Distribution and fractionation of rare earth elements in suspended particulate matter in a coastal river, Southeast China

Study area

The Jiulongjiang River (24°05′N–25°55′N, 106°50′E–118°20′E), which is situated at the southeast coastal margin of the Chinese mainland, has the basin area of about 14,740 km² (Liu & Han, 2020). The main stream flows across the Longyan and Zhangzhou cities with a channel length of 260 km and an annual water discharge of 14 km³. The Jiulongjiang River is comprised of the three main rivers, including Beixi River, Nanxi River, and Xixi River. The basin is mainly controlled by the sub-tropic monsoon climate. The period with the majority of rainfalls (∼80%) and the highest air temperature are simultaneously concentrated in the wet season from April to September. In the basin, mean annual precipitation (MAP) ranges from 1400 mm to 1800 mm and the mean annual temperature (MAT) varies from 19.9 °C to 21.1 °C (Liu & Han, 2020). Magmatic rocks and clastic sedimentary rocks are widely distributed in the basin, while metamorphic rocks and limestones are exposed rarely (Li, Qiu & Yang, 2014). The red soils, which are classified into Alisols (WRB, 2014), account for >90% area of the basin. The region of upper reaches mainly flows through mountain areas with high forest coverage and slight agricultural and industrial perturbations, while other regions are affected by different degrees of human activities (Huang et al., 2013). Furthermore, the Wananxi Reservoir regulates the discharge of river water in the upper reaches of the Beixi River.

Sample collection and in-field measurements

A total of 42 river water samples were collected in the high-flow season (July) of 2014 (Fig. 1 and Table 1). The river water samples of 1–21, 24–33, and 34–37 were collected along with the Beixi River, Xixi River, and Nanxi River, respectively. The sites of 22, 23, and 38–42 were located in the estuary region. The physicochemical parameters of pH values and total dissolved solids (TDS) concentrations in river and estuary water were measured using a water quality monitor (YSI multi-parameter probe) on site. The HCO₃⁻ concentrations were determined using titration with diluent HCl solution (Liu & Han, 2021). All river water samples were hoisted by a clean plastic bucket from the center of the river on bridges and ferries. The samples were collected at a depth about 0.5 m below the water surface. Water samples were stored in a 50L LDPE bag, which had been pre-cleaned with 10% nitric acid. The collected river waters were filtered through a 0.22 µm cellulose acetate membrane (Millipore) to separate SPM samples within 24 h. Compared to the 0.45 µm size, the 0.22 µm size was more widely employed to distinguish SPM and dissolved solutes in natural river water (Zeng & Han, 2020; Zeng, Han & Yang, 2020). An important reason is that the 0.22 µm filter can separate most particles or colloids associated with anthropogenic sources, such as living substances and biopolymer aggregates (Jackson & Burd, 2015). The SPM samples absorbed on the surface of the filter membrane were collected through washing by deionized water and then dried on a hotplate at 55 °C.

Analytical methods

The SPM samples were digested to dissolved loads according to the modified method by Li & Han (2021). The procedure was showed in detail, dried SPM sample was weighed 100 mg, put into a cleaned PFA digestion tank digested, added one mL pure HF and three mL pure HNO₃, heated keeping at 140 °C for 3 days (Li et al., 2020). Finally, the solid sample was transformed into a solution, and then stored in a 2% HNO₃ solution for analyzing the concentrations of REEs and major elements. For the entire procedure, the blank samples and standard samples (GBW07404 and GBW07120) were treated the same as the samples, to monitor procedural reliability. The recovery rate of Ce was more than 90% and over 95% for other REEs during the digestion procedure. The concentrations of REEs (including La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu) in SPM were determined by an inductively coupled plasma mass spectrometry (ICP-MS, ELAN DRC-e, Perkin Elmer, Waltham, Massachusetts, USA), and the concentrations of major elements (including Al, Ca, Fe, K, Mg, Mn, Na, and Ti) were analyzed by an inductively coupled plasma optical emission spectroscopy (ICP-OES, Optima 5300DV, PerkinElmer, Waltham, Massachusetts, USA) (Liu, Han & Li, 2021). To restrict the mass interferences of BaO⁺ on Eu during the instrument testing process, a liquid-liquid extraction method was employed to remove Ba efficiently, as well as other matrix elements (Shabani & Masuda, 1991). The precision and accuracy of measurement were evaluated by repeated analysis of standard solution with multi-element, which were better than ±3% for major elements and better than ±5% for REEs, respectively.

Chemical index of alteration

The chemical index of alteration (CIA) of SPM can indicate the degree of weathering (i.e., the evolution degree from luminum–silicate minerals (especially feldspar) to clay minerals) in the source region (Nesbitt & Young, 1982). The higher CIA value means the more intensive leaching of Na, K, and Ca in silicate minerals, that is the stronger chemical weathering. The CIA > 80% indicates strong chemical weathering; 60% < CIA < 80% indicates moderate chemical weathering; CIA < 60% indicates weak chemical weathering. The CIA can be obtained by the calculation of molecular proportions, as the formula:

where CaO* (mol/kg) is the molecular mass concentration of CaO incorporated in the silicate fraction of the rock. A correction is made for carbonate and apatite content (McLennan, 1993). In brief, if CaO/Na₂O (mole ratio) > 1, the mole fraction of CaO* is replaced by the mole fraction of Na₂O; if CaO/Na₂O < 1, CIA is calculated directly using the mole fraction of CaO.

REE fractionation indexes and anomalies

The Post Archean Australia Shale (PAAS)-normalized REE patterns for SPM was calculated as the formula (Han et al., 2009):

The PAAS-normalized La/Yb ratio ((La/Yb)_N), La/Sm ratio ((La/Sm)_N), and Sm/Yb ratio ((Sm/Yb)_N) indicate the relative fractionation between LREE and HREE, between LREE and MREE, and between MREE and HREE in SPM, respectively (Xu & Han, 2009):

The anomalies of Ce (δCe), Eu (δEu), and Gd (δGd) are calculated as the formulas (Hissler et al., 2015; Olivarez & Owen, 1991):

The positive and negative Ce and Eu anomalies are determined by the values of >1 and <1, respectively. The δGd > 1.6 implies the presence of anthropogenic Gd sources (Louis et al., 2020).

Statistical analysis

Boxplot was used to show the ranges of the concentrations of ∑REE, ∑LREE, ∑MREE, and ∑HREE of SPM in different regions of the Jiulongjiang River basin. The normal distribution of the sample data set were tested via the Shapiro–Wilk test before Pearson correlation analysis. Pearson correlation coefficient determined the relationship between physicochemical parameters and REE fractionation proxies of SPM. All statistical analyses were performed by the SPSS 18.0 software (SPSS Inc., Chicago, IL, USA) and all graphs were drawn by SigmaPlot 12.5 software (Systat Software GmbH, Erkrath, Germany).

Hydrochemical characteristics

The pH, TDS, and HCO₃⁻ concentration of river water at different sampling sites in the Jiulongjiang River are showed in Table 1. The pH values ranged from 6.7 to 7.9 (mean 7.2 ± 0.3), indicating the neutral and slightly alkaline river water. The TDS varied intensively with a range of 27.1–720 mg/L (mean 111 ± 107 mg/L). Moreover, the higher TDS mainly occurred in the water of the estuary region. The HCO₃⁻ concentrations ranged from 7.5 mg/L to 49.0 mg/L (mean 22.1 ± 9.1 mg/L) and showed an increasing trend downstream. Particularly, the water of tributary in the Beixi River had higher HCO₃⁻ concentrations compared to the main stream.

The concentrations of major elements in SPM and CIA values

The concentrations of the major elements in SPM are shown in Table 2. The average Al, Ca, Fe, K, Mg, Mn, Na, and Ti concentrations in SPM were 151 ± 22.6 g/kg, 4.8 ± 7.8 g/kg, 49.6 ± 20.2 g/kg, 17.3 ± 3.7 g/kg, 4.3 ± 2.3 g/kg, 1.2 ± 0.5 g/kg, 2.1 ± 1.9 g/kg, and 2.9 ± 0.6 g/kg, respectively. Generally, the concentrations of the major elements slightly varied among the sites in the river, except for several sampling sites. For example, the No. 21 and 34 sites had relatively high Ca, Mg, and Na concentrations. However, Al and Fe concentrations at the 34 site were significantly lower than those at other sites, but not at the 21 site. Furthermore, most metal elements, besides Mn, were at a relatively high concentration at the 37 site. The CIA values varied among the sites in the river with a range of 83.2%–95.7% (89.6 ± 4.8%), except for the exceptionally low value of 63.7% at the 34 site (Table 3). Particularly, the CIA values in the tributary of the Beixi River were slightly lower than those in the main stream.

REE concentrations of SPM

The concentrations of single REE in SPM at different sampling sites are shown in Table 4. The total REE (∑REE) concentrations of SPM ranged from 111 mg/kg to 1,292 mg/kg with an average of 376 ± 191 mg/kg (Fig. 2), which were higher than those of the UCC (146 mg/kg) (Taylor & McLennan, 1985), the local soils of Fujian Province (198 mg kg⁻¹) (Chen et al., 1992), the SPM of world rivers (175 mg/kg) (Viers, Dupre & Gaillardet, 2009), and the PAAS (185 mg/kg) (Taylor & McLennan, 1985)). The LREEs accounted for the largest proportion of total REEs in SPM at all sites. The ∑LREE concentrations of SPM ranged from 95.5 mg/kg to 1093 mg/kg with an average of 324 ± 164 mg/kg. The ∑MREE and ∑HREE concentrations of SPM varied from 12.5 mg/kg to 162 mg/kg (mean 42.2 ± 22.9 mg/kg) and from 2.6 mg/kg to 36.9 mg/kg (mean 10.2 ± 5.1 mg/kg), respectively. For spatial distribution, the ∑REE ∑LREE, ∑MREE and ∑HREE concentrations of SPM in the main stream of Beixi River were similar to those in the Xixi River and Nanxi River (Fig. 2). However, these concentrations in the tributary of Beixi River were significantly lower than those in the main stream, but near to those in the estuary region.

PAAS-normalized REE patterns of SPM

The PAAS-normalized REE patterns of SPM at each site were showed in Table 5. The PAAS-normalized REE ratios of SPM at most sites were larger than 1, except for the parts of REEs at the 11, 34, and 40 sites. The pattern of average SPM in the main stream of Beixi River was almost identical to that in the Xixi River and Nanxi River (Fig. 3). Additionally, the pattern in the tributary of Beixi River was similar to that in the estuary region. Overall, the enrichment of REEs in SPM was larger in the main stream than that in tributary and estuary. The (La/Yb)_N ratio, (La/Sm)_N ratio, and (Sm/Yb)_N ratio of SPM at different sites are shown in Fig. 4. The (La/Yb)_N and (Sm/Yb)_N ratios at all sites were higher than 1, indicating the enrichment of LREE and MREE relative to HREE in SPM. The (La/Yb)_N and (Sm/Yb)_N ratios generally showed a decreasing trend downstream in the Beixi River. The (La/Sm)_N ratio of SPM varied within a wide range of 0.7–1.3, indicating the strong spatial variability between LREE and MREE fractionation in the river.

Ce, Eu, and Gd anomalies in SPM

The Ce, Eu, and Gd anomalies in SPM at different sites are shown in Fig. 5. The Ce of SPM at most sites showed a slight negative anomaly (δCe: 0.8–1.0), except for the relatively large negative anomaly at the 1 and 28 sites with a δCe value of 0.70 and 0.43, respectively. The Eu of SPM at most sites showed negative anomaly (δEu: 0.7–1.0). Exceptionally, a positive Eu anomaly occurred at the 21 and 34 sites with a δEu value of 1.15 and 1.24, respectively. Additionally, the δEu value generally showed an increasing trend along with the flow direction of the main stream. The δGd values of SPM at most sites ranged from 1.5 to 1.6, except for a relatively higher δGd value at the 37 site (1.72) and a relatively lower value at the 28 site (1.40). This result indicates that the SPM in the Jiulongjiang River is almost not affected by anthropogenic Gd sources.

Variation of REE concentrations and PAAS-normalized REE ratios in SPM

Controls of REE concentrations in SPM of river water by weathering processes

The clay minerals of SPM mainly derived from the weathering of rocks are important carriers of REE (Migaszewski & Galuszka, 2015). Thus, the REE concentrations of SPM are closely associated with the lithologic distribution in a basin. In the main stream of Beixi River, the PAAS-normalized REE ratios of SPM positively correlated with Al concentrations and CIA values, and negatively correlated with TDS, Fe, K, and Mg concentrations (Table 6). These results indicated that the REE concentrations of SPM were dominated by silicate weathering in the main stream, similar to the report from the downstream of Zhujiang River (Xu & Han, 2009). In the basin, the weathering of magmatic rocks and clastic sedimentary rocks contributes to abundant Al-silicate minerals (clay minerals) into soils. These clay minerals, which carry most REEs, are transferred into the river by soil erosion, resulting in the increment of REE concentration in SPM (Linders et al., 2018). Thus, the PAAS-normalized REE ratios positively correlated with Al concentrations in SPM.

In the tributary of Beixi River, the PAAS-normalized REE ratios of SPM positively correlated with Ca concentrations and negatively correlated with CIA values. These results indicated that the REE concentrations of SPM in the tributary were also affected by carbonate weathering. Han, Yang & Zeng (2021) reported a significant correlation relationship between Ca concentrations and REE concentrations of SPM upstream of the Zhujiang River mainly distributed by carbonate rocks. Moreover, the ∑REE, ∑LREE, ∑MREE, ∑HREE, and REE concentrations, PAAS-normalized REE ratios of SPM in the tributary were lower than those in the main stream (Figs. 2 and 3). A similar result about the low REE concentrations of SPM in the karst basin has been reported by Han et al. (2009). The CIA values of SPM in the tributary of the Beixi River were slightly lower than those in the main stream (Table 1). The result indicated that the SPM in the tributary consisted of many low-weathered carbonate minerals. However, the carbonate rock contains very few REEs, with a mean ∑REE concentration of 8.05 mg kg⁻¹ (Han, Yang & Zeng, 2021). Thus, the river flowing through the carbonate rock region is characteristic of the low REE and high Ca concentrations in SPM (Xu & Han, 2009).

The ∑REE, ∑LREE, ∑MREE, and ∑HREE concentrations, PAAS-normalized REE ratios of SPM in the Xixi River and Nanxi River were near to those in the main stream of Beixi River (Figs. 2 and 3). Moreover, the correlation relationships (although not significantly) of the PAAS-normalized REE ratios with major element concentrations and CIA values were also similar in the three rivers (Table 6). These results indicated that the REE concentrations in the Xixi River and Nanxi River were also controlled by the weathering of magmatic rocks and clastic sedimentary rocks. However, the non-significant correlation relationships were likely attributed to the influences from human activities. Compared to the wide forest upstream of the Beixi River, the Xixi River and Nanxi River mainly pass through farmlands and residential areas (Liu & Han, 2020). Human activities can directly cause the increment of REE into the river and disturb REE fractionation by affecting physicochemical parameters of river water (Da Silva et al., 2018; Yang et al., 2021).

Influences of salinity on REE concentrations in SPM of estuary water

The PAAS-normalized REE ratios of SPM in the estuary region were near to those in the tributary of Beixi River (Fig. 3). The result is not attributed to the weathering of carbonate minerals like that in the tributary of the Beixi River. Theoretically, the characteristics of REE concentrations in the estuary region should inherit from the main stream of Beixi river, Xixi River, and Nanxi River because the three main rivers have the larger water discharge compared to the tributary of the Beixi River. In the estuary region, the PAAS-normalized REE ratios of SPM negatively correlated with K and Mg concentrations, and positively correlated with CIA values (Table 6), indicating the effects of silicate weathering on REE concentrations of SPM similar to the effects in the main stream of Beixi River. Compared to river water, the estuary water was lower in REE concentrations of SPM (Fig. 3), which was mainly attributed to REE removal. Elderfield, Upstill-Goddard & Sholkovitz (1990) found that significant REE removal (∼30%) occurred in the Connecticut, Delaware, Mullica, and Tamar estuaries. During the mixing of river water and seawater, the increment of salinity promotes the coagulation of colloidally associated Fe and Mn hydroxides (Migaszewski & Galuszka, 2015). The flocculations easily absorb REEs and transfer them into the sediments, resulting in significant removals of both dissolved and particulate REE. Thus, the coprecipitation of Fe and Mn hydroxides and REEs in the estuary explained the positive correlation (although non-significant) between the PAAS-normalized REE ratios and Fe (and Mn) concentrations of SPM (Table 6).

Table 5:

The PAAS-normalized REE patterns for SPM in the Jiulongjiang River basin.

(T) indicates the site located in tributary of the Beixi River.

Sampling site	LaN	CeN	PrN	NdN	SmN	EuN	GdN	TbN	DyN	HoN	ErN	TmN	YbN	LuN
Beixi River
1	6.61	4.17	5.28	4.77	5.68	4.12	8.01	5.06	4.21	3.49	3.53	3.12	2.90	2.58
2	3.86	2.98	3.07	2.96	3.12	2.26	4.58	2.69	2.24	1.93	2.03	1.88	1.82	1.65
3	3.43	2.77	2.74	2.43	2.91	1.93	4.42	2.64	2.21	1.90	1.94	1.76	1.71	1.53
4(T)	1.37	1.08	1.19	1.25	1.85	2.10	3.26	2.25	1.84	1.58	1.49	1.29	1.20	1.14
5	2.41	2.04	2.03	1.87	2.25	1.63	3.38	2.06	1.74	1.51	1.54	1.44	1.40	1.28
6(T)	1.24	1.04	1.10	1.08	1.44	1.31	2.09	1.45	1.29	1.17	1.22	1.20	1.17	1.12
7(T)	1.64	1.35	1.39	1.35	1.66	1.65	2.50	1.53	1.29	1.14	1.18	1.07	1.03	1.00
8(T)	1.68	1.38	1.42	1.38	1.70	1.67	2.52	1.56	1.33	1.18	1.22	1.12	1.10	1.02
9	2.27	1.90	1.90	1.81	2.29	2.06	3.49	2.14	1.79	1.53	1.54	1.39	1.32	1.23
10	1.84	1.60	1.56	1.42	1.78	1.38	2.67	1.66	1.40	1.23	1.28	1.20	1.18	1.09
11(T)	1.46	1.23	1.22	1.15	1.37	1.31	1.99	1.18	0.99	0.87	0.91	0.83	0.82	0.77
12	2.29	2.06	1.97	1.81	2.22	1.86	3.26	2.00	1.70	1.51	1.55	1.44	1.37	1.28
13	2.50	2.36	2.34	2.14	2.82	1.99	3.98	2.53	2.25	2.07	2.26	2.27	2.28	2.16
14	2.39	2.11	2.08	1.96	2.38	1.93	3.53	2.16	1.85	1.62	1.70	1.61	1.55	1.44
15	2.20	1.90	1.81	1.73	2.17	1.73	3.20	2.04	1.74	1.57	1.65	1.56	1.49	1.42
16	2.64	2.21	2.28	2.06	2.57	2.27	3.77	2.34	2.03	1.85	1.97	1.90	1.89	1.81
17	2.09	1.96	1.82	1.68	2.11	1.76	3.12	1.87	1.60	1.43	1.50	1.44	1.39	1.30
18	2.02	1.91	1.81	1.70	2.12	1.81	3.12	1.92	1.63	1.45	1.54	1.46	1.41	1.30
19	2.02	1.83	1.76	1.65	2.11	1.73	3.17	1.97	1.72	1.56	1.64	1.56	1.51	1.44
20	1.94	1.83	1.73	1.58	2.04	1.64	2.99	1.83	1.57	1.41	1.49	1.41	1.39	1.30
21(T)	2.00	1.76	1.71	1.59	1.94	2.12	2.77	1.64	1.41	1.27	1.35	1.24	1.23	1.14
Xixi River
24	2.13	1.81	1.82	1.66	2.10	1.63	3.09	1.99	1.74	1.56	1.61	1.54	1.49	1.37
25	2.31	1.89	1.87	1.74	2.17	1.68	3.24	2.09	1.83	1.63	1.69	1.63	1.59	1.51
26	2.25	1.94	1.91	1.77	2.19	1.71	3.25	2.04	1.80	1.61	1.69	1.61	1.59	1.49
27	2.27	2.06	2.03	1.89	2.32	1.82	3.42	2.14	1.87	1.65	1.73	1.63	1.59	1.49
28	10.7	4.19	8.57	8.07	8.87	6.16	12.41	8.91	7.46	6.60	6.46	5.61	5.06	4.58
29	3.66	2.30	2.87	2.65	3.12	2.41	4.51	2.96	2.52	2.23	2.26	2.02	1.93	1.77
30	2.79	2.14	2.19	2.04	2.39	2.00	3.60	2.22	1.95	1.76	1.93	1.88	1.91	1.86
31	2.95	2.33	2.43	2.26	2.69	2.16	4.01	2.43	2.09	1.86	1.93	1.78	1.73	1.60
32	2.38	2.02	2.02	1.84	2.17	1.86	3.23	1.92	1.62	1.42	1.49	1.41	1.37	1.28
33	2.30	1.88	1.85	1.77	2.10	1.75	3.12	1.87	1.59	1.40	1.47	1.37	1.35	1.28
Nanxi River
34	0.66	0.57	0.58	0.59	0.74	0.84	0.96	0.56	0.47	0.39	0.41	0.39	0.38	0.35
35	2.77	1.97	2.06	1.88	2.21	1.79	3.30	2.06	1.86	1.70	1.85	1.78	1.74	1.67
36	2.14	1.51	1.76	1.56	1.88	1.69	2.65	1.74	1.57	1.44	1.56	1.54	1.52	1.44
37	2.26	1.82	1.85	1.91	2.23	1.98	3.63	2.05	1.79	1.61	1.74	1.71	1.55	1.53
Estuary
22	1.67	1.52	1.46	1.37	1.72	1.58	2.53	1.56	1.34	1.19	1.27	1.22	1.17	1.09
23	1.32	1.16	1.18	1.16	1.39	1.28	2.07	1.27	1.11	1.01	1.06	1.02	1.00	0.95
38	1.67	1.49	1.48	1.39	1.75	1.49	2.47	1.56	1.35	1.22	1.28	1.17	1.15	1.05
39	1.32	1.15	1.10	1.04	1.37	1.23	2.01	1.27	1.12	1.00	1.05	1.00	0.97	0.93
40	1.03	0.92	0.88	0.86	1.02	0.98	1.48	0.86	0.74	0.67	0.69	0.66	0.64	0.60
41	1.54	1.34	1.30	1.25	1.60	1.38	2.33	1.47	1.28	1.16	1.21	1.15	1.11	1.05
42	1.54	1.36	1.33	1.28	1.59	1.41	2.36	1.44	1.27	1.14	1.20	1.15	1.11	1.05

DOI: 10.7717/peerj.12414/table-5

Table 6:

Pearson correlation coefficient between physicochemical parameters and REEfractionation proxies of SPM in different regions of the Jiulongjiang River.

The normal distribution of the sample data set were tested via the Shapiro-Wilk test before Pearson correlation analysis. Statistical significant correlation at the level of P < 0.05 (*) and P < 0.01 (**).

	Water pH	TDS	HCO3−	Al	Ca	Fe	K	Mg	Mn	Na	Ti	CIA
Beixi River (Main stream)
LaN	–0.38	–0.79**	–0.78**	0.58*	–0.02	–0.52	–0.58*	–0.35	–0.49	0.01	–0.71**	0.45
CeN	–0.34	–0.86**	–0.85**	0.69**	–0.16	–0.55*	–0.70**	–0.51	–0.52	–0.17	–0.69**	0.61*
PrN	–0.30	–0.85**	–0.84**	0.68**	–0.07	–0.57*	–0.70**	–0.48	–0.55*	–0.10	–0.71**	0.58*
NdN	–0.30	–0.83**	–0.82**	0.62*	–0.06	–0.54*	–0.68**	–0.44	–0.54*	–0.08	–0.69**	0.55*
SmN	–0.19	–0.90**	–0.85**	0.73**	–0.06	–0.62*	–0.77**	–0.55*	–0.53	–0.16	–0.66*	0.65*
EuN	0.16	–0.75**	–0.57*	0.37	0.30	–0.47	–0.49	–0.29	–0.41	0.15	–0.21	0.33
GdN	–0.26	–0.87**	–0.82**	0.67**	–0.02	–0.57*	–0.69**	–0.46	–0.53	–0.09	–0.66*	0.56*
TbN	–0.17	–0.88**	–0.81**	0.70**	0.01	–0.61*	–0.73**	–0.50	–0.50	–0.11	–0.65*	0.60*
DyN	–0.08	–0.90**	–0.82**	0.74**	–0.01	–0.64*	–0.79**	–0.58*	–0.47	–0.16	–0.61*	0.66*
HoN	0.06	–0.93**	–0.83**	0.78**	–0.01	–0.69**	–0.84**	–0.67**	–0.40	–0.20	–0.55*	0.72**
ErN	0.15	–0.90**	–0.84**	0.81**	–0.04	–0.71**	–0.88**	–0.75**	–0.36	–0.26	–0.51	0.77**
TmN	0.25	–0.86**	–0.81**	0.82**	–0.08	–0.70**	–0.91**	–0.81**	–0.31	–0.33	–0.45	0.82**
YbN	0.28	–0.83**	–0.80**	0.84**	–0.07	–0.71**	–0.92**	–0.82**	–0.30	–0.34	–0.45	0.84**
LuN	0.37	–0.80**	–0.75**	0.80**	–0.04	–0.70**	–0.89**	–0.82**	–0.24	–0.32	–0.38	0.81**
(La/Yb)N	–0.69**	–0.19	–0.21	–0.01	0.02	–0.02	0.09	0.30	–0.37	0.27	–0.52	–0.17
(La/Sm)N	–0.53	–0.37	–0.43	0.20	0.06	–0.24	–0.15	0.04	–0.29	0.28	–0.63*	0.03
(Sm/Yb)N	–0.74**	0.07	0.11	–0.30	0.01	0.25	0.38	0.58*	–0.36	0.27	–0.27	–0.41
δCe	0.22	0.39	0.36	–0.18	–0.44	0.34	0.23	–0.10	0.39	–0.47	0.60*	0.01
δEu	0.50	0.37	0.55*	–.63*	0.47	0.33	0.54*	0.46	0.28	0.43	0.77**	–0.55*
δGd	–0.71**	–0.09	–0.15	–0.11	–0.03	0.20	0.22	0.33	–0.27	0.27	–0.19	–0.24
Beixi River (Tributary)
LaN	0.58	–0.23	–0.14	0.34	0.83*	–0.38	0.07	0.71	0.60	0.69	0.80	–0.45
CeN	0.56	–0.33	–0.25	0.44	0.88*	–0.46	0.10	0.79	0.54	0.73	0.86*	–0.43
PrN	0.53	–0.22	–0.23	0.34	0.86*	–0.36	0.05	0.77	0.52	0.74	0.79	–0.51
NdN	0.43	–0.01	–0.19	0.14	0.82*	–0.17	–0.10	0.70	0.48	0.74	0.63	–0.63
SmN	–0.08	0.49	–0.27	–0.36	0.66	0.39	–0.53	0.51	0.10	0.73	0.11	–0.91*
EuN	–0.21	0.62	–0.24	–0.49	0.64	0.53	–0.69	0.42	0.07	0.71	–0.01	–0.95**
GdN	–0.38	0.83*	–0.08	–0.74	0.32	0.76	–0.77	0.11	–0.04	0.45	–0.35	–0.86*
TbN	–0.60	0.90*	–0.12	–0.83*	0.09	0.88*	–0.79	–0.05	–0.31	0.28	–0.60	–0.77
DyN	–0.60	0.85*	–0.21	–0.77	0.12	0.84*	–0.75	0.02	–0.38	0.33	–0.57	–0.79
HoN	–0.59	0.79	–0.29	–0.71	0.17	0.79	–0.71	0.10	–0.42	0.38	–0.52	–0.81
ErN	–0.49	0.65	–0.43	–0.54	0.32	0.64	–0.60	0.30	–0.42	0.52	–0.34	–0.86*
TmN	–0.46	0.44	–0.61	–0.33	0.32	0.46	–0.41	0.43	–0.58	0.54	–0.25	–0.78
YbN	–0.38	0.30	–0.69	–0.17	0.42	0.32	–0.32	0.56	–0.56	0.62	–0.11	–0.77
LuN	–0.38	0.32	–0.66	–0.20	0.34	0.35	–0.30	0.50	–0.60	0.56	–0.17	–0.73
(La/Yb)N	0.72	–0.40	0.41	0.39	0.35	–0.53	0.26	0.13	0.90*	0.08	0.71	0.23
(La/Sm)N	0.81	–0.73	0.18	0.73	0.36	–0.83*	0.58	0.32	0.73	0.10	0.875*	0.37
(Sm/Yb)N	0.40	0.22	0.61	–0.22	0.25	0.06	–0.27	–0.15	0.88*	0.05	0.27	–0.09
δCe	0.48	–0.69	–0.38	0.76	0.73	–0.72	0.31	0.72	0.34	0.57	0.92**	–0.04
δEu	0.11	0.32	–0.14	–0.19	0.82*	0.19	–0.53	0.53	0.44	0.77	0.38	–0.78
δGd	0.55	0.04	0.47	–0.01	0.43	–0.14	–0.12	0.10	0.92**	0.22	0.50	–0.14
Xixi River and Nanxi River
LaN	–0.20	–0.13	–0.24	–0.15	–0.27	–0.06	–0.12	–0.18	–0.08	–0.18	0.03	0.11
CeN	0.04	–0.23	–0.24	0.00	–0.30	0.15	–0.06	–0.21	–0.48	–0.27	0.15	0.19
PrN	–0.08	–0.18	–0.30	–0.11	–0.31	0.04	–0.12	–0.21	–0.14	–0.26	0.06	0.20
NdN	–0.09	–0.01	–0.20	0.10	–0.13	0.23	0.10	0.00	–0.17	–0.07	0.22	0.02
SmN	0.04	–0.12	–0.32	0.08	–0.21	0.22	0.04	–0.07	–0.24	–0.17	0.17	0.12
EuN	–0.26	0.19	–0.05	0.20	0.04	0.31	0.23	0.15	0.01	0.09	0.35	–0.15
GdN	0.00	0.05	–0.22	0.28	–0.01	0.39	0.26	0.14	–0.26	0.03	0.36	–0.08
TbN	0.12	–0.19	–0.43	0.08	–0.23	0.17	0.02	–0.09	–0.22	–0.20	0.14	0.16
DyN	0.13	–0.23	–0.50	0.07	–0.23	0.13	0.01	–0.09	–0.16	–0.20	0.13	0.17
HoN	0.10	–0.23	–0.52	0.07	–0.22	0.10	0.01	–0.08	–0.10	–0.17	0.14	0.15
ErN	0.00	–0.18	–0.49	0.10	–0.14	0.07	0.05	–0.02	0.01	–0.08	0.19	0.06
TmN	–0.06	–0.14	–0.49	0.17	–0.02	0.06	0.12	0.07	0.14	0.04	0.28	–0.04
YbN	–0.07	–0.31	–0.52	–0.01	–0.18	–0.15	–0.07	–0.12	0.16	–0.12	0.11	0.11
LuN	–0.15	–0.19	–0.42	0.09	–0.03	–0.11	0.04	0.00	0.23	0.03	0.19	–0.04
(La/Yb)N	–0.30	0.13	0.24	–0.26	–0.23	0.05	–0.12	–0.16	–0.33	–0.15	–0.06	0.03
(La/Sm)N	–0.60*	–0.08	0.05	–0.53	–0.23	–0.56	–0.36	–0.27	0.29	–0.06	–0.24	–0.01
(Sm/Yb)N	0.10	0.23	0.25	0.12	–0.06	0.48	0.15	0.04	–0.57	–0.09	0.12	0.02
δCe	0.41	–0.02	0.15	0.28	0.13	0.30	0.16	0.09	–0.53	0.02	0.14	–0.01
δEu	–0.74**	0.74**	0.78**	0.18	0.58*	0.14	0.36	0.47	0.65*	0.62*	0.30	–0.62*
δGd	–0.31	0.79**	0.63*	0.74**	0.79**	0.75**	0.82**	0.80**	–0.17	0.81**	0.78**	–0.83**
Estuary region
LaN	–0.62	–0.78*	–0.68	0.26	0.23	0.57	–0.80*	–0.88**	0.67	–0.88**	0.38	0.81*
CeN	–0.63	–0.74	–0.63	0.26	0.21	0.55	–0.77*	–0.87*	0.62	–0.85*	0.36	0.79*
PrN	–0.60	–0.77*	–0.66	0.37	0.25	0.59	–0.82*	–0.91**	0.68	–0.90**	0.27	0.86*
NdN	–0.57	–0.78*	–0.68	0.43	0.27	0.61	–0.82*	–0.92**	0.68	–0.92**	0.24	0.88**
SmN	–0.58	–0.82*	–0.72	0.29	0.28	0.62	–0.84*	–0.91**	0.72	–0.91**	0.36	0.85*
EuN	–0.50	–0.80*	–0.72	0.30	0.35	0.65	–0.78*	–0.91**	0.60	–0.87*	0.36	0.80*
GdN	–0.51	–0.85*	–0.76*	0.29	0.34	0.65	–0.82*	–0.92**	0.68	–0.91**	0.41	0.83*
TbN	–0.51	–0.87*	–0.79*	0.26	0.36	0.68	–0.85*	–0.92**	0.73	–0.92**	0.42	0.84*
DyN	–0.48	–0.89**	–0.81*	0.25	0.37	0.68	–0.86*	–0.92**	0.74	–0.92**	0.44	0.83*
HoN	–0.49	–0.90**	–0.81*	0.28	0.37	0.68	–0.87*	–0.93**	0.76*	–0.93**	0.41	0.85*
ErN	–0.47	–0.90**	–0.81*	0.27	0.38	0.69	–0.87*	–0.93**	0.75	–0.93**	0.42	0.84*
TmN	–0.41	–0.91**	–0.84*	0.26	0.43	0.72	–0.83*	–0.92**	0.69	–0.91**	0.46	0.81*
YbN	–0.41	–0.92**	–0.85*	0.29	0.44	0.73	–0.86*	–0.94**	0.73	–0.93**	0.43	0.84*
LuN	–0.35	–0.94**	–0.88**	0.26	0.48	0.75	–0.84*	–0.93**	0.71	–0.92**	0.47	0.81*
(La/Yb)N	–0.36	0.89**	0.94**	–0.26	–0.85*	–0.86*	0.66	0.70	–0.59	0.67	–0.33	–0.56
(La/Sm)N	–0.04	0.93**	0.93**	–0.52	–0.73	–0.90**	0.89**	0.89**	–.80*	0.89**	–0.11	–0.85*
(Sm/Yb)N	–0.48	0.81*	0.89**	–0.13	–0.84*	–0.78*	0.53	0.55	–0.47	0.53	–0.39	–0.39
δCe	–0.20	0.37	0.40	–0.58	–0.31	–0.38	0.52	0.32	–0.63	0.44	0.36	–0.51
δEu	0.43	0.83*	0.75	–0.11	–0.23	–0.52	0.84*	0.73	–0.88**	0.824*	–0.47	–0.72
δGd	0.35	0.79*	0.73	–0.01	–0.35	–0.62	0.84*	0.71	–0.87*	0.74	–0.41	–0.67

DOI: 10.7717/peerj.12414/table-6

Eeffects of physicochemical properties on REE fractionations of SPM

River SPM is mainly derived from local soils by soil erosion (Linders et al., 2018). However, the PAAS-normalized REE patterns of SPM showed a huge discrepancy compared with local soils (Chen et al., 1992) (Fig. 3). The discrepancy is mainly attributed to REE fractionations between the colloidal (solid) pool and dissolved pool (Elderfield, Upstill-Goddard & Sholkovitz, 1990). Overall, the (La/Yb)_N and (Sm/Yb)_N ratios of SPM were near 1.5, and the (La/Sm)_N ratio was near 1 in the basin (Fig. 4), indicating the enrichments of LREE and MREE relative to HREE in SPM. The enrichment of LREE in SPM is closely linked with the strong adsorption by clay minerals, whereas HREE prefers to form stable soluble complexes (Da Silva et al., 2018). The river water pH plays an important role in affecting the fractionation degree between LREE and HREE in SPM. In the main stream of the Beixi River, the (La/Yb)_N ratios of SPM ranged from 1.1 to 2.3 (Fig. 4) and water pH values ranged from 6.7 to 7.6 (Table 1). Similarly, in the granite region of the Zhujiang River basin, the riverine pH decreased from 8.1 to 7.4 during 2000–2014, while the (La/Yb)_N ratio of SPM increased from 1.1 to 1.3 (Xu & Han, 2009). Because HREE is preferentially removed from associated SPM into the dissolved load with increasing river water acidity rather than LREE (Migaszewski, Galuszka & Dolegowska, 2019). This reason also explains the increments of (La/Yb)_N and (Sm/Yb)_N ratios in SPM along the flow direction and negative correlations of them with water pH values in the main stream of the Beixi River (Fig. 4 and Table 6). But the REE fractionation of SPM in the estuary was mainly affected by salinity. The (La/Yb)_N, (La/Sm)_N, and (Sm/Yb)_N ratios of SPM in the estuary region were significantly positively correlated with TDS and HCO₃⁻ concentrations (Table 6). Elderfield, Upstill-Goddard & Sholkovitz (1990) reported that the preferential removal of dissolved LREE occurred compared to HREE with the increment of salinity, which meant the relative enrichment of LREE in SPM.

The slight negative Ce anomaly (δCe: 0.8–1.0) of SPM occurred at most sites in the Jiulongjiang River (Fig. 5), likely related to the preferential loss of them compared to other REEs during rock weathering (Smith & Liu, 2018). In addition to weathering process, the negative Ce anomaly of SPM is usually controlled by the water pH value (Elderfield, Upstill-Goddard & Sholkovitz, 1990; Xu & Han, 2009). Dissolved Ce³⁺ is the major form at low pH, but it is easily oxidized to tetravalent Ce with the alkalization of river water (Da Silva et al., 2018). With the increasing water pH value, the removal of dissolved Ce³⁺ as CeO₂ form leads to Ce enrichment in SPM, i.e., the less negative Ce anomaly of SPM. Thus, the δCe values of SPM positively correlate with riverine pH values (Table 6). However, the correlation relationships between them are not significant (P > 0.05) and the variation of δCe values is very slight in the river. These results indicate that the Ce anomaly of SPM is weakly affected by riverine pH, while mainly depends on lithology. Additionally, the intensive negative Ce anomaly occurred at the 1 and 28 sites (Fig. 5), indicating the significant influences of human activities, including the dam effects and agricultural pollutions. Generally, the Eu anomaly of SPM is only controlled by the lithology of the source region (Han et al., 2009). The negative Eu anomaly of SPM occurred at most sites in the Jiulongjiang River which mainly flows through the granite region (Fig. 5), similar results were observed in the Ipojuca River and downstream of Zhujiang River (Da Silva et al., 2018; Xu & Han, 2009). The negative Eu anomaly of SPM in the granite basin mainly depends on the composition and proportion of feldspar minerals, which are commonly Eu-enriched (Nagarajan et al., 2011). However, a positive Eu anomaly of SPM occurred at the 21 and 34 sites where the Ca and Mg concentrations were relatively higher (Table 2 and Fig. 5). Thus, the positive Eu anomaly of SPM at the two sites is mainly attributed to the input of carbonate minerals, which are generally Eu-depleted (Han et al., 2009; Nagarajan et al., 2011). Generally, the positive Gd anomaly of SPM is attributed to the Gd pollution derived from urban wastewater and modern medical treatments (Bau & Dulski, 1996; Nozaki et al., 2000). The δGd values of SPM at most sites in the river were less than 1.6 (Fig. 5), indicating that the Gd in SPM is almost not affected by anthropogenic sources. Additionally, the relatively higher δGd value at the 37 site (1.72) was likely attributed to slight Gd pollution. Gd concentration of SPM at the 37 site was 1.4 times higher, while the concentrations of other REEs were about 1.1 times higher, compared to that at the nearby 36 site. This result indicates that the 37 site is affected by single Gd point pollution. However, the relatively lower δGd value (1.40) at the 28 site was likely associated with agricultural activities. Compared to other sites in the Xixi River, the riverine NO₃⁻ concentrations at the 28 site were significantly 4 times higher (69 mg/L vs. 15 mg/L) (Han et al., 2020; Liu & Han, 2020), indicating strong agricultural activities. Moreover, the concentrations of REEs in SPM at the 28 site were about 3–4 times higher than those at the other sites in the Xixi River, indicating the anthropogenic input of REEs from agricultural soils. Overall, the 28 site is affected by agricultural Gd pollution although the δGd value is less than 1.6.