
Citation: | Tianyi Zhu, Bochao Xu, Xiaoyi Guo, Qinsheng Wei, Ergang Lian, Pengxia Liu, William C. Burnett, Qingzhen Yao, Zhigang Yu. Submarine groundwater discharge and seasonal hypoxia off the Changjiang River Estuary[J]. Acta Oceanologica Sinica, 2023, 42(8): 125-133. doi: 10.1007/s13131-023-2256-9 |
Hypoxia is a condition that occurs in the water column when dissolved oxygen (DO) falls below the 2 mg/L (Diaz and Rosenberg, 1995) or 3 mg/L (Chen et al., 2007). Recently, hypoxia has been found commonly in many estuaries and coastal areas (Conley et al., 2009; Justić et al., 2002; Li et al., 2002; Montagna and Froeschke, 2009). This includes the East China Sea (ECS), which has long been one of the world’s major fishing grounds. High primary productivity and abundant nutrients lead to high fishery yields, especially in the Changjiang River Plume and adjacent coastal waters. The Changjiang River Estuary (CJE) and its adjacent sea is one of the most serious seasonal hypoxia regions in the world (Chen et al., 2007; Fennel and Testa, 2019), with a record of hypoxia that can be traced back to the 1950s (Gu, 1980). The low-oxygen situation in the waters off the CJE began to appear in late spring or early summer. Hypoxia is usually formed in the southeast portion of the sea during the early stages, then spreads both southward and northward. Temporally, hypoxia is most severe in August, weakening in autumn and disappearing in winter (Wang et al., 2012). The severity of hypoxia off the CJE varies with the year, as does the position of hypoxia regions (Wei et al., 2017).
The traditional view is that organic matter deposition and water stratification are the main mechanisms leading to the formation of hypoxia (Chi et al., 2017; Wei et al., 2015; Zhu et al., 2011). The stratification of a water body is essential for the formation of hypoxia in continental shelf environments. Stratification will prevent deep water from mixing with oxygen-rich surface waters. Organic matter decomposition is the main consumer of DO in seawater. Stratification is important for the development of hypoxia in the deeper levels, and the maintenance of these conditions requires a continuously supply of organic matter. Recent studies suggested that submarine groundwater discharge (SGD) may be a new potential mechanism to change the redox conditions in the bottom layer in the region off the CJE (Guo et al., 2020; Peterson et al., 2016; Sanial et al., 2021). Guo et al. (2020) found a well-developed overlap of the distribution patterns for both SGD fluxes and DO concentrations. This led to a proposed direct and indirect mechanisms in which SGD contributes to hypoxia off the CJE. Directly, SGD transfers anoxic groundwater that contribute to hypoxia via dilution. In addition, groundwater contains a variety of reducing substances that may accumulate in sediments and be released when an outbreak occurs (Emeis et al., 2004). As for the indirect way, groundwater may contain much higher nutrient concentrations than seawater. The region of summer hypoxia off the CJE is similar to the region with higher chlorophyll content (Wei et al., 2015).
SGD is the groundwater flux from the seabed to the ocean, including any and all flow of water regardless of fluid composition or driving force (Burnett et al., 2003; Moore, 2010). SGD is driven by multiple forces, and thus covers a variety of temporal and spatial scales. As a pathway for transporting dissolved substances such as nutrients (Cho et al., 2018; Kim et al., 2005), heavy metals (Alorda-Kleinglass et al., 2019), organic matter (Santos et al., 2009) from land to sea, SGD has been recognized as an important part of the water cycle. Ecological and environmental effects can be caused due to large amounts of materials carried by SGD into the sea, such as eutrophication (Knee and Paytan, 2011), red tides (Lee et al., 2009), hypoxia (Moore et al., 2022; Peterson et al., 2016), acidification (Lee and Kim, 2015), and more. SGD can be followed by geochemistry tracers, among which radium and radon isotopes are mostly applied. The high concentration of 222Rn in groundwater compared to seawater, together with its non-reactive nature and short half-life (t1/2 = 3.82 d) make 222Rn an excellent tracer for identifying significant groundwater discharge regions (Charette et al., 2008). 222Rn is increasingly being used for tracing and quantifying SGD in a wide range of environments such as estuary (Kim et al., 2010), coastal ocean (Smith and Swarzenski, 2012), coastal embayment (Corbett et al., 1999), lagoons (Sadat-Noori et al., 2016), among others.
In this study, we used a 222Rn mass balance model to estimate the SGD fluxes off the CJE based on the 222Rn and 226Ra activities of bottom waters. The seasonal variations of SGD in the region off the CJE are described. The results obtained from this work would help to better understand the correlation between SGD and hypoxia off the CJE.
The Changjiang River is the largest river in China with an annual mean discharge of 9.4×1011 m3/a over the past ten years (Changjiang River Sediment Bulletin in 2021,
A series of field sampling and measurements were conducted in different seasons in the sea adjacent to the CJE. Samples were collected during five cruises, including August 2019 (R/V Runjiang1), July and October 2020 (R/V Zheyuke), March and October 2021 (R/V Runjiang1). The sampling stations of seawater are shown in Fig. 1. The water depth in our study area ranges from 9 m to 64 m.
Seawater at each sampling station was sampled from an onboard SeaBird CTD rosette (SBE 9/11 puls, SBE Inc., USA). Then ~6 L of water was subsampled into sealed and evacuated Nalgene bottles for both surface and bottom 222Rn analysis on board. High-purity helium gas was flushed through the water sample to sweep out the 222Rn gas, which was then captured in a liquid nitrogen cold trap. After the transfer process, the cold trap was heated and 222Rn transferred into Lucas cells. These cells were sealed for 3 h for 222Rn and its α-emitting daughter products to reach secular equilibrium. The α-activity was then measured by a 222Rn counting system (Ludlum Model 2000 Timer/Scaler, Ludlum Measurements Inc., USA) with uncertainty less than 10%. The system was calibrated using NIST-traceable 226Ra standard solutions. More details can be found in Guo et al. (2020).
Surface and bottom water 226Ra were sampled on board and measured in the laboratory (Waska et al., 2008). After 222Rn was sparged out of each sample, the water was filtered through a column filled with about 20 g (dry weight) of MnO2-coated acrylic fiber (Mn-fiber) that was made using the method proposed by Moore (1978). 226Ra in seawater is quantitatively adsorbed onto Mn-fibers (98%). After returning to the laboratory, Mn-fibers were washed to get rid of seawater salt and other content, then the ratio of water content to Mn-fiber was adjusted to approximately one. The Mn-fibers were thereafter stored for the ingrowth of 222Rn. The RaDeCC (Scientific Computer Instruments, USA) developed by Moore and Arnold (1996) was used to measure the activity of 226Ra. The analytical uncertainty was below 5%, which was determined by counting statistics within a 1-sigma confidence interval.
Dissolved oxygen was measured using Winkler titration method. Density was calculated and recorded throughout the water column by the CTD rosette (RBR Ltd., Canada). Wind data were collected onboard.
Assuming steady state conditions, we can use a 222Rn mass balance model to evaluate the SGD fluxes of our study region. The sources of 222Rn in the water column include SGD, river inputs, and diffusive flux from sediments. The sinks include the natural decay of 222Rn, the oceanic output flux to the ECS, and 222Rn loss across the pycnocline layer or the atmosphere. Thus, the SGD flux can be estimated as follows:
$$ {F}_{\rm{SGD}}=\frac{{F}_{\rm{decay}}+{F}_{\rm{pycnocline/atmosphere}}+{F}_{\rm{mixing}}-{F}_{\mathrm{diffusion}}-{F}_{\rm{river}}}{{A}_{\rm{gw}}} , $$ | (1) |
$$ {F}_{\mathrm{decay}}=I \text{λ} , $$ | (2) |
where
The term of
$$ {F}_{\mathrm{a}\mathrm{t}\mathrm{m}\mathrm{o}\mathrm{s}\mathrm{p}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}}=k\left({C}_{\mathrm{w}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{r}}-\alpha {C}_{\rm{atmosphere}}\right) , $$ | (3) |
where
$$ k=0.45{\mu }^{1.6}{\left(\frac{Sc}{600}\right)}^{-\beta } , $$ | (4) |
where
$$ Sc=3\;417.6{\rm{e}}^{-0.063\;4 T} . $$ | (5) |
The activities of dissolved 222Rn in the surface water of the study area ranged from 0.88 Bq/m3 to 8.85 Bq/m3 in spring (March), from below detection limit (0.05 Bq/m3) to 21.25 Bq/m3 in summer (July and August), from 0.70 Bq/m3 to 19.50 Bq/m3 in autumn (October) (Table S1). As a noble gas, 222Rn dissolved in surface water escapes by gas-exchange to the atmosphere, which is mainly controlled by wind velocity and temperature (Schink et al., 1970).
The activities of dissolved 222Rn in the bottom water of the study area ranged from 0.03 Bq/m3 to 14.12 Bq/m3 in spring (March), from below detection limit to 35.15 Bq/m3 in summer (July and August), from 5.98 Bq/m3 to 19.72 Bq/m3 in autumn (October) (Table S1). For the average 222Rn level in bottom water, the lowest average activity occurred in winter ((4.62 ± 3.85) Bq/m3, March 2018), and the highest was found in summer ((21.13 ± 7.92) Bq/m3, August 2019).
The difference of 222Rn activities between surface water and bottom water was the greatest in summer than in other seasons (Fig. 2), due to seasonal stratification of water column. The 222Rn activity in the bottom layer was lower than that in the surface layer in winter, the season with most vertically well-mixed water, illustrating 222Rn flux supported by benthic boundary sources (e.g., SGD) may be the lowest in winter. In contrast to the winter cruises, the 222Rn activity in the bottom layer was higher than that in the surface layer in both the summer and autumn cruises. The activity of 222Rn in bottom water was about two orders of magnitudes lower than that in groundwater endmember (Chen et al., 2021). The seasonal variations in bottom water radon indicate the radon input at the sediment-water interface was stronger in summer and autumn.
222Rn has a short half-life of 3.82 d, so it decays rapidly once it left its source. As shown in Fig. 2e, the highest activities were observed nearshore at the north of the Changjiang River mouth and the south of the Hangzhou Bay during the summer. Considering the long transport time of the Changjiang River water into the study area compared with the half-life of 222Rn (Guo et al., 2020), these 222Rn hotspots off the Changjiang River plume trajectories clearly were not supported by riverine input, thus most likely supported by SGD. The area with high 222Rn concentrations in the north extended much further offshore, implying a stronger and wider existence of the benthic radon sources.
We used two approaches for the quantification of SGD off the CJE. We calculated the SGD flux at all sampling stations from summer cruises for mapping the spatial distribution of SGD dynamics. Meanwhile, to show the seasonal variation of SGD, we pooled all the data of the same season to estimate the weighted SGD flux with the mean value for each season. Considering the heterogenous nature of SGD dynamics, we constrained the spatial range for the seasonal estimates to a specific region (31.00°−32.25°N, 122.50°−123.50°E) to better compare the seasonal variation of SGD dynamics. The data used to estimate SGD were compiled from nine cruises, four of which were previously reported by Guo et al. (2020).
The unsupported 222Rn inventories were used to calculate the decay loss by the Eq. (2). The inventories were calculated depending on whether stratification existed. Stratification of water column was strong in summer, preventing 222Rn from being transported vertically. Here we used bottom water unsupported 222Rn activities multiplied with sub-pycnocline depths as the inventories. Pycnocline depths were determined from the vertical density profiles. Sub-pycnocline depths (from pycnocline to the bottom) were obtained by subtracting pycnocline depths from water depths. When the water column was well-mixed in autumn and winter, we obtained the inventories by multiplying bottom water unsupported 222Rn activities with water depths. It should be noted that in October, the intensity of stratification decreased and the spatial range of stratified water columns were reduced (Zou et al., 2001 ). However, there were still a few sampling stations with recognizable pycnoclines. As a result, the 222Rn inventories were calculated to be (−2.1 ± 139.3) Bq/m2 in winter, (333.4 ± 205.8) Bq/m2 in summer, and (156.7 ± 129.4) Bq/m2 in autumn. The apparent negative 222Rn inventory in winter is a result of more radon loss than input into the water column off the CJE.
Assuming 222Rn activity concentration in the air (
The mixing loss refers to the flux from nearshore relatively high 222Rn to offshore seawater with low 222Rn. To estimate SGD conservatively, considering total SGD must be positive values, we take the maximum negative flux after considering all other sources and sinks (
The transport time (20 d) of the Changjiang River water into the study area was five times longer than the half-life of 222Rn (Guo et al., 2020), therefore the radon contribution of river discharge to this region can be ignored.
$$ {F}_{\mathrm{p}\mathrm{y}\mathrm{c}\mathrm{n}\mathrm{o}\mathrm{c}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{e}}={K}_{{\rm{v}}}\left(\frac{{\rm{d}}C}{{\rm{d}}z}\right) . $$ | (6) |
The resulting 222Rn loss fluxes across the pycnocline ranged from 1.7 × 10−4 Bq/(m2·d) to 3.6 × 10−3 Bq/(m2·d) (Table S2), which are negligible compared with other terms in the balance model.
Term | Unit | Summer | Autumn | Winter |
Excess 222Rn inventory (I) | Bq/m2 | 333.4 ± 205.8 | 156.7 ± 129.4 | −2.1 ± 139.3 |
222Rn sinks | ||||
Excess 222Rn decay loss flux (Fdecay) | Bq/(m2·d) | 60.4 ± 37.3 | 28.4 ± 23.4 | −0.4 ± 25.2 |
Atmospheric 222Rn loss flux (Fatmosphere) | Bq/(m2·d) | − | 10.0 ± 5.2 | 10.5 ± 3.8 |
222Rn loss flux through pycnocline (Fpycnocline) | Bq/(m2·d) | − | − | − |
222Rn mixing with offshore water flux (Fmixing) | Bq/(m2·d) | 41.4 ± 3.7 | 29.5 ± 3.9 | 37.7 ± 2.3 |
222Rn sources | ||||
Sediment diffusion flux of 222Rn (Fdiffusion) a | Bq/(m2·d) | 16.7 ± 3.3 | 16.7 ± 3.3 | 16.7 ± 3.3 |
River discharge flux of 222Rn (Friver) | Bq/(m2·d) | − | − | − |
SGD flux of 222Rn (known sources-known sinks) | Bq/(m2·d) | 85.1 ± 37.6 | 51.2 ± 24.5 | 31.2 ± 25.8 |
222Rn activity in groundwater endmember (Agw) a | Bq/m3 | 2 500.0 ± 266.7 | 2 500.0 ± 266.7 | 2 500.0 ± 266.7 |
SGD flux (FSGD) | m3/(m2·d) | 0.034 ± 0.015 | 0.020 ± 0.010 | 0.012 ± 0.010 |
Note: a refer to Guo et al. (2020). − represents no data. |
The uncertainties of SGD fluxes were mainly caused by estimations of the 222Rn activity of groundwater endmember, 222Rn inputs from sediment diffusion and unsupported 222Rn inventories. The selection of groundwater or porewater endmember is always an important source of uncertainty in the estimation of SGD flux (Taniguchi et al., 2019). In our work, we used the value from Guo et al. (2020) that was estimated using laboratory sediment equilibration experiments. The experiments were conducted under the assumption that 222Rn in groundwater was able to equilibrate with aquifer and associated sediments (Chanyotha et al., 2014). Therefore, this will be the maximum groundwater endmember value, again leading to a conservative (minimum) estimate of SGD flux.
Comparison of our results with previously reported works is shown in Table 2. Gu et al. (2012) estimated the SGD into the Changjiang River Effluent Plume in September 2009 to be 0.008−0.040 m3/(m2·d). Wang et al. (2018) evaluated the SGD flux in the ECS to be 0.0039 m3/(m2·d). Tan et al. (2018) suggested that the SGD flux in the continental shelf of the ECS to be 0.044−0.138 m3/(m2·d). Guo et al. (2020) calculated the SGD flux to be in the range of 0.002−0.022 m3/(m2·d). Our estimated SGD fluxes are comparable with these previous works.
Region | Sampling time | Tracer | FSGD/(m·d-1) | Reference |
Dongsha Bay | Dec. 2008 | 226Ra | 0.24−2.30 | Ji et al. (2012) |
Changjiang River Effluent Plume | Sept. 2009 | 226Ra | 0.008−0.04 | Gu et al. (2012) |
Xiangshan Bay | Oct. 2009 | 222Rn | 0.69 | Wu et al. (2013) |
May 2010 | 222Rn | 0.23 | Wu et al. (2013) | |
East China Sea | Aug. 2013 | 223Ra, 224Ra, 226Ra, 228Ra | 0.003 9 | Wang et al. (2018) |
Changjiang River Estuary | Mar. 2015 | 223Ra, 224Ra | 0.18−0.45 | Liu et al. (2018) |
East China Sea continental shelf | Jan. 2010 | 226Ra, 228Ra | 0.044−0.138 | Tan et al. (2018) |
Shengsi Island | Nov. 2015 | 222Rn | 0.129 | Chen (2019) |
Xiangshan Bay | Mar. 2012 | 222Rn | 0.13 | Wen et al. (2014) |
Lianjiang | Jul. 2019 | 224Ra | 0.140 ± 0.070 | Peng et al. (2021) |
Oct. 2019 | 224Ra | 0.077 ± 0.040 | Peng et al. (2021) | |
The sea adjacent to the Changjiang River Estuary | Aug. 2017 | 222Rn | 0.022 ± 0.011 | Guo et al. (2020) |
Mar. 2018 | 222Rn | 0.002 ± 0.004 | Guo et al. (2020) | |
Jul. 2018 | 222Rn | 0.017 ± 0.009 | Guo et al. (2020) | |
Aug. 2018 | 222Rn | 0.018 ± 0.012 | Guo et al. (2020) | |
The sea adjacent to the Changjiang River Estuary | winter | 222Rn | 0.012 ± 0.010 | this study |
summer | 222Rn | 0.034 ± 0.015 | this study | |
autumn | 222Rn | 0.020 ± 0.010 | this study |
According to the results in Section 3.2, the maximum SGD off the CJE was observed in summer, followed by autumn and then winter. The average 222Rn inventory in winter was found to be negative, indicating that the supply of 222Rn could not compensate for the losses in the box model. The low bottom 222Rn concentrations (lower than surface 222Rn) may imply that groundwater flux in winter was lowest among three seasons, considering the similar mixing losses in different seasons. On the other hand, the water column is mixed vertically during the winter, allowing more 222Rn from the bottom to escape into the atmosphere. The ECS and its coastal areas are obviously affected by the southeast monsoon in summer. Precipitation in this region shows significant seasonal variation. Therefore, the terrestrial hydraulic gradient, which is closely related to precipitation, might be an important reason for the seasonal variation of SGD off the CJE. Figure S1 showed the average monthly precipitation from 1981 to 2010 at three stations (Qidong, Chongming and Shengsi) near the CJE. High precipitation occurs during the wet season (from May to July) and typhoon seasons (from July to October). Precipitation increases rapidly from May to June, and decreases from August to October. In summer, the precipitation on land will lead to an increase of the water level and terrestrial hydraulic gradients, causing more fresh water flow through permeable sediments and discharge into coastal waters (Chen et al., 2018; Wang and Du, 2016). Therefore, higher precipitation in summer might intensify the exchange between land and ocean aquifer, contributing to higher SGD in summer, especially the terrestrial fresh groundwater input. In October, precipitation had already begun to decrease. The process of water flowed through aquifers into the sea is likely to cause the variations of SGD to lag behind variations of precipitation. Therefore, SGD remained significant but smaller than in summer. March belongs to dry seasons, during which precipitation was limited. As a response, the total discharge rate was the smallest. To recap, SGD is highest in wet season and the lowest in dry season.
Our observed seasonal variations of DO were consistent with previous investigations (Li et al., 2011; Wang et al., 2012; Wei et al., 2015). Hypoxia off the CJE begins to develop in late spring and early summer. The hypoxic layer initially forms in the south-east of the CJE. It later spreads both south and north of the CJE and reaches its maximum severity in August, weakens in autumn and finally disappears in winter (Wang et al., 2012). The seasonal variation pattern of SGD fluxes is opposite of that of DO concentrations. A strong negative linear correlation between SGD and oxygen level was observed in the region of 31.00°−32.25°N, 122.50°−123.50°E, based on results from our five cruises and four previously reported cruises (Guo et al., 2020). Figure 3 showed the relationship between mean SGD and DO or apparent oxygen utilization (AOU, the difference between the saturation oxygen concentration and the observed oxygen concentration). The saturation oxygen concentration was calculated as Weiss (1970). With the increase of SGD fluxes, the oxygen level fell. When SGD fluxes were lowest in March, the dissolved oxygen in the bottom water was oversaturated (AOU < 0). Thus, SGD is an important contributor to hypoxia off the CJE.
To give a direct reflection of the relationship between SGD and hypoxia in summer off the CJE, the distribution of SGD in summer and the distribution of hypoxia in past years were mapped as shown in Fig. 4. By comparing the two distribution patterns, one can see that the high SGD area in summer and the low oxygen hypoxic area were correspond to each other spatially. In general, summer hypoxic zones off the CJE mainly include two major parts: (1) hypoxic zone in the northeast of the CJE, which could extend to the northwest of the underwater valley, and (2) hypoxic zone along the Zhejiang coast in the south of the CJE (Wei et al., 2017). Figure 4 shows that there are two zones of high SGD fluxes off the CJE in summer. The high SGD zone in the northern part of our study area shaped like an inverted triangle is geographically similar to the hypoxic zone in the northeast of the CJE, with the southernmost tip located above the underwater valley (31°N, 123°E). High SGD fluxes may also exist in the south of 29.5 °N, which correspond to the southern hypoxic zone.
Assuming that the DO concentration in the groundwater endmember is 0, we evaluated the contribution of SGD to hypoxia in the bottom water through dilution using the method from Guo et al. (2020).
$$ \frac{{C}_{\mathrm{D}\mathrm{O}}^{\mathrm{\text{'}}}}{{C}_{\mathrm{D}\mathrm{O}}}=\frac{D-{F}_{\mathrm{S}\mathrm{G}\mathrm{D}}}{D} , $$ | (7) |
where
We utilized a 222Rn mass balance model to estimate and compare the seasonal variation of SGD fluxes off the CJE among three seasons. The average SGD fluxes were estimated to be (0.012 ± 0.010) m3/(m2·d) in winter, (0.034 ± 0.015) m3/(m2·d) in summer, and (0.020 ± 0.010) m3/(m2·d) in autumn. Pooled DO and SGD fluxes were negatively correlated in our study region. In summer, groundwater with depleted DO fluxing into bottom waters would be prevented from mixing with surface waters because of density stratification. Thus, SGD contributed to the low DO concentrations of bottom water in the region off the CJE. The distribution patterns of SGD fluxes and hypoxic zones in the past years showed similar spatial distribution patterns, suggesting that SGD contributes to summer hypoxia off the CJE. In future investigations, we should further verify and refine the mechanisms by which SGD contributes to the formation of hypoxia.
We would like to thank Han Zhang, Haiming Nan, Shasha Song for their assistance during sample collection. Samples were collected onboard of R/V Runjiang1 and R/V Zheyuke implementing the open research cruises supported by Natural Science Foundation of China ship time sharing project.
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1. | Hyekyung Park, Guebuem Kim, Nahyeon Kwon, et al. Large seasonal variations in distributions, sources, and fluxes of dissolved amino acids in the continental shelf water. Progress in Oceanography, 2025, 231: 103405. doi:10.1016/j.pocean.2024.103405 | |
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5. | Shiping Lei, Dezhi Bu, Xianghui Guo, et al. Mitigation of hypoxia and ocean acidification on the inner East China Sea shelf impacted by the 2023 summer drought. Marine Pollution Bulletin, 2024, 207: 116830. doi:10.1016/j.marpolbul.2024.116830 |
Term | Unit | Summer | Autumn | Winter |
Excess 222Rn inventory (I) | Bq/m2 | 333.4 ± 205.8 | 156.7 ± 129.4 | −2.1 ± 139.3 |
222Rn sinks | ||||
Excess 222Rn decay loss flux (Fdecay) | Bq/(m2·d) | 60.4 ± 37.3 | 28.4 ± 23.4 | −0.4 ± 25.2 |
Atmospheric 222Rn loss flux (Fatmosphere) | Bq/(m2·d) | − | 10.0 ± 5.2 | 10.5 ± 3.8 |
222Rn loss flux through pycnocline (Fpycnocline) | Bq/(m2·d) | − | − | − |
222Rn mixing with offshore water flux (Fmixing) | Bq/(m2·d) | 41.4 ± 3.7 | 29.5 ± 3.9 | 37.7 ± 2.3 |
222Rn sources | ||||
Sediment diffusion flux of 222Rn (Fdiffusion) a | Bq/(m2·d) | 16.7 ± 3.3 | 16.7 ± 3.3 | 16.7 ± 3.3 |
River discharge flux of 222Rn (Friver) | Bq/(m2·d) | − | − | − |
SGD flux of 222Rn (known sources-known sinks) | Bq/(m2·d) | 85.1 ± 37.6 | 51.2 ± 24.5 | 31.2 ± 25.8 |
222Rn activity in groundwater endmember (Agw) a | Bq/m3 | 2 500.0 ± 266.7 | 2 500.0 ± 266.7 | 2 500.0 ± 266.7 |
SGD flux (FSGD) | m3/(m2·d) | 0.034 ± 0.015 | 0.020 ± 0.010 | 0.012 ± 0.010 |
Note: a refer to Guo et al. (2020). − represents no data. |
Region | Sampling time | Tracer | FSGD/(m·d-1) | Reference |
Dongsha Bay | Dec. 2008 | 226Ra | 0.24−2.30 | Ji et al. (2012) |
Changjiang River Effluent Plume | Sept. 2009 | 226Ra | 0.008−0.04 | Gu et al. (2012) |
Xiangshan Bay | Oct. 2009 | 222Rn | 0.69 | Wu et al. (2013) |
May 2010 | 222Rn | 0.23 | Wu et al. (2013) | |
East China Sea | Aug. 2013 | 223Ra, 224Ra, 226Ra, 228Ra | 0.003 9 | Wang et al. (2018) |
Changjiang River Estuary | Mar. 2015 | 223Ra, 224Ra | 0.18−0.45 | Liu et al. (2018) |
East China Sea continental shelf | Jan. 2010 | 226Ra, 228Ra | 0.044−0.138 | Tan et al. (2018) |
Shengsi Island | Nov. 2015 | 222Rn | 0.129 | Chen (2019) |
Xiangshan Bay | Mar. 2012 | 222Rn | 0.13 | Wen et al. (2014) |
Lianjiang | Jul. 2019 | 224Ra | 0.140 ± 0.070 | Peng et al. (2021) |
Oct. 2019 | 224Ra | 0.077 ± 0.040 | Peng et al. (2021) | |
The sea adjacent to the Changjiang River Estuary | Aug. 2017 | 222Rn | 0.022 ± 0.011 | Guo et al. (2020) |
Mar. 2018 | 222Rn | 0.002 ± 0.004 | Guo et al. (2020) | |
Jul. 2018 | 222Rn | 0.017 ± 0.009 | Guo et al. (2020) | |
Aug. 2018 | 222Rn | 0.018 ± 0.012 | Guo et al. (2020) | |
The sea adjacent to the Changjiang River Estuary | winter | 222Rn | 0.012 ± 0.010 | this study |
summer | 222Rn | 0.034 ± 0.015 | this study | |
autumn | 222Rn | 0.020 ± 0.010 | this study |
Term | Unit | Summer | Autumn | Winter |
Excess 222Rn inventory (I) | Bq/m2 | 333.4 ± 205.8 | 156.7 ± 129.4 | −2.1 ± 139.3 |
222Rn sinks | ||||
Excess 222Rn decay loss flux (Fdecay) | Bq/(m2·d) | 60.4 ± 37.3 | 28.4 ± 23.4 | −0.4 ± 25.2 |
Atmospheric 222Rn loss flux (Fatmosphere) | Bq/(m2·d) | − | 10.0 ± 5.2 | 10.5 ± 3.8 |
222Rn loss flux through pycnocline (Fpycnocline) | Bq/(m2·d) | − | − | − |
222Rn mixing with offshore water flux (Fmixing) | Bq/(m2·d) | 41.4 ± 3.7 | 29.5 ± 3.9 | 37.7 ± 2.3 |
222Rn sources | ||||
Sediment diffusion flux of 222Rn (Fdiffusion) a | Bq/(m2·d) | 16.7 ± 3.3 | 16.7 ± 3.3 | 16.7 ± 3.3 |
River discharge flux of 222Rn (Friver) | Bq/(m2·d) | − | − | − |
SGD flux of 222Rn (known sources-known sinks) | Bq/(m2·d) | 85.1 ± 37.6 | 51.2 ± 24.5 | 31.2 ± 25.8 |
222Rn activity in groundwater endmember (Agw) a | Bq/m3 | 2 500.0 ± 266.7 | 2 500.0 ± 266.7 | 2 500.0 ± 266.7 |
SGD flux (FSGD) | m3/(m2·d) | 0.034 ± 0.015 | 0.020 ± 0.010 | 0.012 ± 0.010 |
Note: a refer to Guo et al. (2020). − represents no data. |
Region | Sampling time | Tracer | FSGD/(m·d-1) | Reference |
Dongsha Bay | Dec. 2008 | 226Ra | 0.24−2.30 | Ji et al. (2012) |
Changjiang River Effluent Plume | Sept. 2009 | 226Ra | 0.008−0.04 | Gu et al. (2012) |
Xiangshan Bay | Oct. 2009 | 222Rn | 0.69 | Wu et al. (2013) |
May 2010 | 222Rn | 0.23 | Wu et al. (2013) | |
East China Sea | Aug. 2013 | 223Ra, 224Ra, 226Ra, 228Ra | 0.003 9 | Wang et al. (2018) |
Changjiang River Estuary | Mar. 2015 | 223Ra, 224Ra | 0.18−0.45 | Liu et al. (2018) |
East China Sea continental shelf | Jan. 2010 | 226Ra, 228Ra | 0.044−0.138 | Tan et al. (2018) |
Shengsi Island | Nov. 2015 | 222Rn | 0.129 | Chen (2019) |
Xiangshan Bay | Mar. 2012 | 222Rn | 0.13 | Wen et al. (2014) |
Lianjiang | Jul. 2019 | 224Ra | 0.140 ± 0.070 | Peng et al. (2021) |
Oct. 2019 | 224Ra | 0.077 ± 0.040 | Peng et al. (2021) | |
The sea adjacent to the Changjiang River Estuary | Aug. 2017 | 222Rn | 0.022 ± 0.011 | Guo et al. (2020) |
Mar. 2018 | 222Rn | 0.002 ± 0.004 | Guo et al. (2020) | |
Jul. 2018 | 222Rn | 0.017 ± 0.009 | Guo et al. (2020) | |
Aug. 2018 | 222Rn | 0.018 ± 0.012 | Guo et al. (2020) | |
The sea adjacent to the Changjiang River Estuary | winter | 222Rn | 0.012 ± 0.010 | this study |
summer | 222Rn | 0.034 ± 0.015 | this study | |
autumn | 222Rn | 0.020 ± 0.010 | this study |