Radium isotope assessment of submarine groundwater discharge and associated nutrient inputs in Eastern Liaodong Bay, China

The accurate assessment of submarine groundwater discharge (SGD) and associated nutrient fluxes plays a significant role in water resources management and ecological environment protection in the coastal area. Currently, Liaodong Bay has become one of the most polluted marine areas in China. However, the nutrient fluxes carried by the SGD and its environmental effects have not yet been thoroughly reported in eastern Liaodong Bay, China. In this study, the distribution of ²²⁴Ra/²²³Ra activity ratio and its influencing factors under the geochemical conditions were explored. The activity of radium was affected by the water type and the geochemical factors. The radium isotopes in seawater were positively correlated with the ratios of Mg²⁺/Na⁺ and Ca²⁺/Na⁺ but negatively correlated with salinity and SO₄²⁻. The average apparent water age was evaluated to be 13.0 days. Furthermore, based on the radium mass balance model, the total average SGD flux was calculated to be 1.31 × 10⁸ m³ day^–1. The nutrient fluxes carried by the SGD were 7.16 × 10⁷, 1.01 × 10⁶, 1.61 × 10⁷, 0.92 × 10⁶, and 5.41 × 10⁷ mol day⁻¹ for DIN, DIP, NH₄⁺, NO₂⁻, and NO₃⁻, respectively. The nutrient inputs through the SGD have an average DIN : DIP ratio of 70, which was able to seriously affect the ecological environment. The SGD-derived nutrient fluxes were higher than the local river input, which demonstrated that the SGD was a major source of nutrients affecting regional marine ecosystems.

1 Introduction

Submarine groundwater discharge (SGD) is regarded as any seaward flux of water from the rock pores and fractures on continental margins to the coastal ocean, without considering the constituents of flow or driving forces (Burnett et al., 2003). The SGD consists of freshwater from inland and recirculated seawater discharge through sediments, both of which are important pathways for delivering biochemical substances from land to sea, such as nutrients (Zhang et al., 2016; Liu et al., 2017; Prakash et al., 2020), heavy metals (Ganguli et al., 2012; Wang et al., 2019), and organic contaminants (Taniguchi et al., 2019). A series of reactions of biology and chemistry may occur in the saltwater and freshwater interaction zone due to the migration of a large number of nutrient loadings and heavy metals (Beck et al., 2007; Zhang et al., 2020a; Santos et al., 2021). The accurate assessment of SGD and associated nutrient fluxes is very important for water resource management and ecological environment protection (Burnett et al., 2006; Li and Wang, 2015; Wang et al., 2018).

The quantitative study of SGD is challenging because of the variability in the spatial distribution of SGD. Over the past years, the common methods used for determining the SGD include direct measurement (Debnath and Mukherjee, 2016; Prakash et al., 2018), analytical solution (Guo and Li, 2015), numerical simulation (Vaeret et al., 2012; Gopinath et al., 2016; Gopinath et al., 2019), and isotope tracing method (Moore, 1996; Moore, 2007; Luo and Jiao, 2016; Liu et al., 2019; Lopez et al., 2020; Wang et al., 2020b). Among them, the isotope tracing method is the most effective method to quantify SGD at a large scale (Lopez et al., 2020; Wang et al., 2020c). Typically, Moore (1996) used ²²⁶Ra to assess the SGD along the 320-km-long coastline of the eastern United States. Since then, radium isotopes have been widely used to evaluate SGD in many places of the world, including the Okatee Estuary, USA (Moore et al., 2006); Southeastern Continental Shelf, USA (Moore, 2007); Upper Atlantic Ocean, USA (Moore, 2008); Tolo Harbour, Hong Kong (Lee et al., 2012); Geoje Bay, Korea (Hwang et al., 2016); the Yellow Sea, China (Kim et al., 2005); Laizhou Bay, China (Wang et al., 2020c); Jiaozhou Bay, China (Zhang et al., 2017); and numerous other sets of the world.

Radium isotope tracing is indeed a relevant method due to the wide range of radium isotope half-lives, which are between 3.63 days for ²²⁴Ra and 1,600 years for ²²⁶Ra (Webster et al., 1995; Moore et al., 2006). The mass balance model comprising each key chemical substance in the aquifer and seawater is established by taking the SGD as the main pathway. The sources of radium isotopes are mainly diffusion from sediments, river input, suspended particulate matter desorption, and SGD input. The mixing loss with open seawater and radioactive decay are the sinks of radium isotopes. The radium isotopes of ²²³Ra and ²²⁴Ra are more suitable for studying the water cycle process with a short time scale in a small distribution area, compared with the radium isotopes of ²²⁶Ra and ²²⁸Ra. They can be used to estimate the mixing rate and diffusivity effectively (e.g., Luo et al., 2014; Luo and Jiao, 2016). For example, Liu et al. (2015) estimated the SGD in the embayment of Bohai Sea, China, using the short-lived isotopes ²²³Ra and ²²⁴Ra. Xiao et al. (2019) assessed the groundwater discharge rate based on the model of radium mass balance using ²²³Ra and ²²⁴Ra in a typical urbanized estuary in China.

Previous studies have revealed that the SGD is an important nutrient loading source, which is transported from groundwater to seawater (e.g., Makings et al., 2014; Zhang et al., 2016; Wang et al., 2020b). Recently, Cho et al. (2018) found that dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) from SGD were 0.7~1.4 times higher than those from the river input on a global scale. On a local scale, the ratio of nutrient flux carried by the SGD to that from the river input may be higher. For example, the SGD-associated nutrient loadings in the Yellow River Estuary were at least five times greater than those from the river input (Xu et al., 2013). As a result, eutrophication occurred and nutrient structures (e.g., N/P ratio) were changed by the accumulation of nutrients in the ocean. For instance, the prominent problem was eutrophication caused by the discharge of nutrients, and the growth of phytoplankton was restricted by phosphorus (P) in Bohai Bay, China (Peng, 2015; Qiao et al., 2017). Therefore, to better protect the marine ecological environment, it is of great importance to assess the SGD-derived nutrient fluxes.

Although the SGD has been estimated in many coastal aquifers of China based on the method of isotope tracing (e.g., Wang et al., 2015; Zhang et al., 2017; Xiao et al., 2019; Wang et al., 2020b), there is no study on the SGD and its nutrient inputs in the eastern coastal zone of Liaodong Bay, China. Liaodong Bay is situated in the northeast of Bohai Sea. It is one major water body of the Bohai Sea. It is a typical semi-enclosed embayment. In recent years, with the rapid economic growth in Liaodong Bay, the impacts of human activities on the bay become more frequent (Ma and Wang, 2003; Guo et al., 2020a). Liaodong Bay has become one of the most polluted marine areas in China (Song and Duan, 2019; Wang et al., 2020). A large number of eutrophic substances are discharged into the sea from the rivers in coastal zones, which leads to serious eutrophication problems in Liaodong Bay (Wang et al., 2009; Cai et al., 2013; Pei et al., 2019). However, it is not known how much nutrients are brought into the sea through the SGD in eastern Liaodong Bay. Thus, it is important to carry out the research on SGD and its associated nutrients for the assessment of the ecological environment in eastern Liaodong Bay.

This study aims to estimate the SGD and its associated nutrients in eastern Liaodong Bay, China. The spatial distributions of the short-lived radium isotopes ²²³Ra and ²²⁴Ra were studied. The impacts of the geochemical environmental factors and human activities on the activities of ²²³Ra and ²²⁴Ra were then analyzed and discussed. The radium isotopes ²²³Ra and ²²⁴Ra were used to determine the SGD based on the mass balance model. The pollution of water due to dissolved inorganic nitrogen and phosphorus (DIN and DIP) was discussed, and the nutrient fluxes derived from the SGD were estimated.

2 Study area

Liaodong Bay (located between 117°35′ and 122°15′E longitude and 37°07′ and 41°N latitude) is part of the Bohai Sea and situated in the northern part of the Bohai Sea in northeastern China. It is a nearly closed interior sea (Guo et al., 2020b). Its waters span ~10,000 km² and its mean water depth is 22 m. The research area is situated in the coastal zone, in the eastern part of Liaodong Bay, as described in Figure 1. Geographically, the area is situated at 121°37′ to 122°24′E longitude and 40°3′ to 40°39′N latitude. It starts from the Daliao River in the north to the Fudu River in the south of the coastal area in Yingkou City, Liaoning Province. The total length of the coastline is about 76 km.

FIGURE 1

Figure 1 (A–C) The distribution of sampling points in the Yingkou area of Liaodong Bay in the study area. The rhombi, triangles, and circles represent the sampling points of river water, groundwater, and seawater, respectively.

The research area has a semihumid climate (temperate zone): It is hot and rainy in summer but cold and dry in winter. The annual average temperature of the study area is 9.4°C. The highest temperature (37°C) occurs in July and the lowest temperature (−21°C) occurs in January.¹ The annual precipitation ranges from 600 to 800 mm, and the evaporation for each year is between 1,000 and 1,200 mm (Zhu et al., 2020). The main rainfall intensities occur from July to September, which is about 80% of the annual precipitation (Pei et al., 2019). The coastal zone of the research area is mainly affected by tide, wave, and current. Most of the tides are reciprocating tides and regular semidiurnal tides (Li et al., 2021).

The landform of the eastern coast of Liaodong Bay area changes from the eastern part to the western part regularly, due to the effects of structure, lithology, and neotectonic movement TSGSBOLP (The Seventh Geological Survey Brigade of Liaoning Province), 1973. Generally speaking, the geomorphic types are low mountains, high and low hills, and alluvial plains from east to west (Zhu et al., 2020). The alluvial plain in the research area is bordered by the mountains in the eastern part and by the sea in the western part (Figure 1). The terrain of the alluvial plain slows down from east to west gradually. In the coastal zone, the beach is mainly composed of silty and fine sand, which is distributed in the shallow area. The sandy sediments are mainly distributed in the nearshore areas (Xiong et al., 2020). There is a small amount of sandy silt and silty sand in the seabed. From north to south, the main rivers in Yingkou City are the Daliao River, Daqing River, Shahe River, Xiongyue River, and Fudu River, which flow into the sea from the eastern part to the western part. Among them, the Daliao River is the biggest, and its discharge is almost the same as that of the Yellow River (Ye et al., 2015). According to the data provided by the local hydrological bureau, the total runoff of the rivers is about 3.98 × 10⁶ m³ day⁻¹.

The groundwater flows in the quaternary loose sediments of the Liaodong littoral plain area. The aquifer type is mainly alluvium of Holocene and upper Pleistocene (TSGSBOLP). The aquifer in the research area is mainly recharged vertically. The sources consist of precipitation, lateral replenishment from the river, irrigation recharge, and runoff at the mountain front. The form of groundwater discharge includes the discharge to the river, groundwater runoff, evaporation, and artificial exploitation. The groundwater flows from east to west, and its velocity changes with the aquifer thickness, permeability, and topography (Zhu et al., 2020). The velocity of groundwater flow decreases in the coastal zone as the hydraulic conductivity of the aquifer decreases. Moreover, the amount of groundwater exploitation is larger than that of recharge, due to the rising demand for water in the Yingkou area, under the influences of urban development and human activities. The groundwater level in the aquifer decreases because of the imbalance of pumping and recharge. As a result, the seawater intrusion area is mainly distributed in the sandy aquifer of the coastal zone. The phenomenon of seawater intrusion was investigated in the silt coastal zone, such as the Daqing River estuary (Ma et al., 2019; Zhu et al., 2020).

Nutrient pollution and eutrophication have become increasingly serious in the estuaries of eastern Liaodong Bay due to the discharged wastewater from human activities and industries and due to agricultural fertilizer pollution (Pei et al., 2019). Nutrient pollution was carried into the sea through river input and SGD. However, the rivers were cut off and dried up usually in the year because the rivers were developed and utilized in the upstream areas. Thus, a large quantity of nutrients is brought into the sea through the SGD in eastern Liaodong Bay. In addition, heavy metal pollution in eastern Liaodong Bay is also serious, and heavy metal contaminants, such as Cd, Hg, and As, are most prominent in this area (Lan et al., 2018; Wang et al., 2020).

3 Materials and methods

3.1 Field survey and sampling

The field campaign was carried out from 23 to 25 September 2019 in eastern Liaodong Bay. As shown in Figure 1, the coast of the Daliao River was taken as the boundary because the daily average runoff of the Daliao River was higher than the sum of the daily runoff of other rivers, and the economy was developed and the population activities were concentrated in the Daliao River Basin. There were 41 sampling sites in the area (Figure 1). The features of the selected sample sites are listed in Table 1. There were 41 samples collected in the study area: 9 samples of groundwater, 25 samples of seawater, and 7 samples of river water. The groundwater samples (from GW1 to GW9) were set along the coastline. They were obtained at depths between 0.3 and 1.0 m, with a volume of 5–10 L. The water was pumped out using a peristaltic pump after inserting the push point piezometer into the deposited sediment. At each position, the samples of seawater (from SW1 to SW25) were sampled from depths ranging from 1 to 2 m below the seawater surface, with a volume of 60 L for each sample. One or two samples were collected from each river, and the volume of each sample was 30 L.

TABLE 1

Table 1 The activity concentrations of ²²³Ra and ²²⁴Ra as well as salinity at each sample point in the research area.

The radium isotopes in all the water samples were enriched with Mn fibers, which were made by acrylonitrile fibers (white and heat resistant, 100% acrylic fiber material) (Moore and Reid, 1973). They were boiled until their color became dark brown with 0.5 mol/L of potassium permanganate solution at the temperature of 70–80°C. During the process of preparation, the original toughness of acrylonitrile fibers cannot be reduced. After the preparation, in order to remove the manganese oxide on the surface of Mn fibers, they were quickly rinsed with pure water until the color of the water remained unchanged. Then, after drying, they were put into a sealed bag for the experiment.

During sampling, the radium was withdrawn when the water flowed through a cartridge. The Mn fibers of about 25 g were filled into the cartridge. In order to extract the radium isotopes quantitatively, the water flow velocity of the sample had to be smaller than 1 L/min by controlling the tap at the bottom of the sampling bucket (Moore and Reid, 1973). After the enrichment, the Mn fibers were taken out. In order to remove all salts and particles on the Mn fibers, they were flushed with distilled water. They were later measured for radium isotope activity within 24 h in the laboratory.

The samples for detecting nutrients were filtered using a 0.45-μm filter, which were collected in plastic vials (40 ml). The nutrient samples were immediately frozen after filtering to analyze the DIN and DIP. The water samples were sampled in 1 L bottles, which were labeled for analyzing the major ions. The impurities in the water were filtered using a 0.45-μm polypropylene filter element. A portable HI9828 model probe (Hanna, Italy) was used to measure the salinity, temperature, and electrical conductivity (EC) of the samples at the field site (Wang et al., 2016). The information about the sampling positions, amount of sample, and time was recorded during the sampling.

3.2 Laboratory measurement

The ²²³Ra and ²²⁴Ra activities in surface water and groundwater were detected using the Radium Delayed Coincidence Counter (RaDeCC) instrument (produced by the Scientific Computer Instruments Company, USA). It was widely used in radium isotope measurement. The measurement method was presented in Moore and Krest (2004) and Moore (2008). The half-life of the short-lived isotope ²²⁴Ra was 3.66 days; therefore, the measurement was completed in 3 days. In order to prevent the influence of ²²³Ra decay, the measurement of short-lived isotope ²²³Ra was carried out within 7–9 days after sampling. After the two measurements, the samples were stored for about 30 days, and then the isotope ²²⁸Th was measured to correct ²²⁴Ra produced by ²²⁸Th. The initial ²²⁴Ra activity was thus obtained. The measurement uncertainty of ²²³Ra and ²²⁴Ra was about 12% and 7%, respectively.

After taking the water samples to the laboratory for nutrient measurement, they were immediately filtered with a 1-μm polypropylene filter cartridge, and the impurities were filtered with a 0.45-μm filter membrane. Then, flow injection analysis (FIA) utilizing an autosampler and spectrophotometric measurements were conducted to analyze the DIN (NO₃⁻, NO₂⁻, and NH₄⁺) and DIP. The uncertainty of measurement was 3%, 8%, 10%, and 5% for NO₃⁻, NO₂⁻, NH₄⁺, and DIP, respectively. The method of Wang et al. (2002) was used to measure DIN (the sum of NH₄⁺, NO₂⁻, and NO₃⁻) and DIP.

Cations and anions were analyzed at the Jiangsu Geological Survey Institute, China. The samples were analyzed for HCO₃⁻, Cl⁻, SO₄²⁻, NO₃⁻, Na⁺, K⁺, Ca²⁺, and Mg²⁺ after filtering. The HCO₃⁻ ion concentrations were obtained based on the measured pH and total alkalinity (TA). The anions (Cl⁻, SO₄²⁻, and NO₃⁻) were determined based on the ion chromatography (DX-120, Dionex, America). The cations (Na⁺, K⁺, Ca²⁺, and Mg²⁺) were detected by ICP-AES (Thermo ICAP6300, America). The lower limit of detection was set to 0.01 mg L⁻¹ for these ions.

3.3 Radium ages

The apparent water age can reflect the renewal and purification capacity of a water body, which is very important to study the hydrodynamic process of water and its components transported to the sea (Moore, 2000). The apparent water age is a comprehensive parameter describing the characteristics of water body exchange, ignoring the physical processes under surface water and the spatial distribution of these processes. Moore (2000) proposed a method to estimate the apparent water age by using the ²²⁴Ra/²²³Ra activity ratio (AR). The initial value of ²²⁴Ra/²²³Ra AR was a constant value (Moore et al., 2006). The ratio varied with the radioactive transformation; thus, the apparent water age could be estimated by the following equation (Moore, 2000):

$\begin{array}{ll}{\left[\frac{{}^{224}Ra}{{}^{223}Ra}\right]}_i={\left[\frac{{}^{224}Ra}{{}^{223}Ra}\right]}_{GW}\frac{e^{-{\lambda }_{224}^{}{T}_f} }{e^{-{\lambda }_{223}^{}{T}_f}}& \text{(1)}\end{array}$

Equation (1) can be further transformed into (Moore, 2000)

$\begin{array}{ll}{T}_f=\frac{\text{ln}{\left(\frac{{224}_{Ra}}{{223}_{Ra}}\right)}_i-\text{ln}{\left(\frac{{224}_{Ra}}{{223}_{Ra}}\right)}_{GW}}{{\lambda }_{223}-{\lambda }_{224}},& (2)\end{array}$

where ${\left(\frac{{224}_{Ra}}{{223}_{Ra}}\right)}_i$ is the ²²⁴Ra/²²³Ra activity ratio of the observed point i in seawater; ${\left(\frac{{224}_{Ra}}{{223}_{Ra}}\right)}_{GW}$ denotes the ²²⁴Ra/²²³Ra activity ratio of groundwater entering into the study area; λ₂₂₃ is the ²²³Ra decay constant and its value is 0.0608 days⁻¹; λ₂₂₄ is the ²²⁴Ra decay constant and its value is 0.189 days⁻¹; and T_f is the apparent water age.

3.4 SGD estimates

The radium isotopes in seawater were mainly from the SGD input, river input, sediment diffusion and desorption, and desorption of suspended particulate matters from rivers; the output items mainly included the mixture loss with offshore water and radioactive decay (Dulaiova and Burnett, 2008). The input fluxes from the dust deposit and precipitation were not considered because they were insignificant and negligible (Zhang et al., 2017). Through analyzing the source and sink terms in the study area and using the short-lived isotope ²²⁴Ra, the mass balance equation of radium was built to calculate the SGD. The formula can be expressed as follows (Charette et al., 2003; Lamontagne et al., 2015):

$\begin{array}{ll}{F}_{SGD}+F_{river}+F_{sed}+F_{sp}=F_{decay}+F_{mixing}& (3)\end{array}$

where F_SGD is the ²²⁴Ra flux from the SGD input, F_river is the ²²⁴Ra flux from the river input, F_sed is the ²²⁴Ra flux of diffusion of sediments, F_sp represents the ²²⁴Ra flux of suspended particulate matter desorption in the river, F_decay is the ²²⁴Ra flux from radioactive decay, and F_mixing represents the amount of ²²⁴Ra flux mixing with the outer seawater.

During the sampling process, there was no rainfall in the study area. The time for sampling was during the terminal rainy season. Therefore, the input of radium caused by precipitation was ignored. The river was clear and free of impurities; therefore, the radium ²²⁴Ra flux from riverine particulate desorption F_sp in Eq. (3) was neglected.

The equation for calculating the amount of ²²⁴Ra in the river in Eq. (3) is as follows (Li et al., 2019):

$\begin{array}{ll} F_{river}={\displaystyle {\sum }_{i=1}^n{Q}_{r,i}}{}^{224}R{a}_{RW,i}& \text{(4)}\end{array}$

Where Q_r,i denotes the flux of the river (m³/day) the i-th river (dpm 100 L⁻¹).

The diffusion from the sediment of the seafloor is one of the sources of ²²⁴Ra activity. The ²²⁴Ra isotope is desorbed from the seafloor and transported to the upper ocean through physical mixing, bioturbation, and biological irrigation (Moore, 2007). The diffusion flux ²²⁴Ra of surface sediment is calculated as follows (Moore, 2007; Tang et al., 2015):

$\begin{array}{ll}{F}_{sed}=A_{sed}\times D_{sed},& (5)\end{array}$

where A_sed denotes the area of seafloor sediments, which is the area of the sea in the research area (m²), and D_sed indicates the diffusion flux per unit sediment area (dpm m⁻² day⁻¹).

The mixing loss of ²²⁴Ra includes the mixing diffusion of radioactive decay. The formula of the mixed diffusion term is as follows (Kim and Kim, 2011; Luo et al., 2014):

$\begin{array}{ll}{F}_{mixing}=\frac{V_{bay}\left({}^{224}R{a}_{bay}-{}^{224}R{a}_{sea}\right)}{T_f}& \text{(6)}\end{array}$

where V_bay represents the volume of seawater, ²²⁴Ra_bay is the average activity of ²²⁴Ra in the sea of the study area (dpm 100 L⁻¹), and ²²⁴Ra_sea is the activity of ²²⁴Ra contributed by the open sea (dpm 100 L⁻¹).

In addition, the calculation formula of ²²⁴Ra radioactive decay is as follows (Zhang et al., 2017; Wang et al., 2020c):

$\begin{array}{ll}{F}_{decay}={\lambda }_{224}{V}_{bay}{}^{224}R{a}_{bay}. & \text{(7)}\end{array}$

The F_SGDcan be obtained by substituting F_river, F_sed, F_mixing, and F_decay into Eq. (3). Then, the volume flow V_SGDof SGD in the study area can be obtained, combined with the activity of groundwater (Zhang et al., 2017; Wang et al., 2020c),

$\begin{array}{ll} V_{SGD}=\frac{F_{SGD}}{{}^{224}R{a}_{GW}}& \text{(8)}\end{array}$

where ²²⁴Ra_GW is the ²²⁴Ra activity in the groundwater end-member (dpm 100 L⁻¹).

4 Results

4.1 Distribution of salinity and radium isotopes

The temperature of seawater varied between 14.4°C and 22.1°C, with an average value of 20.51°C, and that of coastal groundwater was between 18.8°C and 25.0°C, with an average value of 20.83°C. The temperature within the river water varied between 20.9°C and 22.5°C, with an average value of 21.53°C. The activity of ²²³Ra and ²²⁴Ra in seawater, river water, and groundwater, as well as salinity, is reported in Table 1.

From Figure 2A, one can see that salinity in surface seawater varied slightly, ranging from 26.22 to 36.2, with an average value of 31.76. The salinity of groundwater ranged from 10 to 35, with an average value of 22.88 (Table 1). The salinity in river water was between 0 and 7.0, and its average value was 1.19 (Table 1). From Figures 2B, C, one can see that the activities of ²²³Ra and ²²⁴Ra in seawater were between 0.72 and 3.24 dpm 100L⁻¹ and between 10.55 and 94.76 dpm 100L⁻¹, with average values of 1.81 and 47.32 dpm 100 L⁻¹, respectively. The ²²³Ra and ²²⁴Ra activities in river water ranged from 0.27 to 1.34 dpm 100 L⁻¹ and from 17.23 to 76.8 dpm 100L⁻¹, with average values of 0.87 and 37.67 dpm 100 L⁻¹, respectively. In coastal groundwater, the activities of ²²³Ra and ²²⁴Ra ranged from 2.92 to 58.88 dpm 100L⁻¹ and from 113.69 to 2,103.78 dpm 100L⁻¹, with average values of 19.29 and 909.72 dpm 100L⁻¹, respectively. The average value of the activity of ²²³Ra in coastal groundwater was 61.45 times higher than that in seawater and 130.68 times higher than that in river water, respectively. The average ²²⁴Ra activity in coastal groundwater was 19.22 times higher than that in seawater and 24.15 times higher than that in river water, respectively. The activities of radium isotope in coastal groundwater were higher because they were desorbed from the particles in the freshwater and saltwater interaction zone. The activities of radium isotopes in surface seawater were lower than those in coastal groundwater, which indicated that the radium isotopes in the bay area were mainly from the SGD (Tang et al., 2015; Wang et al., 2020b).

FIGURE 2

Figure 2 Spatial distribution map of salinity (A), ²²³Ra (B), and ²²⁴Ra (C) in the sea area of Yingkou City, Liaodong Bay.

Figure 3A shows that salinity in seawater increased with the offshore distance from the coast of the Daliao River to the sea. From Figures 3B, C, it can be seen that ²²³Ra and ²²⁴Ra activities were reasonably elevated in the nearshore areas. Then, the activities of ²²³Ra and ²²⁴Ra were reduced with the increase of offshore distances generally. The reason was that the decrease in radium activities mainly resulted from the lack of support from the parent decay in the sediments or particles. Figure 4 shows that ²²³Ra activity was positively correlated to ²²⁴Ra activity in seawater. The activity of ²²⁴Ra increased with the activity of ²²³Ra, which indicated that ²²³Ra and ²²⁴Ra activities in seawater had the same sources. In addition, the value of ²²⁴Ra/²²³Ra RA became smaller as groundwater was discharged into seawater because the decay rate of ²²⁴Ra was faster than that of ²²³Ra in coastal seawater.

FIGURE 3

Figure 3 The box plot for salinity (A), ²²³Ra (B), and ²²⁴Ra (C) in groundwater, river water, and seawater.

FIGURE 4

Figure 4 The correlation between the activities of ²²³Ra and ²²⁴Ra.

4.2 Major elements

The measured values of total dissolved solids (TDS), electrical conductivity, and concentrations of major ions for the samples of seawater, river water, and groundwater are summarized in Table 2. During the mixed process of river water, groundwater, and seawater, the conditions of the water body change and the adsorption–desorption and precipitation–dissolution between the dissolved liquid phase and solid phase of the chemical substances may occur in the water body. As a result, the concentrations of chemical components in different water bodies change. The average concentrations of the main cations in seawater were 348.0, 947.33, 492.0, and 8,801.0 mg L⁻¹ for Ca²⁺, Mg²⁺, K⁺, and Na⁺, respectively. The order of abundance of the cations was Na⁺ > Mg²⁺ > K⁺ > Ca²⁺ in seawater. Generally speaking, the cation concentrations (K⁺, Ca²⁺, Na⁺, Mg²⁺) in seawater increased as the salinity increased in the mixed process of freshwater and saltwater. The order of the abundance of cation concentrations in different water bodies was seawater > groundwater > river water. The average concentrations of Cl⁻, NO₃⁻, SO₄²⁻, and HCO₃⁻ in seawater were 16,266.33, 6.87, 2,371.17, and 160.17 mg L⁻¹, respectively. The orders of the abundance of anion concentrations in different water bodies were as follows: seawater > groundwater > river water for SO₄²⁻, river water > groundwater > seawater for NO₃⁻, groundwater > seawater > river water for Cl⁻, and groundwater > river water > seawater for HCO₃⁻.

TABLE 2

Table 2 The measured data of physics and chemistry obtained for the samples of seawater, groundwater, and river water.

4.3 Nutrient

The nutrient concentrations of DIP and DIN (including NO₃⁻, NO₂⁻, and NH₄⁺) in the samples of groundwater, seawater, and river water are summarized in Table 3. The average values of nutrient concentrations were 7.75 μmol L⁻¹ for DIP, 546.66 μmol L⁻¹ for DIN, 412.79 μmol L⁻¹ for NO₃⁻, 7.03 μmol L⁻¹ for NO₂⁻, and 123.1 μmol L⁻¹ for NH₄⁺ in the samples of groundwater. The average nutrient concentrations in the river water samples were 9.8μmol L⁻¹ for DIP, 865.97 μmol L⁻¹ for DIN, 756.47μmol L⁻¹ for NO₃⁻, 9.02μmol L⁻¹ for NO₂⁻, and 94.83μmol L⁻¹ for NH₄⁺. The average nutrient concentrations in the seawater samples were 4.69μmol L⁻¹ for DIP, 163.79μmol L⁻¹ for DIN, 110.81μmol L⁻¹ for NO₃⁻, 3.81μmol L⁻¹ for NO₂⁻, and 46.91μmol L⁻¹ for NH₄⁺. Therefore, the order of the abundance of DIN, DIP, NO₃⁻, and NO₂⁻ was river water > groundwater > seawater, whereas the NH₄⁺ in the water body followed the order of groundwater > river water > seawater.

TABLE 3

Table 3 Nutrient concentrations in the samples of surface water and groundwater in the study area (μmol L⁻¹).

The water body was polluted. The N/P ratio in the rivers of the study area was 88.36, which was larger than the N/P ratio of 18.0 in the river (Slomp and Van Cappellen, 2004). The N/P ratio in groundwater was 70.54, which was much higher than that in seawater (N/P ratio of 34.92). The N/P ratio of 34.92 in seawater was larger than the Redfield ratio of 16:1 (Refiled et al., 1963), which was required for phytoplankton growth in seawater (Lignell et al., 2008). It indicated that the excessive ratio of nitrogen and phosphorus in seawater was caused by the discharge from the river and groundwater, which have great impacts on the composition of nitrogen and phosphorus in the area. As a result, the degree of eutrophication in seawater was aggravated, and the water environment in the research area deteriorated. The high concentrations of N and P in the river water may be caused by the discharge of domestic and industrial wastewater, and a large quantity of nitrogen and phosphorus nutrients were imported into the river caused by the local agriculture in Yingkou City. River-derived nutrients were considered to be the most serious sources of contamination in Liaodong Bay (Pei et al., 2019). In addition, the nutrients were transported to the coast due to hydraulic gradient and groundwater flow (Taniguchi et al., 2002). However, the dilution of seawater made the content of nitrogen and phosphorus decreased. Therefore, the content of nitrogen and phosphorus in the Yingkou area can fully satisfy the condition of algae growth. Once the temperature, light, and hydrodynamic conditions meet the requirements, serious water pollution would occur.

4.4 Apparent water age and uncertainty analysis

The apparent water age of seawater was calculated using Eq. (2), which ranged from 5.6 to 22.6 days, with an average of 13.0 days, based on the value of ²²⁴Ra/²²³Ra AR at each sampling point (Table 1). Figure 5 shows that the apparent water age increased gradually from northeast to southwest in the seawater of the study area, and it increased as the offshore distance increased. In this model, the selection of the value of the groundwater end-member was the most important factor affecting the result (Wang et al., 2019). The maximum value of ²²⁴Ra/²²³Ra activity ratio in the groundwater along the coast was calculated to be 132.88. In order to verify the influence of ²²⁴Ra/²²³Ra activity ratio of groundwater on the model, the maximum value of ²²⁴Ra/²²³Ra activity ratio of groundwater (132.88) was taken to compute the apparent water age of water (Xu et al., 2013). Thus, the average age of seawater was estimated to be 13.0 days. The results showed that the selection of radium activity value of groundwater has a great impact on the average apparent water age of seawater.

FIGURE 5

Figure 5 The chart of apparent water age with offshore distance.

5 Discussion

5.1 Factors influencing the radium isotope distribution

Previous studies have demonstrated that the main sources and abundance of radium isotopes were obviously different due to the influences of hydrogeological conditions and human activities (urbanization, marine reclamation, and aquaculture) (Tang et al., 2015). Moreover, the activities of radium isotopes from seawater were also restricted by many geochemical environmental factors, such as ionic strength, redox, and cation exchange capacity (Gonneea et al., 2008; Vinson et al., 2013; Tang et al., 2015).

5.1.1 Effect of ionic strength

The ratio of radium adsorbed on the seafloor sediment and suspended particles to that desorbed in saline water may be influenced by the ionic strength of the solution. The radium activities in the water body of the estuary and nearshore areas can be reflected by the parameters of salinity and EC indirectly because they are natural indicators for measuring the ions and TDS in the water body (Burt et al., 2013; Swarzenski et al., 2013). In groundwater of the nearshore zone, the average activities of ²²³Ra and ²²⁴Ra at the GW6, GW7, and GW8 sampling points were higher than those at the other sampling points of groundwater (Table 1). The reason was that it was related to the salinity of seawater in the coastal area. The average salinity at the GW6, GW7, and GW8 sampling points was 31.63, which was higher than that at the other sampling points of groundwater (Table 1). It was due to the seawater invading the nearshore aquifer, which increased the salinity of groundwater. The ionic strength in the water increased, which made the radium isotopes ²²³Ra and ²²⁴Ra adsorbed on the aquifer media and the sediment surface resolved into groundwater after ion exchange (Moore, 1999). As a result, the activities of ²²³Ra and ²²⁴Ra increased.

Figure 6A shows the relationship between ²²³Ra, ²²⁴Ra, and salinity in seawater. ²²³Ra and ²²⁴Ra have a good linear correlation with salinity, that is, the activities of ²²³Ra and ²²⁴Ra decreased as the salinity increased. The main reason was that the freshwater discharged into the sea area was dominated by groundwater. The radium activity in seawater was regarded as the conservative mixing of radium activity in the coastal groundwater and river water as well as that in seawater outside the bay under ideal conditions. Thus, there was a good linear relationship between the radium isotopes ²²³Ra and ²²⁴Ra and salinity in seawater.

FIGURE 6

Figure 6 The relationship between radium isotope activity and salinity in water: (A) ²²³Ra and ²²⁴Ra in seawater change with salinity; (B) ²²³Ra and ²²⁴Ra in groundwater change with salinity.

Figure 6B shows the variations of ²²³Ra and ²²⁴Ra activities with salinity in groundwater. One can see that the activities of ²²³Ra and ²²⁴Ra increased with salinity. The main reason was that the radium isotopes in groundwater were adsorbed by the sediment and dissolved in groundwater. The radium adsorbed on the sediment was desorbed from the sediment particles when groundwater flowed into the sea and the degree of desorption increased with salinity (Tang et al., 2015). Consequently, the activities of radium isotopes increased as the salinity increased during the process of groundwater flowing into the seawater.

5.1.2 Effect of redox

The manganese and iron oxides related to radium adsorption were sensitive to reductive dissolution, even though radium was not sensitive to redox (Gonneea et al., 2008; Vinson et al., 2013; Tang et al., 2015). Nitrate and sulfate can provide kinetic conditions for the solid-phase manganese and iron oxides removing the radium isotopes from seawater (Vinson et al., 2013). The values of SO₄²⁻ and NO₃⁻ in seawater increased as the offshore distance increased generally (Table 2). The increment of the concentrations of SO₄²⁻ and NO₃⁻ enabled the manganese and iron oxides to reduce radium activity; thus, radium activity was reduced in seawater (Vinson et al., 2013).

Figures 7A, B show the variation of the measured concentrations of SO₄²⁻ and NO₃⁻ in seawater with ²²³Ra and ²²⁴Ra activities. The ²²⁴Ra activity decreased as the concentration of SO₄²⁻ increased; however, there was only a slight correlation between the activities of ²²³Ra and SO₄²⁻. The activities of ²²³Ra and ²²⁴Ra have a positive correlation with the concentrations of the NO₃⁻ ion. Nevertheless, the concentration of SO₄²⁻ was much higher than that of NO₃⁻, and the activity of the radium isotope was mainly affected by SO₄²⁻. Therefore, the higher concentrations of SO₄²⁻ in seawater provided support for the adsorption of radium by the manganese and iron oxides. They provided the basis for further analyzing the distribution of radium isotopes.

FIGURE 7

Figure 7 The relationship diagram between ²²³Ra and ²²⁴Ra and SO₄²⁻ (A), NO₃⁻ (B), Mg²⁺/Na⁺ (C), and Ca²⁺/Na⁺ (D) in seawater.

5.1.3 Effect of cation exchange capacity

The exchange of similar cations can elevate the concentration of radium isotopes desorbed in water with high salinity or TDS (Szabo et al., 2012; Tang et al., 2015). As described in the previous studies, the exchange between the ions of Na⁺, Mg²⁺, and Ca²⁺ prevented the decay of radium isotopes. Therefore, the activity of radium isotope in water with divalent cations was generally higher than that in water with monovalent cations as the main components (Vinson et al., 2013). Figures 7C, D show the variation of the ratios of cations of Ca²⁺/Na⁺ and Mg²⁺/Na⁺ in seawater with ²²³Ra and ²²⁴Ra activities. The activities of ²²⁴Ra have positively correlated with Ca²⁺/Na⁺ and Mg²⁺/Na⁺ generally; however, there was only a slight correlation between the activities of ²²³Ra and Ca²⁺/Na⁺ and Mg²⁺/Na⁺. It indicated that the exchange ability of ions with the same valence in water increased when the relative ion concentration of Ca²⁺ and Mg²⁺ increased. As a result, more radium isotopes were dissolved and the decay of radium isotopes was inhibited indirectly. Therefore, more dissolved radium isotopes can be measured in the water. Due to the experimental error and the influence of human factors, the relationship between ²²³Ra and Ca²⁺/Na⁺ and Mg²⁺/Na⁺ was not obvious.

5.2 Estimation of SGD fluxes

5.2.1 River input and sediment diffusion input

During the sampling period, no water samples from the Shahe River were taken because the lower reach of the Shahe River dried up. Therefore, the radium activity in the Shahe River was ignored. The cumulative radium flux input into the river of the study area was calculated by obtaining the flow data of each river except the Shahe River. ²²⁴Ra on the particulate matter of the river in the estuarine area was rapidly desorbed due to the increase in water concentration. The radium activity in the estuarine area was higher than that in the middle–upper section of the river. The concentration of ²²⁴Ra activity in the estuary area was selected to calculate the quantity of ²²⁴Ra, which was more representative of the river input into the seawater. The calculated value of ²²⁴Ra input from the rivers in the study area was 2.76 × 10⁹ dpm day⁻¹ in September 2019 based on Eq. (4).

Moore (2007) concluded that the diffusion flux of ²²⁴Ra in the fine-grained sediments was about 210 dpm/m²/100 L. The area of the seafloor sediments in the study area was about 1,750 km², and the diffused amount of ²²⁴Ra in the seabed sediments was about 3.67 × 10¹¹ dpm day⁻¹ based on Eq. (5).

5.2.2 Mixed loss and decay

The inventory of ²²⁴Ra in the study area V_bay²²⁴Ra_bayV_bay²²⁴Ra_bay was obtained based on the water depth and ²²⁴Ra activity of the seawater sampling points. The sea area was divided into 48 triangular elements based on the sampling points. The inventory of ²²⁴Ra was calculated by multiplying the area, the average water depth, and the average ²²⁴Ra activity in each triangular element. Finally, the inventory of ²²⁴Ra in the study area was calculated by adding the inventory of ²²⁴Ra in each triangular element.

The background value of seawater outside the studied sea area was 15.72 dpm 100L⁻¹, which was the average value of SW22 and SW23. The reason was that the radium active values of SW22 and SW23 were the lowest ones at the sampling locations near the open sea (Peterson et al., 2008). The diffusion value of ²²⁴Ra was about 3.20 × 10¹¹ dpm day^–1 based on Eq. (6). The loss term caused by the radioactive decay of ²²⁴Ra was about 1.17 × 10¹² dpm day^–1 based on Eq. (7).

5.2.3 Estimating the SGD flux

With regard to the value of  ²²⁴Ra_GW , the radium ²²⁴Ra in the nearshore groundwater was more representative of the groundwater input into the seawater. Therefore, the average activity of ²²⁴Ra in coastal groundwater (the average value after removing the abnormally high value and low value) was selected as the end value of groundwater.

The ²²⁴Ra fluxes obtained by calculation and the relevant parameters are reported in Table 4. Substituting the obtained ²²⁴Ra fluxes from rivers F_river , from diffusion of seabed sediments F_sed , from radioactive decay F_decay , and from mixed diffusion F_mixing into Eq. (3), the value of F_SGD based on the balance model of radium mass was estimated to be 1.12 × 10¹² dpm day^–1. Among the source items, the ²²⁴Ra fluxes from the river input accounted for the smallest proportion, and the ²²⁴Ra fluxes from decay loss accounted for the largest proportion among the sink items (Table 4). Finally, the total average SGD fluxes were about 1.31 × 10⁸ m³ day^–1 based on Eq. (8), and the average SGD rate was 7.49 cm day^–1. Compared with the SGD flux in other bays of China by other investigators as summarized in Table 5, the SGD rate of this study area was in the middle value. Additionally, the estimated SGD in this study area may be larger because the suspended particulate matter desorption was not measured directly.

TABLE 4

Table 4 The values of the parameters used in the model of radium mass balance.

TABLE 5

Table 5 Comparison of the results of SGD flux in different study areas.

5.3 Correlation analysis and SGD-derived nutrient fluxes

The quantification of SGD flux was important for environmental governance because the SGD was the main pollution source. The pollution problem has increased seriously in eastern Liaodong Bay in recent years. For example, the problem of eutrophication happened in the local water. The SGD-derived nutrient flux was calculated by multiplying the SGD flux and the nutrient concentration in the groundwater terminal member. Generally, the concentration of nutrients refers to the average concentration at each end-member. The nutrient fluxes carried by the river could be determined by the discharge rates in the river water and the related nutrient concentrations. The calculation formula of the nutrients driven by the SGD or river was as follows:

$\begin{array}{ll} F_m= V_{SGD}{M}_x& \text{, (9)}\end{array}$

where F_m is the flux of nutrients from the SGD or river and  M_x is the concentration of nutrients in groundwater or river water.

As shown in Figure 8, the SGD-derived nutrients were 7.16 × 10⁷ mol day^–1 for DIN, 1.01 × 10⁶ mol day^–1 for DIP, 1.61 × 10⁷ mol day^–1 for NH₄⁺, 0.92 × 10⁶ mol day^–1 for NO₂⁻, and 5.41 × 10⁷ mol day^–1 for NO₃⁻. The nutrient fluxes carried by the river were 3.44 × 10⁶ mol day^–1 for DIN, 3.90 × 10⁴ mol day^–1 for DIP, 3.78 × 10⁵ mol day^–1 for NH₄⁺, 1.52 × 10⁴ mol day^–1 for NO₂⁻, and 3.01 × 10⁶ mol day^–1 for NO₃⁻. The results indicated that the nutrient fluxes carried by the SGD were much higher than those from river inputs. For instance, the SGD-derived nutrient fluxes of DIN were 90–131 times higher than those of rivers, and the SGD was the main channel to carry the source of nutrients into the sea area. The impact of SGD on the coastal zone and marine ecosystem in eastern Liaodong Bay was greater than that of rivers.

FIGURE 8

Figure 8 The nutrient fluxes from the SGD and river.

5.4 Uncertainty analysis

In the radium mass balance model, some items have great uncertainties. The uncertainties may be related to the selection of the groundwater end-member value, the river flow, and the inventory of radium. The groundwater end-member value was one of the key factors for the uncertainty of estimation results (Peterson et al., 2008; Xu et al., 2013). The SGD flux obtained will decrease by about 50% if the maximum value of ²²⁴Ra activity in groundwater (to remove the abnormally high value and low value) was selected for the calculation. Previous studies suggested that the uncertainty of model estimation will be reduced by increasing the number of groundwater samples (Wang et al., 2020b). The SGD fluxes will increase or decrease by about 1% if the average river flow is increased or decreased by 50%, which indicated that the quantity of river flow had a little effect on SGD fluxes. Thus, SGD fluxes should be estimated thoroughly based on the actual conditions.

6 Conclusions

Based on analyzing the radium activities of ²²³Ra and ²²⁴Ra in eastern Liaodong Bay, it was concluded that the distribution of short-lived radium isotopes was influenced by the water body type and geochemical factors. In general, the radium concentrations of groundwater were much greater than those in the bay, and in the south, they were larger than those in the north as a whole. The relationship between radium and chemical composition was analyzed. Radium has a negative correlation with salinity and sulfate concentration. However, radium was positively correlated to the concentrations of cations Ca²⁺ and Mg²⁺. The average apparent water age was calculated to be 13.0 days, and the average SGD flux was determined to be 1.31 × 10⁸ m³/day based on the ²²⁴Ra model of mass balance. In addition, the ratio of DIN to DIP in the water body of Liaodong Bay was higher, and the SGD-derived nutrient fluxes were estimated to be 7.16 × 10⁷ mol day^–1 for DIN, 1.01 × 10⁶ mol day^–1 for DIP, 1.61 × 10⁷ mol day^–1 for NH₄⁺, 0.92 × 10⁶ mol day^–1 for NO₂⁻, and 5.41 × 10⁷ mol day^–1 for NO₃⁻. The nutrient fluxes from riverine inputs were much lower than those from the SGD. The SGD played a decisive role in changing the ecosystem of seawater. The water body in eastern Liaodong Bay was in a state of eutrophication. The nutrient fluxes carried by the SGD should be given attention for the protection and preservation of the environment and the prevention of water pollution.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.

Author contributions

QG: methodology and writing and preparation of the original draft. YZ, ML, and JL: investigation and data analysis. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 41772235) and the Fundamental Research Funds for the Central Universities (No. B210202108).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

1. ^ http://data.cma.cn/

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