the significance of secondary organic aerosol formation and growth in buildings: experimental and...

Atmospheric Environment 37 (2003) 1365–1381

The significance of secondary organic aerosol formation andgrowth in buildings: experimental and computational evidence

Golam Sarwara, Richard Corsia,*, David Allena, Charles Weschlerb

aCenter for Energy and Environmental Resources (R7100), The University of Texas at Austin, 10100 Burnet Road, Austin,

TX 78758, USAbEnvironmental and Occupational Health Sciences Institute, UMDNJ/Robert Wood Johnson Medical School and Rutgers University,

Piscataway, NJ 08854, USA

Received 16 July 2002; accepted 27 September 2002

Abstract

Experiments were conducted in an 11m3 environmental chamber to investigate secondary particles resulting from

homogeneous reactions between ozone and a-pinene. Experimental results indicate that rapid fine particle growth

occurs due to homogeneous reactions between ozone and a-pinene, and subsequent gas-to-particle partitioning of the

products. A new indoor air quality model was used to predict dynamic particle mass concentrations based on detailed

homogeneous chemical mechanisms and partitioning of semi-volatile products to particles. Chamber particle mass

concentrations were estimated from measured particle size distributions and were in reasonable agreement with results

predicted from the model. Both experimental and model results indicate that secondary particle mass concentrations

increase substantially with lower air exchange rates. This is an interesting result, given a continuing trend toward more

energy-efficient buildings. Secondary particle mass concentrations are also predicted to increase with lower indoor

temperatures, higher outdoor ozone concentrations, higher outdoor particle concentrations, and higher indoor a-pineneemissions rates.

r 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Indoor chemistry; Ozone; Secondary particles; Terpenes; a-Pinene

1. Introduction

Recent epidemiological and related studies have

linked fine particles to human health and welfare effects

including premature mortality (Pope and Dockery,

1996; USEPA, 1997). These findings have prompted

the United States Environmental Protection Agency

(USEPA) to promulgate a new national ambient air

quality standard for fine particles. While the aforemen-

tioned regulations focus entirely on outdoor air quality,

the average American spends 18 h indoors for every

hour spent outdoors (Robinson et al., 1991). Thus,

human exposure to fine particles in indoor environments

can be a major fraction of total exposure to fine

particles. Additionally, based on the results of bioassay

experiments involving rats, Long et al. (2001) recently

concluded that particles generated indoors may be more

bioactive than particles generated outdoors.

Santannam et al. (1990) reported the results of indoor

and outdoor sampling completed at 280 residences in

Ohio and Wisconsin. The average ‘‘unexplained’’

percentage of indoor fine particles, i.e., those that could

not be attributed to specific sources, ranged from 19%

to 42%. Similar results (average of 25% ‘‘unexplained’’

fine particles) were observed during the USEPA’s

PTEAM study (Wallace, 1996). Wallace concluded that

the unexplained fraction of fine particles should be the

focus of future studies. Wainman (1999) further

*Corresponding author. Tel.: +1-512-232-3611; fax: +1-

512-471-1720.

E-mail address: [email protected] (R. Corsi).

1352-2310/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved.

doi:10.1016/S1352-2310(02)01013-0

reported that the ‘‘unknown’’ indoor fine particle

concentration in the PTEAM study was 8.75mg/m3

during the daytime, and 6.75 mg/m3 during nighttime.

Recent studies suggest that indoor air chemistry,

particularly as related to reactions between terpenes that

originate from indoor sources and ozone (O3) that

originates outdoors, can be an important source of

indoor fine particles (Weschler and Shields, 1999;

Wainman et al., 2000; Long et al., 2000; Rohr et al.,

2003; Weschler and Shields, 2002). Weschler and Shields

(1999) selectively introduced limonene, a-terpinene and

a terpene-based cleaner into two adjacent unoccupied

and identical offices. In one of the offices, an O3

generator raised the indoor O3 levels to 200–300 ppb; the

adjacent office did not have an O3 generator. The

authors reported a significant increase in particle

number concentrations in the sub-micron range in the

office with elevated O3. The authors attributed the

formation and growth of indoor particles to O3/terpene

reactions and condensation of the subsequent by-

products. In subsequent experiments conducted in these

same adjacent offices, rather than using an ozone

generator, the authors depended on outdoor-to-indoor

transport as the source of ozone—typically between 2

and 40 ppb. In these experiments, one of the offices

contained a limonene source; the other did not. The

office with the limonene source had significantly higher

levels of sub-micron particles when indoor ozone levels

were elevated. The difference in particle levels between

the two offices tracked the indoor ozone level and was

roughly 20mg/m3 when indoor ozone was in the range of

25–30 ppb.

Long et al. (2000) reported evidence that chemical

reactions are a potentially important source of ultra-fine

particles in indoor environments. The authors con-

ducted six sampling events in Boston homes during

which a pine-oil-based cleaner was used for mopping

floors and toilet cleaning. Ozone was not deliberately

added to these homes; however, O3 was present indoors

due to outdoor-to-indoor transport. Five of the six

sampling events demonstrated significant fine particle

formation. Particle number concentrations increased by

7–100 times relative to the original particle number

concentrations. More than 50% of the particles (by

volume) generated during these five events were ultra-

fine in nature.

A nested dynamic system consisting of an inner and

an outer chamber was used by Wainman et al. (2000) to

investigate indoor particle formation and growth due to

O3/limonene reactions. Air exchange could occur

between the inner and outer chambers. Limonene and

O3 were injected incrementally into the inner chamber.

Increases in particle numbers in the 0.1–0.2 mm size

range were observed shortly after the first O3 injection,

but formation of particles in the 0.2–0.3 mm size range

did not occur until a second ozone injection. Combining

the results of this study with the earlier study of

Weschler and Shields (1999), the investigators concluded

that reactions of terpenes that originate from indoor

sources and O3 that originates outdoors can increase

indoor particle mass concentration by more than

20 mg/m3. The authors noted that indoor ozone/terpene

reactions provide a mechanism whereby indoor second-

ary particle mass concentrations can vary coincidentally

with outdoor fine particles during periods of elevated

outdoor ozone.

Rohr et al. (2003) recently conducted experiments

with a-pinene and O3 in a plexiglas chamber as part of a

mouse bioassay study. Ozone concentrations during

these experiments were in the range of 100–400 ppb and

a-pinene concentrations were about 100 ppm, both much

higher concentrations than typically encountered in

indoor environments. Significant increases in ultrafine

particle number concentrations were reported as a result

of a-pinene and O3 reactions.

Weschler and Shields (2002) also conducted experi-

ments to determine the effects of air exchange rates on

indoor secondary particle size distribution and mass

concentrations. They introduced limonene into two

adjacent unoccupied and identical offices. In one of

the offices, an O3 generator was operated to raise the

indoor O3 levels to 50–425 ppb. The other office did not

have an O3 generator. The authors reported that the

lower air exchange rates led to increased particle mass

concentrations and shifted the resulting secondary

particle size distribution toward larger sizes.

Such findings, albeit sparse and somewhat preliminary

in nature, might provide an explanation for the

‘‘unexplained’’ indoor fine particles reported in previous

studies. In this study, the effects of reactions between O3

and a-pinene on indoor particles were investigated using

chamber experiments and a new indoor air quality

model.

2. Methodology

2.1. Experimental methodology

Experiments were conducted in a stainless steel

chamber (11m3) located at the Center for Energy and

Environmental Resources (CEER) at the University of

Texas at Austin. The chamber has dimensions of

2.4m� 1.8m� 2.5m (L�W�H), yielding a surface-

to-volume ratio of 2.7m�1, a value similar to that found

in many commercial and residential buildings (Nazaroff

et al., 1993). A dedicated blower was used to draw air

through the chamber (once through system). Inlet air

was provided from within the general occupied space of

the building. The inlet air was not conditioned for the

experiments described herein. Thus, it contained some

amount of common indoor pollutants, including

G. Sarwar et al. / Atmospheric Environment 37 (2003) 1365–13811366

terpenes, O3, and particles. A diagram of the environ-

mental chamber and associated instrumentation is

shown in Fig. 1.

A commercial corona discharge ozone generator

(Living Air, BORA-IV) was placed in the middle of

the chamber and operated for 10–20 h to achieve steady-

state O3 concentrations prior to the introduction of

a-pinene. A 4ml vial containing pure reagent-grade

a-pinene was then placed on the floor of the chamber,

allowing for evaporation of a-pinene. The difference in

vial mass before and after each experiment was

combined with the duration of the experiment to obtain

the average a-pinene emission rate. This rate was also

confirmed gravimetrically with separate experiments

under a laboratory fume hood.

Two fans (SMCs, Model TR12 and Coll-Breezet,

Model EB24925) were operated near the floor of the

chamber to enhance mixing. A space heater was used to

maintain elevated temperatures in the chamber during

two of the ten experiments.

Chamber particle number concentrations were con-

tinuously measured using two particle counters (Particle

Measuring Systems Inc., LASAIRs—model 1002; and

TSIt, P-TRAKt—model 8525). The P-TRAKt was

used to measure number concentrations of particles

between 0.02 and 1.0 mm in diameter. The sample

averaging time of the P-TRAKt was set to 60 s. The

LASAIRs measures total particle numbers in eight

different channels corresponding to diameters of (all in

mm) 0.1–0.2, 0.2–0.3, 0.3–0.4, 0.4–0.5, 0.5–0.7, 0.7–1.0,

1.0–2.0, and >2.0. The sampling interval of the

instrument was set at 60 s. Total particle number in

each channel was divided by the total sampling volume

to determine the average particle number concentration

during the sampling interval. Particle number concen-

trations from the first six channels of the LASAIRs

were added to obtain the total particle number

concentrations for the size range of 0.1–1.0 mm. This

total particle number concentration was then subtracted

from the particle number concentration detected by the

P-TRAKt to obtain the particle number concentration

in the range of 0.02–0.1 mm. Thus, the two particle

analyzers collectively provided particle number concen-

trations in nine different diameter ranges. This subtrac-

tion technique introduced some level of uncertainty for

concentrations in the 0.02–0.1mm diameter range.

Nevertheless, the results provided useful information

in the ultra-fine range of particles.

Mass concentration was estimated from particle

number concentrations and particle density. Two

different approaches were employed as described below.

Method 1: A geometric mean diameter was estimated

from the minimum and maximum particle diameters in

each size range. The average volume of particles in each

size range was determined by assuming that each

particle was a sphere with a diameter equal to the

geometric mean diameter. The total particle volume in

each of the size ranges was estimated by multiplying the

average volume of the particle by the particle number

concentration in that size range. Particle volumes in each

of the size ranges were summed to obtain the total

particle volume. Total particle volume was then multi-

plied by particle material density to obtain particle mass

concentration. Turpin and Lim (2001) analyzed atmo-

spheric particle density data and suggested a material

density of 1.2 g/cm3 for atmospheric organic aerosols, a

value adopted for this study. This method has been

shown to produce reasonable particle mass concentra-

tions in previous studies. For example, Fan (2002)

concurrently measured particle number and mass con-

centrations during experiments involving reactions of O3

with organic compounds. Particle mass concentrations

were measured using a filter-based technique. Particle

mass concentrations were also derived using measured

particle number concentrations and the geometric mean

diameters as described above. The derived particle mass

concentrations were 5% lower than the results obtained

using the filter-based technique. For this study,

the experimental mass concentrations obtained using

Method 1 contained initial oscillations due to growth

wave kinetics and the coarseness of particle size

channels measured by the analyzers. Therefore, this

method was discarded.

Method 2 (functional fit to data): The particle size

ranges and number concentrations measured by the

LASAIRs were used to develop an exponential best-fit

curve through the data. As discussed earlier, particle

number concentrations in the 0.02–0.1 mm had poten-

tially high uncertainties and were not included in the

curve fitting. For purposes of curve fitting, each size

range was represented by the geometric mean diameter

estimated from the minimum and maximum particle

diameters in each size range. For example, particle

number concentrations in the 0.1–0.2 mm size range were

represented by a geometric mean diameter of 0.14 mm.

The resulting curve was used to estimate particle number

concentrations in small size increments, starting from

0.1 mm and ending at 0.7mm with increments of 0.01 mm.

Particle CountersO3 Analyzer

SF6 Analyzer

Hygrometer

HVAC

Blower

Fans (2)

O3 Generator

Terpene Source

Fig. 1. Schematic diagram of the environmental chamber.

G. Sarwar et al. / Atmospheric Environment 37 (2003) 1365–1381 1367

The resulting particle number concentrations were used

to estimate particle mass concentrations using the

procedure described for Method 1. For each experiment,

this procedure was repeated for each time step.

The LASAIRs and P-TRAKt particle counters were

located outside the chamber during each experiment.

Sample tubing inlets were located in the middle of the

chamber approximately 1.5m above the floor. The

LASAIRs sample tube inlet was placed within about

20 cmof the P-TRAKt sample tube inlet. The LASAIRs

drew sample air from within the chamber through

a 3.5m long (3mm OD) polyurethane tube. The

P-TRAKt pulled air through a 5m long (6mm OD)

tygon tube. Particle losses in tubing were determined by

running the analyzers with and without tubing. The

average loss of particles was 25% in the 5m tube used

for the P-TRAKt and 14% in the 3.5m tube used for

the LASAIRs. Particle numbers measured by these

analyzers were adjusted to account for losses in tubing.

Chamber O3 (inside and outside) was measured using

an ozone analyzer (Dasibi Environmental Corporation,

model 1003-AH). A solenoid valve was used to switch

the intake of the O3 analyzer between the interior and

exterior of the chamber. The solenoid valve was

programmed to maintain the intake of the ozone

analyzer inside the chamber for 50min before switching

to outside the chamber for a period of 10min for each

hour of the experiment. The analyzer was placed outside

the chamber and drew sample air through approxi-

mately 3m (6mm OD) of teflon tubing.

The chamber air exchange rate was measured by

injecting sulfur hexafluoride (SF6) and monitoring its

decay using a GC/ECD optimized for analysis of SF6

(Lagus Applied Technology, Inc., model 101, Autotrac).

Chamber temperature and relative humidity were

measured during each experiment using a portable

digital hygrometer (VWR, model 35519–041). Temper-

ature and relative humidity were recorded every

30–60min during each experiment.

Each experiment began with the measurement of

particle number concentrations outside the chamber for

10–30min followed by measurements inside the chamber

for another 10–30min before the introduction of

a-pinene into the chamber. Experiments continued for

a period of 10–12 h after source introduction into

the chamber. Particle number concentrations outside

the chamber were measured for 10–30min at the end of

each experiment.

The LASAIRs and P-TRAKt particle counters were

calibrated by the manufacturers as per recommendation.

Periodic zero checks were conducted on the LASAIRs

and on the P-TRAKt during these experiments. The

ozone analyzer was calibrated using primary standards 2

weeks prior to and at the end of all experiments.

The analyzer responses were within 1% of primary

standards.

2.2. Modeling methodology

The indoor chemistry and exposure model (ICEM)

was used in this study. Details of the ICEM have been

described elsewhere (Sarwar et al., 2002). The building

interior was modeled as a single well-mixed environment

with homogeneous chemistry. In its simplest mathe-

matical form, the ICEM can be represented by

dCi

dt¼ kilCoi � lCi þ

Ei

V� VdiCia þ

Xn

j¼1

Rij ; ð1Þ

where Ci is the indoor concentration of pollutant

i (ppm), Coi is the outdoor concentration of pollutant

i (ppm), ki is the outdoor-to-indoor penetration factor

for pollutant i (0–1; unitless), l is the fresh air exchange

rate (min�1), Ei is the whole-building emission rate

(all sources) for pollutant i (ppmm3/min), Vdi is the

deposition velocity for pollutant i to indoor materials

(m/min), a is the surface area to volume ratio for the

indoor environment (1/m), Rij is the reaction rate

between pollutant i and pollutant j (ppm/min), V is

the volume of the indoor environment (m3), and t is the

time (min).

The first term in Eq. (1) corresponds to the time rate

of change of pollutant concentration (Ci) within a

building environment. The second term represents the

transport of pollutants from outdoors to indoors. The

third term represents the transport of pollutants from

indoors to outdoors. The fourth term corresponds to the

whole-building emission rate for pollutant i: The fifth

term corresponds to the removal of pollutant i by

deposition on indoor materials. The sixth term corre-

sponds to the summed results of all reactions involving

pollutants i and j: The ICEM employs the detailed

homogeneous chemistry of SAPRC-99 (Carter, 2000).

Particle chemistry for a-pinene, developed by Kamens

et al. (1999), was also incorporated into ICEM and was

combined with the homogeneous reactions of SAPRC-

99. Outdoor photon energy was replaced by typical

indoor photon energy. The current ICEM does not

include adsorption/desorption phenomena that may

occur in indoor environments, but as shown in Eq. (1),

does include a term for irreversible deposition of

particles, ozone, free radicals, and semi-volatile organic

compounds.

2.3. Particle chemistry for a-pinene

Kamens et al. (1999) conducted experiments in a

190m3 outdoor Teflon film chamber under dark

conditions and used the results to develop the particle

formation chemistry for a-pinene. An overview of the

particle chemistry of a-pinene is provided here; details

can be found in Kamens et al. (1999). Particle chemistry

for a-pinene can be divided into two parts: (1) gas-phase


chemistry leading to semi-volatile products and (2)

particle growth by partitioning of semi-volatile products

onto existing particles. The particle chemistry of a-pinene consists of six semi-volatile model compounds:

pinald, pinacid, diacid, oxy-pinald, p3gas, and oxy-

pinacid as shown in Fig. 2. The model compound pinald

represents pinonaldehyde and nor-pinonaldehyde, pina-

cid represents pinonic and nor-pinonic acids, diacid

represents pinic and nor-pinic acids, oxy-pinald repre-

sents hydroxy and aldehyde-substituted pinonaldehydes,

p3gas represents a pinic acid precursor (2,2-dimethylcy-

clobutane-3-acetylcarboxylic acid—C9H14O3), and oxy-

pinacid represents hydroxy and aldehyde-substituted

pinonic acids.

2.4. Gas-phase chemistry

a-Pinene reacts with O3 to produce an ozonide.

However, the ozonide is highly unstable and rapidly

decomposes into two Criegee biradicals (CRIEGEE1

and CRIEGEE2). Several reaction pathways are avail-

able for the decomposition of these Criegee biradicals.

The decomposition of CRIEGEE1 leads to pinacid,

stabilized criegee 1 radical, pinald, oxy-pinald, OH � ,

HO2� , and CO. Stabilized Criegee 1 biradicals react with

H2O to form pinacid. In the presence of O2, pinald reacts

with OH � to form a peroxyacyl radical (PINALD-OO),

which is subsequently oxidized via HO2� to produce

pinacid. Oxy-pinald is oxidized to oxy-pinacid via OH �

and HO2� .

The decomposition of CRIEGEE2 leads to oxy-

pinald, CRGPROD2 (a generalized intermediate pro-

duct), a stabilized criegee 2 radical, HCHO, OH � and

HO2� . Stabilized Criegee 2 radicals can react with H2O to

produce p3gas and methanol (CH3OH). The compound

p3gas reacts with OH � producing a peroxyacyl radical

(PREDI-OO), which in turn produces diacid via oxida-

tion with HO2� . The compound CRGPROD2 reacts with

HO2� to form diacid. a-Pinene also reacts with OH � to

produce pinald, oxy-pinald, and volatile oxygenated

products called FRAG.

2.5. Partitioning of semi-volatile products on to ‘‘seed’’

particles

The six semi-volatile products described above can

partition on to ‘‘seed’’ particles that originate largely

from outdoor-to-indoor penetration. Some of these

products have very low vapor pressures and can self-

nucleate to form new particles and are designated as

‘‘seed1’’ in the model. Partitioning was treated as

sorption to, and desorption of semi-volatile products

from, particles. The ratio of the sorption rate (kon;i) and

desorption rate (koff ;i) constants was taken as the

equilibrium constant (Kp;i) for gas–particle equilibrium:

Kp;i ¼ kon;i=koff ;i: ð2Þ

Here, Kp;i represents the ratio of the sorbed-phase

concentration of species i (ng/mg) to the gas-phase

concentration of i (ng/m3) and has a unit of m3/mg. It

O3+

+ OH.

STABILIZEDCRIEGEE 1

PINALD

CO

PIN

AC

ID

PINALD-OOOXY-PREPINACID

OXY-PINACID

CRGPROD2 HCHOSTABILIZEDCRIEGEE 2OXY-PINALD

P3GAS

PREDI-OO

DIACID

PINALD

CRIEGEE1 CRIEGEE2

OXY-PINALD

HO2.

OH.

OH.

OH.

HO2.

HO2.

HO2.

HO2.OH.

H2O

OH. HO2.

CH3OH

FRAG

(ozonide)

H2O

Fig. 2. Reaction between a-pinene and O3 (semi-volatile organic compounds are shown in bold italics).


was estimated from knowledge of the vapor pressure

and molecular weight of a product according to

Kp;i ¼ 7:501RT=109MWomip0

L; ð3Þ

where Kp;i is the equilibrium constant (m3/mg) for

compound i; R is the universal gas constant (8.31 J/

Kmol), T is the temperature (K), MWom is the average

molecular weight of the ‘‘liquid’’ that constitutes the

organic particles (g/mol), ip0L is the vapor pressure of the

product (Torr), and 7.51 is a conversion factor (Kamens

et al., 1999).

Absorption of semi-volatile products on to particles is

a weak function of temperature; thus it was assumed

that sorption rates (kon;i) are independent of tempera-

ture. Desorption rate constants (koff ;i) of semi-volatile

products from particles are strongly dependent on

temperature and were estimated using

koff ;i ¼ b expð�Ea=RTÞ; ð4Þ

where b is a pre-exponential factor, R is the universal gas

constant (8.31 J/Kmol), T is the temperature (K), and

Ea is the activation energy (J/mol). A general equation

for evaporation from a liquid surface was used to

estimate values of b and Ea (Kamens et al., 1999).

Sorption rates (kon;i) for semi-volatile products were

estimated as the product of equilibrium constant, Kp;i;and the desorption rate constant (koff ) for any given

compound.

Secondary particle mass associated with a-pinenereactions can be estimated by keeping track of all seven

products (six semi-volatile products and ‘‘seed1’’, the

self-nucleated product) in the particle phase. Based on

experiments by Kamens et al. (1999), an average

molecular weight of 120 g/mol was used to convert

secondary particle concentrations from volumetric units

(ppm) to mass units (mg/m3). ‘‘Seed’’ particles needed for

the model were estimated based on outdoor-to-indoor

transport. Based on compositional analysis of outdoor

particles measured in Houston (Tropp et al., 1998), an

average molecular weight of 90 g/mol was used to

convert ‘‘seed’’ particle concentrations from volumetric

units (ppm) to mass units (mg/m3).

Kamens et al. (1999) also determined losses of semi-

volatile reaction products and particles to Teflon film

chamber walls. Several reactions were included in the

particle formation mechanism of a-pinene to account for

these wall losses. The ICEM estimates surface removal

rates using prescribed deposition velocities, the surface

area to volume ratio, and pollutant concentrations in

indoor environments. Thus, reactions that account for

chamber wall losses in the a-pinene particle formation

mechanism were switched off, allowing the ICEM to

estimate surface removal rates of these compounds

based on prescribed deposition velocities.

Deposition velocity data for semi-volatile products in

actual building environments are not known. In the

absence of any measured data in indoor environments,

deposition velocities for semi-volatile organic products

of a-pinene were assigned twice the deposition velocity

of fine particles following Kamens et al. (1999). The

authors acknowledge that this assumption is a source of

uncertainty in the model and will require future

refinement. Deposition velocities for O3 and particles

were previously measured in the chamber by comparing

decay rates at specific air exchange rates with an inert

tracer gas (SF6) and were used in the ICEM. The O3

deposition rate in the stainless steel chamber used for

this study was 0.48 h�1, much lower than the reported

average O3 deposition rate of 3.6 h�1 for indoor

environments (Nazaroff and Cass, 1986). The surface

area to volume ratio of the environmental chamber used

in this study was 2.7m�1. With this surface area to

volume ratio, the deposition velocity of O3 in the

chamber was 0.005 cm/s. The average deposition rate of

fine particles in the chamber was 0.34 h�1. The measured

particle deposition rate compares favorably with the fine

particle deposition rate of 0.33 h�1 reported by

Wainman (1999) and 0.39 h�1 reported by Wallace

(1996). The average deposition velocity of particles

in the chamber was 0.0035 cm/s.

2.6. Model input parameters

Measured a-pinene emission rates, O3 emission rates,

chamber outside O3 concentrations, chamber outside

particle mass concentrations, chamber average air

exchange rates, chamber temperature, relative humidity,

and chamber surface area and volume were provided as

input data to the model to estimate chamber particle

mass concentrations as a function of time.

3. Results and discussions

A summary of the ten experiments involving a-pineneis presented in Table 1. Number concentrations repre-

sent particles in the 0.02–0.7mm diameter range and

mass concentrations represent particles in the 0.1–0.7 mmdiameter range. The ozone generator was not operated

during experiment 1; so for this experiment the O3 levels

were in the range of 10–15 ppb and were derived from

outdoor-to-indoor penetration.

A typical evolution of particle number concentrations

is shown in Fig. 3, in this case for experiment 3. A rapid

‘‘burst’’ of small particles in the 0.02–0.1 mm size range

was detected shortly after the introduction of a-pineneinto the chamber. Particle numbers in the 0.02–0.1 mmsize range then decreased before attaining a steady

concentration of approximately four times the initial

concentration. Particle numbers in the next size range

then increased and subsequently decreased before

attaining a steady concentration. This process continued


for particles with diameters up to 0.5–0.7 mm,

after which no appreciable increase in particle numbers

was observed. The initial ‘‘burst’’ of small particles

followed by a decrease in particle numbers in a given size

range and increase in particle numbers in subsequent

size ranges created an effective particle growth ‘‘wave’’

that was observed for all experiments. Ultimately,

particle number concentrations reached steady-

state conditions controlled primarily by the reaction

rate of O3 with a-pinene and the prevailing air exchange

rate.

The particle size distributions during experiment 3 at

the time of a-pinene introduction into the chamber

(time=0) and at steady state (time=700min) are shown

in Fig. 4. Particle number concentrations in all size

ranges at steady state were consistently higher than the

particle number concentrations at time 0. Similar results

were also observed for other experiments. The increase

in particle number concentrations occurred via the O3/a-pinene reactions and partitioning of subsequent reaction

by-products.

Particle surface area and volume at time 0 for

experiment 3 are shown in Fig. 5. While the initial

particle number concentration was dominated by

particles with diameter with o0.1mm, the maximum

particle surface area and particle volume both occurred

in the 0.2–0.3 mm size range. The bulk of the particle

surface area was contained among the 0.1–0.2, 0.2–0.3,

and 0.3–0.4 mm size ranges. While there was some initial

growth of larger size particles, the initial ‘‘burst’’ of

particles was observed in the 0.02–0.1 mm size range.

This suggests that the initial ‘‘burst’’ of small particles

may not be solely the result of condensation/absorption

of semi-volatile particles onto smaller seed particles, in

which case an initial ‘‘burst’’ would be expected in the

larger size ranges. The initial ‘‘burst’’ of small particles

may be the result of the nucleation of very low vapor

pressure products of the O3/a-pinene reactions. It is,

however, also possible that initial particles in the

chamber during experiment 3 were bimodally distrib-

uted and particles in the smaller size range (lower than

the detectable range of 0.02 mm) may have contained

higher surface area or volume.

Details of the reaction products that can form new

particles via nucleation are not currently known.

However, Kamens et al. (1999) suggested two possible

mechanisms for the nucleation process to occur.

Stabilized Criegee biradicals may react with ‘‘the

carbonyl portion of product compounds to produce an

extremely low-pressure secondary ozonide product’’. It

is also possible that Criegee biradicals can react with

dicarboxylic acids to form low volatility anhydrides.

These products were suggested to have high molecular

weights (B350) and very low vapor pressures

(o10�15 Torr) with significant potential for self-nuclea-

tion (Kamens et al., 1999).Table

1

Summary

ofchamber

experim

entalandmodelingresults

Exptno.

l(h

�1)

E(mg/

min)

InitialO

3

(ppb)

T(1C)

Initial

particle

(#/cm

3)

Max

particle

(#/cm

3)

Tim

e

(min)

Final

particle

(#/cm

3)

Mi(mg/

m3)

Mf;e(mg/

m3)

SOA

(mg/

m3)

Mf;p(mg/

m3)

Difference

(%)

11.25

196

15

25

2760

3423

108

1997

3.6

4.3

0.7

5.0

�16

20.55

75

132

24

7047

96989

17

10004

3.1

39

35

55

�44

30.68

81

134

26

1383

34662

34

7227

2.2

21

19

27

�26

41.06

78

111

24

9202

11852

39

6774

4.3

16

12

20

�22

50.70

70

136

25

4138

18529

31

7324

9.2

29

20

30

�3

60.70

91

170

24

10391

14532

48

9511

5.4

49

43

66

�35

70.75

98

142

25

2836

30114

26

6327

11

33

22

52

�57

81.34

89

157

32

8472

31062

48

35975

6.9

17

10

21

�20

91.50

102

144

33

12529

37729

48

25332

3.3

6.5

3.2

8.8

�35

10

0.71

185

159

25

4438

25131

32

9180

2.7

74

71

181

�146

No

te:l=

air

exchangerate,

E=a-pineneem

ission

rate,

T=

Tim

eatwhich

themaxim

um

particle

number

concentrationsoccurred

inthechamber,

Mi=

initialparticle

mass

concentration

inthe

chamber,

Mf;e=finalexperim

entalparticle

mass

concentration

inthe

chamber,

Mf;p=

finalpredicted

particle

mass

concentration

inthe

chamber,SOA=

secondary

organic

aerosol=

Mf;e�

Mi;difference=

ðMf;e�

Mf;pÞ=

Mf;e:


The initial particle number concentration during

experiments 4 and 6 were relatively high compared to

experiment 3. Particle surface area and volume at time 0

for experiment 4 are shown in Fig. 6. The maximum

particle surface area and particle volume occurred in the

0.1–0.2 mm size range and the bulk of the particle surface

area and volume was contained among the 0.02–0.3 mmsize range. The evolution of particle number concentra-

tions for experiment 4 is shown in Fig. 7. The initial

‘‘burst’’ of particles in the 0.02–0.1mm size range was

negligible compared to experiment 3. The initial

increases in particle number concentrations occurred in

the 0.1–0.2, 0.2–0.3, and 0.3–0.4 mm size ranges and

reflects particle growth from the immediate lower size

ranges containing the bulk of the particle surface area

and volume. This suggests that the initial particles in the

chamber were not bimodally distributed for experiment 4,

and the initial particle growth occurred via condensation

and/or absorption of semi-volatile particles. Similar

results were observed for experiment 6. Thus, it is

conceivable that initial particles during experiment 3

were not bimodally distributed and the initial ‘‘burst’’ of

small particles may have occurred via nucleation of very

low vapor pressure products of O3/a-pinene reactions,

and via the growth of smaller particles into the

detectable size range. Unfortunately, the limited number

of particle size ranges associated with the instruments

used for this study lend enough uncertainty to surface

area calculations to preclude a definitive statement

regarding the relative importance of particle formation

Fig. 4. Particle size distributions at times 0 and 700min for experiment 3.

0.1

1.0

10. 0

100. 0

1,000. 0

10, 000. 0

100, 000. 0

-50 50 150 250 350 450 550 650 750

TIME [min]

PA

RT

ICL

ES

[#/c

m3 ]

0.02- 0.1

0.1-0.2 0.2-0.3

0.3-0.4

0.5-0.7

0.4-0.5

α -pinene introduced

Fig. 3. Particle number concentrations during experiment 3.


versus growth. The issue of particle nucleation/growth

during the initial phase of the experiment should be

further explored using particle analyzers that can

measure much finer size distributions.

With the exception of experiments 8 and 9, there was a

time lag of between 2 and 15min after the introduction

of a-pinene in the chamber prior to a rapid increase in

particle number concentration. Experiments 8 and 9

were performed at 8–91C higher temperature than other

experiments. The burst of particles during these two

experiments was detected by the P-TRAKTM 10–15min

after the introduction of a-pinene in the chamber. These

observations were not due to conveyance times between

sample inlet and particle instruments. The estimated

travel time for particles from the chamber to the P-

TRAKTM was only about 0.5min. The travel time for

particles from the chamber to the LASAIRs was even

shorter.

It takes a finite amount of time for the a-pinene to

evaporate and to mix into the chamber. The effective

time to evaporate into, and mix within, the chamber

should have been fairly similar for all experiments, and

likely contributed partly to the delay in the initial burst

of particles in the chamber. However, the primary

reason for the delay in the initial burst of particles was

likely due to the time needed for the reaction between O3

and a-pinene to raise concentrations of low vapor

pressure semi-volatile products to sufficient levels for

nucleation to occur, or for condensation on existing

smaller particles. The elevated temperatures during

experiments 8 and 9 caused the vapor pressures of these

products to be higher than that of other experiments.

0

5

10

15

20

0.02-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.7

PARTICLE SIZE [µm]

PA

RT

ICL

E S

UR

FA

CE

AR

EA

[ µm

2 /cm

3 ]

0.0

0.2

0.4

0.6

0.8

1.0

PA

RT

ICL

E V

OL

UM

E [

µm3 /c

m3 ]

surface area

volume

Fig. 5. Particle surface area and volume as a function of particle size at time 0 during experiment 3.

0

10

20

30

40

50

60

70

0.02-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.7

PARTICLE SIZE [µm]

PA

RT

ICL

E S

UR

FA

CE

AR

EA

[µm

2/c

m3]

0.0

0.5

1.0

1.5

2.0

PA

RT

ICL

E V

OL

UM

E [µm

3/c

m3]

surface area

volume

Fig. 6. Particle surface area and volume as a function of particle size at time 0 during experiment 4.


Thus, it should have taken longer to raise the

concentrations of these products to sufficient levels for

nucleation, a plausible reason why the initial burst of

particles was further delayed during each of these two

experiments.

The evolutions of experimental and predicted particle

mass and O3 concentrations for experiment 3 are

presented in Fig. 8. Particle mass concentration in the

chamber was initially 2.2 mg/m3 and increased after the

introduction of a-pinene into the chamber, eventually

reaching a steady-state concentration of 21mg/m3; the

secondary organic aerosol (SOA) concentration was

approximately 19 mg/m3. The predicted and measured

particle mass concentrations for experiment 3 were in

reasonable agreement; predicted mass concentrations

were within 26% of experimental results at steady-state

conditions and at worst a factor of two higher between

minutes 150 and 250.

Predicted (using ICEM) constituents of SOA are

shown in Fig. 9 for experiment 3. Model compounds

diacid, oxy-pinald, and oxy-pinacid were the three

highest contributors and represented almost 90% of

the predicted SOA mass concentrations. Self-nucleated

product (‘‘seed1’’) accounted for approximately 5% of

predicted SOA mass concentrations. Model simulations

suggest that O3- and OH � -initiated reaction pathways

produced approximately 92% and 8% of the predicted

secondary particle mass concentrations, respectively.

Similar results were predicted for other experiments.

The evolution of particle number concentrations for

experiment 2 is shown in Fig. 10. Similar to experiment

3, a rapid ‘‘burst’’ of small particles in the 0.02–0.1 mm

0.1

1.0

10.0

100.0

1,000.0

10,000.0

100,000.0

-50 50 150 250 350 450 550 650 750

TIME [min]

PA

RT

ICL

ES

[#/c

m3 ] 0.1-0.2

0.2-0.3

0.3-0.4

0.5-0.7

0.4-0.5

0.02-0.1


Fig. 7. Evolution of particle number concentrations during experiment 4.

0

10

20

30

40

50

0 150 300 450 600 750

TIME [min]

PM

[µg

/m3]

0

30

60

90

120

150

OZ

ON

E [

pp

b]

predicted particles

predicted ozone

experimental ozone

experimental particles

Fig. 8. Experimental and predicted particle mass and O3 concentrations during experiment 3.


size range was detected shortly after the introduction of

a-pinene into the chamber. A particle growth ‘‘wave’’

similar to experiment 3 was also observed.

An analysis of relative time scales suggests that

coagulation phenomena played an insignificant role in

defining the particle growth wave. Hinds (1982) pro-

vided an equation to relate particle number concentra-

tions for coagulation:

NðtÞ ¼ N0=ð1þ N0KtÞ; ð5Þ

where K is the coagulation coefficient, NðtÞ is the

particle number concentration at time t; and N0 is the

initial particle concentration. The coagulation coeffi-

cient, K ; for polydisperse particles was estimated using

the following equation (Hinds, 1982; Lee and Chen,

1984):

K ¼2kT

3Zf1þ expðln2sgÞ

þ2:49lCMD

½expð0:5 ln2sgÞ þ expð2:5 ln2sgÞg; ð6Þ

where k is the Boltzmann constant

(1.38� 10�16 dyne cm/K), T is the temperature (298K),

Z is the viscosity of air (1.90� 10�4 dyne s/cm2), sg is thegeometric standard deviation of the particles, and CMD

is the count median diameter. The count median

0

3

6

9

12

0 100 200 300 400 500 600 700 800

TIME [min]

PM

[µg

/m3 ]

diacid

oxy-pinald

oxy-pinacid

pinacidpinald

p3gasseedseed1

Fig. 9. Constituents of the predicted particle mass concentrations for experiment 3.

0.1

1.0

10.0

100.0

1,000.0

10,000.0

100,000.0

1,000,000.0

-50 50 150 250 350 450 550 650 750

TIME [min]

PA

RT

ICL

ES

[#

/cm

3]

0.1-0.2 0.2-0.3

0.3-0.4

0.5-0.7

0.4-0.5

0.02-0.1


Fig. 10. Evolution of particle number concentrations during experiment 2.


diameter (CMD) and the geometric standard deviation

(sg) were estimated by the following equations (Hinds,

1982):

lnðCMDÞ ¼P

ni ln di

N; ð7Þ

ln sg ¼P

niðln di � ln CMDÞ2

N � 1

� �12

; ð8Þ

where ni is the particle number concentration in size

range i; di is the geometric mean particle diameter for

size range i; and N is the total particle number

concentration.

For purposes of illustration, Eqs. (7) and (8) were

used to estimate particle CMD and sg for experiment 2.

Eq. (6) was used to estimate K for polydisperse particles.

Eq. (5) was used to estimate the time (t1) needed for the

reduction in peak number concentration of smaller

particles to peak number concentration of larger

particles via coagulation. The estimated (t1) and

observed times (t2) are presented in Table 2 for

experiment 2, and are consistent in magnitude with

other experiments. The diameter ‘‘d’’ in Table 2

represents the geometric mean diameter of each size

range. Estimated times for coagulation were greater

than the observed times by 1–4 orders of magnitude.

Thus, coagulation was not the dominant process via

which the number concentrations of smaller particles

decreased after the initial burst of 0.02–0.1 mm particles.

More importantly, chamber particle mass concentra-

tions continued to increase until a stable condition was

attained, reinforcing that coagulation was not the

dominant growth process in the system; coagulation

would lead to changes in particle number concentrations

but would result in a relatively constant mass concen-

tration. Rather than coagulation, we propose that the

particle growth wave occurs via partitioning of semi-

volatile reaction products to smaller particles causing

them to grow in size. As the particle size increases, more

mass is required to effect an incremental growth in

particle diameter. Therefore, the time interval between

successive peaks increases.

The evolutions of experimental and predicted particle

mass and O3 concentrations during experiment 2 are

presented in Fig. 11. The initial ozone concentration was

132 ppb. It decreased after the introduction of a-pineneinto the chamber, and ultimately attained a relatively

steady-state concentration. The predicted O3 concentra-

tions were within 5% of experimental results. Particle

mass concentration was initially 3.1 mg/m3 and increased

after the introduction of a-pinene into the chamber,

eventually reaching a steady-state concentration

of 39mg/m3. The SOA concentration was therefore

35 mg/m3. The predicted particle mass concentration was

44% higher than the measured concentration at steady-

state conditions.

The air exchange rate for experiment 2 was lower than

all other experiments and the resulting SOA mass

concentration was also higher than all experiments

except for experiments 6 and 10. However, the initial

particle number concentrations, the initial O3 concen-

trations, and a-pinene emission rate during experiment 6

were also higher than experiment 2, all conditions that

could have led to higher SOA concentrations during

experiment 6. Experiment 10 was conducted at a much

higher a-pinene emission rate than experiment 2, likely

the reason for a higher SOA concentration for experi-

ment 10.

Predicted particle mass concentrations were within

3–57% higher than measured concentrations for all

experiments except experiment 10 (Table 1). The current

ICEM does not include adsorption/desorption phenom-

ena that may occur in indoor environments, and as

described previously, all surface interactions for semi-

volatile organic compounds were modeled using an

irreversible deposition term that has not been deter-

mined experimentally. As such, it is conceivable that the

consistent over-prediction of particle mass concentra-

tion was due to an underestimation of semi-volatile

organic compound removal to chamber surfaces.

Through model sensitivity analyses, we have confirmed

that predicted particle mass concentrations are highly

sensitive to changes in prescribed deposition velocities

for semi-volatile organic compounds. As such, addi-

tional knowledge of surface phenomena involving semi-

volatile organic compounds is required to improve

model accuracy.

Over all experiments, the reasonably close agreements

between predicted and experimental particle mass

concentrations are encouraging. The model appears to

Table 2

Estimated (t1) and observed time (t2) for the reduction in peak particle number concentrations during experiment 2

Range (mm) d (mm) K (cm3/s) N0 (#/cm3) NðtÞ (#/cm3) t1 (min) t2 (min)

0.02–0.1 0.045 1.3E�09 92,870 14,816 725 98

0.1–0.2 0.141 1.4E�09 14,816 4129 2059 140

0.2–0.3 0.245 1.8E�09 4129 926 7723 136

0.3–0.4 0.346 1.6E�09 926 244 3.1� 104 118

0.4–0.5 0.447 1.7E�09 244 5 1.9� 106 106


capture processes associated with particle formation

and/or growth. However, additional research will be

needed to improve model performance.

3.1. Effects of selected parameters on indoor SOA levels

Model simulations were performed to investigate the

effects of the following parameters on indoor SOA mass

concentrations: air exchange rate, outdoor fine particle

concentration, outdoor O3 concentration, indoor a-pinene emission rate, and indoor temperature. A base-

case scenario was defined as follows:

indoor a-pinene emission rate=2.3mg/min;

outdoor O3 concentration=100 ppb and,

outdoor fine particle concentration (PM2.5)=

15mg/m3.

An indoor volume of 500m3 was used for this

analysis. The prescribed indoor emission rate would

produce an indoor a-pinene concentration of about

100 ppb at an air exchange rate of 0.5 h�1 in the absence

of O3. For simplicity, it was also assumed that no

pollutants other than O3, a-pinene, associated gaseous

by-products, and fine particles existed in the indoor

environment. All model simulations were performed

with an assumed indoor relative humidity of 50%,

indoor temperature of 297K (except when the effects of

temperature were investigated), and an air exchange rate

of 0.5 h�1 (except when the effects of air exchange rate

were investigated).

An average deposition velocity of 0.036 cm/s for O3

was used in the model (Nazaroff and Cass, 1986). An

average deposition velocity of 0.07 cm/s was used for

both hydroxyl and hydroperoxy radicals in the model

(Nazaroff and Cass, 1986). An average deposition

velocity of 0.004 cm/s was used for fine particles

(Wallace, 1996). The deposition velocities of the semi-

volatile organic products of a-pinene were assigned twice

the average deposition velocity of fine particles following

Kamens et al. (1999). It was also assumed that no other

sources of fine particles were present in the building, and

that transport of outdoor fine particles provided ‘‘seed’’

particles in the model.

The predicted indoor O3 concentration for the base-

case scenario was 11 ppb. The total indoor fine particle

concentration was predicted to be 12.1mg/m3. The

predicted indoor SOA concentration resulting from

reactions between O3 and a-pinene for the base-case

scenario was 3.7mg/m3. The predicted indoor ‘‘seed’’

particle concentration resulting from the transport of

outdoor fine particles was 8.4mg/m3.

3.2. Effects of air exchange rate on indoor SOA

concentrations

The air exchange rate was varied from 0.1 to 3.0 h�1.

Resulting steady-state indoor SOA concentrations are

shown in Fig. 12. Indoor seed and outdoor particle

concentrations are also shown in Fig. 12. Predicted

indoor SOA concentrations increased with lower air

exchange rates (above 0.4 h�1). Lower air exchange rates

were associated with lower indoor O3 and ‘‘seed’’

particle levels. However, indoor a-pinene concentrationsalso increased with lower air exchange rates. The O3/a-pinene reaction rate and time available for reactions

increased with the reduction in the air exchange rate

(above 0.4 h�1). The combination of higher reaction

rates and longer reaction times resulted in increased

indoor SOA concentrations. The predicted indoor SOA

concentrations decreased with further reductions in air

exchange rate below 0.4 h�1, primarily due to a decrease

in the O3/a-pinene reaction rate below an air exchange

rate of 0.4 h�1. Interestingly, at air exchange rates of

0.3–1.0 h�1, i.e., typical of many residential dwellings,

SOA was predicted to account for approximately

0

20

40

60

80

100

0 150 300 450 600 750

TIME [min]

PM

[µg

/m3]

0

30

60

90

120

150

OZ

ON

E [

pp

b]

predicted ozone

experimental ozone

predicted particles

experimental particles

Fig. 11. Experimental and predicted particle mass and O3 concentrations during experiment 2.


20–35% of the total indoor fine particle mass

concentrations.

3.3. Effects of outdoor fine particle concentration on

indoor SOA concentrations

Outdoor fine particle concentrations were varied from

0 to 100 mg/m3. Predicted indoor SOA mass concentra-

tions increased with higher outdoor fine particle mass

concentrations. Higher outdoor fine particle concentra-

tions caused higher indoor ‘‘seed’’ particle concentra-

tions, increased partitioning of semi-volatile products,

and increased indoor SOA concentrations. The pre-

dicted indoor SOA concentration was only 0.4 mg/m3

when the outdoor particle level was zero and resulted

from self-nucleation of low vapor pressure reaction

products. However, the predicted indoor SOA concen-

tration increased to almost 12mg/m3 at an outdoor fine

particle concentration of 100 mg/m3, a very high

concentration in outdoor environments.

3.4. Effects of outdoor ozone concentration on indoor

SOA concentrations

The outdoor O3 concentration was varied from 0 to

200 ppb. The higher outdoor O3 concentrations caused

an increase in indoor O3 concentrations, which in turn

increased the O3/a-pinene reaction rate. Increased

amounts of reaction products were generated by the

higher O3/a-pinene reaction rate, and resulted in

increased indoor SOA mass concentrations. The pre-

dicted indoor SOA mass concentration at an outdoor O3

concentration of 200 ppb was almost 50% of the total

indoor fine particle concentration.

3.5. Effects of indoor a-pinene emission rate on indoor

SOA concentrations

The indoor a-pinene emission rate was varied from 0

to 3 times the base-case emission rate. Increased indoor

a-pinene emission rates increased the O3/a-pinenereaction rate and resulted in elevated indoor SOA

concentrations. The contribution of SOA to indoor fine

particle mass equaled that of outdoor-to-indoor pene-

tration for an a-pinene emission rate of 4.6mg/min

(twice the base case).

3.6. Effects of indoor temperature on indoor SOA

concentrations

The indoor temperature was varied from 280 to 315K

(45–1081F). The resulting steady-state indoor SOA

concentrations are shown in Fig. 13. Indoor seed and

outdoor particle concentrations are also shown in

Fig. 13. The indoor SOA concentrations increased

dramatically as indoor temperature was reduced. Lower

temperatures reduced the rates of homogeneous chemi-

cal reactions. However, this effect was more than

compensated for by an increase in gas-to-particle

partitioning of reaction products at lower temperatures.

Predicted indoor SOA concentrations increased by more

than a factor of two for every 101C decrease in indoor

temperature.

Experiments 8 and 9 were conducted at elevated

chamber temperatures. Temperatures during these two

experiments were 32–331C, about 8–91C higher than

other experiments. The lower particle growth observed

during these experiments cannot be entirely attributed to

elevated temperature, since the air exchange rates during

these experiments were also higher than for other

experiments; operation of the space heater tended to

increase the air exchange rate in the chamber.

0

4

8

12

16

20

0.0 0.5 1.0 1.5 2.0 2.5 3.0

AIR EXCHANGE RATE [hr-1]

PM

[µg

/m3 ]

secondary particles

seed particles

outdoor particles

Fig. 12. Indoor fine particle concentration as a function of air exchange rate.


The combination of elevated outdoor O3 concentra-

tions or the presence of indoor O3 sources, low air

exchange rates, high indoor terpene emission rates, and

low indoor temperatures are predicted to produce the

highest secondary particle concentrations. Thus, the

building designer/operator should avoid this combina-

tion to reduce occupant exposure to fine particles. For

example, a control device for O3 can be installed in

buildings to reduce indoor O3 concentration, which can

also prevent the formation of elevated SOA concentra-

tions. During the urban summertime ozone season,

especially midday, sources of indoor terpenes should be

avoided to limit the formation of indoor secondary

particles. Buildings can be operated with higher air

exchange rates in combination with enhanced particle

filters. The use of high-efficiency particle filters can

reduce the transport of outdoor fine particles in

commercial buildings, and higher air exchange rates

can reduce SOA levels.

Outdoor-to-indoor transport is the main source of

indoor ozone for most buildings. However, sources of

ozone can also be present in buildings. For example,

photocopy machines, laser printers, electrostatic air

filters and electrostatic precipitators have been shown

to produce ozone (Weschler, 2000). Typical indoor

ozone concentrations range between 20% and 70% of

outdoor ozone concentrations due primarily to hetero-

geneous reactions between ozone and indoor surfaces,

e.g., carpet (Weschler, 2000). Indoor ozone concentra-

tions are expected to be somewhat lower than ozone

concentrations used during these experiments. For

example, indoor ozone concentrations in some urban

areas have been observed to be less than a factor of two

lower than used in this study (Weschler et al., 1989;

Gold et al., 1999). Thus, particle mass concentrations

resulting from reactions between ozone transported

from outdoors and a-pinene emitted in actual furnished

houses are expected to be somewhat lower than particle

mass concentrations presented in this paper.

Our research team is currently conducting field

experiments to evaluate the importance of indoor

ozone/a-pinene reactions in actual furnished houses.

However, it should be noted that Long et al. (2000)

reported a peak particle mass concentration of 38mg/m3

during six sampling events in Boston area homes in

which a pine-oil-based cleaner was used. Weschler and

Shields (1999) also reported an increase of approxi-

mately 20mg/m3 in indoor fine particle mass concentra-

tion when a limonene source was present in an office in

New Jersey. Indoor ozone generators were not used in

any of these experiments; indoor ozone was present due

to the transport of outdoor ozone.

4. Conclusions

The research described herein included experimental

as well as computational investigations. Ten chamber

experiments were completed to assess the effects of

ozone/a-pinene reactions on indoor secondary organic

particles. A significant contribution of this research was

the prediction of dynamic particle mass concentrations

based on detailed homogeneous chemical mechanisms

and partitioning of semi-volatile products to particles

using a new indoor chemistry and exposure model

(ICEM). The ICEM allows for the simulation of air-

exchange processes, indoor emissions, chemical reac-

tions, deposition, and variations in outdoor air quality.

Predicted indoor secondary particle mass concentrations

were in reasonable agreement with experimental results,

which suggests that the model is capturing the essence of

particle formation/growth processes. Nevertheless,

many uncertainties remain to be resolved. For example,

deposition velocities of the semi-volatile products of

0

4

8

12

16

20

40 50 60 70 80 90 100 110

INDOOR TEMPERATURE [F]

PM

[µg

/m3 ]

indoor secondary particles

indoor seed particles

outdoor particles

Fig. 13. Indoor fine particle concentration as a function of indoor temperature.


ozone/a-pinene reactions were assigned twice the deposi-

tion velocity of fine particles, which warrants further

exploration.

Experimental results indicate that significant particle

formation/growth can occur indoors due to reactions

between O3 and a-pinene. Particle growth occurs

through an initial ‘‘burst’’ of small particles followed

by a decrease in particle numbers in a given size range

and increase in particle numbers in subsequent size

ranges. This process leads to an effective particle growth

‘‘wave’’. If the initial indoor particle levels are low, the

initial ‘‘burst’’ of particles is pronounced and may be the

result of nucleation of O3/a-pinene reaction products

and the growth of smaller particles into larger detectable

sizes. If the initial indoor particle levels are high, the

initial ‘‘burst’’ of particles is smaller and particle growth

appears to occur via partitioning of O3/a-pinenereaction products. Additional research is recommended

to resolve the issue of particle formation/growth during

the initial phase of the experiment using particle

analyzers that can measure smaller particles and finer

size distributions.

Indoor secondary organic particles may account for

some of the previously reported ‘‘unexplained’’ particle

mass in indoor environments. A significant fraction of

indoor secondary particle numbers are in the ultra-fine

range (o0.1 mm). Most of the particle number and mass

associated with ozone/terpene reactions is associated

with particles o0.7mm in diameter. Lower air exchange

rates increase indoor secondary particle mass concentra-

tions, a phenomenon attributed to longer indoor

residence times. The combination of more time to

generate reaction products and longer particle residence

times increases particle mass concentrations and dis-

tributes the resulting mass into larger size ranges. Lower

indoor temperatures promote increased gas-to-particle

partitioning of low vapor pressure by-products of

ozone/terpene reactions, and increased particle mass

concentrations. Higher outdoor fine particle mass

concentrations cause higher indoor ‘‘seed’’ particle

concentrations, which in turn increase the partitioning

of semi-volatile products, resulting in increased indoor

secondary particle mass concentrations. Ozone genera-

tors that are marketed as indoor air ‘‘purifiers’’ should

be avoided since, in the presence of terpenes, they can

lead to extremely high levels of by-products including

formaldehyde, higher molecular weight aldehydes,

organic acids, and fine particles.

Acknowledgements

The authors acknowledge Professor Richard Kamens

of the University of North Carolina for providing

particle chemistry for a-pinene. The Texas Air Research

Center (TARC) provided all necessary funding for this

study. The authors thank Dr. Yosuke Kimura for

assistance with computational analysis.

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