Þ Kk K M t G ! À e k k ð 1ÞÀ þ k þV Dusttrak, Ecochem DC 2000 CE, Ecochem PAS 2000 CE ð10Þ and TSI CPC 3025A. The point of maximum concentration which is the indoor aerosol concentration at a given time coincided with the time at which the cigarettes were put t>t 1. M k (t 1) denotes the value of the kth moment at time out. We calculated the lines by fitting the model to the t 1, and decay part of the curve (by using Equation 13). The first hipart was then plotted using the fitted values, the initial ÀÁ1=2 2 indoor concentration and the cigarette burn time as G ðÞ k þ !=V þ2Kk gk þ !x0;k =V : ð11Þ parameters to calculate the emission rate g. As can be seen here, the model shows an excellent agreement with We shall now analyze some specific cases of Equation 10 the experimental data. and validate it against the first-order mass balance model. A close examination of Figure 1 shows that an upward Let us assume that the outdoor concentration x 0,k =0, which curvature is observed in the decay part of all the plots when is valid for a controlled experiment in an isolated indoor using a semilogarithmic scale. The effect of this curvature is space. Simplifying, we can add together the first coefficients quantified in Table 1 where a comparison with a fit to the and write them as È= k +!/V (also known as the effective first-order model is shown. As can be seen from the air exchange rate). We can distinguish now between two calculated residual values, the linear model will lead us to an cases: a production process with a source emitting aerosol at incorrect estimation of the experimental values. In our case, a constant rate g k for a time interval t 1tt 2, and a decay the typical average difference (average error) is between process where g k =0 for a time t>t 2. one and two orders of magnitude bigger when using the 2 During the emission event t 1tt 2 and À=[È +2K kg k / linear model as when using our model. The largest error is V] 1/2. At this point, we can compare our result with the observed for the number concentration, where the coagu- linear model by setting the value of K k =0, obtaining lation has a stronger impact. Moreover, the curvature also means that, when using the linear model, the error will be gk M ðt tt Þ¼ ½1ÀeÀFðtÀt1ÞþM ðt ÞeÀFðtÀt1Þ; ð12Þ k;lin 1 2 VF k 1 further enhanced if we project the data outside of the fitting interval. which is the expected simple exponential expression for the As mentioned before, all the devices used measured at mass balance model (Ott et al., 1992). most a property that can be related to particle mass For the decay process t>t 2, g k =0,A=È, and Equation 10 concentration and not mass concentration itself. They all becomes rely on a different property and, therefore, different values "# ! have to be expected for the fitted parameters. A similar À1 K 1 K measurement for an inert gas or with a device that measures k FðtÀt2Þ k Mk ðt > t2Þ¼ þ e À : ð13Þ aerosol mass directly, like a piezobalance, should not give 2F Mk ðt2Þ 2F this curvature since, for mass and volume measurements, Equation 13 has a simpler form than our general solution the coefficient K 1 =0 and our population balance equation (Equation 10), and describes the concentration decay in the would be reduced to the mass balance model. case when no indoor sources are present. Here again by The simplest case for understanding how the coefficient making the quadratic term coefficient K k =0, we obtain the K k works is by looking at the coagulation, which is the simple exponential decay that involves a linear model second-order process that plays the most meaningful role in our measurements. Here, as two particles stick together the M ðt > t Þ¼M ðt ÞeÀðtÀt2Þ: ð14Þ k;lin 2 k 2 number concentration is reduced by one. On the other hand, Note that by using a sink coefficient K k6¼0, the decay would the reduction of the surface of the particles during yield a different result than in the case of the simple coagulation depends on the coagulation process itself.

444 Journal of Exposure Analysis and Environmental Epidemiology (2001) 11(6) Condensation and coagulation in aerosol monitoring Keller and Siegmann

103

]

3 103

g/m

DC [S.U./m ]

PM10 [

102 102 0 2000 4000 0 2000 4000

]

3 2

10 [#/cm 105

Conc.

PPAH [ng/m ]

101 Number 104 0 2000 4000 0 2000 4000 t [sec] t [sec]

Figure 1. Semilogarithmic plot of the observed aerosol concentration produced by simultaneously burning four cigarettes, as measured by a Dusttrak (PM10), DC 2000 CE (DC in uncalibrated surface units per cubic meter), PAS 2000 CE (PPAH) and CPC 3025A (number concentration), compared to the concentration calculated by the model (lines). The model was fitted to the decay part of the curves and the results were used to calculate the emission curve. The arrows mark the moment where the cigarettes stopped burning.

Consider agglomerates formed by n spherical primer reduced by a factor n, while the surface is reduced at most 1/3 2/3 particles of surface S 0. The active surface S n of the by a factor of n from NS 0n to NS 0n . A real aerosol agglomerate is related to the number of primer particles n as would have a combination of all kinds of agglomerates and, therefore, different values of , but we can assume S ¼ S n : ð15Þ n 0 the actual change in number concentration to be bigger The coefficient shows us the growing process of the than the change in the total aerosol surface. Therefore, we aerosol. In aerosols agglomerating in chains, the surface will obtain a larger value for the second-order coefficient would be equal to the sum of the individual primer particle K k when measuring the number concentration as when surfaces and =1; in this case we would not notice aerosol measuring the particle cross section. When measuring coagulation when measuring the particle surface. The other number concentration, K k =1=K is the actual coagulation extreme is the case of particles agglomerating as homoge- coefficient; in the other case, K 2/3

Table 1. Summary of the residual values obtained by using our model and the linear model.

a b c b e Device Av diff Av diff linear lin Av diff Av diff linear (%) lin (%)d (%)b (%)b Dusttrak 0.19Â10 À 4 À8.55Â10 À 4 0.71Â10 À 2 1.33Â10 À 2 0.03 À0.65 1.07 2.79 DC 2000 CE À0.17Â100 À1.47Â100 1.73Â101 2.77Â101 À0.06 À0.41 1.42 2.37 PAS 2000 CE À0.33Â10 À 1 À2.97Â10 À 1 3.06Â100 3.32Â100 0.19 À1.50 7.51 7.88 CPC 3025A 0.07Â102 À9.0Â0102 2.22Â103 7.57Â103 0.05 À2.26 1.16 6.4 a This column contains the average of the residual values: residual=x obs Àx model. bSame as previous column but for the linear model. cStandard deviation of the residual values. d Average of the residual values in percent, calculated as: residual=100Â(x obs Àx model )/x obs. eStandard deviation of the residual values in percent. Abbreviations: av, average; diff, difference; obs, observed; lin, linear model.

Journal of Exposure Analysis and Environmental Epidemiology (2001) 11(6) 445 Keller and Siegmann Condensation and coagulation in aerosol monitoring

Table 2. Comparison between the parameters found for the first- and second-order decay rate coefficients and the observed peak concentration, obtained by burning four test cigarettes, in one of our indoor measurements for aerosol devices using different measuring principles.

Device Property Peak Units È K k 1/2(K kÂPeak) [air changes/s] [m3 / (units s) ] [air changes/s] Dusttrak Light scattering 1.029 ( ±0.002)Â103 mg/m3 2.60 ( ±0.03)Â10 À 4 3.94 ( ±0.12)Â10 À 7 2.0Â10 À 4 DC 2000 CE Active surface 2.923 ( ±0.004)Â103 S.U./m3 3.57 ( ±0.04)Â10 À 4 7.61 ( ±0.43)Â10 À 8 1.1Â10 À 5 PAS 2000 CE Active surface, 2.236 ( ±0.008)Â102 ng/m3 5.74 ( ±0.08)Â10 À 4 1.25 ( ±0.14)Â10 À 7 1.4Â10 À 5 photoionization CPC 3025A Number concentration 3.801 ( ±0.005)Â1011 #/m3 2.85 ( ±0.03)Â10 À 4 2.21 ( ±0.03)Â10 À 15 4.2Â10 À 4 S.U. stands for uncalibrated surface units. sensors. The difference is due to the fact that the larger than the one from È. This is again the case of the photoionization is strongly enhanced by the amount of number concentration where the aerosol coagulation PPAH at the particle surface, and the dynamic processes dominates the first part of the decay process; after this first taking place at the surface can be reflected as a change in the part, and in the case of the other sensors, the concentration value of È. In our case, the condensation of species at the decay is dominated by the first-order processes. particle surface blocks the sites covered by PPAHs and reduces the photoionization signal. Source Strength Determination Since, as opposed to È, the units of K k depend on the One of the goals of our approach was to determine if the units of the measured property, it is difficult to directly model with the additional nonlinear terms was suitable for compare the values obtained when using our method. calculating the amount of PPAH produced by a cigarette. Nevertheless, we can do a first approximation by multi- For this reason a calibration of the PPAH monitors (PAS plying the value of 1/2(K k ) by the maximum concentration 2000 CE) was done as described in the Methods section. (denoted as Peak) obtained in one of our indoor measure- The GC-MS analysis of collected mainstream cigarette ments. When doing so, we see that, for high aerosol smoke yielded a total of 1.7 g PAHs; this represents a mean 3 concentrations, the value of 1/2(K kÂPeak) can even be concentration of 155.7 ng/m PPAHs during the 13-h

0.25 Mainstream smoke Environmental tobacco smoke (ETS)

0.20

eight

0.15

ition by W

0.10

Relative Compos 0.05

0.00 e e e ) ) e en ene B B r (2 (2A) (2 (2A) racene rys anthene Pyren h Fluorene C ene Naphtalene Anth luor F Acenaphthene Phenanth d]pyr [g,h,i]perylen Acenaphthalen uranthene o 2,3-c ,h]anthracene k]flo Benzo[a]pyrene1, Benz Benzo[a]anthracene (2A)enzo[ ndeno[ I Dibenzo[a

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Figure 2. Relative PPAH composition by weight of mainstream cigarette smoke and ETS. The compounds where no bar is observed had a contribution smaller than the detection limit. The PAHs are ordered by molecular weight from left (lighter) to right (heavier). The compounds shown in bold have been designated as probable carcinogens (2A) or possible carcinogens (2B) by the International Agency for Research on Cancer (IARC).

446 Journal of Exposure Analysis and Environmental Epidemiology (2001) 11(6) Condensation and coagulation in aerosol monitoring Keller and Siegmann

103

]

n [ng/m

102

PPAH Concentratio

024 t[h]

Figure 3. PPAH concentration time series inside our 77-m3 test room, measured by using a PAS 2000 CE sensor compared with the time series calculated using our model (lines). Each concentration increment represents sets of four or six cigarettes smoked at a time. sampling period. A detail of the distribution of the PAHs can PPAH-to-RSP ratio for traffic aerosol in the Gubrist tunnel be seen in Figure 2; as a comparison, the same type of in Switzerland (Weingartner et al., 1997), determined by a analysis was done to the mainstream smoke sample chemical analysis to be 8.6Â10 À 3 (0.86%). extracted with the smoking machine. We can see that the contribution of PAHs that have been characterized either as probably carcinogenic to humans (2A) or possibly Acknowledgments carcinogenic to humans (2B) by the International Agency for Research on Cancer (see also Denissenko et al., 1996) We thank W. Ott for suggesting this project and for the have an important contribution to the total PPAH weight, interesting and helpful discussions. A. Keller acknowledges specially in the case of the ETS. CONACyT for support. By using the results obtained from the calibration and the indoor measurements technique, we used our PAS 2000 CE References sensor to establish the mean emission rate of our test cigarettes, which was found to be 8 ng/s PPAHs per Bo¨mmel H., Li-Weber M., Serfling E., and Duschl A. The environmental cigarette. This means that the total emission of one cigarette pollutant pyrene induces the production of IL-4. J Allergy Clin for an 11-min burning event would be 5.28 g PPAHs. Immunol 2000: 105 (4): 796–802. These results allow us to predict the PPAH concentration of Brauer M., Hirtle R., Lang B., and Ott W. Assessment of indoor fine aerosol contributions from environmental tobacco smoke and cooking a series of smoking activities. Figure 3 presents a with portable nephelometer. J Exposure Anal Environ Epidemiol 2000: comparison between such a prediction and the actual 136–144. measurement of our controlled cigarette experiments. Burtscher H., and Siegmann H.C. Monitoring PAH-emissions from The same technique would allow us to calculate the total combustion processes by photoelectric charging. Combust Sci Technol aerosol mass emission rate, called respirable suspended 1994: 101: 327–332. Denissenko M.F., Pao A., Tang M., and Pfeifer G.P. Preferential formation particles (RSP), of a cigarette and to obtain the PAH-to- of benzo[a]pyrene adducts at lung cancer mutational hotspots in p53. RSP rate. Klepeis et al. (1996) have calculated the RSP Science 1996: 274: 430. with the linear model for a different kind of cigarettes, using Dubowsky S., Wallace L.A., and Buckley T.J. The contribution of traffic a piezobalance, and found this value to be 1.43 mg/min. to indoor concentrations of polycyclic aromatic hydrocarbons. This gives us an approximated PPAH-to-RSP ratio of J Exposure Anal Environ Epidemiol 1999: 9: 312–321. À 4 Friedlander S.K. Smoke, Dust, Haze. Oxford University Press, New York, 3.35Â10 . We can compare this to the PPAH-to-TAR 2000. ratio from the mainstream smoke sampled using the Godleski J.J., Sioutas C., Katler M., and Koutrakis P. Inhalation of 5 smoking machine, found to be 5.5Â10 À , and with the concentrated ambient air particles in animal models of pulmonary

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disease. Proceedings of the 2nd Colloquium on Particulate Air respirable particles in a chamber of an automobile. J Exposure Anal Pollution and Human Health, vol. 4, 1996, pp. 136–143. Environ Epidemiol 1992: 2 (suppl 2): 175–200. Kasper M., Keller A., Paul J., Siegmann K., and Siegmann H.C. Ott W., Wilson N., Klepeis N., and Switzer P. Real-time monitoring of Photoelectron spectroscopy without vacuum: nanoparticles in gas polycyclic aromatic hydrocarbons and respirable suspended particles suspension. J Electron Spectrosc Relat Phenom 1999: 98–99: 83–93. from environmental tobacco smoke in a home. Proceedings of the Keller A., and Siegmann K. Effects of second-order processes in aerosol International Symposium, Measurement of toxic and Related air monitoring. J Aerosol Sci 2001: 32: 1235–1247. Pollutants, Durham, NC, Report No. VIP-39, Air and Management Klepeis N.E., Ott W.R., and Switzer P. A multiple smoker model for Association, Pittsburgh, PA, NTIS PB-94-20956, 1994. predicting indoor air quality in public lounges. Environ Sci Technol Qian Z., Siegmann K., Keller A., Matter U., Scherrer L, and Siegmann 1996: 30 (9): 2813–2820. H.C. Nanoparticles air pollution in mayor cities and its origin. Atmos Leuenberg P., et al. Swiss study on air pollution and lung diseases in Environ 2000: 34: 443–451. adults. Final Report to the Swiss Nat. Res. Foundation, 1995. Weingartner E., Keller C., Stahel W.A., Burtscher H., and Baltensperger Ott W., Langan L., and Switzer P. A time series model for cigarette U. Aerosol emission in a road tunnel. Atmos Environ 1997: 31: smoking activity patterns: model validation for carbon monoxide and 451–462.

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