Field Calibration of XAD-Based Passive Air Sampler on the Tibetan

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Field calibration of XAD-based passive air sampler on the Tibetan Plateau: wind influence and configuration improvement Ping Gong, Xiao-ping Wang, Xiande Liu, and Frank Wania Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 25 Apr 2017 Downloaded from http://pubs.acs.org on April 28, 2017

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Environmental Science & Technology

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Field calibration of XAD-based passive air sampler on the

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Tibetan Plateau: wind influence and configuration

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improvement

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Ping Gong1,2, Xiaoping Wang1,2*, Xiande Liu3, and Frank Wania4

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Institute of Tibetan Plateau Research, Chinese Academy of Sciences (CAS), Beijing

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100101, China

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Key Laboratory of Tibetan Environmental Changes and Land Surface Process,

CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China

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Chinese Research Academy of Environmental Sciences, Beijing 100012, China

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University of Toronto Scarborough, Department of Physical and Environmental

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Sciences, 1265 Military Trail, Toronto, ON, Canada, M1C 1A4

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* Corresponding Author

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Tel: +86-10-84097120

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Fax: +86-10-84097079

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E-mail: [email protected]

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Word account: text (5000) + 5 figures (5*300=1500) = 6500 1

ACS Paragon Plus Environment


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Abstract

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The passive air sampler based on XAD-2 resin (XAD-PAS) has proven useful for

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collecting atmospheric persistent organic pollutants (POPs) in remote regions.

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Whereas laboratory studies have shown that, due to the open bottom of its housing,

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the passive sampling rate (PSR) of the XAD-PAS is susceptible to wind and other

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processes causing air turbulence, the sampler has not been calibrated in the field at

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sites experiencing high winds. In this study, the PSRs of the XAD-PAS were

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calibrated at three sites on the Tibetan Plateau, covering a wide range in temperature

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(T), pressure (P) and wind speed (v). At sites with low wind speeds (i.e. in a forest

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and an urban site), the PSRs are proportional to the ratio . ⁄ ; at windy sites with

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an average wind speed above 3 m/s, the influence of v on PSRs cannot be ignored.

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Moreover, the open bottom of the XAD-PAS housing causes the PSRs to be

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influenced by wind angle and air turbulence caused by sloped terrain. Field

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calibration, wind speed measurements, and computational fluid dynamics (CFD)

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simulations indicate that a modified design incorporating an air spoiler consisting of 4

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metal sheets dampens the turbulence caused by wind angle and sloped terrain and

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caps the PSR at ~5 m3/day, irrespective of ambient wind. Therefore, the original

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XAD-PAS with an open bottom is suitable for deployment in urban areas and other

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less windy places, the modified design is preferable in mountain regions and other

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places where air circulation is complicated and strong.

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Introduction

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Due to their simplicity, low cost and power-free operation, passive air samplers (PASs)

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have been widely used over the past decades.1-3 They have proven suitable to

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complement conventional high-volume active air sampling (AAS) activities when

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evaluating the global distribution and long-range transport of persistent organic

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pollutants (POPs).1 The challenge to a wider adoption of PASs is the need to obtain

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accurate passive sampling rates (PSRs, m3/day) which are required to convert time-

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integrated amounts of POPs (ng/sampler) into volumetric air concentrations (pg/m3).2

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Given that the Stockholm Convention requires every Conference of the Parties to

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provide comparable monitoring data on the presence of POPs,4 reducing the

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uncertainty of PSRs is essential.3

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Various meteorological conditions, such as temperature, atmospheric pressure, wind

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speed and angle can cause a variation in the rate of POP uptake in a PAS sorption

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medium.3,

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sequestrated by PAS deployed at different sites into volumetric concentrations can be

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expected to introduce considerable uncertainty. Depuration compounds (DCs) are

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commonly added to polyurethane foam (PUF)-disk PAS (PUF-PAS) to obtain PSRs

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that are specific to a location and a deployment period.8-10 The uptake of the sampled

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chemicals is then inferred from the loss kinetics of the DCs.8-10 Although a non-

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negligible kinetic resistance of POPs within the sorption medium (PUF) violates a key

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assumption of this approach,11 it is generally accepted as a practical, albeit expensive

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way to account for differences in PSRs between sites and deployment periods.

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Another commonly used sorption medium in PAS is the polystyrene-divinylbenzene

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resin XAD-2.12An indoor calibration13 found the PSR of a XAD-PAS exposed to

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laboratory-generated windy conditions to be approximately 3-4 times higher than

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under wind-still conditions.13 Field deployments of XAD-PAS in high mountains

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occasionally also reported higher PSRs, which were mainly attributed to high winds.14,

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5-7

Thus, using a single, uniform PSR to convert chemical amounts

In fact, a distinct feature of alpine regions is a wide diversity of climate and surface 3



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cover. For example, there could be tropical, temperate and frigid zones along an

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altitudinal slope, resulting in surface coverage as diverse as forests, meadows and

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glaciers.16, 17 Although PAS have already been used to investigate transport and fate

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of POPs in the European Alps,18,

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Himalayas,16comparing PAS data between and within mountainous areas certainly

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demands careful attention to the influence of climate (temperature; T), elevation

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(atmospheric pressure; P) and complicated wind circulation patterns (planetary wind,

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diurnal valley wind and glacier wind; v) on PSRs. Thus, there is a clear need for a

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systematic field calibration of PASs in a mountain environment.

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The high absorptive capacity of XAD for POPs allows XAD-PAS to be deployed for

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long sampling durations (6~12 months).12, 14, 22 During such long times of deployment,

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according to our experience, the housings of PAS can sometimes become slanted by

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strong winds, causing wind to blow directly into the open bottom of the housing;

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greatly increased wind speeds in the interior of the sampler housing then cause

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elevated PSRs.13, 23Valley winds blowing along mountain slopes may change wind

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angles when they encounter sloped terrain, which may also influence PSRs.14Finally,

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air turbulence in mountain regions frequently arises from inhomogeneous solar

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radiation, which may also exert an effect on PSRs.15 Therefore, modifications to the

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design of the XAD-PAS that can reduce these complex wind effects would be

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valuable.

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In this study, we simultaneously deployed XAD-PAS and AAS at three sites on the

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Tibetan Plateau (TP), the world's largest mountain region. By sampling in a

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mountainous forest, a high altitude city and a high alpine terrain we aimed to test

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whether and how meteorological variations influence the PSRs of the XAD-PAS.

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Specifically, our objectives were to derive empirical relationships for estimating site-

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specific PSRs and to explore the ability of a modified sampler design to minimize the

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influence of wind.

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Materials and Methods

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western Rocky Mountains,20 Andes21 and

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Study regions. The XAD-PAS was calibrated at three sites: Lulang, Lhasa, and Nam

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Co (Figure 1). Lulang (3300 m), located in southeastern Tibet, is covered by forest

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and has a humid and relatively warm climate: Average annual temperature is 5.4°C,

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summer temperatures reach up to 18 °C. Lhasa (3600m), located in a river valley, has

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an average temperature of 7°C. Wind speed in Lhasa (average of 1.6 m/s) is slightly

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higher than in Lulang (1 m/s). Given similar elevation, air pressure is similar in

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Lulang (680 hPa) and Lhasa (650 hPa). Nam Co (4780 m), a truly remote site with

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limited anthropogenic activities in the central TP, is cold and windy. Average wind

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speed is 3.3 m/s and instantaneous wind speeds reach up to 9.9 m/s. Due to Nam Co’s

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high elevation, average temperature (-0.8°C) and air pressure (571 hPa) are low.

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Field calibration of XAD-PAS under varied meteorological conditions. Duplicate

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XAD-PAS were deployed at each site for 2-month periods in summer (Period 1),

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autumn (Period 2), and winter (Period 3). Details for each sampling period are

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provided in the supporting information (SI, Table S1). By using the natural spatial and

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seasonal variation in meteorological parameters (T, P, v), the deployments ranged

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from -11.1 to 16.0°C in T, 565 to 683 hPa in P, and 0.8 to 4.4 m/s in v (Table S2 and

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Figure 2A), which allows for the derivation of relationships between PSRs and these

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factors. Prior to deployment, XAD resin was Soxhlet extracted using in turn methanol,

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acetonitrile, and dichloromethane (DCM). The XAD resin (60 mL of wet XAD in

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methanol) was transferred to a pre-cleaned stainless steel mesh cylinder and dried in a

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clean desiccator. Dry cylinders were sealed in airtight stainless steel tubes with Teflon

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lids. See Wang et al.24 for detailed information about the sampling processes. At all

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three sites, AAS samples were collected for consecutive 2-week intervals during the

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entirety of the three sampling periods, with a final volume of ~600 m3. Polyurethane

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foam (PUF, 7.5 cm × 6 cm diameter) was used to collect gas-phase POPs and

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particles were collected on glass fiber filters (GFF). Before sampling, the PUF plugs

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were pre-cleaned by Soxhlet with DCM for 24 h and the GFFs were heated at 450°C

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for 4 h. All harvested PUFs, GFFs and XAD cylinders were stored at -20 °C until

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extraction. The PSRs of the XAD-PAS (m3/day) was calculated using: 5



=

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(1)

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Where APAS is the amount of a POP sequestered in the XAD-PAS (pg/sample), t is the

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sampling period (days), and Cair is the arithmetic mean of the gas phase

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concentrations of a POP (pg/m3) obtained by AAS during the deployment period of

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the PAS. Given that the XAD-PAS predominantly samples gas-phase POPs,12 data

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obtained from the PUF-plugs in the AAS were used for calibration. AAS data for

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Lulang and Nam Co have been previously published,25, 26 while AAS data of Lhasa

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are provided in Table S3.

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Sample Extraction and Analysis. The XAD samples and PUF plugs were spiked

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with a mixture of surrogate standards (2,4,5,6-tetrachloro-m-xylene, TCmX, and

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decachlorobiphenyl, PCB 209) and Soxhlet-extracted using DCM for 24 h. The

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extracts were concentrated and solvent-exchanged to hexane and then purified on a

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chromatography column (from the top to bottom: 1 g of anhydrous sodium sulfate, 2 g

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of 3% deactivated alumina, and 3 g of 6% deactivated silica gel). The column was

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eluted with 30 mL of a mixture of DCM and hexane (1:1). The eluate was further

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cleaned using gel-permeation chromatography (GPC, containing 6 g of Biobeads

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SX3), and the samples were finally solvent-exchanged and concentrated in 20 µL of

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dodecane containing a known quantity of pentachloronitrobenzene (PCNB) and PCB-

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54 as internal standards. The target compounds in this study are hexachloro-

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cyclohexanes (HCHs, including α-HCH, β-HCH, and γ-HCH), hexachlorobenzene

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(HCB), dichlorodiphenyltrichloroethanes (DDTs, including o,p′-DDT and p,p′-DDT)

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and their degradation products (o,p′-DDE and p,p′-DDE), and selected poly-

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chlorinated biphenyl congeners (PCBs, including PCB-28, -52, -101, -138, -153, and -

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180). POPs were analyzed on a gas chromatograph with an ion-trap mass

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spectrometer (GC-MS, Finnigan Trace GC/PolarisQ) operating in the MS–MS mode.

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A CP-Sil 8 CB capillary column (50 m, 0.25 mm, 0.25 µm) was chosen and helium

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was used as the carrier gas at 1.0 mL min-1 under constant-flow mode. The oven

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temperature began at 100 °C for 2 min and increased to 140 °C at a rate of 20 °C 6


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min-1, to 200 °C (10 min hold time) at a rate of 4 °C min-1, 4 °C min-1 to 300 °C, and

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held for 17 min.

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Quality Assurance/Quality Control (QA/QC). Eight and five field blanks were

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collected for XAD columns and PUF plugs, respectively. Laboratory blanks and field

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blanks were extracted and analyzed in the same way as the samples. None of the

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chemicals was detected in laboratory blanks, but trace amounts of POPs were detected

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in field blanks (SI Table S4 and S5). The limits of detection (LOD, SI Table S4 and

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S5) were derived as the mean blank concentration plus 3 times its standard deviation;

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when a target compound was not detected in the blanks, the concentration of the

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lowest calibration standard was substituted for the LOD. The recoveries were between

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57% and 106% for TCmX and between 63% and 120% for PCB 209. The reported

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values were corrected for field blank levels (i.e. mean blank concentrations were

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subtracted) but not for recovery. Duplicate results, listed in Table S6, indicate that the

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average relative standard deviation (RSD) was mostly less than 30%, suggesting good

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agreement between duplicate PASs. Uncertainties in chemical analysis are discussed

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in Text S1 in the SI.

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Comparison of POPs uptake by XAD-PAS under different modes of deployment

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and in differently sloped terrain. In order to compare PAS deployment on a flat and

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a sloped surface and with a straight and a slanted housing, four sets of XAD-PAS

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(Figure 2B) were deployed in Nam Co, which among the three sites is the windiest

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and the one with the most complicated terrain (Table S2). Site A was flat and site B

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was on a natural slope facing North toward Nam Co lake (Figure 1a); at both sites a

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straight PAS housing (situation 1 and 2 in Figure 2B) and one hanging at a 45° angle

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facing the dominant wind direction (200 °) at Nam Co (situation 3 and 4 in Figure 2B)

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were deployed. In contrast to an earlier indoor study using wind generated with a

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large fan,13 our study represents realistic field conditions.

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Sampler Design Modifications and Wind Influence Test. The design of the XAD-

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PAS housing as described by Wania et al. (design A in SI Figure S1) was modified 7



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with the intention to reduce the influence of wind turbulence in both straight or

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slanted deployment situations. The coarse mesh at the opening of the sampler housing

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was replaced by a series of four stacked spoiler plates (design B in SI Figure S1)

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designed to buffer the wind-driven, direct inflow of air into the housing. The spoiler

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plates consist of metal sheets containing a variable number of round holes (8 mm in

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diameter, 58, 43, 32, and 24 holes from top to bottom, SI Figure S1).

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The efficiency of the spoiler in buffering the wind effect was tested by measuring the

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internal and external wind speeds of the standard and modified XAD-PAS using a

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method described in Text S2 and Figure S2. On the one hand, the gap width (1- or 2-

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cm) between the spoiler plates was optimized to constrain internal wind speed to less

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than ~ 0.1 m/s. On the other hand, the inner wind speed under straight and slanted

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deployments was measured to test if the spoiler can fully eliminate the influence of

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ambient wind turbulence. Similar to the standard XAD-PAS, the modified XAD-PAS

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was deployed on a flat and a sloped surface and with a straight and a slanted housing

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(situation 1-4 in Figure 2C) at Nam Co (windy place). PSRs were observed for the

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modified XAD-PAS and compared with those of the standard XAD-PAS. The

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modified XAD-PAS was also deployed at Lulang, in order to test its performance

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under normal wind conditions.

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Computational Fluid Dynamics Simulations. Computational Fluid Dynamics (CFD)

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has become increasingly popular in environmental technology, especially in cases

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where experimental data are difficult to obtain.27, 28 In this study, CFD simulations

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were performed to assess the wind fields within the sampler housing when the

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sampler is deployed in different environmental settings (forest, urban and mountain)

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with variable ambient wind conditions. Additionally, CFD simulations were also

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performed to investigate how the hanging mode of the sampler and sloped terrain

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affect the wind field inside the PAS, particularly when the outside wind speed is high

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(4.4 m/s in the second sampling period of Nam Co). Thirdly, the inner wind fields of

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the modified XAD-PAS under the complex influence of wind and terrain were also

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simulated. 8


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A two-dimensional domain was selected for the calculations, and the deployment

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height of the sampler was set at 1.5m above ground, as is customary in field studies.

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The domain was selected large enough for the sampler not to influence ambient wind

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conditions. The standard k-ε model is utilized for k (turbulent kinetic energy) and ε

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(rate of dissipation of k) to model continuous phase flow. Coupled equations were

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used to conduct the pressure-velocity coupling and the wall function was applied for

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the surface of the PAS housing. More detailed information on the CFD simulation is

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given in Text S3, Figure S3 and Table S7.

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Results and Discussion

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Measured PSRs. The PSRs recorded at Lulang, Lhasa, and Nam Co are listed in

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Tables S8, S9, and S10, respectively. The average PSR (i.e. the arithmetic mean of the

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PSRs for the 11 analytes) in Lulang during the three sampling periods is relatively

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constant, being 2.8, 2.3 and 2.4 m3/day for summer, autumn and winter, respectively

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(Table S8). Similarly stable PSRs were also observed in Lhasa (Table S9). However,

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the average PSR in Nam Co showed large variation, ranging from 5.2 to 22.6 m3/day

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(Table S10). As mentioned above, the distinct features of Nam Co are high elevation

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(4780 m), low temperature, low air pressure and strong winds. The highest average

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PSR (22.6 m3/day) was measured in autumn when the highest wind speed (4.4m/s)

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was recorded (Table S2 and S10). This suggests that varying meteorological factors

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may impact the uptake in XAD-PAS during field deployments.

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According to the conventional two-film theory, the PSR is proportional to a

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chemical’s diffusivity in air (Dair). Field studies revealed positive correlations

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between the PSR and Dair of a chemical.12, 15 Dair can be estimated using the Fuller,

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Schettler, Giddings equation15:

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. !

" (2)

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Where T is temperature (K), P is the pressure (hPa) and k is a constant. Therefore, the

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PSR should be proportional to T1.75/P. In this study, if we consider PSRs from all 9



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three sites (Table S8-10), the correlation between PSR and T1.75/P is poor (p> 0.05,

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Student’s t test). However, if we only consider the PSRs at Lulang and Lhasa (i.e. the

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less windy places) (Table S8-S9), a positive correlation is observed (p

Field Calibration of XAD-Based Passive Air Sampler on the Tibetan

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