Influence of Air Pollution on Inhalation and Dermal Exposure of

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Ecotoxicology and Human Environmental Health

Influence of Air Pollution on Inhalation and Dermal Exposure of Human to Organophosphate Flame Retardants: A Case Study During a Prolonged Haze Episode Zhiguo Cao, Leicheng Zhao, Yacai Zhang, Meihui Ren, Yajie Zhang, Xiaotu Liu, Jianye Jie, Zhiyu Wang, Changhe Li, Mohai Shen, and Qingwei Bu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b07053 • Publication Date (Web): 08 Mar 2019 Downloaded from http://pubs.acs.org on March 8, 2019

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Environmental Science & Technology

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Influence of Air Pollution on Inhalation and Dermal Exposure of Human to

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Organophosphate Flame Retardants: A Case Study During a Prolonged Haze

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Episode

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Zhiguo Cao,*,†,‡,1 Leicheng Zhao,†,1 Yacai Zhang,† Meihui Ren,† Yajie Zhang,† Xiaotu

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Liu,‡ Jianye Jie,† Zhiyu Wang,† Changhe Li,† Mohai Shen,† and Qingwei Bu*,§

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†

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Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for

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Environmental Pollution Control, Henan Normal University, Xinxiang 453007, China

School of Environment, Key Laboratory for Yellow River and Huai River Water

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‡

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Environment, Tsinghua University, Beijing 100084, China

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§

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Technology-Beijing, Beijing 100083, China

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1 Co-first

Beijing Key Laboratory for Emerging Organic Contaminants Control, School of

School of Chemical & Environmental Engineering, China University of Mining &

authors

1

ACS Paragon Plus Environment


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ABSTRACT

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The health impact of haze is of great concern, but few studies have explored its

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influence on human inhalation and dermal exposure to trace pollutants. Size-segregated

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atmospheric particles (n=72) and forehead wipe samples (n=80) from undergraduates

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were collected in Xinxiang, China, during a prolonged haze episode and analysed for

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ten organophosphate flame retardants (OPFRs). ∑TCPP and TCEP were the most

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abundant OPFR substances in all samples. The arithmetic mean particle-bound and

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forehead OPFR concentrations under a heavy pollution condition (air quality index

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(AQI), 350-550) were 41.9 ng/m3 (∑8OPFRs) and 7.4 μg/m2 (∑6OPFRs), respectively,

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apparently greater than the values observed under a light pollution condition (AQI, 60-

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90) (19.5 ng/m3 and 3.9 μg/m2, respectively). Meteorological conditions played

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distinctive roles in affecting the OPFR occurrence in atmospheric particles (statistically

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significant for TCEP and ∑TCPP) and forehead wipes (excluding TPHP), implying that

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OPFR exposure through inhalation and dermal absorption was synchronously

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influenced by air quality, and OPFRs on the forehead may be mainly absorbed from the

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air. Inhalation contributed dominantly to the total OPFR exposure dose for humans

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when using the relative absorption method to assess dermal exposure, while according

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to the permeability coefficient method, dermal exposure was much more significant

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than inhalation. The results of this study indicate that OPFR exposure should attract

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particular concern in regions with heavy air pollution.

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1.

INTRODUCTION

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As a substitute for polybrominated diphenyl ethers (PBDEs), organophosphate flame

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retardants (OPFRs) have been widely used in a range of products, including textiles,

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furniture, insulation materials, baby products, floor polishes and electronics.1 OPFRs

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are physically (rather than chemically) mixed into original materials and are thus readily

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released into the environment by volatilization and abrasion.2 Some OPFRs,

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particularly those with chlorinated alkyl groups, have low degradation potential and can

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persist in the environment.3,

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environmental matrices, and their occurrence, fate, behaviour and consequent human

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health risk have caused increasing concern in recent years.5-7

4

OPFRs have been detected extensively in multiple

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OPFRs tend to bind to atmospheric particles and resist metabolic breakdown and

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photodegradation.8 One of the significant factors determining atmospheric transport of

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particle-bound contaminants and the associated human health risk is the aerodynamic

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diameter of atmospheric particles.9 Human inhalation exposure to particle-bound

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contaminants is also a function of particle size, and smaller particles are transported

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deep into the human respiratory system and can even enter the bloodstream.10 In recent

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years, relevant studies have generally focused on the occurrence of OPFR in the total

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suspended particles in the air,11 but the particle size distribution patterns of OPFRs in

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the air remain poorly understood.

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While dust ingestion, diet and inhalation are commonly recognized as the main

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OPFR exposure pathways for humans,12 several recent studies have illustrated that

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dermal absorption is also a significant pathway for OPFR exposure.5, 13 In addition, skin 3



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wipes have been found to be an effective method to assess the dermal exposure of

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humans to contaminants.14-16 Xu et al. examined the magnitude of OPFR uptake from

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dermal absorption using hand wipe,17 and Liu et al. reported the variation of OPFR

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dermal absorption from palms, backs of hands, and forearms.18

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To date, investigations on particle-bound OPFRs have been limited to their spatial

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and temporal variations.19,

20

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influencing the contamination characteristics of OPFRs in ambient air and on the human

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skin surface, which has typically been overlooked. Severe haze pollution has frequently

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occurred over China in recent years, and its health impact has caused increasing

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concern.21, 22 With different haze levels, the concentrations of particulate matter in the

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ambient air and meteorological factors, including the height of the atmospheric

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boundary layer, wind speed, humidity, and temperature, are expected to vary greatly,

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with differences of up to orders of magnitude.23, 24 It is unknown whether the variations

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of these parameters would strongly influence the OPFR distribution in ambient air and

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on the human skin surface. Furthermore, while the air quality around the world differs

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considerably, few studies have considered the influence of haze (the metric of haze can

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be PM2.5, PM10 and air quality index (AQI)) when reporting the contamination

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characteristics of trace organic pollutants in ambient air, thus the comparability of data

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from different studies is questionable. Specifically, little is known about the variation

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of OPFR occurrence in ambient air and on human skin under different haze levels. In

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addition, it remains to be clarified whether OPFRs can accumulate in the air

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simultaneously with particulate matter during a haze episode and how haze affects

However, air quality may also be a major factor

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human inhalation and dermal exposure to OPFRs.

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The process and routes of dermal exposure are complex and are currently not well

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understood. Dermal exposure routes of OPFRs may vary among skin locations.

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Comparatively, OPFRs on surface of the exposed skin locations may primarily come

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from the air (absorption of gaseous phase by skin lipid and the deposition of airborne

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particles).25 OPFRs on surface of the covered skin locations may come from both the

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air and clothing. Further, sources of OPFRs on hands are more complex.18 Therefore,

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forehead is a more suitable skin location to reflect the influence of haze on human

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dermal exposure to OPFRs. To the best of our knowledge, however, no study has

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reported OPFR levels on the human forehead.

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The present study addresses these gaps by characterizing OPFRs in size-segregated

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particulate samples from ambient air, and on human forehead surfaces under light and

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heavy haze pollution conditions during a prolonged haze episode. The principal

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objectives of this study are as follows: (1) determine the contamination characteristics

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of OPFRs in atmospheric particles and on the foreheads of undergraduates in Xinxiang,

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China; (2) examine the extent to which haze influences OPFR occurrence and the

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corresponding mechanism; and (3) assess the human inhalation and dermal exposure

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patterns to OPFRs.

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2.

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2.1 Sampling information

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MATERIALS AND METHODS

Atmospheric particles: Particulate samples were collected during a prolonged haze 5



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episode from December 2016 to January 2017. The sampling sites were located on the

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roofs of four university buildings (generally approximately 15 m high) in the Muye

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District of Xinxiang, China. Seventy-two particulate samples (8 batches with 9 size

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fractions in each batch) were obtained through two rounds of sampling processes under

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a light haze pollution condition (with the AQI ranging from 60 to 90) and a heavy haze

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pollution condition (AQI, 350 to 550). Each sample was collected on a Whatman quartz

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fibre filter (preheated for 4 h at 450 °C) with a diameter of 81 mm using an Anderson

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eight-stage cascade impactor (Tisch Environmental Inc., Cleves, OH, USA), and the

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flow rate was controlled at 28.3 L/min. The cut off aerodynamic diameters for each

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stage were > 9.0 μm, 5.8-9.0 μm, 4.7-5.8 μm, 3.3-4.7 μm, 2.1-3.3 μm, 1.1-2.1 μm, 0.7-

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1.1 μm, 0.4-0.7 μm and < 0.4 μm (backup filter), respectively.26 The sampling duration

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was 48 h for the heavy pollution condition and 120 h for the light pollution condition.

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After sampling, the filter samples were wrapped in aluminium foil carefully and stored

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at -20 °C until analysis. Meteorological data, including AQI, PM10, PM2.5, temperature

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and wind speed were recorded during the sampling process in the Supporting

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Information (SI, TableS1).

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Human forehead wipe samples: All samples were collected under normal condition.

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All of the sampling protocols were approved by the Research Ethics Committee of

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Henan Normal University, and all participants gave informed consent prior to providing

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personal information or samples. Similar to former studies, sterile gauze pad (used as

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skin wipe) obtained from a medicine shop was used as sampling matrix to collect

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forehead wipe samples. The forehead surface of a specific participant was wiped thrice 6


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using one surface of a sterile gauze pad, and then wiped for three additional times using

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the other side.18, 27 Eighty forehead wipe samples were obtained through two rounds

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(with the same participants) of sampling processes simultaneously with the collection

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of atmospheric particles from 20 males and 20 females. All of the 40 participants were

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recruited from the undergraduate class at the corresponding campus. We informed the

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participants to keep similar activity patterns between the two rounds of sampling

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activities and not to wash faces at least for two hours before sample collection. More

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detailed information in terms of the sample collection and preparation are provided in

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the SI (Section S2.1).

132 133

2.2 Sample analysis

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Ten OPFRs were analysed, including triethyl phosphate (TEP), tri-n-propyl

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phosphate (TPP), tri-isobutyl phosphate (TIBP), tri-n-butyl phosphate (TNBP), tris-

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(chloropropyl) phosphate isomers (∑TCPP, mixture of 3 isomers), tris-(2-chloroethyl)

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phosphate (TCEP), tris-(2-butoxyethyl) phosphate (TBOEP), triphenyl phosphate

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(TPHP), tris-(1,3-dichloro-2-propyl) phosphate (TDCIPP) and tri-cresyl-phosphate

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isomers (∑TMPP, mixture of 4 isomers). Detailed information on the physical-

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chemical properties of these compounds and the instrumental analysis procedure18, 27

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are provided in the SI (Section S2.2 and Table S2).

142 143 144

2.3 Quality assurance and quality control (QA/QC) The spiked recovery of the sample analysis was determined by spiking 10 ng, 50 ng 7



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and 100 ng of ten standard OPFRs into a quartz fibre filter (n=5) and a forehead wipe

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(n=5), respectively, and analysing using the same method as the samples. One

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procedural blank and one field blank were included for every batch of 8 particulate

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samples or 8 forehead wipe samples. The recovery of triaryl phosphate (TAP) and

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triphenyl phosphate-d15 (TPHP-d15) (surrogate standards) for all samples averaged 89

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± 19% and 93 ± 25% (mean ± SD), respectively. A value of three times of the deviation

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of all blank samples was used as the method detection limit (MDL) for each compound

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detected in blank samples. For compounds undetected in the blanks, a signal of ten

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times of the noise level was used as the MDL (Table S3). More detailed information

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and data on QA/QC are provided in SI (Section S2.3).

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2.4 Data analysis

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Statistical analysis was performed using SPSS statistical software package, version

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17.0 (SPSS Inc.). In the statistical analysis, the concentration below MDL were treated

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as the half value of MDL. Shapiro-Wilk test was used to examine whether the data were

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normally or log-normally distributed. All relevant data were log transformed in case

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their distributions were highly skewed before bivariate comparisons and the level of

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significance was set to p = 0.05 for all statistical tests. Statistical significance of OPFR

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concentrations in particulate and forehead wipe samples between light and heavy haze

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levels was evaluated by a paired-sample t-test. An independent-sample t-test was

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conducted between males and females to test the statistical significance of OPFR

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concentration variation in forehead wipes. A Spearman correlation analysis was used 8


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to explore the correlations between the OPFR concentrations in particulate samples

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(forehead wipe samples) and meteorological parameters.

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3

RESULTS AND DISCUSSION

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3.1 Concentrations, profiles and size distribution of particle-bound OPFRs

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The arithmetic mean concentrations of the sum of ∑TCPP, TCEP, TPHP, TEP,

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TBOEP, TDCIPP, TIBP and TNBP (designated as ∑8OPFRs) in all nine particle

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fractions were 19.5 ± 1.0 ng/m3 (ranging from 18.5 ng/m3 to 20.7 ng/m3) and 41.9 ± 4.1

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ng/m3 (ranging from 38.0 ng/m3 to 47.6 ng/m3) in light and heavy pollution conditions,

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respectively (Figure 1a and Table S4). The OPFR contamination in Xinxiang was much

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lower than that in the e-waste recycling zone of Qingyuan (∑8OPFRs, 130 ± 130 ng/m3)

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and Guangzhou, China (∑8OPFRs, 138 ± 127 ng/m3),19 which was expected and

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consistent with the fact that e-waste recycling zones and metropolitan areas may

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represent prominent OPFR sources. The OPFR concentration under the light pollution

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condition was similar to that in the Baoshan District of Shanghai, China, (∑6OPFRs,

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19.4 ± 10.3 ng/m3)11 but approximately 10 times greater than that in the Great Lakes,

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USA (∑12OPFRs, 2.1 ± 0.4 ng/m3).28

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The mean atmospheric concentration of the chlorinated OPFRs (∑ClOPFRs, sum of

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∑TCPP, TCEP and TDCIPP) was 12.3 ± 0.6 ng/m3 and 34.2 ± 4.4 ng/m3 in light and

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heavy pollution conditions, respectively, accounting for 63.3% and 81.7% of the

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∑8OPFRs (Figure S1a), respectively. Similar results were reported by Yang et al.,26

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Bergh et al.29 and Ren et al.,11 who found that ∑ClOPFRs accounted for 77% (median) 9



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of ∑10OPFRs, 94% of ∑9OPFRs, and 69.0% of ∑6OPFRs in the ambient air,

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respectively. This might be owing to the fact that chlorinated OPFRs had been used

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more widely than non-halogen OPFRs commercially.26, 30

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To the best of our knowledge, this study provides the first comparison of OPFR

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occurrence in atmospheric size-fractionated particles under different air pollution

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conditions. Ratios of OPFR concentration under a heavy pollution condition to that

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under light pollution condition were calculated for individual OPFRs at all four

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sampling sites. Detailed information on the calculation process is described in the SI

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(Section S3.1). Notably, the concentration ratios were apparently greater for chlorinated

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OPFRs (ranging from 0.8 to 3.7) than for non-chlorinated OPFRs (ranging from 0.4 to

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1.7) (Figure 1b), indicating that chlorinated OPFRs can massively accumulate in

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particulate matter during heavy haze pollution condition. Table S5 shows the Spearman

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correlation between particle-bound OPFR concentrations and meteorological

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parameters, including AQI, PM10 (μg/m3), PM2.5 (μg/m3), wind speed (km/h) and

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temperature (°C). In summary, TCEP and ∑TCPP in particulate samples were

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positively (p < 0.01) correlated with AQI, PM10 and PM2.5 levels, but presented

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significant negative correlation (p < 0.01) with wind speed and temperature.

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Conclusively, the contamination of TCEP and ∑TCPP in atmospheric particles was

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more significantly (p < 0.05) affected by haze and the related meteorological parameters

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(Table S6), apparently different from other OPFR constituents. Furthermore, it is

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speculated that the influence of haze on OPFR occurrence in atmospheric particles (as

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well as in forehead wipe samples) is compound-specific because of their different 10


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emission sources and pathways,8 degradation potential31 and physical-chemical

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properties.30 More evidence should be obtained to fully understand the influencing

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mechanism in future.

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According to the size distribution patterns of particle-bound OPFRs (Figure 1c), it is

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clear that OPFRs concentrations in all nine fractions were apparently greater in the

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heavy haze pollution condition than in the light pollution condition. Generally, OPFRs

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in both haze pollution conditions are highly enriched in the 0.7-1.1 μm and 1.1-2.1 μm

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fractions, where ∑ClOPFRs and ∑8OPFRs account for 29.4% and 28.3%, respectively,

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of the total OPFRs in all fractions in the light pollution condition, and 30.4% and 29.0%,

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respectively, of the total OPFRs in all fractions in the heavy pollution condition (Figure

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S2). The abundance of most OPFRs in fine (aerodynamic diameter < 2.1 μm) and coarse

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(aerodynamic diameter > 2.1 μm) particles under both haze pollution conditions were

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approximately equal (Figure S3), representing high tendency to bind to respirable

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particles and potential to be exposed by humans for these OPFRs in atmospheric

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particles. These results are similar to the distribution patterns of atmospheric OPFRs in

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Guangzhou, China,19 but different from those of atmospheric PBDEs32 and polycyclic

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aromatic hydrocarbons (PAHs)33 in Guangzhou, China.

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Mass median aerodynamic diameter (MMAD) is the diameter at which the mass of

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contaminants in all particle fractions are divided into two equal parts and is calculated

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for

231

(http://www.mmadcalculator.com/andersen-impactor-mmad.html).

232

information on MMAD is presented in the SI (Section S3.1). MMAD values of each

individual

OPFRs

with

a

11


MMAD

calculator More

detailed


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OPFR in light and heavy pollution conditions are shown in Figure 1d. For light

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pollution condition, TPHP, TCEP, TDCIPP and TEP had MMADs less than 2.5 μm,

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while the MMADs of other compounds varied from 2.5 μm to 4 μm, except for TIBP

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(the MMAD of which varied from 4 μm to 5 μm). For the heavy pollution condition,

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TPHP, TCEP, TBOEP, TIBP and ∑TCPP had MMADs less than 2.5 μm, while the

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MMADs of TDCIPP, TEP and TNBP varied from 2.5 μm to 4 μm. While the MMADs

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of both TPHP and TCEP exhibited no differences (less than 2.5 μm) between light and

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heavy pollution conditions, those of other OPFRs showed apparent differences between

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light and heavy pollution conditions, indicating for these compounds the particle size

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distribution patterns changed under the influence of haze level. Since smaller particles

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can travel deeper into the human respiratory system and potentially enter the

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bloodstream,34 TPHP, TCEP, TDCIPP and TEP may lead to high human exposure risks

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in the light pollution condition, and TPHP, TCEP, TBOEP, TIBP and ∑TCPP may lead

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to high human exposure risks in the heavy pollution condition.

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The size distribution of atmospheric OPFRs can be correlated to the physiochemical

248

properties of these compounds. A former study reported a significant positive

249

correlation between the MMADs of OPFRs and their vapour pressures.26 However, no

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significant (p > 0.05) positive correlation between the MMADs of atmospheric OPFRs

251

and their vapour pressures in either light or heavy pollution conditions was observed in

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the present study (Figure S4). Similarly, negative correlation between the geometric

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mean diameters (GMDs, a concept similar to MMADs) of OPFRs and their vapour

254

pressures was discovered in the atmosphere at different heights of an e-waste recycling 12


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zone and in urban Guangzhou, China.19 Consequently, in addition to gas-particle

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partitioning, which depends on the vapour pressure of OPFRs, there might be other

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sources of particle-bound OPFRs. As speculated in our previous study, abrasion

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particles or fibres of flame-retarded materials may also contribute to the occurrence of

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OPFRs in coarse particles containing OPFRs.35

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The mean normalized size distribution of atmospheric OPFRs in light and heavy haze

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pollution conditions is shown in Figure 2, indicating there were differences for

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individual OPFRs in terms of particle size distribution patterns. For the light pollution

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condition, TNBP, TIBP, TBOEP and ∑TCPP shared a unimodal distribution pattern,

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with a peak in the 4.7-5.8 μm fraction. TDCIPP, TCEP and TPHP were characterized

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by a bimodal distribution, with two peaks in the 0.7-1.1 μm and 4.7-5.8 μm fractions.

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TEP was characterized by a bimodal distribution, with two peaks in the 2.1-3.3 μm and

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4.7-5.8 μm fractions. For the heavy pollution condition, TEP, TNBP, TBOEP and

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TDCIPP were characterized by a unimodal distribution pattern, with a peak in the 4.7-

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5.8 μm fractions. TPHP, TIBP and TCEP shared a bimodal distribution pattern, with

270

two peaks in the 0.7-1.1 μm and 4.7-5.8 μm fractions. ∑TCPP was characterized by a

271

bimodal distribution, with two peaks in the 2.1-3.3 μm and 4.7-5.8 μm fractions.

272

Overall, the size distribution patterns of OPFRs in atmospheric particles cannot be

273

generalized. These differences in size distribution patterns of OPFRs among different

274

studies can be attributed to the physicochemical properties and source characteristics of

275

these compounds, chemical composition and particle size distribution of the

276

atmospheric particles, as well as meteorological conditions. 13



277 278

3.2 OPFRs in forehead wipe samples, gender variation and implication for dermal

279

exposure route

280

The arithmetic mean concentrations of the sum of ∑TCPP, TCEP, TPHP, TEP,

281

TBOEP and TDCIPP (designated as ∑6OPFRs) in wipe samples were 3.9 ± 0.8 μg/m2

282

(ranging from 2.9 μg/m2 to 5.5 μg/m2) and 7.4 ± 1.6 μg/m2 (ranging from 5.6 μg/m2 to

283

12.4 μg/m2) in light and heavy pollution conditions, respectively (Figure 3a and Table

284

S7). The ∑6OPFR levels in this study were generally less than those on the hands (palms

285

+ backs of hands: 22.7 μg/m2 for ∑3OPFRs), but greater than those on the forearms (3.2

286

μg/m2 for ∑3OPFRs), of participants in Beijing, China.18 Among the OPFRs, ∑TCPP,

287

TCEP and TPHP were the dominant components in both light and heavy pollution

288

conditions, accounting for 36%, 28% and 19% of the ∑6OPFRs, respectively, in the

289

light pollution condition, and 41%, 26% and 15% of the ∑6OPFRs, respectively, in the

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heavy pollution condition (Figure S1b). The OPFR profiles on human foreheads in this

291

study were similar to those observed on human hands18 and in atmospheric particles, as

292

reported by former studies,11, 26 with ∑TCPP, TCEP and TPHP as the most abundant

293

analogues, indicating wide usage of these compounds in China. Limited literature

294

reported that the consumption amount of OPFRs in China reached approximately 70000

295

tons in 2007, and the marketing demand was expected to grow with an annual rate of

296

15%.8, 36 Globally, the usage of OPFRs was 500000 tons in 2011 and was expected to

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reach 680000 tons in 2015.30 With such intensive application, it is suggested that human

298

exposure to OPFRs should cause more concern in the near future. 14


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There were no significant differences for OPFRs (except for TPHP) on foreheads

300

between male and female participants (p > 0.05), but the p-values of TPHP in light (p

301

= 0.04) and heavy (p = 0.03) pollution conditions suggested potential gender-based

302

differences (Table S8). Former studies have investigated OPFR levels on the skin

303

surface without considering the air quality of the sampling sites over time.5, 17, 18 In the

304

present study, the mean concentrations of ∑TCPP, TCEP, TEP, TBOEP and TDCIPP

305

in forehead wipes in heavy pollution condition were all significantly (p < 0.01) greater

306

than those in the light pollution condition, but the p-value (0.06) for TPHP suggested

307

that the influence of haze on dermal exposure to TPHP was not significant (Figure 3b

308

and Table S9). As shown in Table S5, similar with the results for chlorinated OPFRs in

309

particulate samples, most OPFRs (except for TPHP) in forehead wipe samples were

310

positively correlated (p < 0.01) with AQI, PM10 and PM2.5 levels, but wind speed and

311

temperature exhibited negative correlations (p < 0.01) with concentrations of OPFRs

312

except for TPHP. The OPFR profiles in forehead wipe samples were similar with that

313

in particulate samples in the present study, with ∑TCPP and TCEP as the major

314

contributor, accounting for more than 56% and 64% of the total OPFRs in particulate

315

samples and forehead wipe samples, respectively (Figure S1). Nevertheless, TPHP

316

contributed less than 2% to the total OPFRs in atmospheric particles but more than 15%

317

to the total OPFRs in forehead wipes. Nail polish is a specific TPHP source as we

318

know.13 As semi-volatile organic compound, TPHP can volatilize into the ambient air

319

from personal products, and we deduce that there might be higher level of TPHP in the

320

air of females’ dormitories than males’ living environment. Then females’ exposure to 15



321

TPHP might be relatively higher accordingly.37 Further, females’ fingers may contact

322

with forehead on occasion while tidying their hair. Therefore, the application of

323

personal care products (e.g., nail polishes) might be the possible reason for the

324

significant differences for TPHP between genders. Because human forehead directly

325

contacts with the air, and our results indicated that OPFR levels in atmospheric particles

326

and in forehead wipes were synchronously influenced by air quality, it could be

327

concluded that OPFRs on forehead might mainly origin from the air.

328 329

3.3 OPFR exposure doses and comparison between inhalation and dermal

330

absorption pathways

331

Particle size plays a crucial role in human exposure assessment because inhalation

332

exposure to particle-bound OPFRs is a function of particle size. The data on the particle

333

size distributions of OPFRs were used to calculate OPFR fractions that could be inhaled

334

through the nose or mouth (inhalable fraction, IF, %), penetrate progressively into the

335

lung below the larynx (thoracic fraction, TF, %) and even reach deep into the gas

336

exchange region (respirable fraction, RF, %).38 The inhaled particles generally

337

accumulate in three main regions of the human respiratory tract: head airway (HA),

338

tracheobronchial region (TB) and alveolar region (AR). Deposition concentration (DC,

339

ng/m3) is defined as the OPFR concentration potentially deposited in a specific region

340

of the human respiratory tract. Furthermore, the deposition fraction (DF, %) is the ratio

341

of DCTotal (sum of DCHA, DCTB and DCAR) to CTotal (total concentrations of OPFRs in

342

all size-fractionated particles in the air). The daily inhalation dose (DID, ng/kg BW/day) 16


Page 16 of 32

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343

is estimated based on DCTotal (compared with CTotal) and daily inhalation rate (m3/day)

344

of human.19,

345

provided in the SI (Section S3.3).

26, 39

Detailed information on the equations and parameter setting are

346

Overall, the values of inhalable fraction, thoracic fraction, respirable fraction and

347

deposition fraction for individual OPFRs were estimated to be 89.5-93.0%, 83.3-89.7%,

348

50.9-72.6% and 51.9-70.1%, respectively, in light pollution condition, and 89.3-93.7%,

349

84.3-91.3%, 52.0-77.5% and 54.0-69.2%, respectively, in heavy pollution condition

350

(Table S10). The ratios of deposition fraction to inhalable fraction for individual OPFRs

351

ranged from 55.7% to 78.7%, with a mean value of 69.4% in light pollution condition,

352

and from 57.6% to 77.5%, with a mean value of 67.9% in heavy pollution condition

353

(Figure S5).

354

Specifically, the deposition concentrations and fractions of size-fractionated OPFRs

355

in the head airway, tracheobronchial region and alveolar region in light and heavy

356

pollution conditions are shown in Table S11 and S12. The deposition fractions of

357

individual OPFRs in HA, TB and AR of the human respiratory tract were 40.8-59.6%,

358

2.7-3.7% and 7.0-8.7%, respectively, in light pollution condition, and 41.6-58.8%, 3.1-

359

3.6% and 6.9-9.3%, respectively, in heavy pollution condition (Figure 4a and Table

360

S12). The majority of OPFRs were deposited in the head airway (DFHA), averagely

361

accounting for 82.1% and 81.5% of DFTotal (sum of DFHA, DFTB and DFAR) in light and

362

heavy pollution conditions, respectively. Apparently, the deposition fraction of OPFRs

363

in different human respiratory tracts was particle size dependent (Figure 4b and Table

364

S13). With increasing particle size, the deposition concentration of OPFRs increased in 17



365

the HA, remained steady in the TB and decreased in the AR (Figure 4b). Fine particles

366

(particle size < 2.1 μm) were dominant in the alveolar region (60.1% for light pollution

367

condition and 59.7% for heavy pollution condition), while coarse particles (particle size

368

> 2.1 μm) contributed the most in the head airway (77.7% for the light pollution

369

condition and 77.4% for the heavy pollution condition) (Table S13).

370

For adults, Figure S6a and Table S14 depict the total mean DIDDC values (based on

371

DCTotal) of individual particle-bound OPFRs in light and heavy pollution conditions.

372

Chlorinated OPFRs were the main contributors to the total mean DIDDC in both light

373

and heavy pollution conditions. Specifically, the total mean DIDC values of ∑8OPFRs

374

(based on CTotal) in light and heavy pollution conditions were 4.2 ng/kg BW/day and

375

9.0 ng/kg BW/day, respectively, both 1.6 times greater than DIDDC values (2.6 ng/kg

376

BW/day and 5.6 ng/kg BW/day, respectively) (Figure S6a), suggesting apparent

377

overestimations on daily intake dose with bulk OPFR concentrations. Furthermore,

378

DIDDC and DIDC values in heavy pollution condition were 2.1 and 2.2 times greater,

379

respectively, than those in light pollution condition. Comparatively, DIDDC and DIDC

380

values of individual OPFRs for children were all 2.4 times greater than that for adults

381

in both light and heavy pollution conditions (Table S14).

382

Permeability coefficient (Kp) and relative absorption (RA) methods were conducted

383

to calculate daily dermal absorption doses (DAD) of OPFRs in the present study. The

384

Kp method was developed from Fick’s first law of diffusion,40 and the RA method was

385

developed based on the US EPA Exposure Factors Handbook.41, 42 Detailed information

386

on the equations and parameter setting are provided in the SI (Section S3.3 and Table 18


Page 18 of 32

Page 19 of 32

387


S15).

388

For adults, the DAD values for human foreheads, according to the Kp and RA

389

methods, in light and heavy pollution conditions are shown in Figure S6a and Table

390

S16. Chlorinated OPFRs were the dominant contributors to the total mean DAD in both

391

light and heavy pollution conditions. The DADKp and DADRA values of ∑6OPFRs in

392

heavy pollution condition were 1.8 and 1.9 times greater than those in light pollution

393

condition, respectively. Assuming the OPFR contamination on foreheads of children

394

and adults are similar, it is deduced that DAD values of individual OPFRs for children

395

might be 2.1 times greater than that for adults (Figure S7a and Table S16) in both light

396

and heavy pollution conditions, either with Kp method or RA method.

397

Furthermore, according to the DID and DAD data calculated above, the contributions

398

of inhalation and dermal absorption (forehead) to human exposure to OPFRs were

399

compared. DAD values based on the Kp method were approximately 1.5 and 1.2 times

400

greater than DIDDC values in light and heavy pollution conditions, respectively,

401

however, DAD values based on the RA method were approximately 9.3 and 10.3 times

402

less than DIDDC values in light and heavy pollution conditions, respectively (Figure

403

S6a).

404 405

3.4 Health risk assessment

406

The non-cancer risk from inhalation and dermal exposure to OPFRs can be evaluated

407

by the hazard quotient (HQ).18, 43 We used the oral reference dose (RfD) of OPFRs to

408

estimate the health risk because RfD data of OPFRs for inhalation and dermal exposure 19



409

are scarce. Detailed information on the equations and parameters are provided in the SI

410

(Section S3.4 and Table S2).

411

For inhalation exposure of adults, the total mean HQC values of ∑8OPFRs (based on

412

CTotal) in light and heavy pollution conditions were 3.3×10-4 and 9.0×10-4, respectively,

413

which were 1.6 and 1.6 times greater, respectively, than HQDC values (based on

414

deposition concentration, 2.1×10-4 and 5.4×10-4 in light and heavy pollution conditions)

415

(Figure S6b). Furthermore, HQDC and HQC values of ∑8OPFRs for adults in heavy

416

pollution condition were 2.6 and 2.7 times greater, respectively, than those in the light

417

pollution condition. For children, the HQDC and HQC values of individual OPFRs were

418

all 2.4 times greater than that for adults in both light and heavy pollution conditions

419

(Figure S7b and Table S14).

420

For adults’ dermal exposure, the total mean HQKp values for ∑6OPFRs on human

421

forehead (based on the Kp method) in light and heavy pollution conditions were 5.4×10-

422

4

423

calculated by RA method (HQRA: 3.1×10-5 and 5.9×10-5, respectively) (Figure S6b).

424

HQKp and HQRA values in heavy pollution condition were 1.8 and 1.9 times greater,

425

respectively, than those in the light pollution condition. For children, HQKp and HQRA

426

values of individual OPFRs were all 2.1 times greater than that for adults in both light

427

and heavy pollution conditions (Figure S7b and Table S16).

and 9.5×10-4, respectively, which were 17.4 and 16.1 times greater than those

428

Furthermore, for adults, the HQDC of particle-bound OPFRs was compared with the

429

HQRA and HQKp of forehead wipe OPFRs to evaluate the contribution of inhalation and

430

dermal absorption to human health risk (Figure S6c). Specifically, relative to HQRA, 20


Page 20 of 32

Page 21 of 32


431

HQDC was the major contributor to total HQ in light pollution (87.0%) and heavy

432

pollution (90.3%) conditions, indicating inhalation to be the dominant exposure

433

pathway. Nevertheless, HQKp contributed substantially to the total HQ relative to HQDC,

434

accounting for 72.6% of the total risk in the light pollution condition and 63.6% of the

435

total risk in the heavy pollution conditions (Figure S6c).

436 437

3.5 Implications for future studies

438

Influence of haze on human inhalation and dermal exposure to OPFRs was firstly

439

synchronously reported in this study. It is clear that air quality is a crucial factor

440

influencing both inhalation and dermal exposure of humans to OPFRs, and OPFR

441

contamination on human forehead might substantially depend on their distribution in

442

the ambient air, especially for chlorinated OPFRs. As values of meteorological

443

parameters can vary significantly (especially in China) under different sampling

444

conditions, it is recommended that air quality should be considered and labelled when

445

investigating organic contamination in the atmosphere and on human skin surfaces.

446

Without considering air quality, the results and conclusions of relevant studies may

447

suffer from prominent contingencies and poor universality. In addition, in regions and

448

countries with severe air pollution, human exposure to contaminants through inhalation

449

and dermal absorption could be of particular concern. The correlation between OPFR

450

pollution in the air and human dermal exposure, as well as the corresponding

451

mechanism are in need to be explored and verified in the near future.

452 21



453

■ ASSOCIATED CONTENT

454

Supporting Information: The Supporting Information is available free of charge on

455

the ACS Publications website at DOI:

456 457

The SI contains additional detailed information on chemicals, materials, and instrumental analysis and some additional tables and figures, as noted in the text.

458 459

■ AUTHOR INFORMATION

460

Corresponding author

461

*Phone: +86-373-3325971, Fax: +86-373-3325971. E-mail: [email protected]

462

(Zhiguo Cao)

463

* Phone: +86-10-62339298, Fax: +86-10-62339298. E-mail:

464

[email protected] (Qingwei Bu)

465

ORCID

466

Zhiguo Cao: 0000-0002-8580-3368

467

Leicheng Zhao: 0000-0002-9846-5126

468

Xiaotu Liu: 0000-0002-3698-019X

469

Author contributions

470

Zhiguo Cao and Leicheng Zhao contributed equally to the study and should be regarded

471

as joint first authors.

472

Notes

473

The authors declare no competing financial interest.

474

Ethics 22


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Page 23 of 32


475

Ethical approval for this investigation was obtained from the Research Ethics

476

Committee of Henan Normal University.

477 478

ACKNOWLEDGEMENTS

479

This work was supported by National Natural Science Foundation of China (21607038,

480

21806030), China Postdoctoral Science Foundation (2016T90668, 2015M570629),

481

Open Fund of State Key Laboratory of Environmental Chemistry and Ecotoxicology,

482

Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences

483

(KF2015-09, KF2017-01), Science Foundation (2016PL14, 20180572) of Henan

484

Normal University and Key Scientific Research Project Plan of Henan Province

485

(16A610002, 17A610007). We thank the participants for their active involvement and

486

support for this study.

23



487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529

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605

Figure captions

606

Figure 1. Concentrations, size distribution and MMAD (mass median aerodynamic

607

diameter of OPFRs) of OPFRs in light and heavy pollution conditions in particulate

608

samples.

609 610

Figure 2. Mean normalized size distribution of particle-bound OPFR analogues in light

611

and heavy pollution conditions.

612 613

Figure 3. OPFR concentrations and ratios between heavy and light pollution conditions

614

in forehead wipe samples.

615 616

Figure 4. (a): Deposition fraction (DF) of size-fractionated OPFRs in the head airway

617

(HA), tracheobronchial region (TB) and alveolar region (AR) of the human respiratory

618

tract in light and heavy haze pollution conditions; (b): Total mean contribution of size-

619

fractionated OPFR deposition concentrations (DC) in the three areas of human

620

respiratory tracts. ∑ClOPFRs is the sum of TDCIPP, TCEP and ∑TCPP; DFTotal is the

621

sum of DFHA, DFTB and DFAR.

27



622 623

Figure 1

28


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Page 29 of 32


624 625

Figure 2

29



626 627

Figure 3

30


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628 629

Figure 4

31



630

TOC Art

631

32


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Influence of Air Pollution on Inhalation and Dermal Exposure of

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