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Characterization of Natural and Affected Environments

Time-Resolved Measurements of Indoor Chemical Emissions, Deposition, and Reactions in a University Art Museum Demetrios Pagonis, Derek Price, Lucas B. Algrim, Douglas A. Day, Anne Handschy, Harald Stark, Shelly Lynn Miller, Joost A. de Gouw, Jose L. Jimenez, and Paul J. Ziemann Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.9b00276 • Publication Date (Web): 16 Apr 2019 Downloaded from http://pubs.acs.org on April 22, 2019

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Environmental Science & Technology

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Time-Resolved Measurements of Indoor Chemical Emissions, Deposition, and

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Reactions in a University Art Museum

4 5

Demetrios Pagonis1,2, Derek J. Price1,2, Lucas B. Algrim1,2, Douglas A. Day1,2, Anne V.

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Handschy1,2, Harald Stark1,2,3, Shelly L. Miller4, Joost de Gouw1,2, Jose L. Jimenez1,2,

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and Paul J. Ziemann1,2*

8 9 10 11 12 13 14 15 16

1

17

Boulder, Colorado 80309

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2

Department of Chemistry, University of Colorado, Boulder, Colorado 80309

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3

Aerodyne Research, Inc., Billerica, Massachusetts 01821

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4

Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309

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*

Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado,

Corresponding email: [email protected]

1 ACS Paragon Plus Environment


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ABSTRACT

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A six-week study was conducted at the University of Colorado Art Museum during

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which volatile organic compounds (VOCs), CO2, O3, NO, NO2, other trace gases, and submicron

25

aerosol were measured continuously. These measurements were then analyzed using a box

26

model to quantify the rates of major processes that transformed the composition of the air. VOC

27

emission factors were quantified for museum occupants and their activities. Deposition of VOCs

28

to surfaces was quantified across a range of VOC saturation vapor concentrations (C*) and

29

Henry’s law constants (H) and was determined to be a major sink for VOCs with C* < 108 µg m-

30

3

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quantified, with unsaturated and saturated VOCs having oxidation lifetimes of >5 and >15 h,

32

making deposition to surfaces and ventilation the dominant VOC sinks in the museum. Ozone

33

loss rates were quantified inside a museum gallery, where reactions with surfaces, NO,

34

occupants, and NO2 accounted for 62%, 31%, 5%, and 2% of the O3 sink. The measured

35

concentrations of acetic acid, formic acid, NO2, O3, particulate matter, SO2, and total VOCs were

36

below the guidelines for museums.

and H > 102 M atm-1. Reaction rates of VOCs with O3, OH radicals, and NO3 radicals were


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37


INTRODUCTION

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Measurements of indoor pollutants in art museums have been central in the development

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of the field of indoor chemistry (Weschler, 2011). Motivated by a need to understand the effect

40

of air pollutants on art conservation, these measurements and accompanying models describe

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fundamental aspects of how outdoor pollutants deposit and react indoors, with the results being

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applicable to indoor environments in general (Druzik et al. 1990; Nazaroff et al. 1990; Salmon et

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al. 1990; Nazaroff and Cass, 1991; Brimblecombe et al. 1999; Camuffo et al. 1999; Gysels et al.

44

2004). Sampling periods for trace gas measurements in these studies, determined by techniques

45

available at the time, ranged from 1–24 hours, limiting the ability of researchers to study

46

processes that occur on timescales of minutes. Recent studies using techniques with faster time

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response have allowed for new insights into how pollutants are emitted, transported, and

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transformed through chemical reactions indoors. Measurements of volatile organic compounds

49

(VOCs) in university classrooms using proton transfer reaction-mass spectrometry (PTR-MS)

50

have allowed for quantitative source attribution of VOC emissions to occupants, ventilation, and

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surfaces (Liu et al. 2016), and determination of emission rates by occupants for a wide variety of

52

VOCs (Tang et al. 2016). Use of high-resolution, time-of-flight chemical ionization mass

53

spectrometers (CIMS) have allowed for novel source attributions of nearly 100 carboxylic acids

54

(Liu et al. 2017) and of chlorinated emissions following application of cleaning products

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containing bleach (Wong et al. 2017). These studies consistently documented a significant

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contribution of humans to indoor VOC concentrations, with human influence readily also

57

detectable in an open-air soccer stadium and a movie theater (Veres et al. 2013; Williams et al.

58

2016).



59

Even with these advances, significant questions remain surrounding the variability of

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emission profiles across different indoor environments with different occupancy rates,

61

construction materials, and activities. Additionally, broader changes in emissions (McDonald et

62

al. 2018) indicate that in many cities volatile chemical products (VCPs) are emerging as a

63

dominant source of anthropogenic VOCs outdoors. These emissions include personal care

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products, cleaning supplies, paints, and other compounds that are often emitted indoors, and so

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characterizing their indoor emissions is necessary to improve understanding of both indoor and

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outdoor air quality.

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Depending on their volatility, VOCs (and semivolatile and intermediate volatility species

68

(Robinson et al. 2007)) can partition to surfaces and particulate matter (Bennett and Furtaw Jr.,

69

2004; Weschler and Nazaroff, 2017), undergo gas-phase or heterogeneous reactions with

70

oxidants such as O3 and OH radicals (Weschler and Carslaw, 2018), and be transported outdoors

71

through heating, ventilation and air-conditioning (HVAC) systems as well as by infiltration and

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open windows and doors. Partitioning to indoor surfaces is an aspect of VOC fate that is being

73

actively researched. Models of impermeable indoor surfaces describe the formation of organic

74

films on those surfaces by compounds with sufficiently small octanol-air partitioning coefficients

75

(Weschler and Nazaroff, 2017). The contribution of permeable indoor surfaces such as paints

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and plastics to partitioning has received less attention though these surfaces have the potential to

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be significant sinks (Won et al. 2001). Additionally, water-soluble compounds are expected to be

78

absorbed into surface water films (Duncan et al. 2017).

79

In this study we present results from six weeks of indoor measurements at a university art

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museum. We present emission rates from occupants that are consistent with previous literature,

81

emission rates of VCPs emitted from painting and other occupant activities, the volatility


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dependence of VOC deposition to indoor surfaces, and the oxidation lifetimes of VOCs inside

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the museum. This work provides a comprehensive description of how indoor pollutants are

84

emitted, transported, deposited, and chemically transformed in a single indoor setting, and the

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results will be particularly useful for improving models of the chemistry of indoor environments.

86 87 88

EXPERIMENTAL SECTION Art Museum Site. The art museum study of indoor chemistry (ARTISTIC) campaign

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was conducted from April 13th to May 23rd, 2017 at the University of Colorado Art Museum

90

(40.0072 deg. lat. -105.2701 deg. lon. 1,650 m above mean sea level). The museum volume is

91

~6,000 m3 and air is circulated by an HVAC system at a constant volume flow rate of 48,000 m3

92

hr-1, with 4,800 m3 hr-1 of outside air mixed in. The temperature and relative humidity (RH) are

93

tightly controlled at 21 ± 1˚C and 45 ± 2%. From April 13th to May 9th we sampled from one of

94

the museum’s galleries (“the gallery” hereinafter, 780 m3, constant ventilation at 7,800 m3 hr-1)

95

that was exhibiting art created by the University’s students, and from May 9th to May 23rd

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measurements were conducted in the collections room (1,400 m3, constant ventilation at 8,200

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m3 hr -1), where the museum permanent collections are stored.

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Measurements and Instrumentation. VOCs were measured using a quadrupole proton

99

transfer reaction-mass spectrometer (PTR-MS) (de Gouw and Warneke, 2007), and more highly

100

oxygenated compounds were measured using a high-resolution time-of-flight chemical

101

ionization mass spectrometer that was operated using iodide (I-CIMS) or nitrate (NO3-CIMS) as

102

reagent ions by swapping ion sources (Bertram et al. 2011, Jokinen et al. 2012). Calibration

103

procedures for each instrument are described in detail in the SI. Carbon dioxide, carbon

104

monoxide, methane, and water were measured using a Picarro G2401 cavity ringdown



105

spectrometer. Ozone, nitrogen oxides (NOx), and sulfur dioxide (SO2) were measured with

106

Thermo analyzers (49i O3, 42i-TL, and 43i-TLE, respectively). Sub-micron size aerosol size

107

distributions and mass concentration were measured with a TSI scanning mobility particle sizer

108

(SMPS, differential mobility analyzer model no. 3080; condensation particle counter model no.

109

3776, 15-600 nm size range). Relative humidity and temperature were measured with a Vaisala

110

RH probe, model no. HMP75B. Zero air was generated on-site using a Thermo 1160 zero air

111

generator. UV-Vis spectral irradiances were measured using an Ocean Optics USB 2000+

112

spectrometer and used to calculate species photolysis rates as described in the Supporting

113

Information (SI). Trace gases were sampled through 0.47 cm inner diameter (ID) FEP Teflon

114

tubing and aerosols were sampled through 0.47 cm ID copper tubing. The NO3-CIMS sampled

115

through a 1.5 cm ID stainless steel tube 0.7 m in length.

116

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In the gallery and collections rooms the instruments sampled air from inside each room

117

and from the supply air from the HVAC system. The supply air was sampled after all

118

conditioning had occurred, with the sampling lines located immediately (< 30 cm) upstream of

119

the diffusers where the supply air enters either room. The instruments sampled using an

120

automated valve system that alternated sampling between room air and supply air every 5 min,

121

with makeup flows applied so that air was always being pulled with constant flow rate through

122

both sampling lines. The valve timing was chosen to balance the ability to sample both locations

123

as frequently as possible against the delays in response times of the instruments and sampling

124

lines to VOCs (Pagonis et al. 2017).

125

Art Museum Model. A box model that is equivalent to a two-compartment completely-

126

mixed flow reactor (CMFR) model (Shair and Heitner, 1974) was used to quantify emissions,

127

deposition, and reaction rates of chemicals inside the museum, as depicted in Figure 1. The


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assumption of complete mixing of the indoor air is based on a mass balance applied to VOCs

129

within two museum compartments: the gallery and the supply air + rest of the museum. For

130

consistency with the discussion of measurements we refer to the two compartments as the gallery

131

and the supply air, since these correspond to the two air sampling locations. The measured

132

supply air concentration mostly represents the rest of the museum (including ducts) as it consists

133

of 74% recirculated air from the rest of the museum, 16% recirculated gallery air, and 10%

134

outside air. Exchange between the gallery and the supply air, and the supply air and outside air

135

were determined from the ventilation rates given above, assuming both compartments are well

136

mixed. The model was numerically integrated using the Euler method at a time step of 0.36 s.

137

Shorter time steps did not affect the model outputs.

138

The differential equations describing the change in concentration for a compound in the

139

gallery and in the supply air due to transport, chemistry, emission, and deposition are given in

140

Equations 1 and 2: ![!]!

141 142

!"

![!]! !"

= 𝐴𝐸𝑅!,! ([𝐴]! − 𝐴 ! ) +

!! ! !!

+ 𝑅! (𝑡) + 𝑃! (𝑡)

= 𝐴𝐸𝑅!,! ([𝐴]! − 𝐴 ! ) + 𝐴𝐸𝑅! ([𝐴]! − 𝐴 ! )

!! !!

+

!! ! !!

+ 𝑅! (𝑡) + 𝑃! (𝑡)

(1) (2)

143

where the subscripts g, s, and o refer to the gallery, the supply air + rest of the museum, and

144

outdoors. Those subscripts are then applied to the following terms in Equations 1 and 2: [A] is

145

the concentration of compound A (µg m-3), AER is the air exchange rate between the respective

146

compartments in the model (h-1), V is volume (m3), E(t) is the emission rate at time t (µg h-1), R(t)

147

is the rate of chemical production minus loss (µg m-3 h-1), and P(t) is the rate of surface emission

148

minus surface deposition (µg m-3 h-1). A complete list of equation terms and their units is

149

presented in Table S1.



150

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Indoor emission rates. Emissions of VOCs inside the gallery from people during an art

151

exhibit opening, from paint when a wall was painted, and other less well-defined instances where

152

the VOC concentration in the gallery was higher than in the supply air were quantified by

153

assuming that the VOC underwent no chemistry inside the gallery (Rg(t) = 0) and did not

154

partition to surfaces (Pg(t) = 0), in order to solve directly for the emission rate Eg(t). Rearranging

155

Equation 1 we obtain Equation 3 for the emission rate of a compound inside the gallery (Tang et

156

al. 2015): 𝐸! (𝑡) = 𝑉! 𝐴𝐸𝑅!,! [𝐴]! − [𝐴]! +

157

![!]!

(3)

!"

158

Emissions that occurred inside the museum but outside the gallery were quantified similarly

159

using Equation 4:

160

𝐸! (𝑡) = 𝑉! 𝐴𝐸𝑅!,!

𝐴!− 𝐴

!

+ 𝐴𝐸𝑅!,!

𝐴!− 𝐴

!

𝑉𝑔 𝑉𝑠

+

!!! !"

(4)

161

Outdoor air concentrations during the integrated period were assumed to remain constant at the

162

levels measured in the supply air immediately before the start of an emission event (Veres et al.

163

2013). As seen in Figure 2, the significant enhancements in indoor VOC concentrations above

164

background concentrations during an emission event reduce error caused by any variation in

165

outdoor concentration on calculated indoor emission rates.

166

Gas-surface partitioning rates. Partitioning of VOCs to museum surfaces was modeled

167

by analogy to reversible gas-particle partitioning in the atmosphere (Pankow, 1994; Donahue et

168

al. 2006) using Equation 5:

169

𝑃! 𝑡 = 𝑘!"#$$ [𝐴]! − 𝑘!"# [𝐴]!

(5)

170

where kdep and kemiss are the first-order rate constants for surface deposition and surface emission

171

(h-1), and [A]w is the concentration of VOC sorbed to surfaces in the supply air + rest of the 8 ACS Paragon Plus Environment

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museum (µg m-3 air). Because partitioning rates can only be estimated when partitioning

173

equilibrium is disturbed, we estimate kdep and kemiss in the supply air + rest of the museum during

174

periods when in-gallery emission rates have been quantified according to Equation 3. We then

175

configure the model so that gas-surface partitioning and transport are the only sinks for the VOC

176

in the supply air + rest of the museum (Rs(t) = 0). Our model estimates of low O3, NO3, and OH

177

concentrations in the gallery support the assumption that the impact of reactions on most

178

compounds is minor. The rate of change in the concentration of the VOC in the supply air is then

179

given by Equation 6: !!

180

![!]!

181

Values of kdep and kemiss were determined by varying the value of both rate constants

!"

= 𝐴𝐸𝑅!,! ([𝐴]! − 𝐴 ! ) + 𝐴𝐸𝑅!,! ([𝐴]! − 𝐴 ! )

!!

+

!! (!) !!

+𝑘!"#$$ 𝐴

!

− 𝑘!"# 𝐴

!

(6)

182

systematically to find the minimum squared error between model output of supply air and gallery

183

concentrations evaluated against the measured concentrations of the VOC during the emission

184

event. When estimating deposition rates for VOCs emitted by museum occupants during the

185

exhibit opening, Es(t) was calculated using Eg(t) and the occupancies of the gallery and rest of

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the museum (Es(t) = Eg(t) × Occs / Occg). For all other gallery emission events Es(t) was assumed

187

to be zero. Additional details of how the model was initialized are presented in the SI.

188

For our discussion of the results we chose to present VOC deposition rates in terms of the

189

fraction of VOC that is recirculated (and thus not deposited) during each pass through the

190

museum and its HVAC system, Frecirc, instead of kdep. This quantity more clearly represents the

191

measurable range of VOC deposition behavior in the museum, since (as discussed in SI and

192

shown in Figure S1) compounds with Frecirc ≈ 0 have large, highly variable kdep values even

193

though they are almost entirely removed. The fraction of VOC that is recirculated during time t

194

is given by Equation 7:

195

𝐹!"#$!# = 𝑒 !!!"# !

(7) 9

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196

Substituting the time required for a single pass of 0.125 h, calculated from the ratio of the total

197

museum volume (6,000 m3) and the total HVAC volume flow rate (48,000 m3 h–1) then gives

198

Equation 8:

199 200

𝐹!"#$!# = 𝑒 !!.!"# !!"#

(8)

Chemical reaction rates. The model was configured to account for reactions of O3, NO,

201

NO2, and VOCs inside the gallery. To avoid making assumptions about the outdoor

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concentrations of these reactive compounds, we use the model to predict concentrations inside

203

the gallery only, rather than inside the entire museum. To achieve this, we constrain [A]s of the

204

above species in the model using their measured supply air concentrations. The chemical

205

reactions included in the model and corresponding rate constants are presented in Table S2. Rate

206

constants for VOC reactions are those of limonene (Ziemann and Atkinson, 2012), and all other

207

rate constants were taken from the 2015 JPL Kinetics Evaluation (Burkholder et al. 2015).

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Limonene was chosen as the VOC surrogate because it is abundant indoors and reacts rapidly

209

with O3 (with a high OH radical yield), NO3 radicals, and OH radicals, thus maximizing the

210

potential role of oxidation in the modeled fate of VOCs in the museum. Reaction of O3 with

211

surfaces inside the gallery was modeled using a constant deposition velocity, and reaction of O3

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with people was modeled as a constant deposition velocity that scales with the number of people

213

inside the room, with occupancy estimated from CO2 measurements. The O3 deposition

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velocities were varied to find values that gave a minimum summed squared error when model

215

predictions of gallery O3, NO, and NO2 concentrations were evaluated against their respective

216

measured gallery concentrations. Calculations based on measurements of photon fluxes inside

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the gallery gave upper limits of photolysis rates of NO2 and NO3 of 4.6 × 10-7 and 1.2 × 10-4 s-1.

218

These photolysis reactions were included in the model but were too slow to affect model outputs.


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From the model outputs of O3 and NOx concentrations we also estimated the net

220

production rate of NO3 and OH radicals inside the gallery. Since NO3 radical photolysis is very

221

slow inside the gallery it is not significant and the dominant loss pathways for NO3 radicals were

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reaction with NO, NO2, and VOCs. Typical sources of indoor OH radicals are photolysis of

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precursors like HONO (Gligorovski, 2016) and ozonolysis of alkenes (Waring and Wells, 2015).

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We assumed an OH radical yield of 0.5 from alkene ozonolysis (Ziemann and Atkinson, 2012),

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and that the only OH radical loss processes are reactions with VOCs and NO2. In order to assess

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the possible contributions of HONO to OH radical production we introduced an elevated

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background concentration of HONO to the model and ran the model under conditions that would

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maximize OH radical production from HONO photolysis and minimize OH radical production

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from ozonolysis: 1 ppb alkenes (half the average measured concentration of isoprene plus

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monoterpenes in the museum), 10 ppb HONO (twice the concentration previously measured in

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an art museum, Katsanos et al. 1999), and a calculated upper limit for the HONO photolysis rate

232

(jHONO) of 6 × 10-8 s-1. Under these conditions, ozonolysis of alkenes remains the dominant

233

source (>95%) of OH radicals, indicating that because of low light intensities in this museum

234

HONO photolysis is not a significant contributor to OH radical production.

235 236 237

RESULTS AND DISCUSSION VOC Emission Rates. On April 28th an exhibit opening was held for the thesis

238

exhibition of the University’s Bachelor of Fine Arts (BFA) program from 5:00 to 7:00 PM local

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time. Measured time series of CO2 and two selected VOCs, acetone and lactic acid, are shown in

240

Figure 2. The time series for each species is determined by emissions, deposition, reactions,

241

transport, and indoor-outdoor air exchange. Although lactic acid, acetone, and CO2 are all co-



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emitted by gallery occupants during the opening, they show different time series as a result of

243

these processes. The CO2 mass emission rates in the museum (gallery and the rest of the

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building) during the opening were calculated using Equations 3 and 4, the measured time series

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of CO2 in the gallery and supply air (Figure 2a), the CO2 concentration in outdoor air (assumed

246

to be 400 ppb, the typical concentration in the museum during unoccupied periods), and the

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building parameters. Using a CO2 emission factor of 21 g person-1 h-1 measured by Tang et al.

248

(2016) in order to facilitate our comparison with the VOC emission rates measured in that work,

249

we estimated that the average occupancies of the gallery and the rest of the building during the

250

opening were 108 and 68 people. Museum staff counted 300 total attendees at the opening,

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indicating that the average attendee spent 70 min (120 min × 176/300) inside the museum.

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VOC emission rates were calculated for the gallery during the opening using Equation 3,

253

the measured time series of VOCs in the gallery and supply air, and the building parameters. The

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mass balance of Equation 3 is not affected by any variation in the outdoor concentration of

255

VOCs. Gallery emission rates of VOCs that correlated with the CO2 emission rate are listed in

256

Table S3, and were used to calculate average per-person VOC emission rates during the entire

257

opening. The results are shown in Figure 3, where they are compared to human emission factors

258

quantified by Tang et al. (2016) in a classroom. Most emission factors agree with the estimates

259

of Tang et al. (2016) within a factor of two, with the following exceptions: monoterpenes (m/z 81

260

and 137), ethanol (m/z 47), and products of reactions of O3 with skin oil, such as 6-methyl-5-

261

hepten-2-one (6-MHO, m/z 127 and 109) and 4-oxopentanal (4-OPA, m/z 101) (Wisthaler and

262

Weschler, 2010). The elevated ethanol emission rate during the exhibit opening compared to the

263

classroom is possibly due to alcohol consumption by attendees prior to the opening since no

264

alcohol was served at the opening. The ethanol emissions are equivalent to what one would


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expect if 18 people (~16% of gallery occupants) had a blood alcohol content of 0.03, about the

266

amount acquired by consuming one standard drink in the hour prior to the opening (Kypri et al.

267

2005, Wright et al. 1975). Measured emissions of acetaldehyde (m/z 45) were also elevated,

268

possibly because breath acetaldehyde concentrations also increase following alcohol

269

consumption (Wong et al. 1992; Smith et al. 2002), another indication that opening attendees

270

may have consumed alcohol prior to the opening. Lower observed emission rates of

271

monoterpenes were possibly due to reduced emissions from personal care products – either

272

because these products had worn off over the course of the day (Coggon et al. 2018) or because

273

less product was used per person. The lower emission rates of skin oil-O3 reaction products

274

measured in this study compared to Tang et al. (2016) are consistent with the lower O3

275

concentrations inside the museum during the opening (4.5 ppb) compared to the Berkeley

276

classroom (10–25 ppb, X. Tang, personal communication).

277

Molecular assignments of the detected m/z values were based on results of prior PTR-MS

278

studies, including high-resolution measurements of human emissions (Tang et al. 2016), analyses

279

of products of ozone-squalene reactions indoors (Wisthaler and Weschler, 2010), and studies

280

using gas chromatographic pre-separation (Warneke et al. 2003). Assignment of VOCs emitted

281

during the painting of the gallery was facilitated by collecting samples of the paint and primer

282

and analyzing their emissions in the laboratory using a high-resolution Vocus PTR-ToF-MS that

283

was briefly available (Krechmer et al. 2018) and allowed for determination of the molecular

284

formulas. For detected m/z values that arise from fragmentation (e.g., m/z 43, C2H3O+; m/z 57,

285

C3H9+) we do not assign a single compound, rather, we assign a broad compound class such as

286

carboxylic acids or alkanes (Yuan et al. 2017).



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On April 21st, museum staff re-painted a wall inside the gallery to prepare for an

288

upcoming exhibit. A single coat of primer and a single coat of white paint were applied to 12 m2

289

of wall, directly on top of the existing paint. A total of 13 g of VCPs were emitted in this event,

290

and emission factors and maximum concentrations for each measured VCP are presented in

291

Table S4. The compounds emitted in the painting event are consistent with several of the major

292

classes of VCPs described by McDonald et al. (2018), including alkanes, glycol ethers, and

293

acetone. As discussed below, deposition of these compounds to building surfaces prior to being

294

ventilated to outdoor air is a significant fate for VCPs emitted indoors and is a key parameter for

295

bridging VCP indoor emission measurements with fluxes into outdoor air and outdoor

296

measurements. Additional emission events quantified in the museum are presented in Table S5.

297

VOC Deposition Rates. Following emission of a compound inside the museum, the

298

compound is redistributed throughout the museum via the building’s HVAC system. As this

299

happens one expects the concentration of the compound to rise in the supply air. For many of the

300

emissions measured, however, the increase in supply air concentration was significantly lower

301

than that predicted by the model and the measured gallery emission rate, museum volume, and

302

air exchange rates. For example, the difference in recirculation behavior of lactic acid compared

303

to CO2 and acetone can clearly be seen in Figure 2. Although all three compounds were co-

304

emitted by museum occupants during the opening, the relative increase in lactic acid

305

concentration in the supply air compared to the gallery air was significantly less than that of CO2

306

and acetone. This result, and the observation that after the conclusion of the opening at 7:00 PM,

307

CO2 and acetone were removed from the museum at the rate of indoor-outdoor air exchange

308

while lactic acid was lost much faster, indicate a loss process for lactic acid that occurred


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309

between the time it was emitted in the gallery and when it re-entered the gallery via the supply

310

air. A range of loss rates was observed for other VOCs.

311

The fractions of VOCs recirculated during one pass through the HVAC system and

312

museum following emission in the gallery were calculated using Equation 8 and the modeled

313

deposition rate constants kdep. The results are shown in Figure 4. For reference, values of Frecirc of

314

0.1, 0.5, and 0.9 correspond to values of kdep of 18.4, 5.5, and 0.8 h–1. The fractions depend

315

inversely on C* values (Donahue et al. 2006) estimated using the SIMPOL.1 group contribution

316

method (Pankow and Asher, 2008) and proportionally on Henry’s law constants (H) estimated

317

using the GROMHE structure-activity relationship (Raventos-Duran et al. 2010). The observed

318

dependence on C* and H can be explained by losses that occur by reversible gas-surface

319

partitioning during recirculation, since irreversible losses would be independent of these

320

quantities. Thus, VOCs with low C* and high H have gas-surface partitioning constants that

321

favor deposition (Pankow, 1994; Bennett and Furtaw Jr., 2004) and lead to low recirculation

322

fractions. For compounds with C* < 108 µg m-3 or H > 100 M atm-1 deposition to surfaces was

323

found to be a significant sink, with deposition being competitive with removal by ventilation

324

with outdoor air (a 1.25 h ventilation timescale is equivalent to a recirculation fraction of 0.9).

325

From our measurements we are unable to determine the relative contributions of the HVAC

326

system and the rest of the museum to deposition losses – we can only quantify the total

327

deposition rates of VOCs in the museum after they are emitted inside the gallery. The modeled

328

emission rates due to reversible partitioning from the walls back to the gas phase are a significant

329

source of VOCs, sufficient to maintain concentrations of 0–5 ppb for the compounds in Figure 4.

330

Models have been developed previously to describe the partitioning of compounds to

331

organic and aqueous films that are thought to cover indoor surfaces (Bennett and Furtaw Jr.,



Page 16 of 35

332

2004). Necessary inputs include compound volatility and water solubility, and estimates of the

333

amount of organic material and water sorbed to surfaces, which determine the C* and H values

334

at which a gas-phase compound will significantly sorb. In Figure 4 we show the recirculation

335

fraction of VOCs as a function of both C* and H, but are unable to determine the relative

336

contributions from sorption to organic and aqueous films. This is because compound C* and H

337

values tend to show an inverse relationship (i.e., low-volatility compounds generally have high

338

Henry’s Law coefficients; Hodzic et al., 2014; Schwarzenbach et al. 2017); and since the

339

museum relative humidity is held constant we could not systematically explore the role of

340

surface water in gas-surface partitioning. Replicating this study in an environment where relative

341

humidity varies might allow one to uncouple the two effects and thus determine the extent to

342

which indoor deposition of VOCs is controlled by partitioning to organic or aqueous films.

343

We also note that during the emission events used to model deposition in the museum

344

(and for the majority of days in the study) the outdoor air temperature and absolute humidity

345

were below the target values for inside the museum, so the HVAC system was heating and

346

humidifying the air by mixing steam. We expect that when air is instead being cooled by the

347

HVAC system there is potential for increased VOC deposition, as the cooling coils present a cold

348

surface that would promote condensation of water and thus volatility- and solubility-driven

349

deposition.

350

Ozone Loss Rates. Measurements of O3, NOx, and CO2 in the gallery and the supply air

351

were used to quantify the total loss rate of O3 in the gallery and the relative loss rates to gallery

352

surfaces, people, and reactions with NO and NO2. Average depletion of O3 observed in the

353

gallery relative to the supply air was 0.7 ppb, a 10% reduction in the indoor O3 concentration. To

354

simulate this, the model depicted in Figure 1 was run with the reactions given in Table S2


Page 17 of 35


355

included and with the supply air concentration of O3, NO, and NO2 constrained to the measured

356

concentration for each compound. Ozone deposition velocities were then fitted as described

357

above to give the best agreement between the measured and modeled gallery concentrations of

358

O3, NO, and NO2. The estimated per-person deposition velocity calculated for the gallery is 0.38

359

cm s-1 person-1, which is consistent with the range of 0.40–0.62 cm s-1 reported in studies

360

conducted in well-controlled test rooms (Fadeyi et al. 2013; Wisthaler and Weschler 2010) and

361

in classrooms (Fischer et al. 2013). The O3 deposition velocity to surfaces of 0.021 cm s-1 is also

362

consistent with other measurements in indoor environments (Reiss et al. 2004).

363

Modeled loss rates of O3 due to reaction with surfaces, occupants, and NOx during two

364

days of the campaign are presented in Figure 5. Averaged over the three weeks of measurements

365

surfaces accounted for 62% of the O3 loss, NO for 31%, occupants for 5%, and NO2 for 2%.

366

Especially notable in Figure 5 is the temporal variability of the contributions of NO to O3 loss.

367

Depending on the NO concentration and gallery occupancy the O3 removal rate inside the gallery

368

varied in time by a factor of four. The NO concentrations in the museum supply air for the period

369

presented in Figure 5 varied from 0 to 4 ppb, with rapid variations likely due to emissions from

370

nearby traffic and/or pottery kilns in an adjacent building. These variations in NO concentration

371

drastically affected the O3 loss rate, reducing the amount of O3 available to react with other sinks

372

when NO concentrations were high. The opening for the BFA exhibit took place on April 28th,

373

and the high occupancy inside the gallery led to people being the dominant sink for O3 in the

374

gallery. Conversely, on Saturday April 29th museum occupancy and NO concentrations were low

375

(Figure 5), typical of weekends in our study, and surfaces were the dominant O3 sink. These

376

results show that the reactive loss of O3 indoors is highly variable in time, and an accurate

377

accounting of the fate of O3 in a particular indoor environment must account for the variability in



Page 18 of 35

378

occupancy and NOx. This behavior also has implications for indoor production of NO3 and OH

379

radicals, as discussed below.

380

VOC Oxidation Rates. The relative contributions of reactions with O3, OH radicals, and

381

NO3 radicals to VOC chemistry inside the gallery were evaluated using O3 measurements along

382

with model estimates of OH and NO3 radical concentrations. Because the primary source of OH

383

radicals inside the museum is alkene ozonolysis (due to the very low HONO photolysis rates

384

discussed above), a surrogate alkene was added to the model to react with O3 and generate OH

385

radicals. In order to estimate upper limits for the OH radical concentration and oxidation rates, it

386

was assumed that the surrogate alkene concentration was twice the average measured alkene

387

concentration (5 ppb) and that the O3 rate constant was that of limonene (2.1 × 10-16 cm3 molec-1

388

s-1) (Atkinson and Arey, 2003). The maximum measured concentration of O3 and modeled

389

concentrations of OH radicals and NO3 radicals in the museum were 2.4 × 1011 molecules cm-3

390

(12 ppb), 1.2 × 105 molecules cm-3 (5.9 ppq) and 2.0 × 106 molecules cm-3 (98 ppq). From these

391

concentrations and the known rate constants for reaction of limonene with each oxidant (Table

392

S2), the lifetime of the surrogate alkene with respect to reaction with O3, OH radicals, and NO3

393

radicals in the museum was estimated to be 5.5, 15, and 12 h. Since saturated VOCs react almost

394

exclusively with OH radicals, and their rate constants for reaction with OH radicals are usually

395

smaller than that for limonene (Atkinson and Arey, 2003), the lifetimes for most saturated VOCs

396

with respect to oxidation will be much greater than 15 hr. For example, the lifetime of octane

397

with respect to reaction with OH radicals inside the museum is 12 days. These timescales

398

indicate that VOC removal by ventilation (1.25 h) and deposition (< 1 h for compounds with C*

399

below 108 µg m-3) dominate over oxidation, especially for saturated VOCs and aromatics

400

because of their slow reactions with O3 and NO3 radicals.


Page 19 of 35

401


We note that use of a slower-reacting VOC, such as α-pinene (the rate constants for

402

reaction with O3 and OH radicals are factors of 2.5 and 3.1 smaller than those of limonene), can

403

affect the model predictions of OH radical concentrations. At low alkene concentrations (5 ppb), the lower α-pinene

406

OH reactivity leads to an increase in OH radical concentration. For the range of surrogate VOC

407

concentrations modeled here (1–5 ppb) the OH radical concentrations modeled using α-pinene

408

and limonene are within 15%, so the choice of surrogate VOC does not have a large impact on

409

the estimated oxidation lifetimes.

410

IMPLICATIONS FOR ART CONSERVATION

411

The measured concentrations of acetic acid, formic acid, HNO3, NO2, O3, particulate

412

matter, SO2, and total VOCs examined in this study were below the action limits for museums

413

published by the Getty Conservation Institute (Grzywacz, 2006) and the Canadian Conservation

414

Institute (Tetreault, 2003), indicating that the CU Art Museum has good indoor air quality for

415

storing and displaying the University’s collections. The low concentration of pollutants in the

416

museum is partially attributable to the high recirculation fraction imposed by the air handler. We

417

expect that lowering the recirculation fraction (increasing the outdoor air fraction) would

418

increase the concentration of pollutants such as O3 and particulate matter by increasing the rate at

419

which they are brought into the museum. A summary of the pollutant concentrations measured in

420

the museum and the respective standards is presented in Table S6. The measured illuminance in

421

the gallery (33 lx) meets the 100-year standard for museums (Tetreault, 2003). The model allows

422

for estimation of deposition rates of airborne pollutants to a given surface. Using the O3

423

deposition velocity of 0.021 cm s-1 determined above and the calculated surface area of the



Page 20 of 35

424

gallery (assuming that all artwork is flat) we estimate the deposition rate of O3 in the gallery to

425

be 150 µg m2 day-1. The maximum deposition rate of HNO3 is calculated to be 0.81 µg m2 day-1

426

using the maximum gallery HNO3 concentrations obtained from the model and a deposition

427

velocity of 0.87 cm s-1 measured previously in a museum (Salmon et al. 1990). The average

428

submicron aerosol mass in the gallery measured by the SMPS was 0.61 µg m-3. Using the mean

429

difference in submicron aerosol mass in the gallery and supply air (5 ng m-3 campaign average)

430

and Equation 1 we calculate the deposition rate of submicron particles in the gallery to be 1.3 µg

431

m2 day-1. This deposition rate is within the range of 0.22–2.8 µg m2 day-1 reported by Nazaroff et

432

al. (1990) for submicron particles in museums in Southern California. Our results describing

433

VOC gas-surface partitioning indicate that organic pollutants, including acetic acid and formic

434

acid, have significant reservoirs in museum surfaces that can act as sinks when VOCs are emitted

435

and sources when the gas-phase concentration is reduced. Although the same general classes of

436

materials (e.g., wood, glass, wallboard, concrete) and coatings (e.g., paint, varnish, wax) are

437

likely used in most museums, it is not yet known how much variability exists in the gas-surface

438

partitioning properties of different products. Additional research on the nature of gas-surface

439

partitioning indoors is therefore needed to better understand how to control organic pollutants in

440

museums. As the airborne concentrations of all the above-mentioned pollutants are below the

441

published standards for museums, these deposition rates are probably not of concern for art

442

preservation in the museum.

443

IMPLICATIONS FOR INDOOR AIR CHEMISTRY

444

The results of this study show that real-time measurements of VOCs and other trace gases

445

combined with modeling result in a wealth of qualitative and quantitative information about the

446

transport, emission, deposition, and transformation of chemicals in the indoor environment. In


Page 21 of 35


447

our case, modeling was greatly simplified by the museum’s constant volume flow ventilation

448

system. Many indoor environments do not have such consistent air exchange rates, and

449

accurately modeling transport within those environments requires significant effort to determine

450

the variability in air exchange rates over time. Emissions of volatile chemical products were

451

identified as a significant source of VOCs inside the museum, and often occurred in discrete

452

events. The variability in the compounds emitted in each event demonstrates a continued need

453

for real-time characterization of the composition and concentrations of chemical products used

454

indoors.

455

The observed effect of VOC vapor pressure and Henry’s law coefficient on deposition

456

indicates that VOC sorption to indoor surfaces is analogous to gas-particle partitioning in the

457

atmosphere, with the volatility threshold for deposition in the museum being increased by about

458

six orders of magnitude relative to that proposed for partitioning to impermeable surfaces

459

(Weschler and Nazaroff, 2008). This indicates that absorption of VOCs by permeable surfaces,

460

including paints and plastics, may play a significant role in VOC deposition indoors.

461

Deposition to surfaces and ventilation to outside air are the dominant removal processes

462

of VOCs indoors in our study, with some removal of alkenes by O3 and NO3 radical oxidation.

463

Calculations made using our estimates of indoor oxidant concentrations show that indoor VOC

464

oxidation is generally slower than indoor-outdoor air exchange rates and deposition, and in

465

environments without a photolytic OH source saturated VOCs have lifetimes of tens of hours,

466

rendering them nearly inert indoors. Rapid changes in the indoor O3 reaction rate caused by

467

variations in NO concentration demonstrate the importance of O3-NOx reactions in determining

468

the oxidation regime of indoor air for the small fraction of VOCs that react before being

469

ventilated or depositing to a surface.



Page 22 of 35

470

ACKNOWLEDGMENTS

471

We thank the Alfred P. Sloan Foundation (Grant No. G-2016-7173) for funding this study. The

472

authors acknowledge Stephen Martonis, Pedro Caceres, and Sandra Firmin at the University of

473

Colorado Boulder Art Museum, and Patrick Lester of CU Facilities for supporting the use of the

474

museum sampling site.

475 476

SUPPORTING INFORMATION AVAILABLE

477

The online supporting information for this study includes a description of the instrument

478

calibration procedures employed, a description of how the model was initialized, a table of

479

variables and mathematical expressions used in the text, a table of chemical reactions included in

480

the model, tables of emission events, and a comparison of measured pollutant levels to published

481

standards. This information is available free of charge via the Internet at http://pubs.acs.org.

482 483

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Won, D.; Corsi, R.; and Rynes, M.; Sorptive interactions between VOCs and indoor materials. Indoor Air 2001, 11, 246–256. Wong, J. P. S.; Carslaw, N.; Zhao, R.; Zhou, S.; and Abbatt, J. P. D. Observations and impacts of bleach washing on indoor chlorine chemistry. Indoor Air 2017, 27, 1082–1090. Wong, M. K. C.; Scott, B. K.; and Peterson, C. M. Breath acetaldehyde following ethanol consumption. Alcohol 1992, 9, 189–192.


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Wright, B. M.; Jones, T. P.; and Jones, A. W. Breath alcohol analysis and the blood:breath ratio. Med. Sci. Law 1975, 15, 205–210. Yuan, B.; Koss, A. R.; Warneke, C.; Coggon, M.; Sekimoto, K.; and de Gouw. J. A. Proton-

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2017, 117, 13187–13229.

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Zhou, S.; Forbes, M. W.; and Abbatt, J. P. D. Kinetics and products from heterogeneous oxidation of squalene with ozone. Environ. Sci. Technol. 2016, 50, 11688–11697. Ziemann, P. J. and Atkinson, R. Kinetics, products, and mechanisms of secondary organic aerosol formation. Chem. Soc. Rev. 2012, 41, 6582–6605.

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FIGURES

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Figure 1. Schematic of the box model used to describe the transport, emission, deposition, and

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reaction of compounds in the University of Colorado Art Museum. The museum is represented

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by two compartments, the gallery and the supply air + rest of museum, corresponding to the two

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sampling locations of this study. Air in each compartment is assumed to be perfectly mixed.

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Figure 2. Time series of (A) carbon dioxide, (B) acetone, and (C) lactic acid concentration

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measured by Picarro, PTR-MS, and iodide-CIMS, respectively, during a museum exhibit

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opening.



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Figure 3. Human emission factors determined in this study and in Tang et al. (2016). The

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symbols are the detected m/z for each VOC measured with the PTR-MS (Table S3). Emission

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factors of all species quantified by Tang et al. are summed to a unit mass for comparison to the

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ARTISTIC quadrupole PTR-MS data.


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Figure 4. Fraction of organic compound recirculated per pass through the museum and HVAC

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system as a function of the compound (A) saturation vapor concentration and (B) Henry’s law

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constant calculated using SIMPOL (Pankow and Asher, 2008) and GROMHE (Raventos-Duran

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et al. 2010), respectively.



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Figure 5. Ozone loss rates in the museum gallery over a two-day period, apportioned between

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reactions with gallery surfaces, occupants, NO, and NO2.

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For Table of Contents Only:

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Time-Resolved Measurements of Indoor Chemical ... - ACS Publications

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