Measurements of Parameters Controlling the Emissions of

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Measurements of Parameters Controlling the Emissions of Organophosphate Flame Retardants in Indoor Environments Yirui Liang, Xiaoyu Liu, and Matthew R Allen Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00224 • Publication Date (Web): 19 Apr 2018 Downloaded from http://pubs.acs.org on April 23, 2018

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Measurements of Parameters Controlling the Emissions of Organophosphate Flame Retardants in Indoor Environments

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Yirui Liang†, Xiaoyu Liu*, Matthew R. Allen‡

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6

Agency

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*

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Management Research Laboratory, Research Triangle Park, NC 27711

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Oak Ridge Institute for Science and Education participant at U.S. Environmental Protection

U.S. Environmental Protection Agency, Office of Research and Development, National Risk

Jacobs Technology Inc. 600 William Northern Boulevard, Tullahoma, TN 37388

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*Corresponding Author:

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U.S. Environmental Protection Agency, Office of Research and Development, National Risk

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Management Research Laboratory, Research Triangle Park, NC 27711

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Phone: 1-919-541-2459

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Fax: 1-919-541-0359

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Email: [email protected]

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TOC/ABSTRACT ART

M-A-M configured microchamber

Diffusive sampler

yss

   1 

Dual small chamber

Da

 

  

y0

 

C0

C0

C0

source material

source material

sink material

Microchamber emission test: determine y0

Tube diffusion test: determine y0

Sorption test: determine Dm and Kma

hm

hm Dm

Compared y0

Evaluated y0

18

19

ABSTRACT

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Emission of semivolatile organic compounds (SVOCs) from source materials usually occurs

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very slowly in indoor environments due to their low volatility. When the SVOC emission

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process is controlled by external mass transfer, the gas-phase concentration in equilibrium with

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the material (y0) is used as a key parameter to simplify the source models that are based on solid-

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phase diffusion. A material-air-material (M-A-M) configured microchamber method was

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developed to rapidly measure y0 for a polyisocyanurate rigid foam materials containing

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organophosphate flame retardants (OPRFs). The emission test was conducted in 44 mL

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microchambers for target OPFRs including tris(2-chloroethyl) phosphate (CASRN: 115-96-8),

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tris(1-chloro-2-propyl) phosphate (CASRN: 13674-84-5) and tris(1,3-dichloro-2-propyl)

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phosphate (CASRN: 13674-87-8). In addition to the microchamber emission test, two other 2 ACS Paragon Plus Environment

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types of tests were conducted to determine y0 for the same foam material: OPFR diffusive tube

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sampling tests from the OPFR source foam using stainless-steel thermal desorption tubes, and

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sorption tests of OPFR on an OPFR-free foam in a 53 L small chamber. Comparison of

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parameters obtained from the three methods suggests that the discrepancy could be caused by a

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combination of theoretical, experimental, and computational differences. Based on the y0

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measurements, a linear relationship between the ratio of y0 to saturated vapor pressure

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concentration and material-phase mass fractions has been found for phthalates and OPFRs.

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Keywords: OPFRs, SVOC, chamber testing, mass transfer coefficient, material/air partition

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coefficient, material-phase diffusion coefficient

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INTRODUCTION

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Semivolatile organic compounds (SVOCs) are chemicals with vapor pressures ranging from 10-

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14

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and chemical functional uses including phthalate esters, flame retardants, pesticides, and

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preservatives.1,2 Among the SVOCs, organophosphate flame retardants (OPFRs) have been

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produced globally in large quantities and used extensively in a wide array of commercial

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products such as polyvinyl chloride (PVC) floor coverings, furnishings, textile coatings, plastics,

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and electronic products. 3-6 Because OPFRs are not chemically bonded to product materials, slow

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emission of OPFRs from sources to the environment usually occurs. 4,6,7 Human exposure to

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OPFRs can occur through inhalation of indoor air and suspended particles, dermal absorption,

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and direct ingestion.1,4,8-11 Adverse health effects associated with humans and animals, including

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damage to the reproductive system, carcinogenicity, endocrine disruption, and adverse

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neurodevelopmental effects, have been found for OPFRs such as tris(2-chloroethyl) phosphate

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(TCEP), tris(1-chloro-2-propyl) phosphate (TCPP) and tris(1,3-dichloro-2-propyl) phosphate

to 10-4 atm (10-9 to 10 Pa) at 25 °C.1 SVOCs can be found across a range of chemical classes

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(TDCPP).3,8,12 As a result, the fate and transport of OPFRs and human exposure to these

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pollutants have emerged as a high priority research topic over the years.13

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Researchers have studied the mass transfer mechanisms for SVOCs for years to understand the

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fate and transport of these compounds in indoor environments.14,15 Xu and Little16 developed a

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mass transfer model for SVOC emissions and identified that the emissions of SVOCs are

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controlled by parameters that include the initial material-phase concentration of the SVOC (C0,

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µg/m3), the material-phase diffusion coefficient (Dm, m2/h), the material/air partition coefficient

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(Kma, dimensionless), and mass transfer coefficients across source and sorption surfaces (hm and

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hs, m/h). Later, Xu et al.17 found that for SVOCs with very low volatility, such as di-2-ethylhexyl

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phthalate (DEHP), diffusion within the source material can be ignored and the gas-phase

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concentration in equilibrium with the material (y0) is a key parameter controlling the emissions

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of SVOCs. Notably, three assumptions must be made to use y0 as the key parameter for a source

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material. First, both Dm and Kma are independent of the concentration. Second, the off-gassing of

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the SVOCs is controlled by external mass transfer across the material surface and diffusion

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within the material is negligible. Third, y0 remains constant throughout the emission process,

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which is valid with large partitioning coefficients (e.g., Kma > 108)18 and large initial

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concentrations (e.g., C0 >10% by weight).19 With respect to the emission process only, whether

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the internal material diffusion is negligible is dependent on the Fourier number for mass transfer

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(Fom, dimensionless) and the ratio of Biot number for mass transfer (Bim, dimensionless) to

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Kma:20  

  1 



  2      4

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where t (h) is the time and L (m) is the thickness of the source material. The dimensionless

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number Bim/Kma represents the ratio of internal mass transfer resistance (material diffusion) to

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the external mass transfer resistance (mass transfer across the material surface). Fom represents

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the ratio of a compound’s diffusion rate to its storage rate in the substrate. For instance, if

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Bim/Kma is greater than 35 when Fom equals 10-4, internal diffusion controls the emissions of the

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compounds and external mass transfer is negligible.20 Essentially, the primary goal of published

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studies on characterization of SVOC diffusion were to determine these key parameters.

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Considerable efforts have thus been made to estimate these model parameters.

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Early chamber studies on SVOC emissions were conducted using standard chambers including

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the Chamber for Laboratory Investigation of Materials, Pollution and Air Quality (CLIMPAQ)21

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and the Field and Laboratory Emission Cell (FLEC)21-25 designed for measuring the emissions of

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volatile organic compounds (VOCs). These studies revealed the substantial difficulties

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associated with chamber tests for SVOCs of very low volatility. For instance, due to the strong

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sink effect, it may take up to years for SVOCs to reach steady state, and surface adsorption is

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hard to avoid through the sampling pathways. Xu et al.17 designed a special chamber with a high

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ratio of emission area to adsorption area and successfully measured the emission of DEHP from

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vinyl flooring within a month. Inspired by this chamber design, Liang and Xu26 explicitly

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measured the values of y0 and the stainless steel surface/air partition coefficient for multiple

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phthalates with a multi-inlet-and-outlet improved chamber, which further reduced the test period

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for phthalates to less than a week, with the measured values of y0 ranging from 0.02 to 24.7

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µg/m3 for various vinyl flooring at 25 °C. The specially-designed chambers significantly

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improved the measurements of SVOC emissions over traditional chambers (FLEC and

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CLIMPAQ); however, this design relies on the flexibility and imperviousness of the material to

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form an airtight cavity, which limits its viability for materials that are pervious. Therefore,

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improvements are still needed to apply the specially-designed chamber to various other types of

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materials.

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Cao et al.27 developed an innovative Cm-History method to simultaneously measure y0 and the

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cloth/air partition coefficient for several phthalates. Later, they measured y0 for DEHP emitted

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form PVC flooring using the solid-phase microextraction (SPME) method.28 Recently, Wu et

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al.29 proposed a diffusion-based passive sampling method using standard stainless-steel thermal

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desorption tubes to measure y0 and the stainless steel tube surface/air partition coefficient for

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phthalates. Wu et al.30 further extended their diffusion-based method to measuring the value of

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the surface/air partition coefficient independently for different impervious indoor surfaces and

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found that surface roughness plays an important role in the adsorption process. In contrast to

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previous chamber studies,17,26 the SPME method28 and the diffusion-based tube method29,30 are

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much simpler because these methods do not involve any ventilated space and thus avoid

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considering mass transfer across surfaces. Although these sealed chamber/tube methods are

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highly innovative and effective in determining y0 for source materials, some concerns arise

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regarding the uncertainty of these methods. First and foremost, these methods were developed

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based on the constant y0 assumption and may not be applicable when Bim/Kma is greater than 1

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(both internal and external mass transfer need to be considered). An experiment conducted by Ni

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et al. 31 indicated that the y0 of TCPP for wallpaper samples decreased significantly over the test

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period of 280 days. In a more recent study, Pei et al. 32 observed similar decrease trend of y0

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through a 60-day emission test of TCPP from flexible polyurethane foam. Secondly, these

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methods were only applied to determine y0 for materials containing phthalates; therefore, their

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viability remains unknown for other SVOCs. Thirdly, the distance from the sampling device to

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the test material is important for mathematical calculations and yet remained unclear in the

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methods cited.28 Moreover, all the methods assumed a linear equilibrium surface/air relationship,

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which may not be true as demonstrated in experimental studies21 and the mathematical model.16

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Lastly, these methods have not included porous materials for which the gas diffusion into the

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material needs to be considered. Because of these reasons, there is a need to justify these

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methods for SVOCs other than phthalates and to develop more convenient means to estimate y0

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values for materials. For estimating Dm and Kma in sink materials, Liu et al.13, 33 developed a

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method based on a degree of sorption saturation (DSS) model and characterized the sorption

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properties of polychlorinated biphenyl (PCB) congeners and OPFRs. The sorption test method is

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applicable to various materials, including those with permeable surfaces.

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In this study, three types of tests (microchamber emission test, diffusive tube sampling test, and

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dual small chamber sorption test) have been applied to determine the emission parameters for

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OPFRs. The specific objectives are to 1) develop an improved material-air-material (M-A-M)

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configured microchamber that is self-sealed to rapidly measure the value of y0 for

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polyisocyanurate rigid (PIR) foam containing OPFRs, 2) apply the diffusive tube sampling test

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method and the dual small chamber sorption test method to determine y0 for the PIR foam and

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compare with the y0 values obtained from the microchamber emission test, 3) propose a simple

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and rapid method to estimate y0 values for source materials of SVOCs, and 4) compare the

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advantages and disadvantages of different SVOC testing methods for future research.

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METHODS AND MATERIALS

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Chemicals. Certified TCEP, TCPP and TDCPP calibration standards were purchased from

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AccuStandard Inc. (New Haven, CT, USA). An isotopically-labeled compound, tributyl

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phosphate-D27 (99.5% purity, Cambridge Isotope Laboratories, Inc., Andover, MA) was used as 7 ACS Paragon Plus Environment

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the internal standard on the gas chromatography/mass spectrometry (GC/MS) system. Triphenyl

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phosphate-D15 (98% purity, Sigma Aldrich, St. Louis, MO, USA) was used as extraction

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recovery check standard (RCS). Chromatography-grade methylene chloride (Burdick and

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Jackson, Muskegon, MI, USA) and ethyl acetate (OmniSoly, Billerica, MA, USA) were used as

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solvents in extraction and cleaning without further purification. The solvents were regularly

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analyzed to monitor potential contamination with OPFRs.

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Materials. PIR foam material made by ICL-IP America Inc. (Gallipolis Ferry, WV, USA) was

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used as the OPFR emission source material. The TCEP, TCPP and TDCPP contents in the foam

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material are 2%, 4% and 14% by weight, respectively. The same type of PIR foam material,

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which was also made by ICL-IP America Inc. but free of OPFRs, was used as sorption material

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to measure Dm and Kma for TCEP, TCPP and TDCPP. The thickness of both types of PIR foam

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materials is approximately 4 mm. Prior to the tests, the foam materials were wrapped in

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aluminum foil and stored at room temperature.

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M-A-M Configured Microchamber Emission Test. The microchamber (Markes

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International, Llantrisant, UK) consists of an open-ended cylinder (cup) constructed of

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Silicosteel®-coated stainless steel with a depth of 25 mm, a diameter of 45 mm, and a volume of

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44 mL that was reconfigured as a M-A-M emission chamber. As shown in Figure S1, two pieces

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of foam materials were placed at the bottom and top of the microchamber using double sided

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tapes (the tape was extracted prior to the test and no OPFRs were found within the material).

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Because the microchamber is self-sealed, it does not require the materials to be impervious. Two

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microchambers with identical OPFR PIR foam placed inside were connected in series and

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ventilated with dry clean air. The flow rate through each microchamber was maintained at

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approximately 200 mL/min, resulting in an air change rate of 273 h-1. Measurements were 8 ACS Paragon Plus Environment

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conducted at a temperature of 23 ± 1 °C. The microchambers were ventilated with clean air for

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600 hours during the tests. Polyurethane foam (PUF) (small pre-cleaned certified, Supelco, St.

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Louis, MO, USA) samples were collected at the faceplate of the chamber to monitor the gas-

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phase concentrations of emitted OPFRs.

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Diffusive Tube Sampling Test. Stainless steel thermal desorption tubes (89 mm length, 5

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mm ID, 6.3 mm OD, Markes International, Llantrisant, UK) were used as the diffusive samplers.

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Each tube was pre-packed with 200 mg of Tenax TA by the manufacturer. The diffusion system

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includes two stainless steel cylinders, one standard thermal desorption tube and one stainless

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steel shim. The larger cylinder (5 cm OD × 5 cm L) is designed to hold the tube in a direction

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perpendicular to the test material. To prevent direct contact, a shim (0.127 ± 0.013 mm thickness,

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5.23 mm ID, 7.87 mm OD, Model Number 91182A401, McMaster, Elmhurst, IL, USA) was

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placed between the Tenax tube and test material. The smaller stainless steel cylinder (2.5 cm OD

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× 5 cm length) served as a cap to push the sorbent tube and shim against the material surface.

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The diffusive tube sampling test setup is presented in Figure S2a). Tenax tubes containing

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accumulated OPFRs were collected at different time periods (i.e., 2, 4, 8, 16, 24 h, etc.) during

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the test. More details of the diffusive sampler and diffusive tube sampling procedure can be

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found in Wu et al.29

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Dual Small Chamber Sorption Test. The test was conducted using two 53 L electropolished

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stainless steel chambers, one as the source chamber and the other as the material test chamber.

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Both chambers were connected in series in a temperature-controlled incubator (Model SCN4-52,

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Environmental Equipment Co., Inc., Cincinnati, OH, USA). The chamber design and

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construction followed ASTM Standard Guide D5116-10.34 A 5-cm diameter computer cooling

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fan (Model EC4020, Evercool Thermal Corp., Ltd., Taiwan) was installed in each chamber to 9 ACS Paragon Plus Environment

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provide air mixing in the chamber space. Measurements were conducted at 23 ± 1 °C, 50%

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relative humidity and 1h-1 air change rate. Non-OPFR PIR foam was cut into cylinder buttons

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(average diameter is 1.26 cm). The buttons were then mounted on aluminum scanning electron

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microscope specimen pin mounts (Ted Pella, Inc., Redding, CA, USA) with double-sided tape

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and were secured on rails whose surfaces were saturated with gas-phase OPFRs prior to the test

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(Figure S2b). PUF samples were collected to determine the chamber air concentration, and

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button samples were collected to measure sorption of OPFR on the materials during the test.

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More details of chamber setting and test procedure can be found in previous studies.13, 33

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Sample Extraction and Analysis. After PUF sample collection, each PUF cartridge was

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capped in a glass holder, wrapped in aluminum foil, placed in a sealable plastic bag, and

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refrigerated at 4 °C until analysis. PUF samples were placed in individual 40-mL borosilicate

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glass amber I-Chem™ vials (Thermo Scientific, Waltham, MA, USA) with approximately 35

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mL 1:1 methylene chloride/ethyl acetate (MeCl2/EtOAC) and 25 µL of 20 µg/mL RCS and

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extracted horizontally on the Multipurpose Lab Rotator (Barnstead International Model 2346,

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Thermo Scientific, Waltham, MA, USA) for 1 h. The extract was filtered through anhydrous

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sodium sulfate and further concentrated to approximately 1.5 mL using the RapidVap N2

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Evaporation System (Model 791000, LabConco, Kansas City, MO, USA). The PIR foam and

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material buttons removed from the dual small chamber sorption test were extracted using a

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sonicator (Ultrasonic Cleaner FS30, Fisher Scientific, Pittsburgh, PA, USA) with 10 mL of 1:1

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methylene chloride/ethyl acetate (Fisher Scientific, Pittsburgh, PA, USA), 50 µL of 20 µg/mL

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recovery check standard for 30 min in a scintillation vial. The concentrated extract was then

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transferred to a 5-mL volumetric flask and brought up to volume with rinse solution from the

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concentration tube for GC/MS (Agilent 6890A/5973N GC/MS) liquid analysis followed the 10 ACS Paragon Plus Environment

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method described in Liu et al.33 The Tenax tube samples collected in the diffusive tube sampling

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test were analyzed on a thermal desorber (Markes TD100) and Agilent 6890A/5973N GC/MS

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system. Detailed information on instrumental parameters is provided in Tables S1 and S2 and the

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instrument calibration ranges are listed in Table S3.

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Determination of y0 from M-A-M Microchamber Emission Test. In the microchamber,

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assuming that a boundary layer exists above the chamber surfaces, and that the internal material

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diffusion is negligible, the accumulation of gas-phase SVOC in the chamber obeys the following

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mass balance: 

   −     −  −    −  3 

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where V (m3) is the chamber volume, Q (m3/h) is the ventilation rate through the microchamber,

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y (µg/m3) is the gas-phase SVOC concentration in the chamber, yin (µg/m3) is the inlet gas-phase

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SVOC concentration, A0 (m2) is the total emission area of the top and bottom foam in the

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chamber, hs (m/h) is the mass transfer coefficient across the side wall surface of the

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microchamber, As (m2) is the area of the side wall surface of the microchamber, and ys (µg/m3) is

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the gas-phase SVOC concentration in the boundary layer adjacent to the side wall surface of the

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microchamber in the test. The chamber wall surface-phase SVOC concentration can be

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calculated by 

    −  4 

227

where Ksa (m) is the chamber wall surface/air partition coefficient. At steady state, dy/dt equals

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zero, assuming ys equals y in Equation 3, y0 can be calculated by

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 " 5 

229

where yss (µg/m3) is the steady state gas-phase SVOC concentration in the chamber, which can

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be directly measured using PUF during tests. The value of y0 can be determined directly from

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Equation 5, where value of hm can be estimated by empirical equations based on average air

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velocity.35

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Determination of y0 from Diffusive Tube Sampling Test. The SVOC diffusion model

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developed by Wu et al.29 was applied in this study. In this method, gas-phase SVOCs emitted

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from the source material diffuse into the air in the cylindrical space of a Tenax tube. As the

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SVOC diffuses through the air, adsorption will occur on the inner surface of the Tenax tube. The

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governing equation for the two-dimensional diffusion process using cylindrical coordinates (r,z)

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is $ %, ',  1 $ $ %, ',  $  %, ',   !% "   6 $ $% $'  %

%$239

with the following boundary conditions:

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|*+,   (at the surface of emission source, z = 0)

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|*+,  0 (at Tenax tube surface, z = L)

242



243

where C (µg/m3) is the gas-phase SVOC concentration in the Tenax tube, r is the tube radius and

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z is the height of the cylindrical space of the Tenax tube, Da (m2/h) is the diffusivity of the

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SVOC in air, and Ksa (m) is Tenax tube inner surface/air partition coefficient. A complete

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derivation of this method is detailed in Equations 2 – 12 in Wu et al.29 The values of Da for

./

| .+ *+,

./

  .+ |*+, (at Tenax tube surface)

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different SVOCs can be estimated using SPARC online calculator as in Wu et al.29 or based on

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empirical correlations35 as in this study. With measurement of the SVOC mass sorption in Tenax

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tubes at different time durations, the values of y0 and Ksa can be determined by non-linear

250

regression. The mathematical solutions are obtained numerically using MATLAB (Mathworks,

251

Inc. Natick, MA) in this study.

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Determination of y0 from Dual Small Chamber Sorption Test. When the emission

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process is controlled by the external mass transfer, under the equilibrium condition, y0 is

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assumed to be17  

 7  

255

Therefore, y0 can be determined by measuring C0 and Kma of the source material. C0 can easily

256

be determined through material extraction measurement. In this study, we followed the method

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developed by Liu et al.13,

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coefficient (Dm) can be determined simultaneously. The two parameters were estimated by fitting

259

the DSS model to experimentally measured sorption concentrations. The DSS model is defined

260

as 11 

33

to determine Kma. In addition, the material-phase diffusion

2 2   567 , Θ,  8 2 3    4

2  2 3 × 11  5  ,  ,  , , 4, , 6,  9 261

where M(t) (µg) is the amount of SVOC that has entered the sink material at time t, Mmax (µg) is

262

the maximum amount of the SVOC the sink material can absorb at a given air concentration, Ca

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(µg/m3) is SVOC concentration in the air, A (m2) is the exposed surface area of the sink material,

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δ (m) is the thickness of the sink material, N1 is the dimensionless air change rate, Θ is the 13 ACS Paragon Plus Environment

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dimensionless mass capacity, N (h-1) is the air change rate, Dm (m2/h) is the material-phase

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diffusion coefficient for the chemical, and t (h) is time. In this method, TCEP, TCPP and TDCPP

267

belong to the same chemical class, in which the material/air partition coefficients are related to

268

the vapor pressure (Equation 9 in Liu et al.33) and the material-phase diffusion coefficients are

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related to molecular weight (Equation 10 in Liu et al.33). A more detailed description of the DSS

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model is presented in Liu et al.33 In this study, the nonlinear regression fitting was performed

271

using MATLAB to estimate the diffusion and partition coefficients from the experimental data

272

for TCEP, TCPP and TDCPP. The model fitting was applied simultaneously to the data sets for

273

the three compounds to reduce the number of parameters to be estimated from a single data set.

274

Quality Assurance and Control. A quality assurance project plan (QAPP) was prepared and

275

approved prior to measurements. The GC/MS calibration was verified by the internal audit

276

program. Each batch of samples was analyzed along with its corresponding quality control

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samples. Extraction method blank and field blank samples were prepared and analyzed as well.

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All PUF and material samples were extracted and analyzed with the criteria that the percentage

279

recovery of the recovery check standards had to be within 100 ± 25%, and that the precision of

280

the duplicate samples had to be within ± 25%. When the measured concentrations of OPFRs in

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the PUF sample were above the highest calibration level, the extract was diluted and reanalyzed.

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All Tenax tube samples were analyzed with the criteria that the precision of the duplicate

283

samples had to be within ± 25%.

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RESULTS AND DISCUSSION

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Measurements of OPFRs in PIR Foam. The content of OPFRs in the foam materials was

286

extracted and measured following the previously described sample extraction and analysis

287

procedure. Measurement results of C0, are listed in Table S4. 14 ACS Paragon Plus Environment

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M-A-M Microchamber Emission Test. As shown in Figure 1a and Figure S3, gas-phase

289

concentrations of TCEP and TCPP reached steady state very rapidly during the microchamber

290

test. Gas-phase TDCPP concentrations measured were below the quantification range and

291

therefore are not reported. The average concentrations of TCEP and TCPP in microchamber 1

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after reaching steady state were 5.02 ± 0.54 µg/m3 and 2.02 ± 0.27 µg/m3 (n = 25), respectively

293

(microchamber 2 data is presented in Table S4). The values of y0 for TCEP and TCPP in the

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source material were calculated by Equation 5, and mass transfer coefficients across source

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material surface were determined based on air velocity measured above the surfaces.36 With

296

knowing Ksa for TCEP and TCPP from a previous study,36 we further predicted the gas-phase

297

concentrations in the microchamber following Equations 3 and 4, and the modeling results

298

agreed reasonably well (correlation coefficient (R2) > 0.75) with the measured concentrations

299

(Figure 1a and Figure S3). Input parameters for modeling the microchamber emission tests are

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listed in Table S4.

301

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307 308 309 310 311 312 313 314 315 316

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a)

b)

c)

Figure 1. Measured OPFR concentrations with model fittings. a) in the M-A-M Microchamber 1, b) in diffusive sampling test at Position 1, and c) in the dual small chamber sorption test. A limitation of the specially-designed chamber17 is that the testing material needs to be flat,

317

flexible and impervious to be properly installed in the chamber. The M-A-M configured

318

microchamber inherits the advantage of having a large emission surface to adsorptive surface

319

area ratio (1.80) compared to other traditional chamber tests, as in the specially-designed

320

chamber, and features a self-sealed compartment, which does not require the emission material

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necessary for obtaining y0, and the uncertainty of the calculation is related to the mass transfer

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coefficient across the emission surface, hm (yss, Q and A0 can be measured directly during the

324

test). Although Liang and Xu26 experimentally determined hm for their chamber design using

325

dimethyl phthalate (DMP) as a reference chemical, the method is complicated and difficult to

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apply to other chambers and chemicals. The difficulty of obtaining accurate hm reveals the

327

limitation of the chamber tests for y0 measurements. In this study, we explicitly measured the

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average air velocity in the chamber to represent the air velocities adjacent to the material

329

surfaces and wall surfaces to estimate the mass transfer coefficient. This estimation method is

330

based on empirical equations,35 and its accuracy is greatly dependent on the measurement of air

331

velocity across the material surface and/or the chamber wall surface. In addition, hm directly

332

influences how fast gas-phase OPFR concentrations reach steady state in the microchamber. It is

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noticeable in Figure 1a that the measured TCEP concentration reached steady state faster than

334

the modelling results. One possible reason is that hm may be underestimated using the empirical

335

method. Therefore, more accurate means for determining hm values are needed for future SVOC

336

research.

337

Diffusive Tube Sampling Test. As a comparison, we also determined y0 values of TCEP,

338

TCPP and TDCPP for the identical source material using the diffusive tube sampling test

339

method.29 The test was conducted simultaneously at three different positions of the source

340

material strip (Figure S2a). Therefore, three sets of data were obtained from the test (Figure 1b

341

and Figure S4). Using the method described in Wu et al.,29 we fitted the measured mass

342

accumulation by diffusion at different time durations to determine y0 and the Tenax tube

343

surface/air partition coefficient (Ksa) simultaneously. The average R2 values of the fitting for

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TCEP, TCPP and TDCPP are 0.96, 0.91 and 0.91, respectively. Figure 1b shows that the

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measured mass of TDCPP was the highest among the three compounds in the diffusion test. One

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of the limitations of the diffusion test is the starting value issue associated with the non-linear

347

regression when fitting two parameters simultaneously. Compared with the microchamber

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emission test, which uses the same concept of y0 as the diffusive tube sampling test, the y0 values

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obtained from the latter are lower by 48% - 54% (Table 1). Other potential causes of the

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uncertainties of this method include (1) ignoring the solid-phase diffusion process within the

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source material in the method; (2) assuming a linear adsorption isotherm between the

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concentration in the gas-phase and on the tube surface;29 (3) estimation method of Da; (4) lack of

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airtightness of the tested PIF foam compared to the PVC flooring tested in Wu et al. 29 Further

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research is needed to assess the contribution of each factor to the overall uncertainties of this

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method.

356 357

Dual Small Chamber Sorption Test. The mass accumulation of OPFRs in OPFR-free PIR

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foam over time is shown in Figure 1c. Using the DSS model, we fitted the sorption data set for

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TCEP, TCPP, and TDCPP simultaneously to obtain the values of Dm and Kma in the material

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(Table 1). The application of the DSS method provided good fitting results (R2 > 0.9). The

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values of Dm and Kma estimated in this study are of the same order of magnitude as previous

362

estimates.33 The DSS model improves the starting value issue associated with non-linear

363

regression by linking a class of compounds (TCEP, TCPP and TDCPP in this study) with their

364

vapor pressures and molecular weights. Because of these constraints, the TCEP fitting result is

365

slightly below the measurement results (Figure 1c). Fitting each set of data may provide better

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fitting results but will also sacrifice the advantage of the DSS model in improving non-linear

367

regression. It is notable, however, that this method does not fundamentally solve the issue. Liu et

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al.33 provided a detailed discussion on this issue with the DSS model. The parameters used for

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estimating Dm and Kma in the DSS model are listed in Table S4.

370 Table 1. Parameters obtained from the M-A-M microchamber emission test, the diffusive sampling test, and the dual small chamber sorption test Tests Microchamber emission test a

Parameters µg/m3 y0 (Test 1)

TCEP 8.75

TCPP 3.64

TDCPP N/A

µg/m3

8.11

3.64

N/A

µg/m

3

8.43

3.64

N/A

y0 (Position 1)

µg/m

3

4.10

1.60

4.30

Ksa (Position 1)

m

160

350

550

4.50

1.70

4.40

140

340

620

4.40

1.70

4.50

140

325

560

4.33

1.67

4.40

146.67

338.33

576.67

2.01×10-10 7.76×106 116.47

8.25×10-11 6.85×106 77.85

1.39×10-11 1.90×108 16.26

y0 (Test 2) Average y0

Diffusive sampling test b

Dual small chamber sorption test c

371 372 373 374 375

a. b. c. d.

y0 (Position 2)

µg/m

Ksa (Position 2)

m

y0 (Position 3)

µg/m

Ksa (Position 3)

m

Average y0

µg/m

Average Ksa

m

Dm Kma y0 d

m2/h

3

3

3

µg/m3

Calculated by Eq. 5. Obtained from model fitting following the method described in ref 29. Obtained from model fitting following the DSS model. Calculated by Eq. 7.

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As mentioned previously, the PIR foam material used in the dual small chamber sorption test is

377

identical with the PIR foam material used in the microchamber emission test and the diffusive

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tube sampling test, the only difference being that the former does not contain any OPFRs. It is

379

likely that Dm and Kma for OPFRs are dependent on the level of C0. However, given that the

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OPFRs are additives in the PIR foam, their influence on the physical and chemical properties of

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the tested PIR foam is limited. Moreover, Kma can be considered constant if C0 remains

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effectively constant.

Therefore, we assumed that the values of both Dm and Kma are

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independent of C0 in this dual chamber sorption test method. Following Equation 7, we

384

calculated the value of y0 for the PIR foam (Table 1). The calculated y0 values by Kma from the

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dual small chamber sorption test are over an order of magnitude higher than the values obtained

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from microchamber emission test or the diffusive sampling test for TCEP and TCPP. However,

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the difference between the y0 value calculated by Kma and the value obtained through the

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diffusion test for TDCPP is considerably smaller (less than four times). The dual chamber

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sorption method avoids the y0 concept. Instead, it directly measures Dm and Kma from sorption

390

experiments. Its advantages and disadvantages have been discussed in the literature.

391

in this method was simply calculated by Equation 7, which is a rough estimate for comparison

392

purpose with the assumption that the emission process is controlled by external mass transfer.

393

The discrepancy of y0 values from these different methods could be caused by a combination of

394

theoretical, experimental, and computational differences as discussed in the paper. As mentioned

395

previously, y0 remains constant throughout the emission process if the material/air partitioning

396

coefficient is large (e.g., Kma > 108),18 and the initial concentration is at a high level (e.g., C0

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>10% by weight).19 Among the three compounds, only TDCPP meets these requirements (Kma =

398

1.90×10 and C0 ~ 14%) of using a constant y0 throughout the emission process. Following

399

Equation 1, the calculated values of Bim/Kma for the PIR foam material are 3.43, 8.78 and 1.77,

400

for TCEP, TCPP and TDCPP, respectively (Table S5). The results indicate that the emission of

401

TCEP and TCPP from the PIR foam material is possibly controlled by both internal and external

402

mass transfer, which is also consistent with the observations in the literature. 31, 32 However, Dm

403

and Kma were estimated simultaneously based on the DSS method, which assumes an infinite

404

mass transfer coefficient above the sink materials, and thus the calculated Bim/Kma as well as Fom

13, 31

The y0

8

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values may not be very accurate. Therefore, there is an urgent need to develop an experimental

406

method to determine Dm and Kma independently with reduced uncertainty and improved accuracy.

407

As a reference, we listed the calculation results of Fom and Bim/Kma in Table S5 for SVOCs with

408

available literature data in various indoor materials to determine whether internal (Bim/Kma is

409

much larger than 1), external (Bim/Kma is close to or smaller than 1), or both mechanisms need to

410

be considered.14

411

Relationship between y0, Vp and Material Mass Fractions. It is unfortunate that current

412

experimental approaches26,27,29 all involve model fitting to determine y0 for SVOC source

413

materials, including the microchamber emission test in this study. A more convenient means is

414

needed to rapidly estimate y0 values for target compounds. Although previous studies23 found

415

that the value of y0 for a vinyl flooring material is close to the saturated vapor pressure

416

concentration (Vp, µg/m3) of DEHP at different temperatures, Little et al.10 suggested that y0

417

cannot be well approximated by its corresponding Vp in all cases. Indeed, Liang and Xu26

418

explicitly showed that y0 values of phthalates are lower than their vapor pressures, with a trend of

419

higher material phase concentration (C0) corresponding to higher y0 value. A question whether

420

the value of y0 can be estimated based on C0 and Vp, has been raised. Cao et al.28 performed a

421

nonlinear curve fit on y0 values and mass fractions of DEHP in previous studies and found that

422

there is an exponential relationship between y0/Vp and mass fraction. Although the equation

423

proposed by Cao et al.28 is very useful, its applicability for chemicals other than DEHP remains

424

unknown. Using the available phthalate data from emission26 and diffusive tube sampling tests29

425

from the literature and OPFR data from this study, we examined the relationship between the

426

ratio of y0/Vp and the mass fraction in source materials for various materials. For consistency, the

427

OPFR data used in this analysis were obtained from the microchamber emission test and the

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diffusive sampling test in this study. Interestingly, we found that the ratio of y0/Vp is linearly

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related to the mass fraction at low levels (