Risk Assessment of Heavy Metals In Suspended Particulate Matter In A Typical Urban River of Northern China

Suspended particulate matter (SPM) is a major contamination source in urban rivers. In this work, the Beiyun River, northern China, was used as a case study to determine the characteristics of heavy metal spatial distribution in SPM, and to evaluate the potential ecological risks and identify heavy metal sources. The concentration of seven heavy metals and associated indicators (TC, TN, TP, and OM) were measured at 12 sites and analyzed by Pearson correlation (PC) and principal component analyses (PCA). The average concentrations of Cr, Ni, Cu, Zn, As, Cd, and Pb were 70.72, 27.88, 31.35, 115.70, 27.77, 0.23, and 29.62 mg/kg, respectively, and signicant spatial differences occurred between some elements. Igeo values indicated the ranking of heavy metal pollution in SPM as As > Cd > Zn > Cu > Pb > Cr > Ni. The E ir analysis demonstrated that the order of potential ecological risk of the seven metals was Cd > As > Cu > Pb > Ni > Cr > Zn. RI (potential ecological risk index) results conrmed high potential ecological risk in objective area. Of the measured heavy metals, Cd represented the highest pollution risk. Signicant positive correlations were found between TC, TN, TP, and Cu. Three element pairs, Zn-Cd, Cr-Cu, and Cr-Ni, had strong correlations. Zn, Cu, and Ni were mainly introduced by human activities, and Cr was mainly from natural processes. This information on the concentration, risk, and sources of SPM in Beiyun River provides an important reference for reducing heavy metal pollution in SPM of a typical river in the Haihe River Basin.


Introduction
With the rapid development of urbanization, agriculture, and industrialization, urban rivers receive wastewater from residential areas, agricultural cultivation, and industrial production (Yahaya et al. 2019).
Numerous sluice dams along rivers cause surface sediment to move into overlying water, introducing new contaminants as suspended particulate matter (SPM). SPM is a major polluter of aquatic environments, and is the main factor in pollutant migration and transformation in rivers ). In stationary water, SPM is a component in ecosystem construction and aquatic zone construction (Vercruysse et al. 2017; Wang et al. 2018). Furthermore, SPM plays an important role in controlling the reaction rate of water and sediment, the food chain cycle, and the metabolic rate of biota (Al-Saadi et al. 2002;Turner and Millward 2002). SPM mainly comes from agricultural activities and weathered soil and rock from surface erosion or riverbed erosion, while a small proportion comes from organic matter (OM) and minerals formed in rivers. SPM can combine with pollutants and deposits on the bottom of the river, and has an average particle size of 0.45-63 µm (Lamba et al. 2015; Zheng et al. 2008). In river systems, the physical the main source of urban rivers, which are characterized by numerous inputs, various pollutants, diverse dams along the way, and active movement of SPM, Beiyun River is a typical river that demonstrates all of the above characteristics. In this study, the north section of Beijing-Hangzhou Grand Canal-Beiyun River is used as an example, to demonstrate the accumulation of heavy metals on SPM in rapidly-developing cities. The concentration and pollution characteristics of seven metals (Cr, Ni, Cu, Zn, As, Cd, and Pb) and associated indicators (TC, TN, TP, and OM) of SPM were measured and evaluated in the main stream of Beiyun River. The main objectives of this study are: (1) to measure the concentration and distribution of heavy metals in SPM in selected rivers; (2) to evaluate the pollution level and ecological risk caused by heavy metals; (3) to determine the relationship between heavy metal pollution, environmental factors, and human activities; (4) to analyze the characteristics of SPM pollution in Beiyun River, and the relationship between SPM and sediments.

Study area
The Beiyun River is a major tributary of the Haihe River System (Chen et al. 2015b), which is involved in ood discharge, sewage discharge, and landscape construction, and has irreplaceable study value. Located between the Chaobai and Yongding Rivers, the river is the northern section of the Beijing-Hangzhou Grand Canal. It originates in Changping District, Beijing, and ows through Beijing, Tianjin, and Hebei, nally joining the Haihe River at Dahongqiao in Tianjin (Shan et al. 2011). Tianjin is the main river basin, with many tributaries including the Ziya River, Duliujian River, and Machangjian River. The upper reaches of the region are mainly farmland. As it is an ecological agricultural demonstration zone, Beijing has developed planting and soil fertilizer technology. However, the serious agricultural pollution in Beiyun River still cannot be ignored. In the lower reaches, there are many energy-related and petroleum and metallurgy industries. The area of Beijing-Tianjin-Hebei (BTH) is densely inhabited; therefore, the large quantity of sewage is another factor contributing to the river pollution. The Beiyun River has a number of dams, with a slow ow velocity, and numerous sediment and pollutants deposited in the riverbed. It is one of the main sewage rivers in Beijing City, thus the water quality of this river is below class V (Xiaowei et al. 2009). Approximately 4.4 t of phosphorus is discharged into the river in sewage from Beijing every day, which ows into the Haihe River Basin (Pernet-Coudrier et al. 2012). Industrial wastewater, domestic sewage, agricultural run-off, and other harmful substances in the Beijing urban area and surrounding counties are directly or indirectly discharged into the river without treatment. Due to the effects of longterm erosion, the river incorporates the silt, which is dominated by SPM. The silt accumulates and settles on both sides of the river, resulting in heavy metal pollution in the accumulated SPM. Therefore, SPM has become one of the main sources of pollution in the Beiyun River (Bao et al. 2016).

Sample collection
In this study, almost all sampling points were distributed along the ow direction of Beiyun River. When selecting the sampling points, it was necessary to avoid static water, backwater, and sewage outlets, to ensure the points were in the straight river section, with smooth ow and a wide river channel. Twelve samples were collected from the main stream of the Beiyun River in April 2019. The detailed locations of these sampling sites are shown in Fig. 1. To avoid disturbance, a column was used to collect the sediment samples from a depth of 2 cm, and then samples were left to stand for several minutes. SPM combines with pollutants in the aquatic environment, and is deposited on the top layer of sediment; thus the surface layer was selected as the source of SPM. The upper sample can be separated when there is no oating suspended particle in the overlying water. During the sample collection, three surface sediment sub-samples (approximately 5 cm from the top) were collected from each site to obtain representative samples (the distance of three parallel samples was not less than 500 m). Samples (~ 1 kg weight) from the same site were immediately mixed and homogenized and put into No.7 self-sealed bags and transported back to the laboratory.
The collected samples were spread out in the laboratory with enamel plate and then dried at 25℃. Particles of < 63 µm were obtained by sieving through a 250 mesh, after removing rotten branches, leaves, and plant stems. These particles have high geochemical activity and the closest properties to SPM and can, therefore, be utilized as the SPM sample (Pan et al. 2013;Zheng et al. 2008). Finally, a quarter of the sample was removed and stored in sealed plastic bags at room temperature (25°C) until analysis.

Sample analysis
In this study, the contents of heavy metals, OM, TN, TC, and TP in SPM were analyzed. HCl, HNO 3 , and HF were mixed, to a nal volume of 8 ml (9:3:4, v/v/v), then 0.1g SPM sample was digested with a MARS Xpress instrument (CEM, Matthews, USA). After the acid was heated to 150°C for at least 2 h, 1-2 drops of HClO 4 were added to the digestion tube (Tang et al. 2010). The extracted liquid was diluted to 50 ml with ultrapure water, then ltered with a 0.45 µm membrane, and stored at 4°C for analysis. Contents of Cr, Ni, Cu, Zn, As, Cd, and Pb were determined by inductively coupled plasma mass spectrometry (ICP-MS, Diane 7700x, USA). All plastic and glass tubes were cleaned by soaking in 10% HNO 3 for at least 48 hours, then washing and rinsing them with ultrapure water. Ultrapure water and Guaranteed Reagent were used during the whole experiment. Blank samples, standard samples, and parallel samples were used in each experiment, and the content of all heavy metals in each sample was the average value of three replicates. The recoveries of all determination results were 85.71-113.67%, and the relative standard deviation between the measured value and the standard value was within 10%.
To measure the OM, the SPM sample was dried in an oven at 105℃ for 12 h, and the mass M1 was recorded. Then, samples were heated in a mu e furnace at 550℃ for 5 h, and the mass M2 was recorded. The OM content was determined by loss on ignition after heating. To determine TC and TN, 20-30 mg SPM sample was weighed and put into the element analyzer (Vario El III; Elementair, Germany) and the content was analyzed directly. TP was determined by the SMT method (Ruban et al. 2001). Brie y, 0.2 g SPM sample was ashed at 450℃ for 3 h, and 20 ml 3.5 mol/L HCl was added into the ash residue.
Then, the extract solution above was obtained by shaking for 16 h in a thermostat. After extraction, the solid-liquid phase was separated by centrifugation for 15 min, and then the content of TP in the extracts was measured by molybdate colorimetry.

Evaluation method
Due to differences in soil structure, composition, and development, the indices of pollution level, toxicity, and potential risk of soil could not be assessed from the numerical value directly. Therefore, it was necessary to evaluate them by referring to the geochemical background values of corresponding elements in the study area. There are three coe cients that can be used to comprehensively study the degree of heavy metal pollution, including the geoaccumulation index (Igeo) (Muller 1969), the potential ecological risk index (Hakanson 1980), and the average possible effect concentration entropy (MacDonald et al. 2000). These coe cients are widely used because of their universality and accuracy.
Igeo is used to evaluate the pollution level of heavy metals. It can be calculated by following formula: C n is the mass of heavy metals (mg/kg) and B n refers to the geochemical background value contents about different metals (mg/kg). The pollution grade and degree of heavy metals calculated by the Igeo are shown in Table 2. Note: CV = SD/mean value×100%, is a coe cient that represents variation of heavy metals, 10% < CV < 100% indicates moderate variability.
The potential ecological risk index method is used to evaluate the ecological risk of heavy metals. It can be calculated by following formula: where is the potential ecological risk index of corresponding heavy metal, which re ects the toxicity level of the heavy metal to a certain extent; T i f i are the toxicity response parameters and pollution coe cient of the pollutant, respectively; and C i /B i is the ratio of the measured content (mg/kg) and background value (mg/kg).
MacDonald (2000) proposed consistent sediment quality criteria (SQGs), threshold effect concentration (TEC), and possible effect concentration (PEC). If the concentration of heavy metal is higher than PEC, heavy metals will have adverse effects on benthos, while negative effects will not occur when the concentrations are lower than TEC. Since SPM pollution comes from residential pollution, as well as agriculture and industry, the pollution from several heavy metals should be taken into account. The mean probable effect concentration quotient (Q m−PEC ) is used to evaluate the combined pollution caused by the collective action of several heavy metals: where Cn is the measured value of heavy metal elements.

Results And Discussion
To further explore pollution characteristics, based on the measured concentrations, and to compare with other river basins with similar conditions, this research focused on the relationship between the concentration of absorbed heavy metals and the structure of SPM. The Igeo, RI, and Q m−PEC indices were used to determine the degree of pollution, and the pollution sources were inferred from the CA and PCA. The effects from the river system and external factors to SPM were analyzed, and then the effective limit strategies were provided.

SPM heavy metal concentrations
The concentrations of heavy metals are shown in Fig. 2, and corresponding background values are shown in Table 2. Concentrations in SPM from Beiyun River were compared with other typical urban rivers. The average Cr concentration from 12 SPM samples was 70.72 mg/kg, which is higher than concentrations from Luan River (107.17 mg/kg) and lower than that of Bortala (51.55 mg/kg) ( Wang et al. 2014). Of the seven tested metals, Cu, Zn, As, Cd, and Pb were 1.44, 1.48, 2.81, 2.51, and 1.38 times greater than background values, respectively. In terms of concentration distribution, the lower reaches had signi cantly higher concentrations, which increased with the river ow direction. In summary, the concentrations of Ni, Cu, Zn, and Pb in SPM in this study area were all below the average values of rivers and lakes in China mentioned above. However, the concentrations of As and Cd are much higher than concentrations of these metals in rivers and lakes of

Heavy metal concentration and SPM properties
SPM is an essential source of heavy metals in rivers. Cr, Ni, Cu, Zn, Cd, and Pb concentrations in SPM of Beiyun River show an increasing trend, from upstream to downstream, accumulating and migrating downstream, continuously induced by ow (Feng et al. 2017). SPM microstructure changes due to resuspension: more pollutants such as heavy metals and phosphorus, are adsorbed on the surface of SPM and transported downstream, resulting in the accumulation of heavy metals in rivers (Stephens et al. 2001). Heavy metals and SPM can adsorb together as they are affected by van der Waals force. The double-electron-layer structure and large surface area of SPM means that more heavy metals can be adsorbed on the surface (Jin et al. 2018). In addition, the chemical bonds of SPM means they can irreversibly adsorb heavy metals and other pollutants (Chanudet and Filella 2007). Metal oxides in SPM can combine with heavy metals spontaneously, such as Fe and Mn oxides combining with Pb on the inorganic layer, and Mn oxides combining with Zn on the organic layer ). The shear stress of overlying water means that heavy metals on particles are more stable if they are absorbed by a chemical process, and will exist in the river for a long time.

Risk assessment
Pollution level, risk level and toxicity are all derived from Table 1.In terms of sample distribution, that sites B1, B3, B4, B7, B12, B13, and B15 have moderate-strong pollution, while B5, B6, B8, B9, and B14 have moderate pollution. In terms of element type, the SPM of Beiyun River is moderately polluted with Ni, moderate-strongly polluted with Cr, Cu, Zn, and Pb, and strongly polluted with As and Cd (Fig. 3b). The comprehensive potential ecological hazard index (RI) and mean potential effective concentration quotient (Q m−PEC ) of Beiyun River are shown in Fig. 3c and d. From the perspective of different heavy metal elements, the mean values decreased in the order Cd > As > Cu > Pb > Ni > Cr > Zn. Among these, Cd pollution is the most serious, and belongs to extremely high risk level. The contribution of Cd to the RI of the study area was up to 60.03%, demonstrating that Cd is the most critical ecological risk factor in SPM of Beiyun River. Moreover, agricultural non-point source pollution has a signi cant impact on the regional pollution, and Cd should be listed in the priority pollutants list in this study area (Ke et al. 2017). Additionally, Cd has been listed as one of the priory limit pollutants by the United States Environmental Protection Agency (US EPA) (Chen et al. 2015a). In terms of spatial distribution, the concentration of Cr and Zn in the Beijing section was higher, which is consistent with the results of Huo (Huo et al. 2011). In the Tianjin section, the RI value of B6 ~ B9 was low, belonging to slight risk level, which indicates that desilting in Tianjin has played a positive role in controlling heavy metals in recent years. B12, B13, and B15 belong to moderate risk levels, because shipping and petrochemical industry near the estuary seriously affects the quality of river SPM. There is a signi cant difference between the middle and lower reaches, in terms of Cu, Zn, and Cd. The high RI value of the three metals above is due to frequent human activities downstream (Guo et al. 2010). Among all metals, RI is > 600, demonstrating that the whole river is at high risk level, mainly because it is a sewage river. There are 341 sewage outlets along the river, including 42 large-scale outlets, with 209.28 million tons of industrial and residential sewage discharged into the river every year (Zhang et al. 2015). Figure 3d shows that the Q m−PEC of Cr, Ni, and As is > 0.   There was a negative correlation between As and Cu, As and Zn, and Cd and Pb, which suggests that As was different from other heavy metals in enrichment and transformation pathways.
In the PCA, the cumulative variance contribution rate of three principal components was 88.12%, which re ected total pollution. The rst principal component (PC1) with high variance was Zn, Cu, Pb, and Ni, which explain 57.77% of the variance. The second principal component (PC2) was As, Cr, and Ni, that explains 21.56% of total variance. For the third principal component (PC3), the special element explained 8.79% of the variance. Cr had a higher load in PC2 and PC3, and the second one is higher than the third one. However, Ni had a higher load in PC1 and PC2, and the second one is higher than the rst one, which indicates that Cr

SPM impacting factors from the environment
With increasing heavy metal contamination, understanding of aquatic elements cycle needs to be explored so a management system to control pollution can be determined (Ma et al. 2019). Serious pollution is the interaction of multiple factors, and is affected by the interactions among land use, rainfall patterns, soil moisture, and hydrology (Atkinson et al. 2007). It is simultaneously affected by numerous internal factors such as overlying water, sediment, aquatic organisms, and human activities in the river system (Fig. 5). The metabolites of organisms enter aquatic ecosystems, and substances in water are transformed into SPM by adsorption, sedimentation, and occulation processes. The nutrients in SPM are transformed by organisms to maintain their physiological needs via biological assimilation. Organisms continuously metabolize and excrete metabolites, which then enter into SPM again. After subsiding, SPM enters into sediments, and the sediment suspended in organism after disturbed. This is a reciprocating cycle (Turner and Millward 2002). Pollutants in surface water and sediment affect the concentration of SPM through numerous processes, such as sedimentation, migration, and transformation; thus, soil and heavy metal pollution caused by human activities can accumulate in SPM Schwientek et al. 2017). The exchange and transformation of materials in several different media is accompanied by sudden changes in salinity, pH, redox conditions, and dissolved OM concentration, which changes chemical and particulate reactivity (Turner and Millward 2002). Some uncontrollable factors, such as wind-induced resuspension also affect the concentrations and properties of SPM (Shinohara and Isobe 2010). Furthermore, due to the in uence of river hydraulic movement, downstream topography, and industrial structure, scour included, the concentrations of heavy metals at the beginning of the river are far lower than in the Bohai Sea estuary. Scour and hydraulic movement lead to sediment deposition, but excessive sediment deposition may cause more serious accumulation of SPM, even heavy metals in downstream areas ). In addition, human intervention along rivers, such as dam construction, soil and water conservation technology, will affect the sediment supply and transport of the river ). There are many gates and dams along Beiyun River, such as Yangwa gate, Yulinzhuang gate, Beiguan gate, etc. A large amount of industrial wastewater and domestic sewage emerged upstream due to the construction of gates and dams. The interception of these gate and dam causes a reduction in the velocity, runoff, and the self-puri cation capacity of rivers. The increased water pollution further accelerates the accumulation of heavy metals. When the dam is suddenly opened, sewage will discharge at the same time, and the pollutants carried by sewage will induce water pollution events, which is also one of the main factors for heavy metal pollution in the Beiyun River.  (Fig. 6). During industrial production, heavy metal concentrations, such as As, Cd, Cu, and Zn increase in the surrounding areas (Park and Dam 2010). Polluted gas is directly released into the air, then forms a dust, combining with other particles (Route in Fig. 6). Part of the dust deposits on the road, eld, etc., while some enters the river by atmospheric precipitation or rainfall (Route in Fig. 6), then participate in the SPM cycle in the uvial ecosystem. Apart from the industrial waste, polluted sewage from industrial production is discharged directly into the river through the outlets, which aggravates river SPM pollution (Route in Fig. 6). In addition, vehicle exhaust emissions is also a fundamental source for the accumulation of SPM. The way of aautomobile exhaust emission (Route in Fig. 6) is similar to that of industrial gas (Route in Fig. 6 . Irrigation causes pesticide and fertilizer residues to form runoff, which discharges into rivers and aggravates river SPM pollution (Route in Fig. 6). Moreover, ooding alters SPM transport and overbank deposition (Benedetti 2003). Therefore, the air (dust), farmland, and river form a collective cycle, which affects the concentration of SPM. In this study, heavy metal content is high after the Beiyun River con uence with Ziya River. In terms of spatial distribution, the pollution in the downstream area is higher than that of the upper and middle reaches. Gross domestic product (GDP) is a critical indicator to interpret the impact of human production activities on the environment. Speci cally, agricultural and industrial activities represent the primary and secondary industries, respectively. The Beiyun River is located in the BTH region, an area in which the economy is rapidly developing and near to the capital, which is highly sensitive to GDP. GDP is a critical indicator to evaluate the impact of human activities on river pollution (Zhang et al. 2017b). The concentration of Cu and Pb are closely related to agricultural and industrial activities. In SPM from Beiyun River, the pollution level of Cu and Pb is 3 < Igeo < 4 and 80 < E < 160, and the potential ecological hazard index takes in strong risk level. Therefore, agricultural and industrial activities have a great impact on heavy metal pollution in Beiyun River.

Pollution characteristics on SPM and control strategies
Rivers are crucial to agriculture, industry, tourism, transportation, and even ood protection; a balanced river ecology is of great signi cance to development (Li et al. 2020). E cient measures must be implemented to manage and monitor pollution from SPM. There are many gates and dams along the Beiyun River, which has a discontinuous ow and a dense population. SPM is a typical heavy metal adsorbent, which makes it an effective way to reduce heavy metal pollution by controlling the concentration (Laurent et al. 2009). In view of the excessive heavy metals in SPM of Beiyun River, the management of external pollution should be increased, and the sources of heavy metal pollution must be reduced. Intercepting installations in all drainage outlets could control the pollution from SPM in this area (Jeong et al. 2020 and those in the middle reaches, near the Tianjin urban area were signi cantly lower. Thus, the prevention and control policy of urban river pollution is highly e cient. (2) Risk and order of heavy metals in SPM The Igeo results showed that the order of heavy metal pollution degree in SPM was As > Cd > Zn > Cu > Pb > CR > Ni. Zn, Cu, Pb, and Cr were in a state of partial severe pollution. The potential ecological hazard index of single factor heavy metals, , showed that the rank of potential ecological risk about heavy metals was Cd > As > Cu > Pb > Ni > Cr > Zn. Cd presented a very strong ecological risk and Ni was a medium ecological risk. The RI method showed that the Beiyun River system had a strong potential ecological risk. Among them, the risk of Cd is much higher than that of other metals. (

3) Sources of heavy metals in SPM
The Beiyun River is located in a typical agricultural area. The heavy metal pollution of SPM is mainly affected by chemical fertilizers, pesticides, feed additives, industrial activities, and land ll. Human pollution is the main reason for the higher concentration of Zn, Cu, Pb, and Ni in SPM than background concentration. In river systems, heavy metals accumulate continuously, and severe pollution will eventually harm human health through food chains.
(4) Counter-measures In theory, the concentration of SPM should be controlled rst. The sediment pollution in upper reaches should be reduced by ameliorating soil erosion. The river itself should be regularly dredged to avoid resuspension and reduce contaminants. In addition, industrial emissions should also be lessened. Waste incineration, metallurgy, electroplating, and coal combustion all produce numerous pollutants. Controlling industrial pollution emissions can indirectly prevent contamination accumulation in the Beiyun River basin.

Declaration of Competing Interest
The authors declare that they have no known competing nancial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment
This work was supported by Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences (RCEES) and Beijing Forestry University (BJFU). In addition, we also acknowledge other researchers and students who providing management and skills.
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Consent to Participate
The submission has been received explicitly from all co-authors. And authors whose names appear on the submission have contributed su ciently to the scienti c work and therefore share collective responsibility and accountability for the results.