Polycyclic aromatic hydrocarbon (PAHs) geographical distribution in China and their source, risk assessment analysis

Environmental Pollution 251 (2019) 312e327

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Polycyclic aromatic hydrocarbon (PAHs) geographical distribution in China and their source, risk assessment analysis+ Jun Han a, b, Yangshuo Liang a, Bo Zhao a, *, Yu Wang a, Futang Xing a, Linbo Qin a, ** a

Hubei Key Laboratory for Efficient Utilization and Agglomeration of Metallurgic Mineral Resources, Wuhan University of Science and Technology, Wuhan, 430081, PR China b Hubei Provincial Industrial Safety Engineering Technology Research Center, Wuhan University of Science and Technology, Wuhan, 430081, 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 2019 Received in revised form 10 April 2019 Accepted 5 May 2019 Available online 7 May 2019

In China, the huge amounts of energy consumption caused severe carcinogenic polycyclic aromatic hydrocarbon (PAHs) concentration in the soil and ambient air. This paper summarized that the references published in 2008e2018 and suggested that biomass, coal and vehicular emissions were categorized as major sources of PAHs in China. In 2016, the emitted PAHs in China due to the incomplete combustion of fuel was about 32720 tonnes, and the contribution of the emission sources was the sequence: biomass combustion > residential coal combustion > vehicle > coke production > refine oil > power plant > natural gas combustion. The total amount of PAHs emission in China at 2016 was significantly decreased due to the decrease of the proportion of crop resides burning (indoor and open burning). The geographical distribution of PAHs concentration demonstrated that PAHs concentration in the urban soil is 0.092e4.733 mg/g. At 2008e2012, the serious PAHs concentration in the urban soil occurred in the eastern China, which was shifted to western China after 2012. The concentration of particulate and gaseous PAHs in China is 1e151 ng/m3 and 1.08e217 ng/m3, respectively. The concentration of particle-bound PAHs in the southwest and eastern region are lower than that in north and central region of China. The incremental lifetime cancer risk (ILCR) analysis demonstrates that ILCR in the soil and ambient air in China is below the acceptable cancer risk level of 10
6 recommended by US Environmental Protection Agency (EPA), which mean that there is a low potential PAHs carcinogenic risk for the soil and ambient air in China. © 2019 Elsevier Ltd. All rights reserved.

Keywords: PAHs Soil Particulate Air Inventory Combustion

1. Introduction Polycyclic aromatic hydrocarbons (PAHs) are known as a group of environmental organic pollutants, which has received wide concerns due to their well-recognized carcinogenicity, teratogenicity and mutagenicity (Hu et al., 2017b; Qin et al., 2017; Chen et al., 2018c; Zheng et al., 2018). Hence, Sixteen PAHs, containing two to six carbon rings, have been classified as the priority pollutants by the Environmental Protection Agency in the United States (Qin et al., 2016; Hu et al., 2017b). These 16 PAHs include the 7 carcinogenic PAHs BaA (benz [a]anthracene) (4ering), Chr (chrysene) (4ering), BbF (benzo [b]fluoranthene) (5ering), BkF

+ This paper has been recommended for acceptance by Dr. Haidong Kan. * Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (B. Zhao), [email protected] (L. Qin).

https://doi.org/10.1016/j.envpol.2019.05.022 0269-7491/© 2019 Elsevier Ltd. All rights reserved.

(benzo [k]fluoranthene) (5-ring), BaP (benzo [a]pyrene) (5ering), DbA (dibenz [a,h]anthracene) (5ering), InP (indeno [1,2,3ecd]pyrene) (6ering), and 8 nonecarcinogenic PAHs Nap (naphthalene) (2ering), Acpy (acenaphthylene) (3ering), Acp (acenaphthene) (3ering), Flu (fluorene) (3ering), PhA (phenanthrene) (3ering), Ant (anthracene) (3ering), FluA (fluoranthene) (4ering), Pyr (pyrene) (4ering), and BghiP (benzo [g,h,i]perylene) (6ering) (Qin et al., 2018b). It was estimated the total PAHs emission in China was 25300 tonnes (Xu et al., 2006), and China was the country with the highest PAHs emission in the world, about 22% of the global emission of PAHs was originated from China in 2004 (Zhang and Tao, 2009; Shen et al., 2013). At present, there is a growing consensus that the main anthropogenic PAHs emission is incomplete combustion of carbonaceous materials during energy and industrial production process (Zhang and Tao, 2009; Han et al., 2012; Hsu et al., 2016; Han et al., 2017; Han et al., 2018b; Huang et al., 2018; Qin et al., 2018b; Zhu et al., 2019). Once released into the atmosphere, PAHs final destinations are sediment and soil by

J. Han et al. / Environmental Pollution 251 (2019) 312e327

atmospheric precipitation and rainfall due to their low solubility (Jiang et al., 2014). Hence, only a small proportion of PAHs exist in the ambient air or water (Wang et al., 2013a; Zhai et al., 2018). However, PAHs in the ambient air or water can be directly inhaled or drunk, which contributes to more serious human health problem (Gao et al., 2016). In China, the rapid industrialization and urbanization relocated many heavy pollution and energy intensive activity such as steel, coke, pesticide and chemical industries from urban areas to rural area, the status of PAHs pollution in China is also varied (Meng et al., 2015; Ohura et al., 2015; Zhang and Chen, 2017; Ma et al., 2018b). In this paper, PAHs concentrations in surface soil and ambient air were summarized according to the regional geography in China. At the same time, the comparison of PAHs concentration in the urban or rural soil before and after 2012 were carried out. According to the diagnostic ratios, the source of PAHs emission was discussed. Then, PAHs inventory was estimated based on the emission factor in references and China statistical yearbook (Ning, 2016). Lastly, the incremental lifetime cancer risk (ILCR) of PAHs was calculated and their potential risk was analyzed. 2. PAHs concentration in soil and air 2.1. PAHs concentration in the surface soil Wild and Jones reported that there was 90% of the environmental PAHs burden in Britain was stored in soil (Wild and Jones, 1995). As described in the literature (Shen et al., 2014), the emission amounts of PAHs in the different regions depended on fuel

313

consumption, biomass combustion the economic structure and climate. After the dispersion, PAHs concentration in the surface soil are expected to be different (Zhang and Chen, 2017). Zhang and Chen presented that the SPAHs concentration descended in the order of Northeast China (1.467 mg/g) > North China (0.911 mg/ g) > East China (0.737 mg/g) > South China (0.349 mg/g) > West China (0.209 mg/g) after reviewing 100 references, and the mean value of total 16 PAHs was 0.730 mg/g in the surface soil (Zhang and Chen, 2017). The regional geography in China was given in Fig. 1. Ma et al. reviewed the literature at 2004e2013 and stated that PAHs concentration was higher in eastern China and lower in middle and western China. Moreover, they found that the concentrations of P 16PAHs in Chinese rural soil ranged from 0.0037 to 6.250 mg/g P with the geometrical mean values of 0.147 mg/g, while 16PAHs concentration in Chinese urban surface soils were in the range of 0.030e23.300 mg/g, with the geometrical mean values of 0.584 mg/g (Ma et al., 2015). Sun et al. estimated that the total PAHs concentrations in the agricultural soil ranged from < LOD (limit of detection)) to 27.580 mg/g, with a mean of 0.772 ± 0.895 mg/g (n ¼ 40). In Northeast China, the concentrations of PAHs were higher than other regions due to extensive coal combustion and petroleum industrial operations (Sun et al., 2018). The experimental results of Ni et al. showed that the mean concentration of SPAHs in soil samples from different functional zones decreased in the order of gas stations (1.140 mg/g) > industrial areas (1.131 mg/g)> agricultural fields (0.514 mg/g) > residential areas (0.393 mg/g) > colleges and universities (0.245 mg/g) > parks (0.222 mg/g) (Ni et al., 2010). In general, the PAHs concentration is the highest at high-traffic sites, followed by park/residential sites and suburban sites, with rural

Fig. 1. The regional geography in China.

314

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Table 1 PAHs concentration in the surface soil of urban area (mg/g). Province

before 2012

Anhui Beijing Chongqing Fujian Gansu Guangdong

location

Sampling time after 2012

1.78 (Zhang et al., 2007) 0.093e1.314 (Peng, 2009) No available data 0.578 (Ni et al., 2010) 0.249 (Dong, 2010) 0.36e0.664 (Yang et al., 2008; Zhang et al., 2008a) Guangxi 0.18 (Miao et al., 2013) Guizhou 0.247e1.56 (Jian et al., 2011) Hainan No available data Hebei 0.55 (Zhao et al., 2009) Heilongjiang 0.508e0.527 (Ma, 2007; Ma and Li, 2009) Henan 0.109 (Zhou et al., 2012b) Hubei 0.991 (Xue et al., 2011) Hunan 1.43 (Tian et al., 2006)

Huai'an Beijing

No available Sep. 2008 No available Fuzhou Aug. 2007 Lanzhou Aug.2005 Guangzhou; Mar.eApr. 2006 Nanning 2009 Guiyang No available No available Baoding Jul.2007 Harbin Oct.2006 Shangqiu Nov.2011 Wuhan No available Changsha No available

Jiangsu

0.61 (Ge et al., 2008)

Xuzhou

No available

Jiangxi

4.21 (Gao, 2008)

Nanchang

Aug. and Oct.2007

Jilin Liaoning

0.484 (Bao, 2011) 0.65e1.23 (Wang et al., 2007)

Inner Mongolia Ningxia Qinghai Shaanxi

No available data

Changchun Dalian Apr. and Oct.2005 No available

No available data No available data 2.727 (Zhou et al., 2012a)

Shandong Shanghai Shanxi Sichuan Tianjin Xinjiang

0.394e1.08 (Wang et al., 2011) 0.092e3.78 (Jiang et al., 2011) 8.65 (Liu et al., 2008) 0.12e3.23 (Shi et al., 2010; Xing et al., 2011) 1.84 (Zuo et al., 2007) No available data

Jinan Shanghai Taiyuan Nanchong Tianjin

No available Oct.2007 No available Apr.2006 May.2001 No available

Tibet Yunnan

0.01 (Sun et al., 2007) 1.132 (Lin, 2012)

Lhasa Kunming

Dec.2004 Jul.2011

No available data 0.01 (Wang et al., 2014a) 0.21e0.591 (Wang et al., 2015b; Zhou and Lu, 2017b) 0.45e1.081 (Zhang et al., 2016a) 1.97 (Miao, 2013; Wang et al., 2013b) 0.723e6.315 (Gao, 2016) 3.106 (Zheng et al., 2018) No available 0.059 (Simayi et al., 2016; Chen et al., 2015a) No available data 0.10e1.034 (Lin et al., 2013; Yang, 2015a, b)

Zhejiang

0.08e3.88 (Ping et al., 2007; Sun, 2012)

Hangzhou

No available

0.611 (Yu et al., 2014b)

Xi'an

No available No available Aug.2008

sites containing the lowest levels of PAHs (Zhang et al., 2011; Lin et al., 2013; Chen et al., 2015b; Wang et al., 2017a). Based on the results of the 157 surface soil samples collected in 2005, PAHs concentrations in agricultural topesoil ranged from 0.277 to 3.217 mg/g with a mean concentration of 1.023 ± 0.815 mg/ g, the total concentrations of seven carcinogenic PAHs (C-PAHs) were between 0.045 mg/g and 1.147 mg/g, accounting for 6%e49% of the total PAHs (Liu et al., 2016b). Jiang et al. also thought the seven possible carcinogenic PAHs accounted for 4.8e50.8% of the total PAHs, and fluoranthene, pyrene, and benzo [b]fluoranthene were the most dominant components in soil samples (Jiang et al., 2011). In order to further understand PAHs concentration in the soil in China, we reviewed 160 references at 2002e2018, and summarized PAHs concentration in the soil in Tables 1e2. The sampling location was marked in Fig. 2. In the urban area, PAHs concentration in the soil was 0.092e4733 ng/g. The geographical distributions of PAHs in the surface soil were presented in Figss. 3 and 4. At 2008e2012, the serious PAHs contamination in the urban soil (the soil in the metropolis) occurred in the east China, which was shifted to west China after 2012. The new ambient air quality standards (GB30952012) was issued in 2012, which gave a limit of BaP in the ambient air. Hence, the temporal distribution of PAHs concentration in soil was divided into two stages. PAHs concentration in the urban topsoil of Xinjiang Province area was significantly increased after 2012. The increase rate of energy consumption in Xinjiang Province

3.636 (Hua, 2018) 1.004 (An et al., 2017) No available data 0.911 (Jiang et al., 2015) 0.084e10.9 (Ding et al., 2018a) 0.286 (Ke et al., 2017) 0.756 (Miao et al., 2018) 1.154 (Lin et al., 2015) No available data 0.607 (Yang et al., 2016a, b) 1.33e11.55 (Song et al., 2015) 0.433 (Wang et al., 2014c) 0.112e0.553 (Zhang et al., 2016b) 3.515e4.017 (Long et al., 2013)

location

Sampling time

Wuhu Beijing

Aug.2016 Aug. 2012 No available No available Jun. 2016 May. 2014

Fuzhou Lanzhou Guangzhou Liuzhou Guiyang

Xingtai Harbin Zhengzhou Wuhan Changsha eZhuzhou 0.975e3.3 (Wang et al., 2015a; Yang et al., Nanjing 2017b) 0.364 (Li, 2016) Nanchang No available data 0.123e3.675 (Li et al., 2018a; Liu et al., 2018b) 1.94 (Hou, 2014)

Aug. 2015 No available No available No available Oct. 2012 No available Oct. 2014 No available Jun.2014 Dec.2015

Shengyang

Mar. 2017

Hohhot

Jun.2013

Golmud Xi'an

No available No available No available

Qingdao Shanghai Taiyuan Chengdu Tianjin Urumqi

Dec.2013 Apr.2012 Oct.2013 No available No available May.2015

Kunming Hangzhou

No available Mar.2012 eMar.2014 No available

was the highest in the recent year according to energy statistic yearbook (Wang, 2017), which caused the variation of PAHs concentration in the topsoil. Zhang and Chen described that the mean concentration of SPAHs in the surface soil of Northeast China was 4e7 times higher than that of South China and West China (Zhang and Chen, 2017). In the rural area (suburbs of cities or countryside), PAHs concentration in the soil was found to be slightly decreased due to the prohibition of biomass open burning, as Figss. 5 and 6. 2.2. PAHs concentration in the air Polycyclic aromatic hydrocarbons (PAHs) are formed and released to the atmosphere during the incomplete combustion of fossil fuels and biomass, through both natural and anthropogenic processes (Han et al., 2018c; Qin et al., 2018a; Qin et al., 2018b). In the ambient air, PAHs are found in both gas phase and particulate phase. The fractions of individual PAHs of the total atmospheric concentrations in the particulate phase depended strongly on the molecular mass, and the particulateePAH accounts for 5%e39.8% of total PAHs (Gao et al., 2015; Dat and Chang, 2017; Han et al., 2018a). Adsorption and absorption are the two classical mechanisms that govern the association between PAHs and atmospheric aerosols, and hence gaseparticle partitioning (Yang et al., 2018). The distribution of PAHs between the gaseous and particulate phases was described by the partitioning coefficient (Kp) (Terzi and Samara, 2004; Wei et al., 2015a). PAHs gas/particle partitioning is

J. Han et al. / Environmental Pollution 251 (2019) 312e327

315

Table 2 PAHs concentration in the surface soil of rural area (mg/g). Province

before 2012

location

Sampling time

after 2012

location

Sampling time

Anhui Beijing

0.561e0.716 (Zhang et al., 2007) 0.139 (Li et al., 2010)

Huainan Beijing

No available 0.101 (Wei, 2016) Nov. 2008 0.258 (Li et al., 2017b)

Huainan Beijing

Chongqing Fujian

No available data 0.1e1.215 (Han et al., 2008)

Fuzhou

Sep.2007

No available Jun. and Sep. 2015 Nov.2013 No available

Gansu Guangdong

Shantou

Mar. 2002

Guangxi Guizhou

No available data 0.021e1.256 (Hao et al., 2007a; Hao et al., 2007b) 0.038 (Miao et al., 2013) 0.008e0.339 (Zhang et al., 2009)

Nanning Zunyi

Hainan Hebei Heilongjiang Henan

No available data 0.417 (Zhao et al., 2009) 0.03e0.870 (Ma et al., 2013) 0.152 (Zhou et al., 2012b)

Baoding Harbin Shangqiu

Hubei Hunan Jiangsu Jiangxi Jilin

0.089e0.312 (He, 2015) 0.28 (Zhang, 2009) 0.029e0.533 (Yin et al., 2008) 0.197 (Fan, 2009) 0.59 (Lu et al., 2010)

Wuhan Zhuzhou Nanjing Nanchang Jilin

Liaoning

0.223e1 (Wang, 2007; Wang et al., 2007) No available data

Dalian

Inner Mongolia Ningxia No available data Qinghai 0.07 (Sun et al., 2007) Shaanxi 0.073e0.595 (Li et al., 2011a) Shandong

0.027e0.128 (Yuan et al., 2008)

Shanghai

0.665e0.757 (Jiang, 2009; Jiang et al., 2011) 1.259 (Wang et al., 2011) 0.112e0.330 (Xu et al., 2009) 0.27e0.933 (Lv et al., 2010) 0.382 (Li et al., 2011b) 0.041 (Zhang, 2012b) 0.149e0.520 ( Lü et al., 2009a,b) 0.445 (Sun, 2012)

Shanxi Sichuan Tianjin Xinjiang Tibet Yunnan Zhejiang

Golmud Yanhe River basin yellow river delta Shanghai Datong Mianyang Tianjin Shihezi Lhasa Xuanwei Average of Zhejiang

0.75 (Lan et al., 2016) 0.177e0.482 (He and Zhang, 2014; Sun et al., 2016; Ding et al., 2018) No available data 0.100e1.04 (Zheng et al., 2014a)

Chongqing Longyan Fuzhou, Huizhou

No available

2009 0.038e3.351 (Long et al., 2017) Mar. 0.037e0.780 (Chen et al., 2017b; Fang et al., 2014) eAug.2008 No available data Aug.2007 0.399 (Wu et al., 2016) May. 2009 0.0137 (Wang et al., 2015c) Nov. 2007 0.139 (Li, 2015)

Nanning Bijie

Sep.2015 2014e2015

Handan Suihua Biyang

Jun. 2012 No available No available No available Autumn 2007 Apr.2005

0.122 (He, 2015) 0.078e0.534 (Yang et al., 2017a) 1.06 (Wang et al., 2015a) 0.242 (Li, 2016) 0.589e0.877 (Chen et al., 2018a; Chen et al., 2018b)

Xiangyang Yueyang Nanjing Jiujiang Changchun

No available No available Jun. and Sep. 2013 Jun.2013 Dec.2015 Jun.2014 Dec. 2015 Apr. 2016

0.326 (Li et al., 2017a)

Shengyang

No available

0.338 (Zhang and Zhang, 2017)

Hohhot

2013

Dec.2004 May. 2008

No available data 0.194 (Zhou et al., 2018; Xie et al., 2014) 0.589e0.72 (Ye, 2013; Pan et al., 2015)

Golmud Weinan

Jul.2013 May.2012

May.2006

0.227e1.137 (Chen et al., 2016b; Chai et al., 2017)

Shouguang

Jul.2015

Oct.2007

0.216e0.233 (Miao, 2013; Wang et al., 2016b)

Shanghai

May.2015

No available Apr.2006 Aug.2008 Aug. 2010 Oct. 2010 Jan.2007 No available

0.209e0.982 (Zhang et al., 2014; Gao, 2016) 0.032e1.13 (YanePing et al., 2013) 0.368 (Xu et al., 2018) 0.343e0.998 (Maimaiti et al., 2016) 0.267 (Zhou et al., 2018) 0.499e1.20 (Li et al., 2015a) 0.568 (Ping et al., 2019; Cha, 2015)

Taiyuan Mianzhu Tianjin Urumqi Lhasa Kunming Taizhou

Oct. 2013 No available Jun. 2017 May.2015 Jul. 2013 Ag.2013 No available

dependent on the molecular weight (MW) and vapor pressure. PAHs with MW  202 g/mol were mainly in the gaseous phase (>80%) while heavier PAHs (MW  252 g/mol) were associated with the particulate phase (>95%). Intermediate PAHs with MW ¼ 216e234 g/mol were partitioned between both phases (Tomaz et al., 2016). The distribution of compounds between gaseous and particulate phases is dependent upon temperature, air humidity, property of adsorption surface, available adsorption surface, molecular weight and vapor pressure. In particular, the high ambient temperatures could change the distribution of chemicals between the two phases by increasing the vapor pressure of compounds and favoring their volatilization from the particulate to the gaseous phase (Gregoris et al., 2014). Table 3 and Fig. 7 summarized the gaseous and particulate PAHs in the different region. The concentration of particulate PAHs in China is 1e151 ng/m3, which was comparable to that in Latin America (26e230 ng/m3) (S
anchez et al., 2016), and Korea (78e132 ng/m3) (Kim and Kim, 2015). However, it was higher than that measured in Croatia (2.8e20 ng/m3) (Alebi
ceJureti
c, 2015), _ Singapore (0.68e3.07 ng/m3) (Urban cok et al., 2017), Istanbul (0.05e7.4 ng/m3) (Kural et al., 2018), the United State of America (5.8e42.3 ng/m3) (Liu et al., 2017a), and Italy (3.8 ng/m3) (Donateo et al., 2014). Moreover, Table 3 also presented that the

concentration of particle associated PAHs in the southwest and east China was lower than that in north and central region China. The concentration of PAHs was basically higher in the winter than that in other seasons, the possible reason might be the residential heating resulting more biomass and domestic coal combustion as well as the unfavorable atmospheric diffusion and degradation conditions during the winter (Tang et al., 2017). Hence, the winter, PAHs emissions in north China were higher than those in south China (Liu et al., 2017b). In Table 3, the concentration of the particulate PAHs in Hebei, Jilin and Liaoning province is significantly higher than those of other region due to sampling in the winter. After reviewing the literature, it was found that the concentration of gaseous PAHs in China ranged from 1.08 to 217 ng/m3, which was lower than that of Indian rural area (28e496 ng/m3) (Salve et al., 2015). In India, the high PAHs concentration may also be due to higher emission from biomass burning, fuel used for cooking such as coal and kerosene and other heating activities to protect from cold winter. While biomass burning was strictly limited to reduce the pollutants emission. 3. Diagnostic ratios Diagnostic ratios identify the origin of the contamination by

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J. Han et al. / Environmental Pollution 251 (2019) 312e327

Fig. 2. Soil sampling location.

Fig. 3. PAHs concentration in the urban soil before 2012.

Fig. 4. PAHs concentration in the urban soil after 2012.

J. Han et al. / Environmental Pollution 251 (2019) 312e327

Fig. 5. PAHs concentration in rural soil.

317

2017). The ratios of FLA/(FLA/PYR) of atmospheric PAHs in Yangtze River Delta was the range of 0.49e0.61, which designated coal/ biomass burning and automobile exhaust as the major origin. The ratios of BaA/(BaA/CHR) exceeded 0.35 for all air samples, which indicated a dominant emission origin of vehicle exhaust (i.e., traffic tailing gas). Yi et al. also reported PAHs mainly came from biomass combustion in the winter at Fuzhou, while coal, biomass and diesel fuel combustion contributed to PAHs emission in the ambient air at the summer (Yi et al., 2013). As for PAHs in the soil, the ratios of FLA/(FLA/PYR) ranged from 0.32 to 0.70, with an average of 0.50, and the ratios of IcdP/ (IcdP/BghiP), which ranged from 0.32 to 0.61, with a mean of 0.52. Consequently, PAHs were largely derived from a mix of coal/biomass combustion and traffic exhaust. A minor amount could be attributed to petrogenic, such as petroleum leakage (Cai et al., 2017). The PAHs in the soil of Tianjin mostly originated from coal combustion (Zhu et al., 2014b). Based on the composition characteristics of PAHs and the ratios of Fla/(Fla þ Pyr) and BaA/(BaA þ Chr), the combustion of coal, biomass and automobile exhaust was responsible for PAHs emission, as shown in Table 4. 4. PAHs emission inventory in China

Fig. 6. PAHs concentration in the rural soil before 2012 after 2012.

comparing the relative concentrations of individual PAHs (fluoranthene (Flu), pyrene (Pyr), benz [a]anthracene (BaA), chrysene (Chr), indeno [1,2,3ecd]pyrene (InP); benzo [g,h,i]perylene (BgehiP), anthracene (Ant), phenanthrene (Phe), benzoe [a]pyrene (BaP), etc.) with welleknown references and thus qualitatively distinguishing petrogenic and pyrolytic sources. The boundary value of the Flu/(Flu þ Pyr) ratio for petroleum appears to be closer to 0.4 rather than 0.5, the values between 0.4 and 0.5 are more characteristic of liquid fossil fuel (vehicle and crude oil) combustion, and the values > 0.5 are characteristic of biomass, or coal combustion. The BaA/(BaA þ Chr) ratio < 0.2 implies petroleum, from 0.2 to 0.35 either petroleum or combustion, and >0.35 combustion. The InP/(InP þ BghiP) ratio ranging 0.2e0.5 is considered as good markers for petroleum source and 0.35e0.7 for diesel source (Yunker et al., 2002). Diagnostic ratios of particulate PAHs in Beijing demonstrated that the primary PAHs were originated from the diesel vehicle, gasoline vehicle, coal combustion and biomass burning (Chen et al.,

In general, the available literature as well as Table 4 suggested that coal, biomass combustion and vehicular emissions were categorized as major sources of PAHs in China. Zhang and Tao also reported biomass burning, including both biofuel combustion and wildfires, dominated the PAHs emission sources with contributions of 66.4% of the total PAHs emissions in China. Other important PAHs sources included traffic oil combustion, coke production and domestic coal combustion which contributed 2.0%, 14.4% and 10.7%, respectively (Zhang and Tao, 2009). PAHs emissions from the coke industry were predominately from smallescale coke ovens run by local farmers adjacent to coal mines (Zhang et al., 2008b). In the recent year, industrial structure was optimized due to the implementation of the more stringent environmental law or acts, and the smallescale coke oven or power plant were prohibited in China. Mu stated that PAHs were predominantly emitted from diesel vehicle emission (28.6%), followed by straw burning (24.5%), and domestic coal combustion (10.9%) (Mu, 2016). While Liu et al. thought coking industry and domestic coal combustion were the major PAHs emission sources, which accounted for 34.7% and 21.3% of total PAHs emission in Shanghai city. Additionally, natural gas and refining industry accounted for 15.6% and 10.7% of the total emission, respectively (Liu et al., 2015b). The emission factors (EFs) of PAHs was widely used to estimate the total PAHs emission. The parent polycyclic aromatic hydrocarbons (pPAHs) and oxygenated PAHs in the flue gas from coal combustion were in the range of 0.129e16.7 mg/g and 0.059e0.882 mg/g, respectively. Pergal et al. reported the emission factor of lignite combustion was 0.004e0.016 mg/g (Pergal et al., 2013), which was similar with the results of Yin et al. (2007). PAHs emission from coal domestic combustion was higher than that from the industrial furnace, and its value was 58e229 mg/g (Geng et al., 2014; Liu et al., 2015b). As for the coke oven, the emission factor was 0.439 mg/g (Liu, 2014). Gasoline and diesel combustion from the vehicle was another important emission source, and their emission factor were 0.072e4.3 and 0.014e2.4 mg/ g respectively (Miguel et al., 1998; Liu et al., 2015b). Kim et al. found wood fuel produced almost the same emission factor of the total of 18 PAHs (110 mg/g) as coal briquettes but twice as much as genotoxic PAHs, 13.4 vs 6.5 mg/g (Kim Oanh et al., 1999; Han et al., 2019). The emission factors of PAHs from combustion process were summarized in Table 5.Here, EPAHs is the output of PAHs, g; EFi is

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Table 3 PAHs concentration in the ambient air (ng/m3). Location

province

gaseous PAHs concentration

particulate PAHs concentration

Particle size

Sampling time

references

Hefei Beijing Chongqing

Anhui Beijing Chongqing

No available data No available data 6.27

29.19 87.8 29.92

PM2.5 PM2.5 PM2.5

Aug. 2013eJan. 2014 Jan.2015eDec.2015 Mar.eMay.2012

Fuzhou

Fujian

45.73

4.3e14.5

PM2.5

Lanzhou Guangzhou Nanning Guiyang

Gansu Guangdong Guangxi Guizhou

118e201 98 56.88 31.49

90e210 33.89 59.92 16.9

PM2.5 PM2.5 TSP PM2.5

Sep. 2007, Jan. 2018; JSpringSummer 2010 Jan. 2016-Dc.2016 Jun. 2012eMay.2013 Aug.2011eJan.2012 Aug.2012

Haikou Shijiazhuang Harbin Zhengzhou Wuhan

Hainan Hebei Heilongjiang Henan Hubei

No available data No available data 13.6 57.7 No available data

6.77 139.84 22.69 162 59.77

PM2.5 PM2.5 PM2.5 PM2.5 PM2.5

Zheng et al. (2014b) Wang et al. (2016a) (Zhao et al., 2014; Zhu et al., 2014a) (Zhang et al., 2013; Yi et al., 2013) (Wang, 2015; Wang et al., 2017) (Liu et al., 2015a; Li et al., 2016b) Ying and Kong (2016) (Lan et al., 2014; Zhou et al., 2016) Liu et al. (2016a) Zhang (2016) (Fu et al., 2016; Ma et al., 2010) (Li, 2015c; Zhang et al., 2016c) Li et al. (2018b)

Xiangtan Hunan Nanjing; Wuxi; Nantong, Jiangsu Suzhou Nanchang Jiangxi Jilin Jilin Shenyang Liaoning Hohhot Inner Mogolia Yingchuan Ninxia Xining Qinghai

No available data 56.8

19.31 19.04

PM2.5 PM2.5

Autumn.2014-Winter 2014 May.2015eApr.2016 Jan.eDec. 2014 Apr.eDec. 2013 Oct. 2011, Jan. 2012, Apr. 2012, Jul.2012 Dec. 2015, Feb.2016 Jan.2010eDec.2010

62.5 No available data No available data No available data

22.5 7.35 (114.7) 170.5 (average) 43.42

PM2.5 PM2.5 PM2.5 PM2.5

Jul.2010eJul.2011 Jul. 2016 (Dec. 2016) Apr. Aug. Oct. 2004 and Jan.2005 Jan.eDec.2015

57.89 No available data

99.42 43.73

PM2.5 PM10

Jinan Shanghai Xi'an

Shandong Shanghai Shaanxi

107.88 27.24 62.5e255 (62.5 sum)

26.74 7.14 82.57

PM2.5 PM2.5 PM2.5

Jul. 2016, Dec.2016 Mar. 2009, Mar. 2010 and May. 2010 Oct.2015eJul.2016 Jan.2016eJan.2017 Mar. 2012

Taiyuan Chengdu

Shanxi Sichuan

49.9 217

138.-547 71.38

PM2.5 PM2.5

Oct.2013eJul.2014 Dec.2011eJan.2012

Tianjin

Tianjin

No available data

70.0

PM2.5

Feb.2013eDec.2013

Urumqi

Xinjiang

14

37.68e254.24

PM2.5

Nov.2016eFeb.2017

Lhasa Kunming

Tibet Yunnan

150 227

10 22.07e40.67

TSP PM2.5

May.2002 Apr.2013eJan.2014

Hanzhou

Zhejiang

1.08

1.61

PM2.5

Mar.2015eSep. 2015

Fig. 7. Particulate PAHs concentration in the ambient air.

Wang et al. (2016c) (Yang et al., 2016a, b; Niu et al., 2017a) (Xiao, 2012; Liu et al., 2016c) Diao et al. (2018) Kong et al. (2010) Wei et al. (2017) Guo (2017) Shi et al. (2012) Li (2017) Jin (2018) (Niu et al., 2012; 2012a; Zhou et al., 2013) Xia et al. (2013) (Chen et al., 2015b; Yang et al., 2018) (Wang et al., 2015d; Niu et al., 2017b) (Simayi et al., 2018; Zhang et al., 2016e) Liu et al. (2013) (Bi et al., 2015; Yang et al., 2015a, b) Lu et al. (2017)

PAHs emission factor of i fuel combustion, g/kg; mi is the amount of i fuel, kg; The output of crop residues was estimated according to the ratio of residue/grain and the amount of grain (Liang et al., 2006; Ning, 2016). The indoor burning and open burning percentage of straw was summarized in Table 6 according to the statistic of renewable fuel in the rural area and satellite remoting sensing data (Satellite environmental center, 2016; China, 2017). According to China energy statistical yearbook, the energy consumption in different regions is presented in Table 7 (Wang, 2017). According to the data in Table 7, the total PAHs emission in China in 2016 was about 32720 tonnes. After the comparison with the estimated data in 2007 (about 106000 tonnes) (Shen et al., 2013), it was found the total amount of PAHs emission in China was significantly decreased. Although the consumption of coal was increased from 1283 million tone to 424900 million tonnes at 2003e2016, the biomass indoor burning and crop resides open burning was also decreased (Zhao et al., 2011). The alternative fuels such as electricity of natural gas were used as cooking fuels in the rural area. In 2010, the proportion of crop residue open burning in Henan province was 20.8% (Peng et al., 2016), which was decreased to 12% at 2014 (Le et al., 2017). The open burning of rice straw was prohibited due to its pollution and PAHs emission from rice straw open

J. Han et al. / Environmental Pollution 251 (2019) 312e327

319

Table 4 Diagnostic ratios of PAHs in topsoil or air. Index

1 2 3 4 5 6 7

Location

Inp/ (Inp þ Bgp)

Flt/ (Flt þ Pyr)

Bap/ (Bap þ Chr)

0.589

0.286 >0.5 >0.55 >0.5 0.63 <0.4 0.56

0.29

Source

reference

8 9 10

<0.4 >0.5 0.50

11

0.49e0.61

12 0.159e0.892 13 14 15 16 17

0.4e0.887

Straw, wood and coal combustion biomass combustion biomass and coal combustion biomass and coal combustion Coal, grass, and wood combustion petroleum input Coal, liquid fossil fuel and wood combustion Changchun farmland soil, Jilin petroleum sources residential areas of Xi'an in Shaanxi biomass, coal combustion Nanjing, Shanghai, Suzhou, Wuxi, Hangzhou surface coal/biomass combustion and traffic soil sources Nanjing, Shanghai, Suzhou, Wuxi, Hangzhou coal/biomass combustion and traffic atmosphere sources Lanzhou urban soil in Gansu biomass, coal and petroleum combustion

>0.5 >0.35 >0.5 0.181e0.728 0.138e0.608 0.13e0.51 0.17e1.0

soil of industrial district in Changzhi of Shaanxi arable soils in Beijing Soil of Yinma River basin in Jilin Soil of Wuhan in Hubei

coal, biomass, or petroleum combustion biomass and coal combustion coal, petroleum, andbiomass combustion pyrogenic origin

18 0.51 19 0.53 20 0.53 21 22 23 24 25

0.83 0.54 0.51 0.4e05 0.50 0.5 0.5

0.3

PM2.5 of Beijing PM2.5 of Jinan, Shandong PM2.5 of Jinan, Shanghai PM2.5 of Guiyang in Guizhou PM of Guangzhou in Guangdong PM of Guangzhou in Guangdong PM in Xi'an, Shaanxi PM in zhengzhou, Henan

26

0.5

0.4

PM in zhengzhou residential site, Henan

27 28

0.578 0.56

0.41 0.26

PM in Taiyuan, Shanxi PM in Hefei, Anhui

Gasoline, coal and biomass combustion; Gasoline, coal and biomass combustion; Oil, coal combustion, and vehicle combustion of biomass/coal vehicle emissions Coal, biomass combustion and vehicle coal combustion vehicle and grass, wood, or coal combustion grass, wood, or coal combustion and vehicle Coal combustion and vehicle coal and wood combustion and vehicle

0.51 0.38

0.33 0.29

0.47 0.46 0.33 0.02e0.49

Fujian, Jilin, Shanxi, Guizhou, Jiangxi garden and dry land in Tianjin Rural of Chongqing Rural in Jiangsu Rural in Shangdong cropland soil in Tianjin Rural in Hunan

Zhang et al. (2017a) Shi et al. (2017) Tian et al. (2017) Cao et al. (2017) Liu et al. (2017c) Shi et al. (2017) Li et al. (2015b) Chen et al. (2016c) Bao et al. (2018) Cai et al. (2017) Cai et al. (2017) Cai et al. (2017) Jiao et al. (2017) Liu et al. (2018a) Chen et al. (2018c) Gereslassie et al. (2018) Li et al. (2016a) Li et al. (2016a) Li et al. (2016a) (Fan et al., 2019) Liu et al. (2015a) Liu et al. (2015a) Xu et al. (2016) Wang et al. (2014b) Wang et al. (2014b) Li et al. (2014) Hu et al. (2017a)

Table 5 Emission factor of PAHs during combustion process. EPAHs ¼

n X

EFi  mi

(1)

i¼0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

fuel type

emission factor (mg/g)

reactor type

reference

wood rice straw straw Straw coke charcoal gasoline gasoline diesel diesel diesel MSW natural gas coal coal coal coal coal coal bituminous coals anthracite coals coal briquettes coal refine oil

110 0.0115e1.782 11.54e35.69 63 4.05 24 4.3 0.072 2.4 0.0143 0.5 252 0.001e2 0.004e0.016 0.002e0.018 0.1e0.2 0.0002 0.95 230 140.75e229.11 58.48e129.47 102 0.439 0.272

charcoal stove open burning open burning Indoor burning iron and steel plant coal briquette stove gasoline engine gasoline engine diesel engine diesel engine ship (Marine diesel engine) incinerator (mechanical grate) natural gas home appliances power plant power plant power plant power plant or Industrial furnace power plant or Industrial furnace domestic coal stove domestic coal stove domestic coal stove open burning in pile coke oven

Kim Oanh et al. (1999) Hai et al. (2008) Liu et al. (2015b) Shen et al. (2011a,b) Yang et al. (2002) Kim Oanh et al. (1999) Liu et al. (2015b) Miguel et al. (1998) Liu et al. (2015b) Miguel et al. (1998) Ravindra et al. (2008) Lee et al. (2002) Rogge et al. (1993) Pergal et al. (2013) Yin et al. (2007) Yuan et al. (2018) Liu et al. (2015b) Oros and Simoneit (2000) Liu et al. (2015b) Geng et al. (2014) Geng et al. (2014) Kim Oanh et al. (1999) Liu (2014) Liu et al. (2015b)

The amount of PAHs emission was calculated by Eq. (1).

320

J. Han et al. / Environmental Pollution 251 (2019) 312e327

Table 6 Straw domestic and open burning percentage of each province. province

Domestic burning percentage (%)

Open burning percentage (%)

province

Domestic burning percentage (%)

Open burning percentage (%)

Anhui Beijing Chongqing Fujian Gansu Guangdong Guangxi Guizhou Hainan Hebei Heilongjiang Henan Hubei Hunan Jiangsu Jiangxi

29 9.23 49.22 30 33.8 17 22.26 35 45 35 26 30 28.3 40 30 23

31.9 9.6 12.11 30 15.9 19.76 22.73 20 20 16.5 50 20 19.7 20 22.5 20

Jilin Liaoning Inner Mongolia Ningxia Qinghai Shaanxi Shandong Shanghai Jiangxi Sichuan Tianjin Xinjiang Tibet Yunnan Zhejiang

30 39.6 33.8 33.8 33.8 33.8 45 20 23 45 42 14.3 33.8 20 30

25.9 20 24.6 17.2 14.7 15.9 20 14.8 20 20 16.5 13.7 14.8 10 30

Table 7 Fuel consumption and PAHs formation from fuel combustion in China. province

industrial Coal consumption (million tonnes)

residential Coal consumption (million tonnes)

coke consumption (104 tonnes)

gasoline consumption (million tonnes)

natural gas diesel refine oil straw consumption (102 consumption consumption (million 3 (million tonnes) million m ) (million tonnes) tonnes)

EFs(mg/g) Anhui Beijing Chongqing Fujian Gansu Guangdong Guangxi Guizhou Hainan Hebei Heilongjiang Henan Hubei Hunan Jiangsu Jiangxi Jilin Liaoning Inner Mongolia Ningxia Qinghai Shanxi Shandong Shanghai Jiangxi Sichuan Tianjin Xinjiang Tibet

0.01 154.42 6.07 56.3 68 59.76 160.66 65.09 128.73 10.15 263.23 136.87 228.06 111.18 109.63 280.48 74.45 91.18 164.68 363.84

150 2.58 2.4 0.44 0.26 4.01 0.69 0.08 7.69 0 17.82 3.47 4.20 5.67 4.80 0 1.72 2.98 4.75 2.91

0.439 1164 0.21 384 608 548 782 1120 253 0 8079 184 3045 1095 960 3840 839 477 2993 1635

2 5.09 4.70 2.19 4.94 1.99 15.02 3.79 3.43 1.02 4.94 3.16 7.00 7.43 5.75 10.12 2.94 1.78 7.86 3.53

1 6.22 1.72 5.14 4.29 3.07 16.76 5.38 4.90 1.08 8.43 3.30 8.08 8.65 7.12 8.21 5.46 3.43 10.08 4.26

0.7 39.18 162.31 89.32 48.55 26.4 167.8 12.89 17.11 41.29 70.45 38.04 92.75 41.50 28.32 172.73 20.04 21.51 50.63 45.06

63a 825.57 4.20 304.48 114.98 242.57 243.44 830.00 268.88 74.05 919.32 1416.21 1475.12 582.68 839.39 749.98 343.32 882.16 620.88 726.63

10# 5.39 8.21 0 20.89 13.67 50.44 13.40 0 11.18 17.61 22.10 7.07 12.39 8.41 40.92 7.25 10.51 70.57 4.19

2.72 1252.12 397.93 382.89 229.25 892.29 537.27 898.62 1437.23 107.71 3709.23 2009.06 2166.77 1498.18 1607.82 915.14 638.12 1368.58 1570.53 1199.21

86.27 18.72 193.48 402.82 46.06 346.85 86.85 41.57 184.56 No available data

0.38 0.90 3.22 6.57 0.19 9.36 1.84 0.73 5.29 No available data

450 228 840 3718 596 2198 1636 887 804 No available data

0.28 0.56 2.57 7.39 6.37 2.28 9.40 2.74 2.76 No available data

1.24 1.28 4.09 13.68 5.62 5.36 8.0 3.70 6.51 No available data

22.40 46.25 98.22 98.61 79.04 69.35 181 74.53 132.38 No available data

84.00 26.63 308.48 1655.59 12.81 232.18 1048.59 62.40 178.00 9.34

5.76 1.49 18.23 102.03 24.74

162.00 169.68 857.34 2973.20 130.98 1662.86 1386.58 186.77 1057.09 9.34

Yunnan Zhejiang PAHs emission

70.73 138.88 41.50

3.88 0.6 14914.50

912 329 237.67

3.40 7.96 284.78

6.01 8.81 179.88

7.71 87.78 1.49

358.50 156.37 15596.77

a Indoor burning of straw # open burning of straw

9.02 24.52 No available data 0 26.67 145.97

PAHs (tonnes)

959.51 347.04 32720.33

.

burning was sharply decreased (Hai et al., 2008). The above reasons were responsible for the variation of PAHs emission in China. Table 7 also demonstrated that the biomass combustion (indoor burning and open burning) was the major PAHs emission source. Zhang et al. also thought crop residue combustion was the largest PAHs emission source in China (Zhang et al., 2008b). Laboratory scale tests were carried out to investigate the

emission factors of 15 PAHs from rice straw burning, and on this base, the annual emission of PAHs from rice straw open burning in Jiangsu Province were 39.2 tonnes (Hai et al., 2008). PAHs emitted from Hebei, Shandong, Henan, Anhui, Guangxi, Heilongjiang, Hunan, Sichuan was significantly higher the national average value due to their grain output, as listed in Table 7. The residential coal consumption was the secondary PAHs emission

J. Han et al. / Environmental Pollution 251 (2019) 312e327

321

Table 8 PAHs concentration in the surface soil (mg/g).

Xi'an (Shaanxi) Chengdu (Sichuang) Deyang (Sichuang) Mianyang (Sichuang) Shanghai Yangtze River Delta Lanzhou (Gansu) Wuhan (Hubei) Kunming (Yunnan) Tianjin Shenyang (Liaoning) Jilina (Shangdong) Minjianga (Fujian) Linfena (Shanxi) Hohhota (Inner Mongolia) Shenyanga (Liaoning) Beijinga Taiyanga (Shanxi) Urumqia (Xinjiang) Nanjinga (Jiangsu) a

Nap

Acy

Ace

Flu

PhA

AnT

FluA Pyr

BaA

Chr

BbF

BkF

BaP

DbA

BghiP InP

reference

0.229 0.106 0.179 0.04 0.114 0.013 0.215 0.006

0.014 0.00778 0.0291 0.0008 0.003 0.002 0.011 0.002 0.005 0.020 ND 0.004 0.046 0.006 0.001

0.004 0.00591 0.0334 0.0007 0.003 0.00 0.008 0.002 0.003 0.016 ND ND 0.004 0.004 0.001 0.044 0.001 0.005 0.033 ND

0.023 0.0327 0.162 0.012 0.021 0.012 0.016 0.003 0.016 0.045 279 0.009 0.007 0.011 0.004 0.047 0.008 0.014 0.030 0.007

0.074 0.3075 0.982 0.068 0.110 0.030 0.084 0.033 0.074 0.446 614 0.022 0.019 0.076 0.032 0.039 0.054 0.16 0.034 0.042

0.003 0.0465 0.413 0.008 0.021 0.004 0.16 0.004 0.004 0.051 225 ND 0.011 0.021 0.004 0.002 0.003 0.038 0.031 0.020

0.056 0.599 1.121 0.029 0.066 0.044 0.282 0.056 0.068 0.531 414 0.014 0.047 0.091 0.022 0.029 0.027 0.239 0.082 0.069

0.017 0.326 0.671 0.014 0.037 0.021 0.316 0.027 0.018 0.231 154 0.003 0.009 0.041 ND 0.002 0.006 0.173 0.081 0.077

0.041 0.483 0.47 0.038 0.039 0.025 0.084 0.042 0.042 0.378 142 0.005 0.034 0.083 0.024 0.061 0.010 0.159 0.157 0.076

0.034 0.759 1.353 0.038 0.060 0.023 0.646 0.06 0.055 0.665 157 0.010 0.042 0.089 0.003 0.014 0.039 0.268 0.080 0.100

0.024 0.397 1.039 0.011 0.025 0.008 0.143 0.017 0.016 0.215 58 ND 0.012 0.035 0.023 0.007 0.012 0.116 0.126 0.032

0.022 0.313 0.749 0.0179 0.034 0.014 0.052 0.034 0.029 0.460 152 0.002 0.022 0.052 0.017 0.007 0.014 0.150 0.048 0.050

0.017 0.457 0.572 0.0204 0.008 0.01 0.295 0.034 0.005 2.089 19 ND 0.005 0.049 0.011 0.002 0.007 0.084 0.020 0.066

0.037 0.183 0.225 0.009 0.018 0.003 0.176 0.010 0.027 0.595 74 ND 0.036 0.013 0.062 0.009 0.028 0.149 0.131 0.043

Zhou and Lu (2017a) Zheng et al. (2018) Zheng et al. (2018) Zheng et al. (2018) Cao et al. (2017) Cai et al. (2017) Jiang et al. (2016) Wu et al. (2018) Yang et al. (2015a, b) Yu et al. (2014a) Wei et al. (2015b) Chen et al. (2016a) Sun et al. (2016) Tao et al. (2016) Zhang and Zhang (2017) Li et al. (2017a) Li et al. (2017b) Gao (2016) Maimaiti et al. (2016) Zhu et al. (2016)

0.068 2700 0.031 0.145 0.027 0.089 0.002 0.004 0.021 0.007 ND

00001 0.028 0.009 ND

00014 0.416 0.788 0.020 0.053 0.038 0.235 0.041 0.044 0.366 ND 0.010 0.017 0.071 0.018 0.011 0.018 0.179 0.051 0.075

0.023 0.346 0.452 0.022 0.023 0.011 0.279 0.035 0.025 1.813 67 ND 0.016 0.049 0.027 0.009 0.023 0.182 0.022 0.054

Meaning the rural area.

Table 9 PAHs concentration in air (ng/m3).

Beijin Haerbin (Heilongjiang Lanzhou (Gansu Xi'an (Shaanxi) Daliang (Liaoning) Chengdu (Sichuang) Guangzhou (Guangdong) Kunmin (Yunnan Taigua (Shanxi) Anshuna (Guizhou) Xi'an (Shaanxi) Mianyanga (Sichuang) Qujinga (Yunnan) Nanning (Guangxi) Shanghai Nanjing (Jiangsu) Zhengzhou (Henan) Xiamen (Fujian) Wuhan (Hubei) Kunming a

Nap

Acy

Ace

Flu

PhA

AnT

FluA

Pyr

BaA

Chr

BbF

BkF

BaP

DbA

BghiP

InP

reference

4.14 20.2 24.5 10.8 9.96 7.40 1.77 7.27 297.2 73.8

10.3 6.93 45.3 10.9 6.92 13.9 0.61 11.3 162.3 39.3 2.9 0.44 22 ND 0.88 1.29 ND ND 0.05 0.05

2.31 1.62 9.41 3.45 3.57 4.29 0.28 2.81 71.7 39.1 1.6 0.63 56 0.6 0.29 1.53 0.3 ND 0.01 0.93

22.0 7.22 57.2 24.2 17.0 29.1 4.37 28.4 155.2 45 1.0 2.3 295 10.76 0.55 3.36 4.8 ND 0.08 1.76

46.3 22.4 120 63.3 72.4 94.3 46.7 116 235 30.6 3.4 11.4 669 23.89 5.71 14.14 35 1.0 2.75 1.12

7.20 2.12 17.1 6.35 4.75 7.81 2.71 11.5 26.8 4.1 1.1 0.59 158 0.59 0.43 1.84 1.5 0.19 0.23 14.45

25.6 11.5 57.1 24.7 21.7 43.4 13.9 36.5 159.1 14 8.6 5.67 81 ND 8.02 5.14 11.5 0.30 2.13 15.75

18.9 8.32 38.2 15.3 13.9 28.1 9.48 25.0 111.4 21.2 9.1 4.67 64 ND 6.64 7.15 7.6 0.27 2.19 2.36

11.3 3.13 17.0 3.89 2.77 7.40 1.29 5.98 70.9 4.3 8.5 0.74 53 0.99 6.34 1.79 4.48 0.15 1.49 3.4

11.2 3.76 22.1 6.95 3.85 13.5 2.32 8.51 113.5 5.5 17.3 1.8 58 2.13 6.07 2.07 1.2 0.46 3.08 3.44

16.0 2.89 21.1 7.11 2.71 14.6 2.06 6.53 101.7 8.9 13.6 1.44 45 1.14 7.67 1.66 1.5 0.44 4.86 0.36

7.74 2.25 13.2 4.20 2.18 8.04 1.38 4.70 59.6 3.3 8.6 0.87 27 0.42 ND 1.88 1.54 0.48 1.40 0.87

8.48 2.47 11.5 3.74 2.02 7.74 1.01 4.74 61 4 9.3 0.67 37 0.24 5.32 1.51 2.11 0.18 1.91 0.24

2.21 0.56 3.46 0.98 0.59 1.95 0.34 1.27 11.4 0.1 5.0 0.1 10 ND 5.36 0.36 0.73 0.08 0.22 0.23

7.07 2.13 10.8 4.94 1.52 8.92 1.53 5.50 64.6 2.9 10.1 0.6 45 0.53 1.11 1.19 3.34 0.59 2.04 0.88

6.50 2.00 10.1 4.04 2.16 7.73 1.41 4.49 37.1 3 9.4 0.6 39 0.56 6.16 1.27 637 0.45 2.22 1.04

Ma et al. (2018a) Ma et al. (2018a) Ma et al. (2018a) Ma et al. (2018a) Ma et al. (2018a) Ma et al. (2018a) Ma et al. (2018a) Ma et al. (2018a) Du et al. (2018) Du et al. (2018) Wang et al. (2017b) Zhuo et al. (2017) Zhang et al. (2010) Miao and Kong (2016) Liu et al. (2018c) Wang et al. (2017c) Zhang et al. (2016b) Zhang et al. (2018) Zhang et al. (2019) Yang et al. (2015a, b

0.61 51 15.02 1.38 2.29 ND ND 1.01 1.04

Meaning the rural area.

source, which accounted for 9.3% of the total PAHs emission. The emission of PAHs from motor vehicles in China were about 460 tonnes, which was lower than the data predicted by Shen et al. (Shen et al., 2011a,b). Shen et al. estimated the total PAHs from vehicles in 2016 was about 18000 tonnes. However, Limits and measurement methods for emissions from lighteduty vehicles (China 6) was issued and PAHs emission was decreased. The other PAHs emission source was followed the sequence according to the proportion: vehicle > coke production > refine oil > power plant > natural gas combustion.

10
6 incidence for an individual carcinogen and 10
4 incidence for cumulative risk from multiple carcinogens (Chen et al., 2018c). The ILCRs were calculated according to the following equations: ILCRsingestion ¼

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðBW=70ÞÞ  IRingestion  EF  ED

CS  ðCSFingestion 

BW  AT  106 (2)

ILCRsinhalation ¼

CS  ðCSFinhalation 

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðBW=70ÞÞ  IRinhalation  EF  ED BW  AT  PEF (3)

5. Risk assessment The incremental lifetime cancer risk (ILCR) was used to identify the different age groups and different exposure modes of the integrated lifetime risks that exposure to environmental PAHs pollution. The ILCRs (unitless) included ingestion, dermal contact and inhalation.(Chen et al., 2018c). The US Environmental Protection Agency (EPA) recommends an acceptable cancer risk level of

where CS is the sum of converted PAHs concentrations for 7 CarPAHs based on toxic equivalents of BaP using the Toxic Equivalency Factor (TEF). CSF is carcinogenic slope factor (mg kg
1 day
1)
1, BW is the body weight of the exposed local resident (kg), AT is the average lifespan (years), EF is the exposure frequency (day year
1), ED is the exposure duration (years), IRingestion is the soil ingestion rate (mg day
1), IRinhalation is the inhalation rate (m3 day
1), and

322

J. Han et al. / Environmental Pollution 251 (2019) 312e327

Table 10 Risk of cancer due to human exposure to PAHs in soil and air. Place

ILCRingestion Child

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 a

Xi'an (Shaanxi) Chengdu (Sichuang) Deyang (Sichuang) Mianyang (Sichuang) Shanghai Yangtze River Delta Lanzhou (Gansu) Wuhan (Hubei) Kunming (Yunnan) Tianjin Shenyang (Liaoning) Jilina (Shangdong) Minjianga (Fujian) Linfena (Shanxi) Hohhota (Inner Mongolia) Shenyang (Liaoning) Beijinga Urumqia (Xinjiang) Nanjinga (Jiangsu)

Place Adolescence


7

2.46  10 3.69  10
6 6.48  10
6 1.82  10
7 2.21  10
7 1.18  10
7 1.88  10
6 3.17  10
7 1.78  10
7 1.10  10
5 8.56  10
4 1.32  10
8 1.38  10
7 4.76  10
7 1.32  10
7 5.03  10
8 1.17  10
7 3.93  10
7 5.53  10
7


7

1.57  10 2.35  10
6 4.13  10
6 1.16  10
7 1.41  10
7 7.53  10
8 1.20  10
6 2.02  10
7 1.13  10
7 6.98  10
6 5.46  10
4 8.42  10
9 8.81  10
8 3.03  10
7 8.41  10
8 3.20  10
8 7.47  10
8 2.50  10
7 3.52  10
7

Adulhood
7

3.00  10 4.50  10
6 7.89  10
6 2.22  10
7 2.70  10
7 1.44  10
7 2.29  10
6 3.87  10
7 2.17  10
7 1.34  10
5 1.04  10
3 1.61  10
8 1.68  10
7 5.80  10
7 1.61  10
7 6.13  10
8 1.43  10
7 4.79  10
7 6.73  10
7

ILCRinhalation Child

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Beijin Haerbin (Heilongjiang Lanzhou (Gansu Xi'an (Shaanxi) Daliang (Liaoning) Chengdu (Sichuang) Guangzhou (Guangdong) Kunmin (Yunnan Taigua (Shanxi) Anshuna (Guizhou) Xi'an (Shaanxi) Mianyanga (Sichuang) Qujinga (Yunnan) Nanning (Guangxi) Shanghai Nanjing (Jiangsu) Zhengzhou (Henan) Xiamen (Fujian) Wuhan (Hubei) Kunming

Adolescence
9

1.24  10 3.42  10
10 1.78  10
9 5.66  10
10 3.12  10
10 1.14  10
9 1.71  10
10 7.03  10
10 8.32  10
9 5.23  10
10 1.51  10
9 9.66  10
11 5.46  10
9 5.14  10
11 1.04  10
9 5.47  10
9 3.46  10
11 2.59  10
10 1.01  10
10 1.24  10
9


9

2.56  10 7.08  10
10 3.69  10
9 1.17  10
9 6.45  10
10 2.35  10
9 3.54  10
10 1.46  10
9 1.72  10
8 1.08  10
9 3.13  10
9 2.00  10
10 1.13  10
8 1.06  10
10 2.15  10
9 1.13  10
8 7.16  10
11 5.36  10
10 2.10  10
10 2.56  10
9

Adulhood 4.83  10
9 1.34  10
9 6.97  10
9 2.22  10
9 1.22  10
9 4.44  10
9 6.69  10
10 2.75  10
9 3.26  10
8 2.04  10
9 5.91  10
9 3.78  10
10 2.13  10
8 2.01  10
10 4.06  10
9 2.14  10
8 1.35  10
10 1.01  10
9 3.96  10
10 4.83  10
9

Meaning the rural area.

PEF is the particle emission factor (m3 kg
1). CSFingestion, and CSFinhalation of BaP were assigned as 7.3 and 3.85 (mg kg
1 day
1)
1, respectively, based on the cancerecausing ability of BaP. Tables 8 and 9 summarized PAHs concentration in the soil or air of part regions, and ILCRs were calculated according to Eqs. (2) and (3). Table 10 presented that ILCRinggetion in the most region ranged from 10
7 to 10
8, which were below the baseline of acceptable risk (1.0  10
6). However, PAHs of soil in Chengdu (Sichuang), Deyang (Sichuang), Lanzhou (Gansu), Tianjin, Shenyang (Liaoning) were relatively high, and ILCRs were the magnitude of 10
6e10
4, which had a high carcinogenic risk. Moreover, it was also found that ILCRs for child were higher than adults due to their hand to mouth activity (Chen et al., 2018c). Zhu et al. claimed that the mean value of the ILCRs for urban were noticeably higher than those for rural residents (Zhu et al., 2019). As for PAHs in the ambient air, ILCRinhalation was 10
3e10
4 times lower than ILCRingestion, and ranged 10
8e10
10, the above data mean that the ingestion mad more contribution to cancer risk. Meanwhile, ILCRinhalation had an important relation with weather. In northern China, the heating supply consumes more fuel and emitted more PAHs. ILCR in Taiyuan induced by the inhalation exposure for all age groups were larger than 10
6 in spring and winter, while the values for male and female adults in summer and autumn were also larger than 10
6 (Zhang et al., 2016d). The above results indicated soil and ambient air in China had a low carcinogenic risk. However, the potential risk was still existed in part of regions. Since children were more vulnerable to higher cancer risk due to the differences of behavior. Therefore, more protective measures should be taken to protect children from damaging, especially in winter and autumn (Liu et al., 2018c).

was the sequence: biomass combustion > residential coal combustion > vehicle > coke production > refine oil > power plant > natural gas combustion. Moreover, the geographical distribution of PAHs concentration in urban and rural soil was also presented. It was found that PAHs concentration in the urban soil was 0.092e4.733 mg/g, and PAHs concentration in the top soil of east cities was higher than that of the western cities. At 2008e2012, the serious PAHs contamination in the urban soil occurred in the east China, which was shifted to western China after 2012. Especially, PAHs concentration in the urban topsoil of Xinjiang Province area was significantly increased after 2012 due to the significantly increase of energy consumption. In the rural soil, PAHs concentration ranged 0.1e1.259 mg/g at 2008e2018, and PAHs concentration in rural soil was above 0.8 mg/ g was disappeared due to reducing biomass burning (indoor and open burning). The concentration of particulate and gaseous PAHs in China is 1e151 ng/m3 and 1.08e217 ng/m3, respectively. The concentration of particle associated PAHs in the southwest region and eastern is lower than that in north and central region China. The incremental lifetime cancer risk (ILCR) analysis demonstrated that ILCR in the soil and ambient air in China was below the acceptable cancer risk level of 10
6 recommended by US Environmental Protection Agency (EPA), which meant that there was a low potential carcinogenic risk for the soil and ambient air in China. Acknowledgements The present work is supported National Natural Science Foundation of China (Grant No. 51576146&51706160) and Foundation for Outstanding Youth Innovative Research Groups of Higher Education Institution in Hubei Province (T201906).

6. Conclusions Appendix A. Supplementary data The huge amounts of energy consumption caused severe carcinogenic PAHs concentration in the soil and ambient air in China. This paper summarized that the references published in 2008e2018 and suggested that biomass, coal and vehicular emissions were categorized as major sources of PAHs in China. In 2016, the total PAHs emission in China due to the incomplete combustion was about 32720 tonnes. The contribution of the emission sources

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