Environmental Pollution 192 (2014) 83e90

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Atmospheric polycyclic aromatic hydrocarbons in rural and urban areas of northern China Wei Li a, Chen Wang a, Hongqijie Wang a, Jiwei Chen a, Huizhong Shen a, Guofeng Shen a, Ye Huang a, Rong Wang a, Bin Wang a, Yanyan Zhang a, Han Chen a, Yuanchen Chen a, Shu Su a, Nan Lin a, Jianhui Tang b, Qingbo Li c, Xilong Wang a, Junfeng Liu a, Shu Tao a, * a b c

Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China Yantai Institute of Coastal Zone Research, CAS, Yantai, Shandong 264003, PR China College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, PR China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 24 February 2014 Received in revised form 29 April 2014 Accepted 30 April 2014 Available online xxx

Air pollution in rural China has often been ignored, especially for the less developed west China. Atmospheric polycyclic aromatic hydrocarbons (PAHs) were measured monthly at 11 rural sites (5 rural villages and 6 rural fields) together with 7 urban stations in northern China between April 2010 and March 2011. PAH concentrations at rural village sites were similar to those in urban areas and significantly higher than those in rural fields, indicating severe contamination in rural villages. PAH concentrations in the west were similar to those in the more developed North China Plain, and higher than those along the coast. Such a geographical distribution is mainly caused by the differences in residential energy consumption and meteorological conditions, which can explain approximately 48% of the total variation in PAH concentrations. With heavy dependence on biofuel combustion for heating, seasonality in rural areas is more profound than that in urban areas. © 2014 Elsevier Ltd. All rights reserved.

Keywords: PAHs Rural village Northern China Spatial distribution Temporal variation

1. Introduction Polycyclic aromatic hydrocarbons (PAHs) from incomplete combustions are ubiquitous in the environment. As the first suspected carcinogenic pollutants, the exposure of populations to € m et al., 2002; IARC, PAHs has been studied extensively (Bostro 1987; WHO/IPCS, 1998). The majority of PAHs in air are emitted from solid fuel combustion or motor vehicle emissions (Zhang et al., 2009). The global total emission of 16 PAHs was about 504 Gg in 2007, of which 60.5% and 12.8% were from residential/commercial biomass burning and on-road motor vehicles, respectively (Shen et al., 2013a). Due to the variations in population density, energy demand, and type of fuel utilized, PAH emissions in China vary widely depending upon locations (Zhang et al., 2007, 2009). In general, ambient PAH concentrations in the northern China are higher than those in the south due to additional needs for heating in winter (Zhang et al., 2009). So far, a majority of studies on air pollution in China have focused on the eastern cities where rapid economic development,

* Corresponding author. E-mail addresses: [email protected], [email protected] (S. Tao). http://dx.doi.org/10.1016/j.envpol.2014.04.039 0269-7491/© 2014 Elsevier Ltd. All rights reserved.

industrialization, and urbanization have led to severe pollution (Liu et al., 2007; Wang et al., 2011b). To the west, however, with lower energy combustion efficiency and the need for more heating fuel in winter, particulate matter pollution was as severe as that in the east (Li et al., 2014). Atmospheric PAHs in cities have been extensively monitored, because of the high density of population, the abundance of motor vehicles, and massive industrial activities (Ravindra et al., 2008), and some have shown that PAH concentrations in the cities are higher than those in the surrounding rural areas (Cotham and Bidleman, 1995; Motelay-Massei et al., 2005). However, most of these comparisons were conducted in developed countries (Cotham and Bidleman, 1995; Motelay-Massei et al., 2005). It had been reported that globally, the PAH emission in urban areas was only half of that in rural areas, and the difference was even larger in the developing countries (Shen et al., 2013a). Only a few studies, conducted around BeijingeTianjin area in the east of China, reported that PAH concentrations in the rural villages were similar to, even slightly higher than those in the cities (Liu et al., 2007; Wang et al., 2011b). The aim of the present study was to investigate atmospheric PAHs pollution from the east coast to the west inland of northern China, especially the spatial variations of PAHs in the rural area. The sites are classified into three categories e rural villages, rural fields

84

W. Li et al. / Environmental Pollution 192 (2014) 83e90

and urban settings e and are evaluated in the light of spatial distribution pattern, source contribution and seasonal variation. 2. Methodology 2.1. Study area and sampling The study area spans a breadth of nearly 2500 km from Wuwei to an unnamed island at the east of Dalian in northern China (Fig. 1). Under the influence of the East Asia monsoon, a generally decreasing trend of temperature in winter and precipitation in summer occurs from east to west (NBSC, 2011). Information about temperature, wind velocity, precipitation (including both rain and snow), gasoline consumption, and residential energy consumption for each sampling city were collected (NBSC, 2011, 2012; Zhu et al., 2013) and summarized in Table S1. Generally, the gasoline consumption followed a decreasing trend from east to west, while the residential energy consumption was higher in the west than that in the east (Table S1). Five rural villages, six rural field sites, and seven urban locations were set up for active air sample collection (Fig. 1). The rural village sites were in the residential villages with 100 households or above in the suburban areas of the corresponding cities, and the rural field sites were located at least 500 m away from the nearest buildings to avoid local point sources. All urban sites located in the downtown areas of large cities (Dalian, Yantai, Beijing, Dezhou, Taiyuan, Yinchuan, and Wuwei). As shown in Fig. 1, Wuwei and Yinchuan are located in the west of China; Taiyuan, Beijing and Dezhou sit on the North China Plain; Yantai and Dalian distribute in the coasts of Bohai Bay. Both gaseous and particulate phase (PM10, particulate matter with aerodynamic size less than 10 mm) PAH samples were collected at 1.5e22 m above ground monthly from April 2010 to March 2011 by medium volume (200e400 L/min) cascade impactors (PM10-PUF-300, Guangzhou, China) for 72 h. The sampling media were polyurethane foam (PUF, 45 mm o.d.
60 mm high, 0.03 g/cm3) and glass-fiber filters (GFF, 200
150 mm2). Prior to use, PUFs were Soxhlet extracted using acetone, dichloromethane, and hexane in that order for 8 h each, and GFFs were baked at 450  C for 12 h. GFFs were equilibrated at 25  C in a desiccator for 24 h before weighing. Twelve paired samples (gaseous and particulate phases) were collected at each site. With a few samples lost during the sampling, the total numbers of paired samples for rural village, rural field and urban sites were 59, 68 and 81, respectively. 2.2. Sample extraction and cleanup PUFs were assayed by Soxhlet extraction with 150 mL hexane/ acetone (1:1, v/v) for 8 h. The GFFs were extracted using a

microwave extractor (CEM, U.S.) with 25 mL hexane/acetone (1:1, v/v). The temperature of the microwave accelerated system ramped to 110  C in 10 min and held at 110  C for another 10 min. After extracts were concentrated to one mL, silica/alumina gel columns (10 mm i.d.
300 mm length with 120 mm alumina at the bottom and 120 mm silica on the top) were used for purification. The silica gel and alumina were baked at 450  C for 6 h and activated at 130  C for 16 h prior to use (Shen et al., 2013b). Columns were first eluted with 20 mL hexane, which was discharged, and then by 70 mL hexane/dichloromethane mixture (1:1, v/v). The collected elutes were concentrated on a rotary evaporator to approximately 1 mL at 38  C, and spiked with internal standards (acenaphthene-d10, anthracene-d10, chrysene-d12, and perylene-d12, J&K Chemical, USA) prior to gas chromatography analysis. All glassware devices were cleaned ultrasonically with deionized water, and then baked at 400  C for 6 h. 2.3. Sample analysis A gas chromatograph (GC, Agilent 6890, U.S.) coupled with a mass spectrometer (MS, Agilent 5973, U.S.) with a capillary column (HP-5MS, 0.25 mm i.d.
30 m, 0.25 mm film thickness, J&W, U.S.) was used for PAHs analysis. The carrier gas was helium. The oven temperature was held at 50  C for one min, ramped to 150  C in 10 min, to 240  C at a rate of 3  C/min, then to 280  C for 20 min. Twenty one different PAHs were measured based on retention times and qualitative ions of standard PAHs (J&W Chemical, U.S.), including acenaphthene (ACE), acenaphthylene (ACY), fluorene (FLO), phenanthrene (PHE), anthrancene (ANT), fluoranthene (FLA), pyrene (PYR), benz(a)anthracene (BaA), chrysene (CHR), benzo(b) fluoranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), dibenz(a,h)anthracene (DahA), indeno(1,2,3-cd)pyrene (IcdP), benzo(g,h,i)perylene (BghiP), retene (RET), perylene (PER), benzo(e)pyrene (BeP), dibenzo(a,l)pyrene (dBalP), dibenzo(a,e) pyrene (dBaeP), dibenzo(a,h)pyrene (dBahP). The PAH concentrations were quantified using internal standard method. The retention time, quantification ions, and internal standard of individual PAH were listed in Table S2, and a representative chromatogram of dBalP was also shown in Fig. S1. 2.4. Quality control and data analysis Procedural and reagent blanks were analyzed and subtracted from the measured values of samples. Before sample analysis, method recoveries were tested by spiking standards of 21 target PAHs in cleaned sampling media. The recoveries were 102 ± 11 and 98 ± 19% for PUFs and GFFs, respectively. The method detection limits calculated from the instrument detection, method recovery

Fig. 1. Map of sampling area.

W. Li et al. / Environmental Pollution 192 (2014) 83e90

and the sampling volume were 7.7e47 and 18e44 pg/m3 for gaseous and particulate phase PAHs, respectively. To monitoring the entire analytical procedure, 20% randomly selected samples were spiked with surrogates (2-fluoro-1,10 -biphenyl and p-terphenyl-d14, J&W Chemical, USA) prior to the extraction. The recoveries of spiked surrogates were 87 ± 24 and 91 ± 30% for 2fluoro-1,10 -biphenyl and p-terphenyl-d14, respectively. Duplicate GFFs samples were measured, and the mean coefficient of variation was 0.17. Statistical analysis was conducted using SPSS (IBM, Armonk, NY, USA) with a significance level of 0.05. 3. Results and discussion 3.1. Atmospheric PAH concentrations The annual mean concentrations and standard deviations of PAHs at all sampling sites are listed in Table 1. The total (gaseous and particulate phases) concentrations of 21 parent PAHs (PAH21) in the ambient air samples collected from all 18 stations varied over three orders of magnitude from 7.6 (Yantai rural village site, July) to 4187 (Taiyuan rural village site, December) ng/m3, with an arithmetic mean and standard deviation of 211 ± 392 ng/m3 (77.3 ± 70.2 and 135 ± 368 ng/m3 in gaseous and particulate phase). Previous emission inventory and modeling studies showed that air in northern China, especially in Tianjin, Beijing, Hebei and Shanxi, is heavily contaminated by PAHs due to high population density, heating requirements in winter, and heavy dependence on coal and biomass fuels in residential and commercial sectors (Shen et al., 2013a; Zhang et al., 2009). In fact, this area is among the most heavily PAH contaminated region in the world (Shen et al., 2013a). As shown in Table S3, total concentrations of 15 PAHs in the aerosols from Xi'an (the capital city of Shaanxi, Fig. 1) were 344 ± 150 and 137 ± 56.7 ng/m3 in winter and summer, respectively (Okuda et al., 2010). Xia et al. (2013) found that the atmospheric PAH concentrations (gaseous and particulate phases) in rural and urban areas of Taiyuan were 199 and 209 ng/m3, respectively. Based on an extensive survey during 2005e2006, it was reported that PAHs (gaseous and particulate phases) in ambient air in North China Plain reached 514 ± 563 and 610 ± 645 ng/m3 in urban and rural areas, respectively (Liu et al., 2007). Meanwhile, those measured in southern China were often much lower due to many factors like lower population density, no heating requirement in winter, less dependence of residential/commercial sector on coal and biomass fuels, relatively higher temperature and more frequent and stronger precipitation. Also shown in Table S3, concentrations of 15 PAHs in the atmospheric PM10 from Xiamen in the southeast of China were 17.5, 3.7, 32.6, and 10.5 ng/m3 in spring, summer, fall, and winter, respectively (Hong et al., 2007). Even at industrial sites of Qingyuan in South China, PM2.5-bound PAHs were only

85

7.38e33.1 ng/m3 in summer and 42.2e112 ng/m3 in winter (Wei et al., 2012). Besides, observations on PAHs at many nonbackground sites around the world were at least one order of magnitude lower than what we found in this area (Table S3, Gigliotti et al., 2005; Motelay-Massei et al., 2005; Park et al., 2002). For the total (gaseous and particulate phases) PAH concentrations, the predominated ones are PHE, FLA, and PYR, contributing over 50% of the total at the majority of sites (Fig. S2). The most abundant PAHs in the gaseous phase are PHE, FLA and FLO, while BbF, FLA and PHE dominate in the particulate phase (Fig. S2). Similar patterns have been reported for 16 PAHs measured in ambient air in BeijingeTianjin area (Wang et al., 2011b; Liu et al., 2008). This pattern is expected since it fits with the emission composition profiles of major sources including firewood, straw and coal combustion in the study area (Shen et al., 2013a). PAHs with molecular weights of 228 or above (from BaA to BghiP) accounted for 33% of the total, and these compounds are of particular concern in terms of health impact, specifically their carcinogenic behavior. Because biomass fuel and coal combustion are the main emission sources in the study region, the fraction of high molecular weight PAHs is generally high. This is particularly true for sites in the northwest of China. Similarly, it was also reported that approximately half of the 15 PAHs in the aerosols from Xi'an were high molecular weight PAHs (Okuda et al., 2010). In comparison, the fractions of PAHs with high molecular weight were only 5.7% and 12.8% in the total (gaseous and particulate phases) PAH concentrations in Guangzhou and Birmingham (Table S3, Delgado-Saborit et al., 2013; Li et al., 2006). In this study, three dibenzopyrenes were measured due to their high carcinogenicity. For most samples, dBalP and dBaeP were detectable, ranging from 0.116 to 18.7 and from 0.113 to 5.77 ng/m3, respectively. Among limited data reported on dibenzopyrenes in air, most of them were much lower than what we found (0.0011e0.013 and 0.012e0.057 ng/m3 for dBalP and dBaeP in Sweden and 0.020 ± 0.022 ng/m3 for dBalP in Portugal) (Table S3, Bergvall and Westerholm, 2007; Castro et al., 2009). To our knowledge, the only data with similar concentration ranges were also found in Beijing within our study area (Table S3, Wang et al., 2011a). Although the concentrations were relatively lower than those of most other PAHs, the carcinogenic potency of dBalP could be in a € m et al., 2002). It was recently range of 10e100 times of BaP (Bostro reported that firewood and coal, which happened to be the major energy sources in this area, were important emission sources of dibenzopyrenes (Shen et al., 2012, 2013b). 3.2. Ruraleurban difference The annual mean total (gaseous and particulate phases) concentrations of PAH21 at the rural village, urban, and rural field sites

Table 1 Annual mean concentrations and standard deviations of PM10 (mg/m3, Li et al., 2014) and PAH21 (ng/m3) at each site. Wuwei Rural field

Rural village

Urban

PM10 Gaseous Particulate Total PM10 Gaseous Particulate Total PM10 Gaseous Particulate Total

195 58 108 166 354 95 144 239 361 88 153 242

± ± ± ± ± ± ± ± ± ± ± ±

107 37 145 178 210 70 189 239 349 96 227 317

Yinchuan 147 71 98 169 152 114 80 193 119 72 103 175

± ± ± ± ± ± ± ± ± ± ± ±

78 41 92 128 89 82 76 144 078 50 171 200

Taiyuan 144 99 218 317 182 108 525 633 288 142 382 524

± ± ± ± ± ± ± ± ± ± ± ±

93 60 295 302 142 82 1162 1184 119 42 773 759

Beijing

193 118 133 251

± ± ± ±

99 156 220 305

Dezhou 135 53 112 165 116 60 58 118 140 96 96 192

± ± ± ± ± ± ± ± ± ± ± ±

39 22 182 181 37 18 54 68 54 52 98 135

Yantai 95 13 33 46 107 69 73 143 103 44 31 75

± ± ± ± ± ± ± ± ± ± ± ±

Dalian 99 13 22 31 94 62 109 166 47 42 31 71

47 12 32 44

± ± ± ±

16 3 50 50

68 28 34 62

± ± ± ±

29 22 56 57

Average 128 54 101 154 182 90 176 265 180 87 135 220

± ± ± ± ± ± ± ± ± ± ± ±

89 45 168 191 154 68 542 564 171 84 334 364

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W. Li et al. / Environmental Pollution 192 (2014) 83e90

were 265 ± 564, 220 ± 364, and 154 ± 191 ng/m3, respectively. No significant difference was found between PAHs concentrations in the rural villages and those in the cities (p > 0.05), and the former were even slightly higher than the latter. It is occasionally reported that rural ambient air is severely contaminated by emissions from solid fuel combustion in China. For example, based on an extensive monitoring campaign, it was found that PAH concentrations in ambient air in rural villages were not lower than those in big cities in North China Plain in winter (Table S3, Liu et al., 2007) and in BeijingeTianjin area (Table S3, Wang et al., 2011b). Similarly, no significant difference was found in the atmospheric PM10 concentrations between rural village (0.18 ± 0.15 mg/m3) and urban (0.18 ± 0.17 mg/m3) sites in northern China (Li et al., 2014). That is the reason why we distinguished rural villages from rural fields in this study. Relationships found in northern China are very different from those observed in developed countries or other developing countries. A strong urban-rural gradient of PAHs in air, up to five times higher at urban sites, was found in Canada (Table S3, Motelay-Massei et al., 2005). Similar patterns were observed in the U.S. (Table S3, Cotham and Bidleman, 1995; Gustafson and Dickhut, n et al., 2011). Also in Malaysia in 1997) and Spain (Table S3, Calle Southeast Asia, concentrations of 14 PAHs in the urban samples (6.3 ± 4.4 ng/m3) were much higher than those in rural locations (0.30 ± 0.15 ng/m3) (Table S3, Omar et al., 2002). Still, it is surprising to see that not only in the winter, but even on an annual basis the mean concentrations of PAH21 at rural village sites were higher than those at urban sites. Almost all the recent reports and studies on the air pollution in China focus on cities, leaving air quality in rural China largely ignored, even though almost half of the population still live in rural areas. According to the published results of the Global Burden of Disease Study, household air pollution ranked 5th in the leading risk factors in China (Yang et al., 2013). According to our results, ambient PAH concentrations in the studied rural villages were as high as, if not higher than, those in cities. Moreover, it is expected, and supported by limited studies (Ding et al., 2012; Zhong et al., 2012), that indoor air quality in rural households could be even worse due to the use of traditional indoor stoves and solid fuels. Such a widespread air pollution in rural residential areas not only causes a disproportionate number of premature death among rural population (World Bank, 2007), but also contributes considerably to regional air pollution, which struck over almost entire eastern China during a series of massive air pollution events in early 2013 (Wang, 2013). In fact, emission of PAHs from biomass fuel in the residential sector alone accounts for 47% of the total for the country and a large fraction of this emission occurs in northern China (Zhang et al., 2009). During the past decade, a series of measures have been taken to fight air pollution in Chinese cities, among which replacement of household coal stoves with natural gas, promotion of centralized heating system, and relocation of heavily polluting facilities are the most effective (Vennemo et al., 2009). However in the rural areas, only limited efforts have been undertaken. In the future, promotion of cleaner fuel and cleaner stoves could be one of the main ways to alleviate the problem (Anenberg et al., 2013; Shen et al., 2013b). The concentrations observed at rural field sites were significantly lower than those at other sites, even though some of these sites are not too far away from nearby residential areas. Among all rural field sites, the easternmost one, a small unnamed island offshore of Dalian, was approximately 60 km away from the nearest coast and could serve as a background site for the study area. Very low PM10 concentrations (0.047 ± 0.016 mg/m3, as annual mean) were detected there, compared with annual mean PM10 concentrations of 0.16 ± 0.15 mg/m3 in northern China (Li et al., 2014). With limited human activities on this island, PAHs observed there

were mainly from long-range transport. The annual mean concentrations of PAH21 were as low as 44.4 ± 50.1 ng/m3. However, this PAH level was still higher than those in other background sites around the world (Table S3), likely due to the outflow of PAHs from the Northern China Plain (Lang et al., 2008). For example, the concentrations of 20 PAHs (gaseous þ particulate phase) were in 1.3e3.7 ng/m3 in 1-week sampling periods in cold and warm seasons in high mountain regions of Europe (Fern andez et al., 2002). The annual average level for 13 PAHs in the remote area from southern UK to northern Norway was 0.04e20 ng/m3 (Gioia et al., 2006), and during a period from April to May in 2005 at the background site in Waliguan in China, the total concentrations of 14 PAHs were measured at 7.4e30 ng/m3 (Cheng et al., 2006). Fig. 2 shows composition profiles for the three types of sampling sites. The profiles are generally similar to one another among the three categories. One reason is that the corresponding sites are tightly clustered, possibly resulting in cross-impact among them, which is supported by the correlations in PAH concentrations among the three categories. With relatively strong emission from motor vehicles in the cities, which can be almost ignored in the studied villages, slight difference between urban and rural village areas appeared in the predominant compound and high molecular weight PAHs. The fractions of PHE, FLA and PYR in the urban areas were higher than those at rural village sites, while the total fraction of high molecular weight PAHs (from BaA to BghiP) was smaller in the cities. According to the previous PAHs emission inventory (Zhang et al., 2007), the fractions of high molecular weight PAHs (from BaA to BghiP) are 26, 10, and 6% for emissions from residential coal, residential biofuel, and motor vehicles, respectively, while the percentages of PHE are 20, 19, and 29%, respectively. Calculated PAH isomer ratios, including FLA/(FLA þ PYR), IcdP/(IcdP þ BghiP), ANT/ (ANT þ PHE), and BaA/(BaA þ CHR), also support the dominance of solid fuel combustion sources in the study area and the influence of vehicle emissions in urban area (Fig. S3). 3.3. Meridional difference Annual mean concentrations of PAH21 at all 18 sites are shown in Fig. 3, in which the areas of the pie charts are proportional to the total concentrations of both gaseous and particulate phase PAHs. Generally, the concentrations among urban, rural village, and rural field sites were positively correlated. The highest concentrations were observed in Taiyuan. This area is one of the most important heavy industrial centers in China, focusing on coal mining, coke production and other coal chemistry industries, iron-steel production, and coal-fired power plants (Meng et al., 2007). In 2010, the output of coke from Shanxi contributed 22% of the national total production, ranking first place in China (NBSC, 2012). Extreme hot spots with the highest emission densities can be found in this area (Zhang et al., 2007). Moreover, sitting at the bottom of Taiyuan basin, the terrain is not favorable for diffusion of emitted PAHs, making it one of the most severely contaminated cities in China, even around the world (Yang et al., 2011). High PAH concentrations in air, soil and food have been extensively detected in Taiyuan recently (Xia et al., 2010, 2013). Relative low concentrations for all site types can be found in sites in coastal areas, namely Dalian and Yantai. This is particularly true for the two rural field sites. Apart from the sites in Taiyuan and along the coastal areas, there is hardly any difference among other sites. To this stage, most studies of atmospheric PAHs focused on the east of China, where densities of population and emission are both higher than those in the west. It is generally accepted that environmental deterioration is more severe in rapidly developing areas in the east. According to evidence collected in this study, air in urban and rural residential areas in the west are equally severely

W. Li et al. / Environmental Pollution 192 (2014) 83e90

87

0.8 Rural field Rural village Urban

Fraction

0.6 0.4 0.2

BaA-BghiP

dBahP

dBaeP

dBalP

BghiP

DahA

IcdP

BeP

BaP

PER

BkF

BbF

RET

CHR

BaA

PYR

FLA

ANT

PHE

FLO

ACE

ACY

0

Fig. 2. PAHs composition profiles of rural field, rural village, and urban sites (from left to right), shown as annual means and standard errors. Filled and hollow bars show particulate and gaseous phase PAHs, respectively. Fractions of all high molecular weight PAHs (from BaA to BghiP) are shown on the right side.

contaminated by PAHs as that in the east, which should not be overlooked in the future. Relative low energy efficiency in industry and high heating energy demand in residential sector in the west make great contributions to local PAHs emission. In 2010, energy efficiencies in Gansu and Ningxia, where Wuwei and Yinchuan are located, were 1.801 and 3.308 tce (ton coal equivalent) per 10,000 yuan Gross Domestic Product (GDP), compared with 1.025 tce in Shandong, where Dezhou and Yantai sites lie (NBSC, 2012). Since the East Asia monsoon cannot reach Gansu and Ningxia, winter there is colder than in other sites in the east, and the mean winter temperature in the west inland area is 5  C, approximately 8  C lower than that in the coastal areas (NBSC, 2011), leading to a very large difference in the demand for heating fuel. In fact, the heating degree day in the inland provinces was 2165, comparing with only 471 in the east (Zhu et al., 2013). In 2010, rural residential energy consumption per capita in Gansu and Ningxia (0.25 and 0.20 ton coal) in the west were much higher than those in Shandong and Liaoning (0.048 and 0.075 ton coal) in the east, due to low combustion efficiency and high heating demand (NBSC, 2012). Moreover, removal process of wet deposition is relatively slow in the west due to the low precipitation (~113 mm in Wuwei vs. ~673 mm in Dezhou) (NBSC, 2011). Although the composition profiles of PAHs seem similar among three site categories with domination of PHE, FLA, and PYR, there is a generally increasing trend of PHE and a decreasing trend of most high molecular weight PAHs from west to east (from Wuwei to Dalian) at urban and rural field sites (Fig. 4). There is no such trend for rural village sites. Variations in emission sources could be an important reason for such difference. Residential fuels in rural areas in northern China are dominated by coal and biomass. In the cities, however, motor vehicles are also important PAH emission source,

especially in the east where there was a higher contribution of motor vehicle. It was reported that the PAH emission density from motor vehicles in Yantai and Dalian were 0.11 and 0.061 ton/km2, comparing with 0.021 and 0.027 ton/km2 in Wuwei and Yinchuan (Zhang et al., 2007). Moreover, central heating systems and pipeline natural gas are more popular in the more developed eastern cities, while more residents in the western cities rely on household stoves for cooking and heating. As mentioned above, the fraction of PHE from motor vehicle emission (29%) is higher than that from coal (20%), while the fraction of high molecular weight PAH is lower (6% vs. 26%) (Zhang et al., 2007). Because of the meridional trend of PHE and relatively constant values of ANT (Fig. 4), a general decreasing trend of ANT/(ANT þ PHE) in cities from west to east can be found (Fig. S4). Similar patterns were also found in the values of BaA/ (BaA þ CHR) and IcdP/(IcdP þ BghiP) (Fig. S4), again reflecting trends in the relative influence of petroleum and solid fuels (Yunker et al., 2002). 3.4. Seasonal variation Fig. 5 illustrates the calculated mean monthly concentrations for the three categorities of sampling sites. A clear seasonality of atmospheric PAH concentrations with relatively high PAH concentrations in heating season and lower ones in non-heating seasons was observed for both phases. The heating season in this region usually begins in November and ends in March depending on the exact location, during which emission of PAHs increases dramatically. PAH concentrations reach the peak of the year in the coldest months (circles in Fig. 5). In addition to seasonal variation in source emissions, meteorological conditions also affect the PAHs seasonality in air. An important factor affecting the air concentration is

Inner Mongolia Liaoning

Beijing Wuwei

Hebei

Yinchuan

Bohai Bay

Dalian

Ningxia Gansu

Rural field Rural village Urban

Taiyuan Shanxi

Dezhou

Yantai

Shandong

Shaanxi

0

150

300km

Fig. 3. Annual mean concentrations of PAH21 at each sampling site. Filled and hollow pie charts show the fractions of particulate and gaseous phase PAH21, respectively.

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W. Li et al. / Environmental Pollution 192 (2014) 83e90

0.4 Rural field 0.3 0.2 0.1 0.0 Rural village

Fraction

0.3 0.2 0.1 0.0 Urban

Wuwei Yinchuan Taiyuan Beijing Dezhou Yantai Dalian

0.3 0.2 0.1

dBahP

BaA-BghiP

dBaeP

dBalP

BghiP

DahA

PER

IcdP

BeP

BaP

BbF

BkF

CHR

BaA

PYR

FLA

RET

ANT

PHE

FLO

ACE

ACY

0.0

Fig. 4. Composition profiles of total PAH21 at urban, rural village, and rural field sites from west to east, shown as mean fraction and standard error of each compound. Total fraction of high molecular weight PAHs (from BaA to BghiP) are presented together on the right.

precipitation (triangles in Fig. 5), and wet deposition is one of the most important processes removing PAHs from air (Ravindra et al., 2008). In the study region, the average precipitations varied from ~295.3 mm in summer to ~28.6 mm in winter (Table S1, NBSC, 2011), and precipitation in summer concentrated in the three summer months from June to August (rainy season) primarily due to influence of the East Asian monsoon. For example, precipitation in Taiyuan during the rainy season that year was ~265 mm, contributing to 61% of the annual sum (Table S1). Moreover, relatively high temperatures in northern China in summer are also favorable for atmospheric photochemical reactions and PAH

degradation in air (Reisen and Arey, 2005). In Taiyuan, mean temperature was 22  C in August, comparing with 5.5  C in January (Table S1, NBSC, 2011). Finally, lower inversion layer in winter prevents PAHs from fast diffusion (Ravindra et al., 2008). Similar seasonal variations in PAH concentrations have been observed in other places. For example, during a regional campaign in 2005e2006, it was found that PAH concentrations in winter in North China Plain were eight times higher than those in summer (Liu et al., 2008). The particulate PAHs in seven cities in the PanJapan Sea countries also showed a clear seasonality with relatively high concentrations in winter (Tang et al., 2005). Although

Fig. 5. Monthly mean concentrations and standard errors of PAH21 at the three site categories. Gaseous-phase, particulate-phase and total concentrations are shown in the top left, bottom left and right panel, respectively. The circles and triangles in the right panel represent the monthly temperatures and precipitations.

W. Li et al. / Environmental Pollution 192 (2014) 83e90

both gaseous and particulate phase PAHs followed a similar seasonal pattern, the difference of particulate phase PAHs appeared to be larger than that of gaseous phase ones between heating and non-heating seasons (Fig. 5). This was most likely caused by the temperature dependent partitioning of PAHs between gaseous and particulate phases in different seasons. As temperature drops in winter, the subcooled liquidevapor pressure of PAHs decreased, driving the partitioning more favorable in the particulate phase (Paasivirta et al., 1999). By developing a space-for-time substitution method, temporal variation in residential fuel consumption in China has been modeled recently to predict inter-annual and seasonal variations of air pollutant emissions (Zhu et al., 2013). The model was applied here to calculate emissions from residential energy consumption at various sites during the sampling period and tested as an independent variable to predict PAH concentrations using a regression model (Zhu et al., 2013). Gasoline consumption is added to the regression model as the motor vehicle source of atmospheric PAHs. The other two variables included are precipitation and wind velocity as the removal forces (wet deposition and diffusion, respectively) of atmospheric PAHs. The least-square fitted regression model is as follows:

logC ¼ 0:515 logE þ 0:347 logG  0:322 logW  0:444 logP þ 2:841;

R2 ¼ 0:48

where C, E, G, W, and P are measured PAH concentrations at urban sites (ng/m3), PAHs emission from residential energy consumption (g per capita), gasoline consumption (tce per capita), wind velocity (m/s), and precipitation (mm). All the regression coefficients are significant at a level of 0.05 except E (p ¼ 0.06). The relationship between the modeled and observed PAH concentrations in logscale is shown in Fig. S5. With the R2 of only 0.48 and no validation for additional data, the regression model cannot be used for prediction purpose. Instead, the analysis was conducted to identify main factors affecting the air concentrations. It was demonstrated that 48% of the variance in the atmospheric PAH concentrations can be explained by these factors. It should be noted that only data for the urban sites with meteorological and gasoline consumption data available were used in the analysis. PAH concentrations at rural village and rural field sites were not included due to the lack of relative parameters. To better characterize the spatial variations among different site categories, these factors in rural villages and rural fields should be taken into measurements in future. Many other factors including industrial emissions, long-range transport, and degradation can also affect PAH concentrations, which could not be characterized at this stage with limited information available. For the three site categories, the general trends of seasonal variation were similar to one another (Fig. 5), even though the concentrations are significantly different between the rural field and the other sites. In fact, the monthly mean PAH concentrations are significantly correlated to one another for both gaseous and particulate phase PAHs. However, subtle difference in seasonality can still be seen among three site categories. Even though the annual mean PAH concentrations were not significantly different between rural village (265 ± 564 ng/m3) and urban sites (220 ± 364 ng/m3) (p > 0.05) partly due to large variation, large difference can be seen in the winter, leading to the difference in rural village/urban concentration ratios between summer and winter (Fig. S6). The rural village/urban concentration ratios in winter were much higher than those in summer. As a matter of fact, more apparent seasonality in the rural villages than those in the cities was observed (Fig. 5). Monthly mean total PAH

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concentrations at all rural village sites (367 ± 670 ng/m3) were higher than those at all urban sites (295 ± 428 ng/m3) during the eight months from September to April. The probability of such difference caused by pure chance is as low as 0.039%. As the most important PAH emission source, combustion of solid fuels in rural residence area increases dramatically in winter because of heating demand. According to a survey of residential fuel consumption in Jilin, China, biomass consumption amount in winter is twice as much as that in summer (Qin et al., 2007). From May to August, however, PAH concentrations at all rural village sites (61.3 ± 27.2 ng/m3) were slightly lower than those at corresponding urban sites (73.0 ± 50.0 ng/m3). Without large volume fuel needed for heating, the major contribution of PAHs is from motor vehicles, which are mainly operated in urban areas. On the other hand, concentration ratios of rural field/urban and rural field/rural village show an inverse seasonality to that of urban/rural village (Fig. S6), suggesting non-linear relationship in PAH concentrations between sources (urban and rural village sites) and receptors (rural field sites). Although the composition profiles in all seasons were generally similar to one another, subtle differences can still be seen. For example, the fractions of the three dominant PAHs including PHE, FLA, and PYR were higher in summer than in winter, suggesting more contributions from motor vehicle emission sources (Chang et al., 2006). This is also confirmed by the relatively low ratios of ANT/(ANT þ PHE) and BaA/(BaA þ CHR) in summer (Fig. S7). 4. Conclusion Similarity in PAH concentrations in the rural villages and cities was found, suggesting that the heavy air contamination in rural China caused by high dependence on coal and biomass combustion deserves more concerns. Although economy is less developed in the west of China, and urbanization and industrialization still falls behind the east, PAH concentrations there were as high as those in the North China Plain, both of which were higher than those along the coastal area. A strong seasonality due to vast heating demands in winter and concentrated precipitation in summer was observed in all three site categories. Approximately 48% of the total spatial and seasonal variance in PAH concentrations can be explained by residential energy and gasoline consumption, wind velocity, and precipitation. Conflict of interest The authors declare no competing financial interest. Acknowledgment Funding for this study was provided by the National Natural Science Foundation (41130754, 41101490) and Beijing Municipal Government (YB20101000101). We thank Raymond M. Coveney Jr. (the University of Missouri-Kansas) for kind comments on the manuscript. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2014.04.039. References Anenberg, S.C., Balakrishnan, K., Jetter, J., Masera, O., Mehta, S., Moss, J., Ramanathan, V., 2013. Cleaner cooking solutions to achieve health, climate, and economic cobenefits. Environ. Sci. Technol. 47, 3944e3952.

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