Diurnal variations of atmospheric polycyclic aromatic hydrocarbons (PAHs) during three sequent winter haze episodes in Beijing, China

Science of the Total Environment 625 (2018) 1486–1493

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Diurnal variations of atmospheric polycyclic aromatic hydrocarbons (PAHs) during three sequent winter haze episodes in Beijing, China Rong Cao a,b, Haijun Zhang a,⁎, Ningbo Geng a, Qiang Fu c, Man Teng c, Lili Zou a, Yuan Gao a, Jiping Chen a,⁎ a b c

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China University of Chinese Academy of Sciences, Beijing 100049, China State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing, 100012, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Effect of haze occurrence on atmospheric PAH distribution was investigated in Beijing winter. • Evident diurnal variation of atmospheric PAH distribution was observed during haze episode. • Atmospheric Σ18PAHs negatively correlated with the planetary boundary layer heights. • The levels of atmospheric PAHs were significantly higher during haze episode nighttime.

a r t i c l e

i n f o

Article history: Received 4 September 2017 Received in revised form 28 December 2017 Accepted 29 December 2017 Available online xxxx Editor: Jianmin Chen Keywords: Polycyclic aromatic hydrocarbons Haze Meteorological variables Gas–particle partitioning

a b s t r a c t Gas- and particle-phase concentrations of 18 atmospheric polycyclic aromatic hydrocarbons (PAHs) were respectively measured during daytime and nighttime at an urban site of Beijing around the New Year's Day of 2015. The average concentration of total atmospheric PAHs (Σ18PAHs) during three haze episodes (PM2.5 N 75 μg/m3) was 1473.1 ng/m3, which was 2.6 times higher than that (405.1 ng/m3) during normal periods (PM2.5 b 75 μg/m3). Significant diurnal variations in the Σ18PAH concentrations, homologue pattern and gas– particle partitioning were observed during haze episodes. There was a significantly negative correlation between Σ18PAH concentrations and planetary boundary layer heights. During haze episodes, PAHs in daytime atmosphere should mostly originate from the vehicle emission, while the main sources shift to coal combustion in the nighttime. The gas–particle distribution behavior of PAHs was decisively affected by air temperature and relative humidity, and generally simulated by Junge–Pankow model. During haze episodes, the average benzo[a]pyrene equivalent concentration of atmospheric PAHs in the nighttime were 0.7-fold higher than that in the daytime, indicating that people staying out more during haze episode nighttime would pose a considerably higher cancer risk for inhalation exposure to PAHs. © 2017 Published by Elsevier B.V.

1. Introduction

⁎ Corresponding authors. E-mail addresses: [email protected] (H. Zhang), [email protected] (J. Chen).

https://doi.org/10.1016/j.scitotenv.2017.12.335 0048-9697/© 2017 Published by Elsevier B.V.

The frequent occurrence of haze pollution poses a severe problem to East China especially in the winter heating season (Huang et al., 2014; Fu and Chen, 2017). The concentrations of fine particle often reached to several hundred micrograms per cubic meter (μg/m3) during the

R. Cao et al. / Science of the Total Environment 625 (2018) 1486–1493

haze events occurred around many Chinese megacities (Elser et al., 2016). The average PM2.5 concentration during the winter period from November 2014 to March 2015 was 96 μg/m3 in Beijing, which was 9.6 times the World Health Organization (WHO) safe level of 10 μg/m3, and 1.3 times the severe pollution level (75 μg/m3) of National Ambient Air Quality Standards of China (NAAQS, 2012). Aerosol particles especially fine particle contain a large number of toxic substances such as heavy metals, bacteria, virus and highly toxic organic compounds (Huang et al., 2014). Polycyclic aromatic hydrocarbons (PAHs) are the principal toxic organic contaminants in the atmosphere, and their inhalation has been confirmed to pose an excess risk of lung cancer, male semen quality, and DNA damage (Zhang et al., 2009; Wang et al., 2011; Pieterse et al., 2013; Yang et al., 2017; Yue et al., 2015). In view of the elevated PAH concentration during haze weather condition (Gao et al., 2016), inhalation exposure to the hazeassociated PAHs has raised a health concern in Beijing (Hong et al., 2016; Chen et al., 2017). Many studies have reported the source, pollution levels and distribution of atmospheric PAHs in Beijing. Atmospheric PAHs in Beijing showed an evident seasonal variation, characterized with remarkably higher concentration in winter (Jiang et al., 2009; Zhang et al., 2009; Tang et al., 2017). During the heating season, PAHs were mainly locally generated from the incomplete combustion of coal, gasoline, diesel, plant and animal matter, and natural gas (Liu et al., 2007; Zhang et al., 2009; Wu et al., 2014). Regional transport of pollutants also contributed considerably to the concentrations of atmospheric PAHs in Beijing (Inomata et al., 2012). The main urban environments with heavy traffic often exhibited higher pollution levels of atmospheric PAHs (Li, Y., et al., 2017). Meteorological conditions were significantly different between haze weather and normal weather. Meteorological conditions under haze weather are usually characterized by the high humidity, low wind speed, low irradiation, and a significant two-way feedback between fine particle and boundary layer evolution (Li, J., et al., 2017). Meanwhile, secondary inorganic species were demonstrated to be the major contributor to severe haze (Sun et al., 2014). These significant variations in meteorological conditions and particle composition not only affect the levels of atmospheric PAHs but also influence their partition between gas- and particle-phase (Alam et al., 2015; Elorduy et al., 2016). On the other hand, PAHs played an essential role in the formation of secondary organic aerosol. Gaseous PAHs could easily be depleted by oxidizing species (ozone, OH radical and NOx) under solar radiation especially ultraviolet light to form oxygenated organic matter, which could instantly generate particle nucleation (Keyte et al., 2013; McWhinney et al., 2013; Friedman et al., 2014). However, knowledge is still inadequate to better elucidate the mechanism underlying the effect of haze occurrence on atmospheric PAH distribution. The evident diurnal variation in the meteorological factors, such as ambient temperature, wind speed, relative humidity, turbulent mixing and the depth of the atmospheric boundary layer, usually take place during the winter time of Beijing (Lin et al., 2011; Zhao et al., 2009). Thereby, the levels and sources of atmospheric PAHs as well as the levels and particle density of PM2.5 in the urban environment might also undergo the significant diurnal fluctuations (Liu et al., 2015; Zhao et al., 2009; Elorduy et al., 2016; Zhang et al., 2012; Gu et al., 2010). These simultaneous diurnal variations certainly contain information about the interactions between atmospheric PAHs and haze aerosols. In this study, the mass concentrations of gaseous and particulate PAHs in the daytime and nighttime were respectively measured at a main urban site of Beijing during three sequent winter haze episodes. This study aimed at characterizing the variations in levels and gas–particle partitioning of atmospheric PAHs during the transition from normal period to haze episode, and further to explore the mechanism underlying the effect of haze occurrence on atmospheric PAH distribution. The obtained results could also be helpful to assess the inhalation exposure risk of PAHs during haze weather.

1487

2. Material and methods 2.1. Chemicals All deuterium-labeled PAH standards were purchased from Cambridge Isotope Laboratories, Inc. (Andover, MA). The stock internal standard solution contained 16 deuterium-labeled PAHs (Table S1). Two kinds of deuterium-labeled PAHs, 2-methylnaphthalene-d10 and pterphenyl-d14, were used as injection standards. The native PAH standard solution (610 PAH Solution) obtained from o2Si (USA) contained 18 PAH congeners (Table S1). Dichloromethane (DCM) and n-hexane were both in pesticide residue grade and purchased from Honeywell Company Inc. (USA). 2.2. Sampling Atmospheric PAHs were sampled in a stationary station (40°2′51.8″ N, 116°25′29.7″ E) within the urban area of Beijing. The sampling station is established on a building rooftop approximately 15 m above ground level with a mixed-use neighborhood including schools, supermarkets, and residence around. The sampling building located between the north third and fourth ring road of Beijing, 200 m west of northsouth running G6 Highway and 50 m south of Beitucheng West Road (east to west). The nearest crossroad with a distance of 100 m had moderate vehicular traffic (b 10 thousand vehicles per day). Thus, main sources of PAHs in the sampling area were considered to be industries emissions, household cooking and road transport. A high volume sampler (TCR TECORA, Italy) was used to collected particle and gas samples, with a sampling flow rate of 200 L/min. Two independent pairs of particle and gas samples were collected during the daytime (8 a.m. to 8 p.m.) and nighttime (8 p.m. to 8 a.m.) for each day. Quartz fiber filters (Whatman QMA, Φ 97 mm) were used to collect aerosol particles. Prior to sampling, all filters were cleaned by baking in a muffle furnace, and polyurethane foam (PUF) plugs were cleaned by solvent extraction. A total of 22 pairs of particle and gas samples were obtained through the measurements performed from 8 a.m. on 25th December 2014 to 8 a.m. on 5th January 2015. After collection, the filter and PUF samples were sealed by aluminum films, placed in cleaned polyethylene bags with zippers, and then stored at −20 °C. 2.3. PAH analysis Particle-phase PAHs deposited on the quartz fiber filters and the gasphase PAHs adsorbed by the PUF plugs were Soxhlet-extracted with nhexane/DCM (1:1, v/v), respectively. Prior to extraction, a surrogate mixture consisting of 16 deuterium-labeled PAHs were spiked. The extract was concentrated to approximately 0.2 mL, filtered through a polytetrafluoroethylene membrane (pore size: 0.22 μm, Jinteng of China), and then transferred to a vial. The final extract was spiked with the injection standards and finally submitted to instrumental analysis. The determination of PAH was conducted with a gas chromatography-mass spectrometer (GCMS-QP 2010, Shimazu) equipped with a DB-EUPAH gas capillary column (30 m × 0.25 mm i.d. × 0.25 μm film thickness, Agilent Technologies) in electron impact (EI) mode. Helium was used as the carrier gas at a flow rate of 1.5 mL/min and the injector was operated in the splitless mode at 280 °C. The GC oven temperature program was as follows: 60 °C, held for 1 min, increased to 210 °C at a rate of 15 °C/min, and increased to 310 °C at 3 °C/min, held for 10 min. The electron impact (EI) ion source was operated at 70 eV and 220 °C. A total of 18 PAH compounds were quantified (Table S1). All of the glassware was rinsed in triplicate with n-hexane before use. Strict quality control procedures were taken to minimize artifact and contamination through the whole analysis procedure with simultaneous analysis of field and laboratory blanks. The procedural blanks

1488

R. Cao et al. / Science of the Total Environment 625 (2018) 1486–1493

spiked with a small quantity of PAH standards were used to determine the method detection limits (MDL), which was defined as triple standard deviation at 6 time measurement, in the range 0.001–0.05 ng/m3 for all monitored PAHs. The recoveries of deuterium-labeled PAH standards in all of the samples were in the range of 67%–130%. The concentrations of PAHs in the blank samples were measured to be close to the MDL levels, which were 3–5 orders of magnitude lower than those in the atmospheric samples. Therefore, correction by the field blanks was not conducted. 2.4. Meteorological and air pollution parameter collection Atmospheric conditions containing wind speed (WS), wind direction (WD), ambient temperature (T), pressure, humidity and precipitation were real-time recorded using CAMS620\\HM (Huatron, China). The levels of particle with aerodynamic diameter lower than 2.5 μm (PM2.5) and 10 μm (PM10) were simultaneously measured by two automatic monitors TEOM 1405-F (Thermo Fisher Scientific Inc. the USA), respectively. The Thermo Scientific™ series analyzers (Thermo Fisher Scientific Inc. the USA) were used for the online monitoring of gaseous pollutants, including CO, SO2, NO/NO2/NOx and O3. The data of planetary boundary layer (PBL) height was received from the Global Data Assimilation System (GDAS) reanalysis global meteorological data. 3. Results and discussion 3.1. Formation and evolution of three sequent haze episodes Primary atmospheric pollutant in Beijing during the sampling period was PM2.5, which constituted about 45%–78% of PM10 mass. This ratio increased when PM2.5 pollution became worse (Fig. 1). Here, a haze episode was defined as a set of continuous period with PM2.5 exceeding 75 μg/m3 (NAAQS, 2012). In general, three haze episodes were identified: period from morning of December 25 to 8 a.m. on December 28 (Haze episode 1), nighttime of December 28–29 (Haze episode 2), and period from 8 p.m. on January 2 to morning on January 5 (Haze episode 3). The highest PM2.5 concentration was measured in the nighttime of December 27–28 (248.6 μg/m3). The average PM2.5 concentration was 196.5 μg/m3 during three haze episodes, which were 3.4-fold higher than that (43.9 μg/m3) of normal periods (PM2.5 average: b 75 μg/m3). The lowest PM2.5 concentration (8.0 μg/m3) was observed in the nighttime of December 30. The relative humidity was significantly higher during the haze episodes (47.0 ± 2.6%) than the clear period (28.0 ± 1.3%) (P b 0.001) (Fig. 1). The concentrations of gaseous pollutants SO2, NOx and CO simultaneously elevated with the increase of PM2.5 concentration, whereas O3 concentration presented an opposite trend with PM2.5 concentration (Fig. 1).

Fig. 1. Variations of particulate matter concentrations together with main meteorological and typical air pollution parameters during the sampling period (HE: haze episode).

elevated levels of atmospheric PAHs during haze periods especially the nighttime. During a diurnal cycle, the PBL height was typically shallow in the nighttime of Beijing winter due to the strong near-surface stability.

3.2. Concentration variations of total atmospheric PAHs As shown in Fig. 2, the evolution of PAH pollution coincided with the haze occurrence. A significantly positive correlation (P b 0.01, r = 0.874) was perceived between the atmospheric concentrations of total PAHs (Σ18PAHs) and PM2.5 concentrations (Table S2). The average atmospheric concentration of Σ18PAHs during haze episodes (1473.1 ng/m3) was 2.6 times higher than that (405.1 ng/m3) during normal periods. The measured atmospheric concentrations of Σ18PAHs during haze episodes were similar to those (88.4–1907.3 ng/m3) reported earlier in Beijing area and Tianjin city (nearby Beijing) during winter haze days (Jin et al., 2017; Elser et al., 2016). When haze events occurred, the levels of atmospheric PAHs showed an obvious diurnal variation. The atmospheric concentrations of Σ18PAHs during nighttime of haze episodes were 0.4–0.9 folds higher than those measured during subsequent daytime. The Σ18PAHs concentrations increased dramatically with the reducing PBL height (Table S3), suggesting the shallow PBL heights should be mainly responsible for the

Fig. 2. Diurnal variation in atmospheric concentrations of total PAHs (Σ18PAHs) during the sampling period (HE: haze episode).

R. Cao et al. / Science of the Total Environment 625 (2018) 1486–1493

3.3. PAH composition profile and source apportionment In order to understand the mechanism underlying the relationship between haze occurrence and atmospheric PAH pollution, principle component analysis (PCA) was performed on the atmospheric concentrations of 18 PAH compounds. In the PCA score plot, the first component (PC1) discriminated haze episodes from normal episodes (Fig. 3). Except the daytime sample of December 28, all haze episode samples had the negative scores on PC1 explaining the relatively high concentrations of 3-ring PAHs, whereas all normal period samples showed the positive scores on PC1 mainly due to the relatively high concentration of 2-ring PAH NAP (Figs. S1 and S2). Moreover, the second component (PC2) discriminated haze episode daytime from haze episode nighttime. The daytime samples of haze episodes also had the relatively high concentrations of NAP, and thus they showed the negative scores on PC2 (Figs. S1 and S2). The 3- and 4-ring PAHs with higher volatility potential can be transported in the longer range compared with 5- and 6-ring PAHs, and thus the ratios of 3- and 4-ring PAHs to 5- and 6-ring PAHs (PAHs (3, 4)/PAHs (5, 6)) are often used to identify the geological origin of atmospheric PAHs. The lower value suggested local emission sources rather than long range transport (Halsall et al., 2001; Kong et al., 2015). In this study, the ratios of PAHs (3, 4)/PAHs (5, 6) in the atmosphere of Beijing winter ranged from 2.1 to 6.8 during the whole sampling period (Table S4), which were much lower than those (9.5–28.7) in the remote sites far away from the urban and emission fresh areas (Hou et al., 2006; Tan et al., 2011; Liu et al., 2013; Alam et al., 2014; Mulder et al., 2014). Dispersion rate of air pollutants usually became lower when haze events occurred, and thus most of atmospheric PAHs during haze episodes inevitably originated from the local emission sources. However, the ratios of PAHs (3, 4)/PAHs (5, 6) in haze episode atmosphere were not significantly different from those in normal period atmosphere. The variation of NAP level with the atmospheric dispersion condition was further investigated. The relative contents of atmospheric NAP were found to be much higher (N15%) under the better dispersion condition characterized by higher PBL height (N180 km) and higher wind speed (N 6 m/s), Moreover, it was found that the relative contents of atmospheric NAP exhibited a logarithmic increase with the increase of PBL height (Fig. S3). These results indicated the long-range transport

1489

made a higher contribution to the atmospheric NAP in Beijing under the better dispersion condition. During normal periods, the distribution profiles of PAH compounds in daytime atmosphere were almost similar to those in nighttime atmosphere (Fig. 4). However, an obvious diurnal variation was observed for the PAH homologue pattern during haze episodes. Compared with the daytime samples of haze episodes, the relative contents of total 4- and 5-ring PAHs in the nighttime samples of haze episodes were significantly (P b 0.05) increased, while the relative contents of NAP with 2 rings in the nighttime samples were significantly (P b 0.01) decreased (Fig. S3). The elevated NAP loading in the daytime atmosphere of haze episodes evidently originated from the long-range transport (Table S4). However, the significant diurnal variation in distribution profile of PAHs with 3- to 6-rings during haze episodes should mainly result from the diurnal differences in local emission sources. In addition, the diurnal variation of PAH distribution profile might be partly attributed to the degradation of some PAH species with oxidative species (Butler and Crossley, 1981; Liu et al., 2013). During the sampling period, the contents of O3 and NOx both exhibited an obvious diurnal variation (Fig. 1). The emission sources of atmospheric PAHs were identified according to the diagnostic ratios of PAH compounds. The average ratios of FLA/ (FLA + PYR), ANT/(ANT + PHE) and BaA/(BaA + CHR) in all samples were larger than 0.5, 0.1 and 0.35, respectively (Table S4); indicating a predominant influence of combustion (Zencak et al., 2007; Li and Kamens, 1993; Manoli et al., 2004; Mirante et al., 2013). Values of IcdP/(IcdP + BghiP) for the emissions from the combustion of gasoline and coal were measured as 0.18 and 0.56, respectively (Gogou et al., 1996; Kavouras et al., 2001; Ravindra et al., 2008). In this study, The values of IcdP/(IcdP + BghiP) in the atmosphere of Beijing winter were in the range of 0.44–0.50 (average: 0.46) (Table S4), implying that fossil fuel burning and traffic emission were both major sources of atmospheric PAHs of Beijing winter. During haze episodes, the relative contents of two 3-ring PAHs FLU and PHE in the daytime atmosphere were significantly higher than those in the nighttime atmosphere (Fig. 4). The higher loading of these two 3-ring PAHs in the daytime atmosphere should result from the heavier traffic during daytime. Vehicle emission from gasoline and diesel combustion has been reported to have a high loading factor for FLU and PHE (Ho et al., 2009). The distribution profiles of PAH compounds in daytime atmosphere were found to resemble with those monitored in the traffic tunnels (Fig. S4) (Wu et al., 2014), which further verified the higher contribution of vehicle emission to the atmospheric PAHs in daytime atmosphere. Compared with the daytime atmosphere of haze episodes, the relative contents of PYR, BaA, CHR, BjF, BkF, BeP and BghiP in the nighttime atmosphere of haze episodes were significantly higher (Fig. 4). The higher factor loading of CHR, BkF and BghiP have been proposed for their origin from coal combustion (Gao et al., 2011; Zhang et al., 2008). Therefore, coal combustion was deducted to contribute more to atmospheric PAHs during nighttime. 3.4. Gas–particle partitioning of PAHs

Fig. 3. PCA score plot for PAH compounds in atmospheric samples collected during different periods.

As shown in Fig. 2, the concentrations of Σ18PAHs in gas-phase were obviously higher than those in particle phase during most of the sampling period, whereas 3 sample pairs collected during period from 8 p.m. on January 1 to 8 a.m. on January 3 (new year holiday) had much lower ratios (b 0.5) of gas-phase Σ18PAHs to particle-phase Σ18PAHs mainly due to the extremely low concentrations of NAP in gas-phase (1.2–2.0 ng/m3). The decreased gas-phase concentrations of NAP should mainly result from the remarkable decrease of industrial activities around the Beijing urban during New Year holiday. Except these 3 sample pairs, the relationship between the ratio of gas-phase Σ18PAHs to particle-phase Σ18PAHs (K) and the ambient air temperature (T, absolute temperature) could be described with an Arrhenius equation, this result indicated the decisive effect of air temperature on the gas– particle partitioning of PAHs (Fig. 5).

1490

R. Cao et al. / Science of the Total Environment 625 (2018) 1486–1493

Fig. 4. Distribution profiles of individual PAH compounds in the atmospheric samples collected during different periods. ⁎ and ⁎⁎ indicated the significant difference at 0.05 level and 0.01 level, respectively.

The distribution profiles of PAH compounds were evidently different between gas-phase and particle phase. The predominant PAHs in gasphase were 3-ring compounds, whereas the dominant species in the particle phase were 4- and 5-ring PAHs (Fig. S5). During haze episodes, the significant diurnal variations in the distribution profiles of PAH compounds were observed in both gas and particle phases. The relative contents of NAP and ANT showed the most significant (P b 0.01) diurnal variations in gas-phase of haze episodes, while the larger diurnal variations were observed for the relative contents of PHE, FLA, BaA and BeP in particle phase of haze episodes (Fig. S6). In order to further understand how different PAH compounds distribute themselves between the gas and particle phases during different weathers, the gas–particle partitioning coefficient Kp (m3/μg) of each PAH compound was calculated (SI), the larger KP value indicated a higher capacity of a certain PAH compound to sorb to atmospheric particulate matter. In this study, the calculated values of log KP for 8 PAH compounds with higher volatilities, including NAP, ACY, ACE, FLU, PHE, ANT, FLA and PYR, were significantly (P b 0.05) larger during

Fig. 5. Correlation between the ratio of gas-phase Σ18PAHs to particle-phase Σ18PAHs (K) and the ambient air temperature (T, absolute temperature). A is the pre-exponential factor, Ea is the activation energy for the adsorption, and R is the universal gas constant.

normal periods than those during haze episodes (Fig. S7). Meanwhile, during haze episodes the log KP values for 10 PAH compounds with lower volatilities, including BaA, CHR, BbF, BjF, BkF, BaP, BeP, DahA, IcdP and BghiP, were found to be significantly (P b 0.05) larger in the nighttime than those in the daytime (Fig. S8). These results indicated that the gas–particle distribution of PAHs varied remarkably with the change of weather conditions. In the atmosphere, the KP values for PAHs are generally correlated with sub-cooled vapor pressures (P0L ) (Simcik et al., 1998), and thus their relationship can be described by Junge–Pankow (J–P) model (Pankow and Bidleman, 1992): log K p ¼ mr log P 0L þ br

ð1Þ

where the slope mr and the intercept br are constants. Regression of log Kp against the temperature-corrected log P0L of PAH could potentially yield useful information on the gas–particle partition mechanism from the values mr and br. Under equilibrium distribution mr is expected to have a value of near − 1 for either adsorption or absorption mechanisms. The intercept br depends on the surface concentration of sorption sites, specific surface area of particulate matter and desorption enthalpy. The larger br value indicates a higher adsorption capacity. In this study, the log Kp values for 4 nonvolatile PAH compounds, BjF, DahA, IcdP and BghiP, were not adopted to fit the J–P model due to their extremely low concentrations in the gas-phase. The linear regression results of log Kp versus log P0L for other 14 PAH compounds are shown in Table S5. Good correlations between log Kp and log P0L were found, with R2 values in the range 0.84–0.95. The slope mr values during haze episodes (range: −0.87 to −0.70, average: −0.78) were significantly lower than those during normal periods (range: −0.84 to −0.43, average: −0.63), and the average values of slope mr followed the order: normal period nighttime (−0.56) N normal period daytime (−0.60) N haze episode daytime (−0.67) N haze episode nighttime (−0.73). This result suggested that the gas–particle distribution of PAHs were closer to equilibrium during haze episodes. In addition, the intercept br during haze episodes (range: − 4.48 to −3.62, average: −4.43) were also significantly lower than those during normal periods (range: − 3.91 to − 2.28, average: − 3.32). This suggested a lower adsorption capacity of PAHs on particulate matter during haze episodes. This phenomenon

R. Cao et al. / Science of the Total Environment 625 (2018) 1486–1493

should mainly result from the lower content of organic matter in the haze particulates. Previous studies have indicated that the secondary inorganic aerosols usually contribute more to particulate pollution than dose secondary organic aerosols during haze episodes (Huang et al., 2014; Sun et al., 2014). In addition, the significantly lower br in haze episodes might be partly caused by the higher RH in haze episodes. In this study, a significantly negative correlation (correlation coefficient − 0.73, P b 0.001) was observed between br and RH. The water molecule under high RH would cover the sorption site on the aerosol particle surface, and thus decrease the sorption of organic compound (Healy et al., 2009; Liu et al., 2017). 3.5. Risk assessment for the inhalation exposure to PAHs In order to assess the PAH-induced inhalation cancer risks under different air pollution condition, the concentrations of individual PAH compounds were converted to BaP equivalent concentration (∑BaPeq) according to the following equation: X

BaPeq ¼

X

ðC i  RPF i Þ

ð2Þ

i

where Ci (ng/g) and RPFi are the concentration and relative potency factor of the ith PAH, respectively. The RPF values based on tumor bioassay data from the U.S. EPA's Integrated Risk Information System Program were adopted (U.S. EPA, 2010). Thirteen carcinogenic PAHs with reported RPF values were covered for health effect evaluation (Table S6). The time trend of total estimated BaPeq concentration (∑BaPeq) for the typical three sequent winter haze is shown in Fig. 6. The ∑BaPeq values ranged from 11.8 ng/m3 to 124.9 ng/m3 during the normal periods, and from 112.0 ng/m3 to 307.4 ng/m3 during the haze episodes. The average ∑BaPeq value during sampling period was 126.8 ng/m3, which was lower than those reported for the winter of polluted megacities in the north China (201–427 ng/m3) such as Tianjin and Xi'an, whereas higher than those (7.4–45.6 ng/m3) reported for the central or south China (Zhu et al., 2014; Kong et al., 2015; He et al., 2014; Ren et al., 2017; Hong et al., 2016; Elser et al., 2016; Jin et al., 2017; Jia et al., 2011). In this study, the ∑ BaPeq values all largely exceeded the China's State Environmental Protection Agency's daily BaPeq standard (2.5 ng/m3) (Ministry of Environmental Protection of the People's Republic of China (MEP), 2012) and the European Union's annual average BaPeq standard (1 ng/m3) (EC, 2001). The average of ∑BaPeq values

1491

increased from 53.9 ng/m3 to 199.7 ng/m3 (an increase of 2.7 times) from normal periods to haze episodes, and during haze episodes. The ∑ BaPeq values of atmospheric PAHs in the nighttime (range: 176.7–307.4 ng/m3, average: 235.3 ng/m3) were significantly (P b 0.01) higher those (range: 112.0–174.3 ng/m3, average: 137.4 ng/m3) in the daytime. This result indicated that people stays out more during haze episode nighttime would pose a relatively higher cancer risk for inhalation exposure to PAHs. 4. Conclusions The concentrations of 18 PAH compounds in the atmosphere of Beijing winter were measured during three sequent haze episodes around the new year's day of 2015. The evolution of PAH pollution was found to coincide with the haze occurrence. The average concentration of Σ18PAHs in the atmosphere (1473.1 ng/m3) during three haze episodes was 2.6 times higher than that (405.1 ng/m3) during normal periods. As a result, the average of ∑ BaPeq value increased by 2.7 folds from normal periods to haze episodes. During haze episodes, atmospheric PAHs showed a significant diurnal variation in the total level, congener distribution profile and gas–particle partitioning. The elevated levels of atmospheric PAHs during haze periods especially the nighttime mainly resulted from the decrease of PBL heights. The longrange transport contributed more NAP to the atmosphere of normal periods. Most PAHs in daytime atmosphere should originate from the vehicle emission, while the main source of atmospheric PAHs shift to coal combustion in the nighttime. Air temperature and RH decisively affected the gas–particle partitioning behavior of PAHs, and the KP values for PAHs were significantly correlated with their P0L values. The gas–particle distributions of PAHs were closer to equilibrium during haze episode nighttime. Conflict of interest There is no conflict of interest. Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No. 91543201, and 91643104); the National Basic Research Program (Grant No. 2015CB453100) for the financial support. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2017.12.335. References

Fig. 6. Variation of the total BaP equivalent concentrations (∑BaPeq) of atmospheric PAHs during the sampling period (HE: haze episode).

Alam, M.S., Delgado-Saborit, J.M., Stark, C., Harrison, R.M., 2014. Investigating PAH relative reactivity using congener profiles, quinone measurements and back trajectories. Atmos. Chem. Phys. 14:2467–2477. https://doi.org/10.5194/acp-14-2467-2014. Alam, M.S., Keyte, I.J., Yin, J., Stark, C., Jones, A.M., Harrison, R.M., 2015. Diurnal variability of polycyclic aromatic compound (PAC) concentrations: relationship with meteorological conditions and inferred sources. Atmos. Environ. 122:427–438. https:// doi.org/10.1016/j.atmosenv.2015.09.050. Butler, J., Crossley, P., 1981. Reactivity of polycyclic aromatic hydrocarbons adsorbed on soot particles. Atmos. Environ. 15:91–94. https://doi.org/10.1016/00046981(81)90129-3. Chen, Y., Li, X., Zhu, T., Han, Y., Lv, D., 2017. PM2.5-bound PAHs in three indoor and one outdoor air in Beijing: concentration, source and health risk assessment. Sci. Total Environ. 586:255–264. https://doi.org/10.1016/j.scitotenv.2017.01.214. Elorduy, I., Elcoroaristizabal, S., Durana, N., Garcia, J.A., Alonso, L., 2016. Diurnal variation of particle-bound PAHs in an urban area of Spain using TD-GC/MS: influence of meteorological parameters and emission sources. Atmos. Environ. 138:87–98. https:// doi.org/10.1016/j.atmosenv.2016.05.012. Elser, M., Huang, R.-J., Wolf, R., Slowik, J.G., Wang, Q., Canonaco, F., Li, G., Bozzetti, C., Daellenbach, K.R., Huang, Y., Zhang, R., Li, Z., Cao, J., Baltensperger, U., El-Haddad, I., Prevot, A.S.H., 2016. New insights into PM2.5 chemical composition and sources in two major cities in China during extreme haze events using aerosol mass spectrometry. Atmos. Chem. Phys. 16:3207–3225. https://doi.org/10.5194/acp-16-3207-2016.

1492

R. Cao et al. / Science of the Total Environment 625 (2018) 1486–1493

European Commission (EC), 2001. Air Quality Standards. Available. http://ec.europa.eu/ environment/air/quality/standards.htm, Accessed date: 25 January 2010. EPA, U., 2012. National Ambient Air Quality Standards (NAAQS). Retrieved 9/01/2017, 2017, from http://www.epa.gov/air/criteria.html. Friedman, C.L., Pierce, J.R., Selin, N.E., 2014. Assessing the influence of secondary organic versus primary carbonaceous aerosols on long-range atmospheric polycyclic aromatic hydrocarbon transport. Environ. Sci. Technol. 48:3293–3302. https://doi.org/ 10.1021/es405219r. Fu, H., Chen, J., 2017. Formation, features and controlling strategies of severe haze-fog pollutions in China. Sci. Total Environ. 578:121–138. https://doi.org/10.1016/ j.scitotenv.2016.10.201. Gao, B., Yu, J.-Z., Li, S.-X., Ding, X., He, Q.-F., Wang, X.-M., 2011. Roadside and rooftop measurements of polycyclic aromatic hydrocarbons in PM2.5 in urban Guangzhou: evaluation of vehicular and regional combustion source contributions. Atmos. Environ. 45:7184–7191. https://doi.org/10.1016/j.atmosenv.2011.09.005. Gao, Y., Guo, X., Ji, H., Li, C., Ding, H., Briki, M., Tang, L., Zhang, Y., 2016. Potential threat of heavy metals and PAHs in PM2.5 in different urban functional areas of Beijing. Atmos. Res. 178:6–16. https://doi.org/10.1016/j.atmosres.2016.03.015. Gogou, A., Stratigakis, N., Kanakidou, M., Stephanou, E.G., 1996. Organic aerosols in eastern Mediterranean: components source reconciliation by using molecular markers and atmospheric back trajectories. Org. Geochem. 25:79–96. https://doi.org/ 10.1016/S0146-6380(96)00105-2. Gu, Z., Feng, J., Han, W., Li, L., Wu, M., Fu, J., Sheng, G., 2010. Diurnal variations of polycyclic aromatic hydrocarbons associated with PM2.5 in shanghai, China. J. Environ. Sci. 22: 389–396. https://doi.org/10.1016/s1001-0742(09)60120-0. Halsall, C.J., Sweetman, A.J., Barrie, L.A., Jones, K.C., 2001. Modelling the behaviour of PAHs during atmospheric transport from the UK to the Arctic. Atmos. Environ. 35:255–267. https://doi.org/10.1016/s1352-2310(00)00195-3. He, J., Fan, S., Meng, Q., Sun, Y., Zhang, J., Zu, F., 2014. Polycyclic aromatic hydrocarbons (PAHs) associated with fine particulate matters in Nanjing, China: distributions, sources and meteorological influences. Atmos. Environ. 89:207–215. https://doi.org/ 10.1016/j.atmosenv.2014.02.042. Healy, R.M., Temime, B., Kuprovskyte, K., Wenger, J.C., 2009. Effect of relative humidity on gas/particle partitioning and aerosol mass yield in the photooxidation of p-xylene. Environ. Sci. Technol. 43:1884–1889. https://doi.org/10.1021/es802404z. Ho, K.F., Ho, S.S.H., Lee, S.C., Cheng, Y., Chow, J.C., Watson, J.G., Louie, P.K.K., Tian, L., 2009. Emissions of gas- and particle-phase polycyclic aromatic hydrocarbons (PAHs) in the Shing Mun tunnel, Hong Kong. Atmos. Environ. 43:6343–6351. https://doi.org/ 10.1016/j.atmosenv.2009.09.025. Hong, W.J., Jia, H., Ma, W.L., Sinha, R.K., Moon, H.B., Nakata, H., Nguyen Hung, M., Chi, K.H., Li, W.L., Kannan, K., Sverko, E., Li, Y.F., 2016. Distribution, fate, inhalation exposure and lung cancer risk of atmospheric polycyclic aromatic hydrocarbons in some Asian countries. Environ. Sci. Technol. 50:7163–7174. https://doi.org/10.1021/ acs.est.6b01090. Hou, X.M., Zhuang, G.S., Sun, Y., An, Z.S., 2006. Characteristics and sources of polycyclic aromatic hydrocarbons and fatty acids in PM2.5 aerosols in dust season in China. Atmos. Environ. 40:3251–3262. https://doi.org/10.1016/j.atmosenv.2006.02.003. Huang, R.J., Zhang, Y., Bozzetti, C., Ho, K.F., Cao, J.J., Han, Y., Daellenbach, K.R., Slowik, J.G., Platt, S.M., Canonaco, F., Zotter, P., Wolf, R., Pieber, S.M., Bruns, E.A., Crippa, M., Ciarelli, G., Piazzalunga, A., Schwikowski, M., Abbaszade, G., Schnelle-Kreis, J., Zimmermann, R., An, Z., Szidat, S., Baltensperger, U., El Haddad, I., Prevot, A.S., 2014. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514: 218–222. https://doi.org/10.1038/nature13774. Inomata, Y., Kajino, M., Sato, K., Ohara, T., Kurokawa, J.-I., Ueda, H., Tang, N., Hayakawa, K., Ohizumi, T., Akimoto, H., 2012. Emission and atmospheric transport of particulate PAHs in Northeast Asia. Environ. Sci. Technol. 46:4941–4949. https://doi.org/ 10.1021/es300391w. Jiang, Y., Hou, X., Zhuang, G., Li, J., Wang, Q., Zhang, R., Lin, Y., 2009. The sources and seasonal variations of organic compounds in PM2.5 in Beijing and shanghai. J. Atmos. Chem. 62:175–192. https://doi.org/10.1007/s10874-010-9147-0. Jin, R., Liu, G., Jiang, X., Liang, Y., Fiedler, H., Yang, L., Zhu, Q., Xu, Y., Gao, L., Su, G., Xiao, K., Zheng, M., 2017. Profiles, sources and potential exposures of parent, chlorinated and brominated polycyclic aromatic hydrocarbons in haze associated atmosphere. Sci. Total Environ. 593–594:390–398. https://doi.org/10.1016/j.scitotenv.2017.03.134. Kavouras, I.G., Koutrakis, P., Tsapakis, M., Lagoudaki, E., Stephanou, E.G., Von Baer, D., Oyola, P., 2001. Source apportionment of urban particulate aliphatic and polynuclear aromatic hydrocarbons (PAHs) using multivariate methods. Environ. Sci. Technol. 35: 2288–2294. https://doi.org/10.1021/es001540z. Keyte, I.J., Harrison, R.M., Lammel, G., 2013. Chemical reactivity and long-range transport potential of polycyclic aromatic hydrocarbons–a review. Chem. Soc. Rev. 42: 9333–9391. https://doi.org/10.1039/c3cs60147a. Kong, S., Li, X., Li, L., Yin, Y., Chen, K., Yuan, L., Zhang, Y., Shan, Y., Ji, Y., 2015. Variation of polycyclic aromatic hydrocarbons in atmospheric PM2.5 during winter haze period around 2014 Chinese spring festival at Nanjing: insights of source changes, air mass direction and firework particle injection. Sci. Total Environ. 520:59–72. https:// doi.org/10.1016/j.scitotenv.2015.03.001. Li, C.K., Kamens, R.M., 1993. The use of polycyclic aromatic hydrocarbons as source signatures in receptor modeling. Atmos. Environ. Part A 27:523–532. https://doi.org/ 10.1016/0960-1686(93)90209-H. Li, J., Du, H., Wang, Z., Sun, Y., Yang, W., Li, J., Tang, X., Fu, P., 2017. Rapid formation of a severe regional winter haze episode over a mega-city cluster on the North China plain. Environ. Pollut. 223:605–615. https://doi.org/10.1016/j.envpol.2017.01.063. Li, Y., Song, N., Yu, Y., Yang, Z., Shen, Z., 2017. Characteristics of PAHs in street dust of Beijing and the annual wash-off load using an improved load calculation method. Sci. Total Environ. 581− 582:328–336. https://doi.org/10.1016/ j.scitotenv.2016.12.133.

Lin, W., Xu, X., Ge, B., Liu, X., 2011. Gaseous pollutants in Beijing urban area during the heating period 2007–2008: variability, sources, meteorological, and chemical impacts. Atmos. Chem. Phys. 11:8157–8170. https://doi.org/10.5194/acp-11-81572011. Liu, S., Tao, S., Liu, W., Liu, Y., Dou, H., Zhao, J., Wang, L., Wang, J., Tian, Z., Gao, Y., 2007. Atmospheric polycyclic aromatic hydrocarbons in north China: a winter-time study. Environ. Sci. Technol. 41:8256–8261. https://doi.org/10.1021/es0716249. Liu, J., Li, J., Lin, T., Liu, D., Xu, Y., Chaemfa, C., Qi, S., Liu, F., Zhang, G., 2013. Diurnal and nocturnal variations of PAHs in the Lhasa atmosphere, Tibetan plateau: implication for local sources and the impact of atmospheric degradation processing. Atmos. Res. 124:34–43. https://doi.org/10.1016/j.atmosres.2012.12.016. Liu, Z., Hu, B., Ji, D., Wang, Y., Wang, M., Wang, Y., 2015. Diurnal and seasonal variation of the PM2.5 apparent particle density in Beijing, China. Atmos. Environ. 120:328–338. https://doi.org/10.1016/j.atmosenv.2015.09.005. Liu, Y., Wu, Z., Wang, Y., Xiao, Y., Gu, F., Zheng, J., et al., 2017. Submicrometer particles are in the liquid state during heavy haze episodes in the urban atmosphere of Beijing, China. Environ. Sci. Technol. Lett. 4:427–432. https://doi.org/10.1021/ acs.estlett.7b00352. Manoli, E., Kouras, A., Samara, C., 2004. Profile analysis of ambient and source emitted particle-bound polycyclic aromatic hydrocarbons from three sites in northern Greece. Chemosphere 56:867–878. https://doi.org/10.1016/j.chemosphere.2004.03.013. McWhinney, R.D., Zhou, S., Abbatt, J.P.D., 2013. Naphthalene SOA: redox activity and naphthoquinone gas-particle partitioning. Atmos. Chem. Phys. 13:9731–9744. https://doi.org/10.5194/acp-13-9731-2013. Ministry of Environmental Protection of the People's Republic of China (MEP), 2012. Ambient Air Quality Standard (GB3095-2012). http://kjs.mep.gov.cn/hjbhbz/bzwb/ dqhjbh/dqhjzlbz/201203/W020120410330232398521.pdf. Mirante, F., Alves, C., Pio, C., Pindado, O., Perez, R., Revuelta, M.A., Artiñano, B., 2013. Organic composition of size segregated atmospheric particulate matter, during summer and winter sampling campaigns at representative sites in Madrid, Spain. Atmos. Res. 132–133:345–361. https://doi.org/10.1016/j.atmosres.2013.07.005. Mulder, M.D., Heil, A., Kukučka, P., Klánová, J., Kuta, J., Prokeš, R., Sprovieri, F., Lammel, G., 2014. Air–sea exchange and gas–particle partitioning of polycyclic aromatic hydrocarbons in the Mediterranean. Atmos. Chem. Phys. 14:8905–8915. https://doi.org/ 10.5194/acp-14-8905-2014. Pankow, J.F., Bidleman, T.F., 1992. Interdependence of the slopes and intercepts from loglog correlations of measured gas-particle paritioning and vapor pressure—I. Theory and analysis of available data. Atmos. Environ. Part A 26:1071–1080. https:// doi.org/10.1016/0960-1686(92)90039-N. Pieterse, B., Felzel, E., Winter, R., van der Burg, B., Brouwer, A., 2013. PAH-CALUX, an optimized bioassay for AhR-mediated hazard identification of polycyclic aromatic hydrocarbons (PAHs) as individual compounds and in complex mixtures. Environ. Sci. Technol. 47:11651–11659. https://doi.org/10.1021/es403810w. Ravindra, K., Sokhi, R., Van Grieken, R., 2008. Atmospheric polycyclic aromatic hydrocarbons: source attribution, emission factors and regulation. Atmos. Environ. 42: 2895–2921. https://doi.org/10.1016/j.atmosenv.2007.12.010. Ren, Y., Zhou, B., Tao, J., Cao, J., Zhang, Z., Wu, C., Wang, J., Li, J., Zhang, L., Han, Y., Liu, L., Cao, C., Wang, G., 2017. Composition and size distribution of airborne particulate PAHs and oxygenated PAHs in two Chinese megacities. Atmos. Res. 183:322–330. https://doi.org/10.1016/j.atmosres.2016.09.015. Simcik, M.F., Franz, T.P., Zhang, H., Eisenreich, S.J., 1998. Gas-particle partitioning of PCBs and PAHs in the Chicago urban and adjacent coastal atmosphere: states of equilibrium. Environ. Sci. Technol. 32:251–257. https://doi.org/10.1021/es970557n. Sun, Y., Jiang, Q., Wang, Z., Fu, P., Li, J., Yang, T., Yin, Y., 2014. Investigation of the sources and evolution processes of severe haze pollution in Beijing in January 2013. J. Geophys. Res. Atmos. 119:4380–4398. https://doi.org/10.1002/2014jd021641. Tan, J., Guo, S., Ma, Y., Duan, J., Cheng, Y., He, K., Yang, F., 2011. Characteristics of particulate PAHs during a typical haze episode in Guangzhou, China. Atmos. Res. 102:91–98. https://doi.org/10.1016/j.atmosres.2011.06.012. Tang, N., Suzuki, G., Morisaki, H., Tokuda, T., Yang, X., Zhao, L., Lin, J., Kameda, T., Toriba, A., Hayakawa, K., 2017. Atmospheric behaviors of particulate-bound polycyclic aromatic hydrocarbons and nitropolycyclic aromatic hydrocarbons in Beijing, China from 2004 to 2010. Atmos. Environ. 152:354–361. https://doi.org/10.1016/j.atmosenv.2016.12.056. U.S. EPA (U.S. Environmental Protection Agency), 2010. Development of a Relative Potency Factor (RPF) Approach for Polycyclic Aromatic Hydrocarbon (PAH) Mixtures. External review draftEPA, Integrated Risk Information System, Washington, DC:U.S. Wang, W., Jariyasopit, N., Schrlau, J., Jia, Y., Tao, S., Yu, T.-W., Dashwood, R.H., Zhang, W., Wang, X., Simonich, S.L.M., 2011. Concentration and photochemistry of PAHs, NPAHs, and OPAHs and toxicity of PM2.5 during the Beijing Olympic games. Environ. Sci. Technol. 45:6887–6895. https://doi.org/10.1021/es201443z. Wu, Y., Yang, L., Zheng, X., Zhang, S., Song, S., Li, J., Hao, J., 2014. Characterization and source apportionment of particulate PAHs in the roadside environment in Beijing. Sci. Total Environ. 470–471:76–83. https://doi.org/10.1016/j.scitotenv.2013.09.066. Yang, P., Wang, Y.X., Chen, Y.J., Sun, L., Li, J., Liu, C., Huang, Z., Lu, W.Q., Zeng, Q., 2017. Urinary polycyclic aromatic hydrocarbon metabolites and human semen quality in China. Environ. Sci. Technol. 51:958–967. https://doi.org/10.1021/acs.est.6b04810. Yue, H., Yun, Y., Gao, R., Li, G., Sang, N., 2015. Winter polycyclic aromatic hydrocarbonbound particulate matter from Peri-urban North China promotes lung cancer cell metastasis. Environ. Sci. Technol. 49:14484–14493. https://doi.org/10.1021/ es506280c. Zencak, Z., Klanova, J., Holoubek, I., Gustafsson, O., 2007. Source apportionment of atmospheric PAHs in the western balkans by natural abundance radiocarbon analysis. Environ. Sci. Technol. 41:3850–3855. https://doi.org/10.1021/es0628957. Zhang, Y., Schauer, J.J., Zhang, Y., Zeng, L., Wei, Y., Liu, Y., Shao, M., 2008. Characteristics of particulate carbon emissions from real-world Chinese coal combustion. Environ. Sci. Technol. 42:5068–5073. https://doi.org/10.1021/es7022576.

R. Cao et al. / Science of the Total Environment 625 (2018) 1486–1493 Zhang, S., Zhang, W., Wang, K., Shen, Y., Hu, L., Wang, X., 2009. Concentration, distribution and source apportionment of atmospheric polycyclic aromatic hydrocarbons in the southeast suburb of Beijing, China. Environ. Monit. Assess. 151:197–207. https:// doi.org/10.1007/s10661-008-0261-2. Zhang, K., Zhang, B.-Z., Li, S.-M., Zhang, L.-M., Staebler, R., Zeng, E.Y., 2012. Diurnal and seasonal variability in size-dependent atmospheric deposition fluxes of polycyclic aromatic hydrocarbons in an urban center. Atmos. Environ. 57:41–48. https://doi.org/ 10.1016/j.atmosenv.2012.04.014.

1493

Zhao, X., Zhang, X., Xu, X., Xu, J., Meng, W., Pu, W., 2009. Seasonal and diurnal variations of ambient PM2.5 concentration in urban and rural environments in Beijing. Atmos. Environ. 43:2893–2900. https://doi.org/10.1016/j.atmosenv.2009.03.009. Zhu, Y., Yang, L., Yuan, Q., Yan, C., Dong, C., Meng, C., Sui, X., Yao, L., Yang, F., Lu, Y., Wang, W., 2014. Airborne particulate polycyclic aromatic hydrocarbon (PAH) pollution in a background site in the North China plain: concentration, size distribution, toxicity and sources. Sci. Total Environ. 466–467:357–368. https://doi.org/10.1016/ j.scitotenv.2013.07.030.