Distribution and ecological risk of substituted and parent polycyclic aromatic hydrocarbons in surface waters of the Bai, Chao, and Chaobai rivers in northern China

Journal Pre-proof Distribution and ecological risk of substituted and parent polycyclic aromatic hydrocarbons in surface waters of the Bai, Chao, and Chaobai rivers in northern China Meng Qiao, Lujing Fu, Zhuorong Li, Dongqing Liu, Yaohui Bai, Xu Zhao PII:

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DOI:

https://doi.org/10.1016/j.envpol.2019.113600

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ENPO 113600

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Environmental Pollution

Received Date: 5 July 2019 Revised Date:

18 September 2019

Accepted Date: 8 November 2019

Please cite this article as: Qiao, M., Fu, L., Li, Z., Liu, D., Bai, Y., Zhao, X., Distribution and ecological risk of substituted and parent polycyclic aromatic hydrocarbons in surface waters of the Bai, Chao, and Chaobai rivers in northern China, Environmental Pollution (2019), doi: https://doi.org/10.1016/ j.envpol.2019.113600. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

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Distribution and ecological risk of substituted and parent

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polycyclic aromatic hydrocarbons in surface waters of the

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Bai, Chao, and Chaobai rivers in Northern China

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Meng Qiaoa,b, Lujing Fua, Zhuorong Lia, Dongqing Liua, Yaohui Baia, Xu Zhaoa,c,*

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a

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Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

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b

Key Laboratory of Drinking Water Science and Technology, Research Center for

Key Laboratory of Eco-restoration of Regional Contaminated Environment

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(Shenyang University), Ministry of Education, Shenyang 110044, China

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c

University of Chinese Academy of Sciences, Beijing 100049, China

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Abstract

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Like their parent polycyclic aromatic hydrocarbons (PAHs), substituted polycyclic

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aromatic hydrocarbons (SPAHs), including methyl PAHs (MPAHs), oxygenated PAHs

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(OPAHs), and chlorinated PAHs (ClPAHs), exist ubiquitously in urban and

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agricultural rivers. Although laboratory studies have found the biological toxicities of

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certain SPAHs to be higher than that of their parent PAHs, the ecological risk of

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SPAHs in rivers has been largely ignored. Here, we studied the distribution, source

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and transport of PAHs and SPAHs as well as ecological risks in the Chaobai River

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System, which experiences a high level of anthropogenic activity. The results show

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that the concentration of ΣOPAHs (321 ± 651 ng/L) was higher than that of ΣPAHs

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(158 ± 105 ng/L), ΣMPAHs (28 ± 22 ng/L), and ΣClPAHs (30 ± 12 ng/L). We also

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found that (S)PAHs in Chaobai River mainly originated from Beiyun River (53%–

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65%), which receives considerable municipal wastewater treatment plant effluent

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from Beijing. The major transport pathway of (S)PAHs from Chaobai River was

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likely for irrigation (83%–86%) and transportation into Yongdingxin River (13%–

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16%), which finally merged into the Bohai Sea. The mixed chronic risk of (S)PAHs

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(risk quotient = 45 ± 53) was higher than the mixed acute risk (risk quotient = 1.9 ±

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1.4), with all sites facing chronic risk and 90% of sites experiencing acute risk.

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Although the chronic and acute risks of (S)PAHs to plants, invertebrates, and

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vertebrates were mainly from PAHs (97.5% to chronic risk and 96.5% to acute),

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SPAHs still posed a chronic risk to invertebrates and vertebrates (risk quotient > 1).

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Accordingly, the ecological risk of (S)PAHs in Chaobai River should be taken into 2

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consideration for ecosystem protection. The transmission of PAHs and SPAHs from

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Chaobai River may also pose potential risks to farmland through irrigation, as well as

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to the Bohai Sea via river water discharge.

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Capsule:

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SPAHs posed significant chronic risk to invertebrates and vertebrates in Chaobai

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River, although the high acute and chronic risks were primarily from PAHs (> 95%).

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Keywords: Polycyclic aromatic hydrocarbons; Substituted polycyclic aromatic

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hydrocarbons; Source; Transport pathway; Aquatic ecological risk; Taxonomic groups

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1. Introduction

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Currently, 16 priority polycyclic aromatic hydrocarbons (PAHs) have been

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designated by the US Environmental Protection Agency (US EPA) as persistent and

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ubiquitous in aqueous environments (Yao et al., 2017). Recent research has also

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shown substituted PAHs (SPAHs) to be widely distributed in aqueous environments at

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similar or even higher concentrations than PAHs (Qiao et al., 2018; Qiao et al., 2017a).

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The sources of SPAHs in the environment are similar to those of PAHs and include

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emissions from incomplete combustion of fossil fuels and vehicle exhaust (Tsapakis

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and Stephanou, 2007; Yoshino and Urano, 1997). Furthermore, some SPAHs can be

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transformed from their corresponding PAHs through photochemical and biological

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reactions (Iino et al., 1999; Lundstedt et al., 2007). Importantly, based on laboratory

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research, the toxicities of some SPAHs are reported to be higher than that of their

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corresponding PAHs. For example, although parent PAHs, such as anthracene, pyrene,

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fluoranthene and chrysene are considered to be non- or weakly carcinogenic, their

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corresponding chlorinated PAHs (ClPAHs) are highly mutagenic when tested against

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Salmonella typhimurium TA 98 and TA 100 (Durant et al., 1996; Lofroth et al., 1985).

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In addition, while anthracene exhibits no estrogenic activity, its corresponding

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oxygenated PAHs (OPAHs) anthraquinone has shown detectable estrogenic activity

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(Machala et al., 2001). Similarly, the estrogenic activity of OPAHs benzanthrone and

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benz[a]anthracene-7,12-dione are higher than that of their corresponding parent PAH

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benz[a]anthracene (Machala et al., 2001). Therefore, when assessing the ecological

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toxicities of PAHs, SPAHs should also be considered. 4

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The ecological risks of PAHs have been assessed previously using risk quotient

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(RQ) and species-sensitivity distribution (SSD) methodologies (Aziz et al., 2014; Cao

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et al., 2010; Hu et al., 2017; Liang et al., 2019; Liu et al., 2010; Tang et al., 2017;

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Zhang et al., 2017). Earlier research in the Hai River Basin of China identified high

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and moderate risks in several estuaries using the RQ method, with 3-ring and 4-ring

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PAHs accounting most for most of the ecological risk caused by PAHs (Yan et al.,

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2016). However, mixed RQs can overestimate the risk to an ecosystem if species

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exhibit different sensitivities to different target compounds, and therefore should only

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be used as a first-step indicator of ecological risk (Dudhagara et al., 2016; Gdara et al.,

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2018; Li et al., 2015; Meng et al., 2019). Accordingly, the SSD method was developed

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to describe variation in species sensitivity with statistical distribution functions (De

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Zwart and Posthuma, 2005) and assess the spatial distribution differences in

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ecological risk. For example, in Chaohu Lake, China, the multi-substance potentially

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affected fractions (msPAFs) of seven PAHs were obtained by the SSD model and

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varied from 0.29% to 1.58%, lower than the 5% threshold, with Pyr presenting the

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greatest ecological risk, followed by Ant, Flua, Phe, Nap, Fluo and Ace (Qin et al.,

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2013). However, as the toxic action mechanism of compounds can differ depending

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on the type of recipient species, a mixed risk taxon-specific method was developed

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based on the SSD method, known as the RQ_EQS_Taxa approach (Junghans et al.,

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2013; Spycher et al., 2018). This approach first classifies organisms into three

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taxonomic groups, i.e., plants (P), invertebrates (I) and vertebrates (V). The most

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sensitive species to each target compound is then chosen to calculate the acute and 5

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chronic quality criteria (AQC and CQC), which are derived based on maximum

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acceptable concentration environmental quality standard (MAC-EQS) and annual

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average environmental quality standard (AA-EQS), respectively. Acute and chronic

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quality criteria are calculated combined and separately for each of the three groups.

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As such, the resulting RQ_EQS_Taxa values more closely reflect the ecological risk of

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PAHs than the RQ or SSD methods. To date, however, the ecological risk of SPAHs in

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aquatic environments has been rarely reported. Therefore, we used the RQ_EQS_Taxa

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approach to assess the ecological risk of PAHs and SPAHs to the aqueous

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environment.

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The Chaobai River System, one of the five largest rivers in the Haihe River Basin

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in China, runs across Beijing, Hebei, and Tianjin (Xiong et al., 2017). The system

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consists of a typical anthropologically disturbed river with several water gates and

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several different water sources, including the Bai and Chao rivers upstream and the

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Beiyun, Ju, and Yongdingxin rivers downstream. Population density is a key factor for

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the contamination of PAHs (Yao et al., 2017). As of 2017, the population density

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around the Chaobai River System is approximately 1500 persons/km2. In addition, the

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incomplete combustion of biomass and/or fossil fuel for heating is one of the most

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significant sources of PAHs and SPAHs in northern China (Qian et al., 2017).

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Therefore, this river is considered to be heavily contaminated by PAHs and SPAHs.

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As such, understanding the distribution, sources, transport pathways, and ecological

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risks of PAHs and SPAHs in this river system is critical.

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We investigated the distributions of PAHs and SPAHs in the surface waters of the 6

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Bai, Chao, and Chaobai rivers, identified the sources and transport pathways of PAHs

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and SPAHs in these rivers, and, most importantly, assessed the ecological risks of

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PAHs and SPAHs to the aquatic environment.

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2. Materials and methods

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2.1 Target compounds

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We studied 16 target PAHs and 18 target SPAHs, including four methyl PAHs

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(MPAHs), six OPAHs, and eight ClPAHs. Detailed information on the target PAHs

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and SPAHs as well as their physical and chemical properties are listed in Table 1 and

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Table S1. Details on the four surrogate standard d-PAHs, two internal standards, and

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organic solvent are shown in Text S1.

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2.2 Sampling sites and strategies

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The Chaobai River System, which is located in Beijing, Hebei, and Tianjin, China,

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includes the Bai and Chao rivers upstream and Chaobai River downstream (Figure 1).

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The Bai (sampling sites M1–M7) and Chao rivers (M8–M13) originate in Hebei

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Province, and finally merge into Chaobai River (U1) after discharging from the

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Miyun Reservoir. In the urban area, the Suzhuang water gate at sampling site U5

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experiences relatively low water flow. The agricultural area receives water from

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Beiyun River, which is mainly composed of effluent from municipal wastewater

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treatment plants in Beijing via the Yunchaojian River (A1). Downstream, the Chaobai

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River also receives water from Ju River via Yinjuruchao River (A5) and merges into

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Yongdingxin River at site A13, before finally discharging into the Bohai Sea in

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Tianjin. 7

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Surface water samples were collected in March, June, September 2017 and January

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2018. One 4-L sample was taken per site in each season. The GPS coordinates of all

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the sites are listed in Table S2. Temperature, pH, conductivity, dissolved oxygen, and

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oxidation reduction potential were measured in situ at each sampling site. All samples

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were transported to the laboratory on ice and stored at 4 °C before analysis. Although

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sediments are deposited in Chaobai River, the sediment load in 2017 was 0, based on

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data obtained from the Beijing River Sediment Bulletin (2017). Therefore,

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particulates and sediments did not significantly influence the SPAHs and PAHs in the

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aqueous phase, and thus were not considered in this study.

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2.3 Analytics

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The pretreatment and analytical procedures have been reported in our previous

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study (Qiao et al., 2017b). In brief, the water samples were filtered with glass

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microfiber filters after transport to the laboratory. The four surrogate standards were

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added to each water sample after filtration. The aqueous phase samples then

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underwent solid phase extraction (SPE) using C18 columns preconditioned with 5 mL

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of dichloromethane (DCM), 5 mL of methanol (MeOH), and 5 mL of purified water.

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After extraction, the columns were eluted with 10 mL of DCM and 5 mL of hexane

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successively, with the eluent then concentrated to 0.5 mL and internal standards added

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for instrument analysis. An Agilent 7890A gas chromatograph equipped with a 5975C

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mass detector (GC-MS) under electron impact (EI) source in selected ion monitoring

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(SIM) mode was used for detection. A fused silica capillary column (DB-17MS, 30 m

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× 0.25 mm × 0.25 µm) was used for compound separation. The injector and detector 8

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temperatures were 280 °C and 290 °C, respectively. The temperature program was:

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60 °C (held for 1 min), heating to 110 °C at a rate of 20 °C/min, and to 290 °C at a

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rate of 3 °C/min (held for 20 min).

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The recoveries of the four surrogate standard d-PAHs were 92% ± 17%, 93% ±

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19%, 96% ± 20%, and 93% ± 22% [mean (%) ± standard deviation (%)], respectively.

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The limits of detection (LODs) and limits of quantification (LOQs) were calculated

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based on signal-to-noise ratios of 3 and 10, respectively. The recoveries of all target

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compounds and LODs and LOQs are listed in Table S3.

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Total organic carbon (TOC), ammonia nitrogen (NH3-N), nitrate nitrogen (NO3-N)

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total nitrogen (TN) orthophosphate (PO4-P) and total phosphorus (TP) were also

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measured, with details shown in Text S2.

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The mass loading calculations for PAHs and SPAHs in Chaobai River are detailed

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in Text S3.

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2.4 Ecological risk assessment

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Both MAC-EQS and AA-EQS were used to assess ecological risk, representing AQC and CQC, respectively.

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The RQs for all mixed compounds were calculated separately for three taxonomic

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groups, i.e., plants (P), invertebrates (I), and vertebrates (V) according to the RQ-

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EQS_Taxa

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compounds against different species were obtained from the EU Water Framework

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Directive (EU-WFD), National Institute for Public Health and the Environment

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(RIVM), and L'Institut national de l'environnement industriel et des risques (Ineris)

approach (Spycher et al., 2018). The AQC and CQC values for most

9

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websites (Table S4). If no AQC and CQC data were available, the values were

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calculated based on toxicity data from the Ecotoxicology Knowledgebase of the US

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Environmental Protection Agency Unites (USEPA ECOTOX) (2019) and other

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literature (Table S5). The following calculation procedures were carried out. The

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species were firstly classified into the P, I, and V groups. The median effective

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concentration (EC50) and no observed effect concentration (NOEC) endpoints were

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used for estimating acute and chronic risk for different species. The minimum value

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of the same endpoint (i.e., EC50 and NOEC) was selected as the AQC and CQC for

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each group. The minimum value was divided by an assessment factor based on the

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available number of toxicity data derived from the Technical Guidance for Deriving

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Environmental Quality Standards (European Commission, 2018), resulting in AQC

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and CQC values. The RQmix,j of compound i in taxonomic group j was calculated as: RQ୫୧୶,௝ = ෍ ௜஫௝

MEC௜ QC௜

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where, MECi is the concentration of compound i and QCi is the AQC or CQC of

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compound i to taxonomic group j. An RQmix,j value > 1 indicates risk on the

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respective taxonomic group.

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3. Results and discussion

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3.1 Distribution of PAHs and SPAHs in Chaobai River

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The average concentration (± standard deviation) of ΣOPAHs (321 ± 651 ng/L) was

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much higher than that of ΣPAHs (158 ± 105 ng/L), ΣMPAHs (28 ± 22 ng/L), and

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ΣClPAHs (30 ± 12 ng/L) (Table 2). The OPAH contamination in Chaobai River was

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more severe than that in the urban rivers receiving effluent from the wastewater 10

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treatment plants in Beijing and Guangdong province, whereas PAH, MPAH, and

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ClPAH contamination was similar (Qiao et al., 2018; Qiao et al., 2019). The

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concentration of OPAHs only reached very high levels at certain sampling sites and in

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certain seasons (Figure S1), with AT and AQ showing the greatest contribution to total

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OPAHs, accounting for 55% and 18%, respectively (Figure S2).

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Individual compounds, including Nap, Fluo, Phe (all PAHs), and 2-MN (MPAH),

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and all target OPAHs were the major detected PAHs and SPAHs, the median

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concentrations of which ranged from 10 ng/L to 100 ng/L (Figure 2, Figure S2). All

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eight detected ClPAHs were found at lower concentrations than those of PAHs and

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other SPAHs, similar to previous results reported in urban rivers in Beijing and

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Guangdong (Qiao et al., 2018; Qiao et al., 2019).

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The concentrations of PAHs, MPAHs, and OPAHs did not vary significantly among

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the mountain, urban, and agricultural areas, which showed population densities of 215,

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1 244, and 628 persons/km2, respectively (Figure S3). In 2017, the urban area in

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Beijing changed from coal combustion for heating to natural gas and electrical power

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(Xinhuanet, 2017), whereas the mountain area in Miyun district in Beijing and

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agricultural areas in Hebei and Tianjin was still changing their energy use until 2018

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(Tianjin Municipal Peoples's Govenment, 2018; Miyun District Government, 2018;

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The People's Government of Langfang Municipal, 2018). Thus, although the human

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habitation densities in the mountain and agricultural areas were lower than that in the

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urban area, the emissions of PAHs and SPAHs may have been heavier during the

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study period, resulting in the similar pollution profiles among the three areas. The 11

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different ratios of isomers demonstrated that PAHs in the mountain areas originated

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primarily from combustion (Figure S4). Accordingly, the higher concentrations of

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PAHs, MPAHs, and ClPAHs in September and January than in March and June

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resulted from coal combustion in the cold seasons. In contrast, the concentration of

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OPAHs was significantly higher in June than in other seasons, indicating that OPAHs

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originated from different sources other than PAHs and other SPAHs (Figure S3).

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3.2 Sources and transport pathways of PAHs and SPAHs in Chaobai River

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In the Chaobai River System, the concentrations of TN were significantly

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correlated with those of NH3-N and NO3-N (Pearson correlation, r = 0.596, p < 0.001);

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the concentrations of TP were significantly correlated with those of NH3-N, PO4-P,

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and TOC (Pearson correlation, r = 0.383, 0.973, 0.414, p < 0.01, 0.001, 0.01,

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respectively); and the concentrations of NH3-N were significantly correlated with

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those of TOC (Pearson correlation, r = 0.353, p < 0.01) (Table S6). These results

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indicate that the nutrients and TOC likely originated from treated or untreated

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municipal wastewater. In contrast, the concentrations of ΣPAHs, ΣMPAHs, ΣOPAHs,

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and ΣClPAHs were not correlated with the levels of nutrients or TOC (r < 0.3, p >

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0.01). In comparison, in the wastewater treatment plant effluent receiving rivers, the

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concentrations of PAHs and SPAHs were well correlated with TOC (Pearson

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correlation, r = 0.298, p < 0.01) and certain nutrients (Pearson correlation, r = 0.416, p

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< 0.01 for NH3-N; r = 0.377, p < 0.01 for PO4-P, r = 0.357, p < 0.05 for TP),

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suggesting that PAHs and SPAHs mainly came from domestic wastewater (Qiao et al.,

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2018). As such, PAHs and SPAHs in Chaobai River may have other emission sources. 12

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The concentrations of ΣPAHs, ΣMPAHs, and ΣClPAHs were significantly

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correlated (Pearson correlation, r = 0.920, 0.437, 0.426, p < 0.001), whereas the

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concentration of ΣOPAHs was not well correlated with that of ΣPAHs, ΣMPAHs, or

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ΣClPAHs (r < 0.3, p > 0.05), suggested that PAHs, MPAHs, and ClPAHs likely

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originated from similar sources, i.e., incomplete combustion of fuel and vehicle

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exhaust emissions. In addition to fuel combustion and vehicle emissions, OPAHs are

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used as raw material in the dyeing and paper-making industries (Kaur et al., 2019;

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Srinivasan et al., 2019). OPAHs can also be transformed from PAHs or nitro-PAHs

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through photo chemical and biological processes (Lundstedt et al., 2007).

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Due to the cutoff of Bai and Chao River before merging into Chaobai River, we

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only considered the mass flow in Chaobai River, but Bai and Chao River. To identify

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the sources and transport pathways of the target compounds in Chaobai River, the

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mass loadings of PAHs and SPAHs were calculated based on the Chaobai River flow

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rate (Figure 3). The yearly average flow from Beiyun River via Yunchaojian River

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(A1) contributed most (69%, 24.47 m3/s) to the flow in Chaobai River. The flow from

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Suzhang Gate upstream of Chaobai River (U5) and Ju River via Yinjuruchao River

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(A5) contributed only 0.2% and 5%, respectively. The remaining flow originated from

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unknown sources, with a contribution of 25% (I1). The unknown sources may include

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precipitation, street sweeping water, and other unknown water discharge. The Chaobai

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River flow discharged through Niumutun Gate between sites A2 and A3 accounting

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for 1% (0.5 m3/s) of the total mass flow, likely for irrigation. The flow merged into

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Yongdingxin River accounting for 33% at Ningchegu Gate (A13, 11.8 m3/s). The 13

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transport pathways of the remaining flow were unknown, but probably for irrigation,

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accounting for 43% (O2, 15.2 m3/s) between A3 and A11, and 22% between A11 and

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A13 (O3, 7.8 m3/s). To identify the sources and transport pathways of PAHs and

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SPAHs in Chaobai River, we determined their average mass loadings in the four

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sampling seasons (Figure 3). Similar to the flow rate in Chaobai River, A1 was the

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major contributor to the total mass loading of PAHs (65%, 286 g/d) and SPAHs (53%,

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526 g/d). In addition, unknown sources contributed 35% and 47% of the total mass

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loading of PAHs (153 g/d) and SPAHs (461 g/d), respectively. The discharge at

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Niumutun Gate, which was likely for irrigation, reduced the loadings of PAHs and

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SPAHs by 3% (15 g/d) and 20% (208 g/d), respectively. However, the major transport

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pathways of PAHs and SPAHs were unknown (O2 + O3), but were probably for

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irrigation, accounting for 80% (362 g/d) and 66% (688 g/d), respectively, with the

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remaining PAHs (16%, 74 g/d) and SPAHs (13%, 139 g/d) transported into

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Yongdingxin River at A13.

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3.3 Ecological risk assessment of PAHs and SPAHs in Chaobai River

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3.3.1 Risk caused by SPAHs compared with corresponding PAHs

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Based on the AQC and CQC in Table S4, we identified several MPAHs, OPAHs,

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and ClPAHs that posed a risk to the aqueous environment, but which have been

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largely ignored in previous investigations on the ecological risk of PAHs. Here, both

280

the acute and chronic risks of SPAHs and their corresponding PAHs were compared

281

(Figure 4). Results demonstrated that the acute and chronic risks of 2-MN were

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approximately 10 to 100 times higher than the risk of Nap. The acute risk quotients 14

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(ARQs) of 2-MN and Nap ranged from 0.002 to 0.07 and 0.0000 to 0.001,

284

respectively; whereas, the chronic risk quotients (CRQs) of 2-MN and Nap ranged

285

from 0.06 to 2.2 and 0.0006 to 0.08, respectively. The risks of 2-CN and 1-CN (ARQs

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= 0–0.0009, CRQs = 0–0.009) were similar or lower than those of Nap (ARQs = 0–

287

0.0013, CRQs = 0.0006–0.082). Regarding OPAHs, the CRQs of AQ ranged from 0.2

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to 5.9, which was approximately 10 times higher than that of Ant (CRQs = 0.04–0.33),

289

whereas its acute risk was markedly lower (ARQs = 0.007–0.2 for AQ and ARQs =

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0.04–0.33 for Ant). The acute and chronic risks of BAT (0–0.01 and 0–1.3,

291

respectively) were more than 10 times lower than that of BaA (0–0.8 and 0–35,

292

respectively). Thus, certain SPAHs appear to exhibit significantly higher acute and/or

293

chronic risk than their corresponding PAHs, i.e., 2-MN and AQ.

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3.3.2 Risk profiles of mixed PAHs and SPAHs

295

The CRQmix values of all compounds were >1, ranging from 13.3 to 334 (45 ± 53),

296

much higher than the ARQmix values, which ranged from 0.4 to 13.0 (1.9 ± 1.4)

297

(Figure 5). According to the risks standard identified in previous research (Spycher et

298

al., 2018), for acute risk, only 10% of sites were good (0.1 < RQ < 1), 60% of sites

299

were moderate (1 < RQ < 2), 30% of sites were unsatisfactory (2 < RQ < 10), and 1%

300

of sites were poor (10 < RQ < 100); whereas, for chronic risk, 90% of sites were poor

301

(10 < RQ < 100) and 10% of sites were very poor (RQ > 100) (Table S7). Thus, the

302

chronic ecological risk of PAHs and SPAHs against the aqueous ecosystem was much

303

more severe than that of acute risk.

304

Individually (Figure 5), BaP (49%) and Chry (33%) showed the greatest 15

305

contribution (82%) to CRQmix, followed by BaA (7%) Flua (3%), and AQ (2%);

306

whereas, the 4-ring PAHs, including Pyr (17%), BaA (4%), Chry (13%), BbF (23%),

307

and BkF (13%), showed the greatest contribution to ARQmix (70%), followed by 5–6

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ring DBA (13%) and BghiP (5%), and 3-ring Ant (5%) and Flua (4%). Both BaP and

309

4-ring Chry were the main components of mixed chronic risk, whereas, all 4-ring

310

PAHs, several 3-ring PAHs (including Ant and Flua), and several 5–6 ring PAHs

311

(including DBA and BghiP) exhibited the highest contribution to mixed acute risk. In

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addition, the total contributions of SPAHs to CRQmix and ARQmix were only 2.5% and

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3.5%, respectively, much less than that of the PAHs. Among SPAHs, both AQ and

314

2-MN showed the greatest contribution to CRQmix and ARQmix (1.7% and 1.5% for

315

AQ; 1.1% and 0.8% for 2-MN, respectively). Even so, the chronic risks of SPAHs

316

were >1 at more than 85% of sites (Figure S5), indicating that the chronic risks of

317

SPAHs should not be ignored. Additionally, AQC and CQC values have only been

318

derived for five SPAH compounds (i.e., 2-MN, AQ, BAT, 2-CN and 1-CN) from

319

previous literature (Table S5). Thus, if enough published toxicity data were available

320

for all detectable SPAHs, the evaluated risks caused by SPAHs would likely be much

321

higher.

322

3.3.3 RQs for different taxonomic groups

323

We determined the RQs based on the three different taxonomic groups (Figure 6).

324

The ARQmix,I values of PAHs and SPAHs were significantly higher than the values for

325

plants and vertebrates (ANOVA, p < 0.05). The ARQmix,

326

invertebrates were >1 at 83% of sites in Chaobai River; whereas, ARQmix,P and 16

I

values of risk to

327

ARQmix,I values of risk to plants and vertebrates were >1 at 63% and 53% sites,

328

respectively. In addition, the CRQmix, P, CRQmix, I, and CRQmix, V values were >1 for

329

all sampling sites and taxonomic groups (100%). Accordingly, the acute and chronic

330

ecological risk of PAHs and SPAHs posed to invertebrates, plants, and vertebrates in

331

Chaobai River should be taken into serious consideration for ecosystem protection.

332

The acute and chronic risks to the three different taxonomic groups by individual

333

PAH and SPAH compounds were evaluated using the average value at different

334

sampling sites and seasons (Figure 6). For PAH compounds, Pyr and BaA showed

335

obvious acute risk to plants and invertebrates (contributing ~0.4 to ARQmix, P and I), but

336

not to vertebrates. In contrast, Chry, DBA, and BghiP posed an acute risk to

337

invertebrates (contributing ~0.6 to ARQmix, I), but not to plants or vertebrates. Hence,

338

certain compounds only posed a risk to invertebrates, contributing 18% to ARQmix, I,

339

resulting in the highest acute risk. BaP and Chry posed the highest chronic risk to all

340

three taxonomic groups (contributing ~37 to CRQmix, I, P and V), whereas, BaA posed a

341

chronic risk only to plants (contributing ~3.4 to CRQmix, P). Thus, more compounds

342

presented a chronic risk to plants than to invertebrates and vertebrates. Regarding

343

SPAHs, all individual compounds posed risks to different taxonomic groups with RQs

344

<1. For example, 2-MN, AQ, and BAT contributed 0.016, 0.025 and 0.002 to ARQmix,

345

P, I and V,

346

V.

347

and 1-CN contributed 0.8, 0.003, and 0.001 to CRQmix, I and V. Thus, SPAHs posed

348

higher acute and chronic risks to invertebrates and vertebrates than to plants.

whereas 2-CN and 1-CN contributed only 0.0003 and 0.00012 to ARQmix, I and

Both 2-MN and BAT contributed 0.5 and 0.2 to CRQmix, P, I and V, whereas AQ, 2-CN,

17

349

3.3.4 Temporal and spatial variation of ecological risks

350

Based on the water sources and transport pathways of Chaobai River, Yunchaojian

351

River (A1) showed the highest contribution to yearly mass flow of both PAHs and

352

SPAHs. The acute and chronic risks of PAHs and SPAHs to all taxonomic groups at

353

A1 were slightly higher than that upstream of Chaobai River (U5) (Figure 7). Thus,

354

A1 was a major risk contributor in Chaobai River. Although the chronic risks of

355

SPAHs at Yinjuruchao River (A5) were slightly higher than those in Chaobai River,

356

the mass loadings of SPAHs was relatively low; thus A5 was not a major contributor

357

to the risk in Chaobai River. The SPAHs did not pose an acute risk to all taxonomic

358

groups (ARQmix, P, I and V < 1) or chronic risk to plants (CRQmix, P < 1) in Chaobai River,

359

except at the flow input sites (A1 and A5). The CRQmix, I and V values of SPAHs to

360

invertebrates and vertebrates were >1 at all sites. Thus, the PAHs exhibited both acute

361

and chronic risks and SPAHs exhibited chronic risks at the output sites (between U5,

362

A3, A11, and A13 for irrigation, and at A13 to Yongdingxin River) in Chaobai River.

363

Therefore, the transmission of PAHs and SPAHs from Chaobai River may pose

364

potential risks to farmland via irrigation, as well as to Bohai Sea via river water

365

discharge.

366

4. Conclusions

367

The concentrations of ΣPAHs, ΣMPAHs, ΣOPAHs, and ΣClPAHs in Chaobai River

368

were 158 ± 105 ng/L, 28 ± 22 ng/L, 321 ± 651 ng/L, and 30 ± 12 ng/L, respectively,

369

with the main components including Nap, Fluo, Phe, 2-MN, Fluo, AT, and AQ. Both

370

2-MN and AQ posed greater acute and/or chronic risks than their corresponding PAHs. 18

371

In addition, BaP and Chry showed the highest contribution (82%) to total chronic risk,

372

whereas, all 4-ring PAHs showed the highest contribution (70%) to total acute risk.

373

The chronic risks of PAHs and SPAHs were much higher than their acute risk. All

374

sites faced chronic risk and 90% of sites also experienced acute risk. PAHs posed

375

higher acute risk to invertebrates than to plants and vertebrates, whereas, plants were

376

threatened by more chronic risk compounds. SPAHs posed a significant chronic risk

377

to invertebrates and vertebrates (CRQmix >1).

378

Both PAHs and SPAHs in Chaobai River mainly originated from Beiyun River

379

which receives effluent from municipal wastewater treatment plants in Beijing.

380

Beiyun River was also a major risk contributor to Chaobai River. The major transport

381

pathways of PAHs and SPAHs were likely for irrigation (83%–86%) and transmission

382

to Yongdingxin River (13%–16%), which merges into Bohai Sea. Therefore, the

383

transmission of PAHs and SPAHs from Chaobai River may pose potential risks to

384

farmland through irrigation and to Bohai Sea via river water discharge.

385 386

Acknowledgements

387

We gratefully acknowledged Dr. Mireia Marti and Dr. Marion Junghans from the

388

Swiss Centre for Applied Ecotoxicology Eawag/EPFL for providing the AQC and

389

CQC calculation methods, Dr. Els Smit from the National Institute for Public Health

390

and the Environment (RIVM) for deriving AQC and CQC data on different taxonomic

391

groups, and the Beijing Water Authority for deriving the flow rate data in Chaobai

392

River. This work was supported by the Open Funds of the Key Laboratory of 19

393

Eco-restoration of Regional Contaminated Environment (Shenyang University)

394

Ministry of Education, Key Program of the Chinese Academy of Sciences (Grant No.

395

ZDRW-ZS-2016-5-6) and National Natural Science Foundation of China (Grant No.

396

51420105012, 51508552).

397 398

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517

22

518

Table 1 Information on PAHs and SPAHs Type

Compounds

PAHs

Naphthalene Acenaphthylene Acenaphthene Fluorene Phenanthrene Anthracene Fluoranthene Pyrene Benz[a]anthracene Chrysene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[a]pyrene Indeno[1,2,3-cd]pyrene Dibenz[a,h]anthracene Benzo[g,h,i]perylene

Abbreviation

Purity

Solvent

Company

Nap Acy Ace Fluo Phe Ant Flua Pyr BaA Chry BbF BkF BaP IncdP DBA BghiP

Mixture, 200 µg/mL

CH2Cl2: MeOH (1:1)

AccuStandard, Inc., USA

MPAHs

2-Methylnaphthalene 2,6-Dimethylnaphthalene 3,6-Dimethylphenanthrene 1-Methylfluoranthene

2-MN 2,6-DMN 3,6-DMP 1-MF

100% 100% 100% 10 µg/mL

Solid Solid Solid Cyclohexane

AccuStandard AccuStandard AccuStandard AccuStandard

OPAHs

9-Fluorenone Anthrone Anthraquinone 2-Methylanthraquinone Benzanthrone Benz(a)anthracene-7,12-dione

9-FL AT AQ 2-MAQ BAT BA-7,12-D

100% 98% 100 µg/mL 99.0% 100% 50 µg/mL

Solid Solid Acetonitrile Solid Solid Toluene

AccuStandard AccuStandard AccuStandard AccuStandard AccuStandard AccuStandard

ClPAHs

1-Chloronaphthelene 2-Chloronaphthelene 1,4-Dichloronaphthelene 9-Chlorophenanthrene 2-Chloroanthracene

1-CN 2-CN DCN 9-ClPhe 2-ClAnt

95.5% 100 µg/mL 99.4% 50 µg/mL 50 ug/mL

Solid Methanol Solid Isooctane Isooctane

AccuStandard AccuStandard AccuStandard Chiron, Norway Chiron, Norway

1-Chloroanthraquinone

1-ClAQ

98%

Solid

AccuStandard

3-Chlorofluoranthene 1-Chloropyrene

3-ClFlua 1-ClPyr

50 µg/mL 50 µg/mL

Isooctane Isooctane

Chiron, Norway Chiron, Norway

519

23

520

Table 2 Concentrations of ΣPAHs, ΣMPAHs, ΣOPAHs, and ΣClPAHs in Chaobai River ng/L

ΣPAHs

ΣMPAHs

ΣOPAHs

ΣClPAHs

ΣSPAHs

Ave ± sd Min Max

158 ± 105 55 882

28 ± 22 5 155

321 ± 651 49 4659

30 ± 12 7 66

379 ± 652 86 4711

521

24

522 523

Figure 1 Sampling sites in Chaobai River System

25

Nap Acy Ace Fluo Phe Ant Flua Pyr BaA Chry BbF BkF BaP IncdP DBA BghiP 2-MN 2,6-DMN 3,6-DMP 1-MF 9-FL AT AQ 2-MAQ BAT BA-7,12-D 2-CN 1-CN D-CN 9-ClPhe 2-ClAnt 1-ClAQ 3-ClFlua 1-ClPyr

Concentration (ng/L) 10000

1000

524 525 100

10

1

0.1

0.01

Figure 2 Concentrations of individual target compounds in Chaobai River System

26

526 527 528 529 530 531

Figure 3 Yearly average flow rate (m3/s) and average PAH and SPAH mass loading in Chaobai River: Average mass loading (g/d) = [CMar. (ng/L) × FMar. (m3/s) + CJun. (ng/L) × FJun. (m3/s) + CSept. (ng/L) × FSept. (m3/s) + CJan. (ng/L) × FJan. (m3/s)] × 0.25 × 86 400 (s/d) / 106, where C is the concentration of PAHs or SPAHs, F is the flow rate at different water gates.

27

2.0 Acute Chronic

Lg (SPAH/PAH)

1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5

2-

M N

/N ap AQ /A BA nt T/ Ba 2A C N /N ap 1C N /N ap

-2.0

532 533

Figure 4 Ratios of SPAH RQ and corresponding PAH RQ for acute and chronic risk

28

1000

RQmix

100

10

1

0.1

534 535 536

Acute

Chronic

Figure 5 RQmix and contribution of individual compounds to RQmix

29

100

10

63%

a

83%

53%

2.0

1000

a

a

50

a

b a

40

1.5

30 RQ

RQmix

100 1

1.0 20

10 0.1

0.5

0.01

537 538 539

100%

100%

100%

C-P

C-I

C-V

1 A-P

A-I

A-V

10

0.0

0 A-P

A-I

A-V

C-P

C-I

C-V

Nap Acy Ace Fluo Phe Ant Flua Pyr BaA Chry BbF BkF BaP IncdP DBA BghiP 2-MN AQ BAT 2-CN 1-CN

Figure 6 Acute (A) and chronic (C) RQ for mixed (left) and individual compounds (right) of the three taxonomic groups (P-plants, I-invertebrates, V-vertebrates)

30

RQmix for PAHs

100 10 1 0.1 0.01 RQmix for SPAHs

100

U5

A1

A2

A3

A5

A11

A13 A-P A-I A-V C-P C-I C-V

10 1 0.1 0.01

540 541 542 543 544

U5

A1

A2

A3

A5

A11

A13

Figure 7 Mixed acute (A) and mixed chronic (C) risk quotients to plants (P), invertebrates (I), and vertebrates (V) caused by PAHs and SPAHs, respectively, along Chaobai River with known input and output flows

31

• • • • •

Concentrations of oxygenated PAHs similar to or higher than PAHs (S)PAHs originated from Beiyun River and transported for irrigation or to Bohai Sea All sites facing chronic risk and 90% of sites experiencing acute risk Risks of anthraquinone and 2-methlynaphthalene higher than corresponding PAHs SPAHs posed significant chronic risk to vertebrates and invertebrates

Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: