
Citation: | Chunqing Chen, Qibin Lao, Fajin Chen, Guangzhe Jin, Jiacheng Li, Qingmei Zhu. Isotope constraints on seasonal dynamics of nitrogen in Zhanjiang Bay, a typical mariculture bay in South China[J]. Acta Oceanologica Sinica, 2024, 43(6): 60-70. doi: 10.1007/s13131-024-2373-0 |
Coastal waters, situated between the land and ocean, possess rich biological resources and diverse ecosystems that provide invaluable services for the survival and development of humanity (Dai et al., 2023). The behavior of nitrogen (N), a major limiting nutrient for primary production in coastal waters, is complex due to complicated hydrodynamics, various biochemical processes, and human interference that govern the fate of N (Dähnke et al., 2008; Lao et al., 2019; Wankel et al., 2007). In particular, increasing terrestrial N inputs strongly influence the coastal N cycle and environmental health, causing a series of environmental problems, such as eutrophication, seasonal hypoxia, and harmful algal blooms in coastal waters (Dai et al., 2023; Howarth, 2008; Khangaonkar et al., 2018; Lao et al., 2023b). Consequently, multiple N sources and their time-varying nature over recent decades have made it more challenging to understand the fate of N in coastal waters (Ye et al., 2016; Yan et al., 2017).
Among many methods, nitrate dual isotopes (δ15N-
Zhanjiang Bay, a typical semi-enclosed bay located in the northwestern South China Sea (SCS), is a renowned maricultural production and export region in China. However, rapid industrialization and urbanization have led to increasing eutrophication stress in the bay (He et al., 2023). This is mainly due to the large influx of terrestrial nutrients and intense local human activity (He et al., 2023; Li et al., 2020). More importantly, intensified human activities, including artificial dams and dredging, have significantly increased the intrusion of seawater from the outer SCS over the past decades. This intrusion can introduce and retain contaminants in the bay (Lao et al., 2022b), thereby exacerbating the eutrophication of seawater in the bay (He et al., 2023). This significantly threatens maricultural breeding activities in Zhanjiang Bay (Lao et al., 2022b). The complexity of the hydrodynamic processes and intense human activity make the dynamic processes of N in the bay more complex. However, a systematic understanding of N sources and their migration and transformation processes in mariculture bays remains limited, which greatly hinders the control of eutrophication and pollution in mariculture bays. To address this issue, the seasonal stable isotopes of dissolved N (δ15N-
Zhanjiang Bay, surrounded by the developing coastal city of Zhanjiang in Guangdong Province, South China, has a population of approximately 7.3 million (Chen et al., 2022b). The bay spans an area of about 490 km², with depths ranging from 2 m in the upper bay to 32 m in the lower bay (Fig. 1). Zhanjiang Bay is geographically and hydrodynamically complex, mainly influenced by the local discharge from the Suixi River at the top of the upper bay and the intrusion of high-salinity water from the SCS through a narrow channel at the bay mouth (~2 km wide) (Lao et al., 2022b). Zhanjiang Bay is famous for its mariculture industry, which includes cage culturing and oyster farming. Oyster culture is mainly located in the upper bay, while cage culture is primarily in the lower bay (Chen et al., 2022b). However, due to the influence of intensive human activities and weak hydrodynamic conditions, seawater pollution in the bay, such as eutrophication, is gradually intensifying (He et al., 2023). Affected by the East Asian Monsoon, the annual rainfall in this region is approximately
Two cruises were conducted in Zhanjiang Bay, China in September 2017 and March 2018 (Fig. 1). A total of 26 seawater sampling stations were established from the top of the upper bay to the outer bay during these two periods (Fig. 1). Seawater samples were collected using 10-L Niskin bottles. The temperature, salinity, and depth of the water were determined onsite using an RBR Maestro multiparameter water quality monitor (RBRmaestro3, RBR, Canada). For the collection of Chl-a, PN, and δ15N-PN samples, approximately
Dissolved oxygen (DO) was measured using Winkler titration with a precision of 0.07 mg/L. Chl-a samples were extracted using 90% acetone, and the levels were determined using the fluorometric method. Nutrient samples (
The PN and δ15N-PN samples were tightly packed into a tin cup and acidified with concentrated HCl vapor for at least two days to remove carbonate. Subsequently, the HCl was removed in a caustic soda dryer for 48 h (Lao et al., 2023a). The samples were then analyzed using an elemental isotope ratio mass spectrometer (EA Isolink-253 Plus, Thermo Fisher Scientific, USA). Atmospheric N2 references were utilized for δ15N-PN measurements. The average standard deviation of PN was ±0.1%, and the precision for δ15N-PN was ±0.2‰.
The analysis of δ15N-
In this study, a conservative mixing model was used to calculate the mixing between diluted riverine water and seawater in the bay to reveal the behavior of various N species along the salinity gradient (Fry, 2002; Lao et al., 2019; Ye et al., 2016). The formula is as follows:
$$ {N}_{\mathrm{m}\mathrm{i}\mathrm{x}}=q\times {N}_{\mathrm{d}}+(1-q)\times {N}_{\mathrm{m}} , $$ | (1) |
where Nd and Nm denote the concentrations of various N species in the diluted water endmember and marine endmember, respectively, and q denotes the contribution of diluted water to each sample, calculated from salinity as follows:
$$ q=({S}_{{\mathrm{m}}}-{S}_{{\mathrm{mix}}})/({S}_{{\mathrm{m}}}-{S}_{{\mathrm{d}}}) , $$ | (2) |
where Smix, Sd, and Sm denote the salinity of the sample, diluted water end-member, and marine end-member, respectively.
Additionally, the isotopic composition (δmix) of various N species in a sample is the concentration-weighted mean of values derived from diluted water and marine end-members during physical mixing. The formula is as follows:
$$ {\text{δ}}_{\mathrm{m}\mathrm{i}\mathrm{x}}=\left[q\times {N}_{\mathrm{d}}\times {\text{δ} }_{\mathrm{d}}+\left(1-q\right)\times {N}_{\mathrm{m}}\times {\text{δ} }_{\mathrm{m}}\right]/{N}_{\mathrm{m}\mathrm{i}\mathrm{x}} , $$ | (3) |
where δd and δm denote the isotopic values of various N species in the diluted water and marine end-members, respectively.
In this study, the diluted water end-member was selected from the lowest-salinity water at the top of the upper bay (Station Z25), and the marine end-member was selected from the highest-salinity water in the outer bay (Stations Z13 and Z14). Endmember values are listed in Table 1.
End-member | Salinity | ${{{\rm {NO}}_3^-} }$ concentration/ (μmol·L−1) |
${{\rm {NH}}_4^+} $ concentration/ (μmol·L−1) |
PN concentration/ (mg·L−1) |
${\text{δ}} $15N-${{\rm {NO}}_3^-} $/ ‰ |
${\text{δ}} $15N-PN/ ‰ |
${\text{δ}} $18O-$ {{\rm {NO}}_3^-} $/ ‰ |
|
September | Diluted water | 15.04 | 47.72 | 5.82 | 0.078 | 7.3 | 6.8 | −0.6 |
Marine | 27.12 | 3.96 | 2.24 | 0.109 | 0.5 | 9.6 | 4.1 | |
March | Diluted water | 20.59 | 78.11 | 0.21 | 0.054 | 6.1 | 9.4 | 6.9 |
Marine | 29.50 | 1.48 | 0.01 | 0.052 | 1.4 | 8.6 | 11.3 | |
Note: PN: particulate nitrogen. |
The seasonal distributions of the physicochemical parameters are illustrated in Fig. 2. Seawater temperature was higher in the rainy season (29.9–32.9℃) and lower in the dry season (22.2–29.4℃). Significant variations in salinity were observed in the bay (t-test, p<0.01), with lower values in the rainy season (15.04–27.89) and higher values in the dry season (20.59–30.46). There was a remarkable salinity gradient from the upper bay to the outer bay, with low salinity occurring at the top of the upper bay, while high salinity was observed in the outer bay during both seasons. The DO values in the rainy season (3.79–7.33 mg/L) were much lower than those in the dry season (6.99–10.50 mg/L). Low DO values were recorded at the top of the upper layer during the rainy season. However, the Chl-a concentration in the rainy season (2.09–22.33 μg/L) was remarkably higher than that in the dry season (1.52–11.37 μg/L).
The seasonal distributions of the dissolved nutrients (
The δ15N-
The δ15N-PN values in the rainy season (ranging from 3.1‰ to 11.1‰, an average of 5.6‰) were lower than those in the dry season (ranging from 6.5‰ to 11.6‰, an average of 9.2‰). Except for the higher δ15N-PN values in the outer bay during the rainy season, the values generally decreased from the upper bay to the outer bay (Fig. 4). The distinct seasonal and spatial distributions of isotopic values suggest seasonal N sources and biogeochemical processes in the bay.
In Zhanjiang Bay, nutrient concentrations in the upper bay were remarkably higher than those in the lower bay during both seasons (Fig. 3), consistent with observations by He et al. (2023) and Li et al. (2020). Similarly, low salinity was recorded in the upper bay (Fig. 2), indicating that elevated nutrient levels were predominantly influenced by terrestrial input. Heavy rainfall in this region typically occurs from April to October (Lao et al., 2022b). Such rainfall can erode and wash away land-based pollutants into the rivers surrounding Zhanjiang Bay, ultimately entering the coastal waters (He et al., 2023). The nutrient concentrations increased significantly during the rainy season, indicating the significant impact of heavy land-based sources discharged from anthropogenic activities (He et al., 2023; Zhang et al., 2021). Over the past decades, increasing terrestrial nutrient inputs have contributed to enhanced eutrophication in the bay (He et al., 2023). However, in the lower bay, the lower nutrient levels could be attributed to the intrusion of high-salinity water from the outer bay. Water mass transport dramatically affects nutrient distribution, thus impacting local marine ecosystems (Lao et al., 2022a, 2023b, 2023c). Human activities have significantly increased the intrusion of high-salinity water from the outer bay over the past two decades (Lao et al., 2022b), resulting in the dilution of nutrients in the lower bay. Although the intrusion of high-salinity water was more pronounced in summer owing to the stronger west-Guangdong coastal current during this period (Lao et al., 2022b), the nutrient concentration in the lower bay during the rainy season was still significantly higher than that during the dry season (t-test, p<0.01) (Fig. 3). This suggests that during the rainy season, terrestrial inputs had a more pronounced effect on nutrient distribution than water mass transportation from the outer bay.
Notably, the N/P ratio in the two seasons (ranging from 4.0 to 11.2, an average of 6.2 in the rainy season, and from 0.7 to 22.6, an average of 5.1 in the dry season) was significantly lower than the Redfield ratio (16.0). High N and P concentrations suggest that N and P did not act as limiting nutrients in the bay and that the environmental conditions were favorable for phytoplankton blooms (Yang et al., 2018). Over recent decades, eutrophication and harmful algal blooms have increased substantially in the bay (He et al., 2023; Zhang et al., 2022). Before the 1980s, harmful algal blooms rarely occurred in Zhanjiang Bay, but have occurred periodically and frequently since the 2000s (Zhang et al., 2022). This is mainly due to the increasing nutrient input in the bay, particularly P input (He et al., 2023; Zhang et al., 2022). The dissolved inorganic nitrogen concentration increased threefold from 1990 to 2019, while the P concentration increased 21-fold owing to the continuous input of high-concentration phosphorus from industrial factories around Zhanjiang Bay (He et al., 2023; Zhang et al., 2022). The faster rate of increase in the P concentration in the bay has been responsible for the decrease in the N/P ratio over the past decades (He et al., 2023). Therefore, the ecosystem in Zhanjiang Bay has shifted from P-limited oligotrophic conditions before the 2020s to N-limited eutrophic conditions (Zhang et al., 2022). This implies that the N input plays an important role in the health of the Zhanjiang Bay ecosystem. However, in addition to the impact of the watershed, sewage outlets around Zhanjiang Bay can also input large amounts of anthropogenic nitrogen into the bay (Zhang et al., 2021), resulting in a complex and diversified source of N in the bay.
In the rainy season, the negative offset of
Active
Both offset-
In the dry season, a negative offset of
Indeed, in mid-March 2018, a red tide of Phaeocystis globosa in Zhanjiang Bay, with a maximum cell density of 1.13 ×109 cells/L (2018 South China Sea Region Marine Disaster Bulletin;
Due to the reduced input of terrestrial nutrients and the dominance of biological processes (assimilation and mineralization) in isotopic fractionation, the isotopic values of nitrate cannot be used for source apportionment during the dry season. In contrast, despite some fluctuations, nitrate concentrations mainly aligned with the theoretical mixing line, indicating that nitrate was in a conservative mixing state during the rainy season, and that nitrate isotopes should be similar to the source. Therefore, we quantified the sources of nitrate in Zhanjiang Bay during the rainy season. Because Zhanjiang Bay is surrounded by cities and rivers, heavy rainfall can erode and wash away land-based pollutants from the basin into rivers, which then flow from the top of the bay to the lower bay during the rainy season. Thus, four potential nitrate sources, namely manure and sewage, fertilizer, soil N, and atmospheric deposition, were considered in this study. The values of δ15N-
Source | δ15N-${{\rm {NO}}_3^-} $ | δ18O-${{\rm {NO}}_3^-} $ | |||||
Range/‰ | (Mean ± SD)/‰ | Literature | Range/‰ | (Mean ± SD)/‰ | Literature | ||
Manure and Sewage |
4 – 25 | 10.3 ± 4.0 | Xue et al., 2009 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Fertilizer | −1.87 – 2.96 | 0.04 ± 1.87 | Kendall, 1998; Zhang et al., 2018 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Soil N | −0.05 – 8.25 | 4.52 ± 2.67 | Kendall, 1998; Zhang et al., 2018 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Atmospheric N deposition |
−1.8 – 4.1 | 0.8 ± 1.5 | Chen et al., 2019 | 42.7 – 61.6 | 52.4 ± 5.1 | Chen et al., 2019 |
Our study on the stable isotopes of particulate and dissolved N pools provides detailed insights into N sources and cycling in a typical mariculture bay. We observed significant seasonal variations in nutrient concentrations, with higher level in the rainy season and lower level in the dry season. This trend is primarily attributed to the influx of terrestrial nutrients discharged into the bay during the rainy season. In addition, significant nitrate loss occurred in the upper bay during the rainy season, which was related to intense physical sediment-water interactions, with less isotopic fractionation. Among the multiple sources, soil N (36%) and manure and sewage (33%) were the predominant N sources contributing to the N loads in Zhanjiang Bay during the rainy season. However, during the dry season, more biogeochemical processes in the bay may be related to a decrease in runoff and an increase in water retention time. Owing to the impact of red tides, the ammonium in Zhanjiang Bay has been almost completely consumed during the dry season. In addition, the observed nitrate loss and concurrent increase in stable isotopes of dissolved and particulate N during the dry season indicate strong coupling of assimilation and mineralization.
Chen Fajin, Deng Ziyun, Lao Qibin, et al. 2022a. Nitrogen cycling across a salinity gradient from the Pearl River Estuary to offshore: Insight from nitrate dual isotopes. Journal of Geophysical Research: Biogeosciences, 127(5): e2022JG006862, doi: 10.1029/2022JG006862
|
Chen Fajin, Huang Chao, Lao Qibin, et al. 2021. Typhoon control of precipitation dual isotopes in southern China and its palaeoenvironmental implications. Journal of Geophysical Research: Atmospheres, 126(14): e2020JD034336, doi: 10.1029/2020JD 034336
|
Chen Fajin, Lao Qibin, Jia Guodong, et al. 2019. Seasonal variations of nitrate dual isotopes in wet deposition in a tropical city in China. Atmospheric Environment, 196: 1–9, doi: 10.1016/j.atmosenv.2018.09.061
|
Chen Fajin, Lao Qibin, Liu Mengyang, et al. 2022b. Impact of intensive mariculture activities on microplastic pollution in a typical semi-enclosed bay: Zhanjiang Bay. Marine Pollution Bulletin, 176: 113402, doi: 10.1016/j.marpolbul.2022.113402
|
Chen Chunqing, Lao Qibin, Shen Youli, et al. 2022c. Comparative study of nitrogen cycling between a bay with riverine input and a bay without riverine input, inferred from stable isotopes. Frontiers in Marine Science, 9: 885037, doi: 10.3389/fmars.2022.885037
|
Chen Fajin, Lao Qibin, Zhang Shuwen, et al. 2020. Nitrate sources and biogeochemical processes identified using nitrogen and oxygen isotopes on the eastern coast of Hainan Island. Continental Shelf Research, 207: 104209, doi: 10.1016/j.csr.2020.104209
|
Dähnke K, Bahlmann E, Emeis K. 2008. A nitrate sink in estuaries? An assessment by means of stable nitrate isotopes in the Elbe Estuary. Limnology and Oceanography, 53(4): 1504–1511, doi: 10.4319/lo.2008.53.4.1504
|
Dai Minhan, Zhao Yangyang, Chai Fei, et al. 2023. Persistent eutrophication and hypoxia in the coastal ocean. Cambridge Prisms: Coastal Futures, 1: e19, doi: 10.1017/cft.2023.7
|
Fry B. 2002. Conservative mixing of stable isotopes across estuarine salinity gradients: A conceptual framework for monitoring watershed influences on downstream fisheries production. Estuaries, 25(2): 264–271, doi: 10.1007/BF02691313
|
Glibert P M, Wilkerson F P, Dugdale R C, et al. 2016. Pluses and minuses of ammonium and nitrate uptake and assimilation by phytoplankton and implications for productivity and community composition, with emphasis on nitrogen-enriched conditions. Limnology and Oceanography, 61(1): 165–197, doi: 10.1002/lno.10203
|
Granger J, Sigman D M. 2009. Removal of nitrite with sulfamic acid for nitrate N and O isotope analysis with the denitrifier method. Rapid Communications in Mass Spectrometry, 23(23): 3753–3762, doi: 10.1002/rcm.4307
|
Granger J, Sigman D M, Lehmann M F, et al. 2008. Nitrogen and oxygen isotope fractionation during dissimilatory nitrate reduction by denitrifying bacteria. Limnology and Oceanography, 53(6): 2533–2545, doi: 10.4319/lo.2008.53.6.2533
|
He Guirong, Lao Qibin, Jin Guangzhe, et al. 2023. Increasing eutrophication driven by the increase of phosphate discharge in a subtropical bay in the past 30 years. Frontiers in Marine Science, 10: 1184421, doi: 10.3389/fmars.2023.1184421
|
Howarth R W. 2008. Coastal nitrogen pollution: a review of sources and trends globally and regionally. Harmful Algae, 8(1): 14–20, doi: 10.1016/j.hal.2008.08.015
|
Kendall C. 1998. Tracing nitrogen sources and cycling in catchments. In: Kendall C, McDonnell J J, eds. Isotope Tracers in Catchment Hydrology. New York: Elsevier, 519–576
|
Khangaonkar T, Nugraha A, Xu Wenwei, et al. 2018. Analysis of hypoxia and sensitivity to nutrient pollution in Salish Sea. Journal of Geophysical Research: Oceans, 123(7): 4735–4761, doi: 10.1029/2017JC013650
|
Lao Qibin, Chen Fajin, Jin Guangzhe, et al. 2023a. Characteristics and mechanisms of typhoon-induced decomposition of organic matter and its implication for climate change. Journal of Geophysical Research: Biogeosciences, 128(6): e2023JG007518, doi: 10.1029/2023JG007518
|
Lao Qibin, Chen Fajin, Liu Guoqiang, et al. 2019. Isotopic evidence for the shift of nitrate sources and active biological transformation on the western coast of Guangdong Province, South China. Marine Pollution Bulletin, 142: 603–612, doi: 10.1016/j.marpolbul.2019.04.026
|
Lao Qibin, Liu Sihai, Ling Zheng, et al. 2023b. External dynamic mechanisms controlling the periodic offshore blooms in Beibu Gulf. Journal of Geophysical Research: Oceans, 128(6): e2023JC019689, doi: 10.1029/2023JC019689
|
Lao Qibin, Lu Xuan, Chen Fajin, et al. 2023c. Effects of upwelling and runoff on water mass mixing and nutrient supply induced by typhoons: Insight from dual water isotopes tracing. Limnology and Oceanography, 68(1): 284–295, doi: 10.1002/lno.12266
|
Lao Qibin, Lu Xuan, Chen Fajin, et al. 2023d. A comparative study on source of water masses and nutrient supply in Zhanjiang Bay during the normal summer, rainstorm, and typhoon periods: Insights from dual water isotopes. Science of the Total Environment, 903: 166853, doi: 10.1016/j.scitotenv.2023.166853
|
Lao Qibin, Wu Junhui, Chen Fajin, et al. 2022a. Increasing intrusion of high salinity water alters the mariculture activities in Zhanjiang Bay during the past two decades identified by dual water isotopes. Journal of Environmental Management, 320: 115815, doi: 10.1016/j.jenvman.2022.115815
|
Lao Qibin, Zhang Shuwen, Li Zhiyang, et al. 2022b. Quantification of the seasonal intrusion of water masses and their impact on nutrients in the Beibu Gulf using dual water isotopes. Journal of Geophysical Research: Oceans, 127(7): e2021JC018065, doi: 10.1029/2021JC018065
|
Li Jiacheng, Cao Ruixue, Lao Qibin, et al. 2020. Assessing seasonal nitrate contamination by nitrate dual isotopes in a monsoon-controlled bay with intensive human activities in South China. International Journal of Environmental Research and Public Health, 17(6): 1921, doi: 10.3390/ijerph17061921
|
McIlvin M R, Altabet M A. 2005. Chemical conversion of nitrate and nitrite to nitrous oxide for nitrogen and oxygen isotopic analysis in freshwater and seawater. Analytical Chemistry, 77(17): 5589–5595, doi: 10.1021/ac050528s
|
Sigman D M, Altabet M A, McCorkle D C, et al. 1999. The δ15N of nitrate in the Southern Ocean: Consumption of nitrate in surface waters. Global Biogeochemical Cycles, 13(4): 1149–1166, doi: 10.1029/1999GB900038
|
Sigman D M, Granger J, Difiore P J, et al. 2005. Coupled nitrogen and oxygen isotope measurements of nitrate along the eastern North Pacific margin. Global Biogeochemical Cycles, 19(4): GB4022
|
Wang Shuangling, Zhou Fengxia, Chen Fajin, et al. 2021. Spatiotemporal distribution characteristics of nutrients in the drowned tidal inlet under the influence of tides: A case study of Zhanjiang Bay, China. International Journal of Environmental Research and Public Health, 18(4): 2089, doi: 10.3390/ijerph18042089
|
Wankel S D, Kendall C, Pennington J T, et al. 2007. Nitrification in the euphotic zone as evidenced by nitrate dual isotopic composition: Observations from Monterey Bay, California. Global Biogeochemical Cycles, 21(2): GB2009
|
Xue Dongmei, Botte J, De Baets B, et al. 2009. Present limitations and future prospects of stable isotope methods for nitrate source identification in surface- and groundwater. Water Research, 43(5): 1159–1170, doi: 10.1016/j.watres.2008.12.048
|
Yan Xiuli, Xu M N, Wan X S, et al. 2017. Dual isotope measurements reveal zoning of nitrate processing in the summer Changjiang (Yangtze) River plume. Geophysical Research Letters, 44(24): 12289–12297
|
Yang Zhi, Chen Jianfang, Li Hongliang, et al. 2018. Sources of nitrate in Xiangshan Bay (China), as identified using nitrogen and oxygen isotopes. Estuarine, Coastal and Shelf Science, 207: 109–118
|
Ye Feng, Jia Guodong, Xie Luhua, et al. 2016. Isotope constraints on seasonal dynamics of dissolved and particulate N in the Pearl River Estuary, South China. Journal of Geophysical Research: Oceans, 121(12): 8689–8705
|
Zhang Peng, Peng Conghui, Zhang Jibiao, et al. 2022. Long-term harmful algal blooms and nutrients patterns affected by climate change and anthropogenic pressures in the Zhanjiang Bay, China. Frontiers in Marine Science, 9: 849819, doi: 10.3389/fmars.2022.849819
|
Zhang Jibiao, Zhang Yanchan, Zhang Peng, et al. 2021. Seasonal phosphorus variation in coastal water affected by the land-based sources input in the eutrophic Zhanjiang Bay, China. Estuarine, Coastal and Shelf Science, 252: 107277
|
Zhang Man, Zhi Yuyou, Shi Jiachun, et al. 2018. Apportionment and uncertainty analysis of nitrate sources based on the dual isotope approach and a Bayesian isotope mixing model at the watershed scale. Science of the Total Environment, 639: 1175–1187, doi: 10.1016/j.scitotenv.2018.05.239
|
End-member | Salinity | ${{{\rm {NO}}_3^-} }$ concentration/ (μmol·L−1) |
${{\rm {NH}}_4^+} $ concentration/ (μmol·L−1) |
PN concentration/ (mg·L−1) |
${\text{δ}} $15N-${{\rm {NO}}_3^-} $/ ‰ |
${\text{δ}} $15N-PN/ ‰ |
${\text{δ}} $18O-$ {{\rm {NO}}_3^-} $/ ‰ |
|
September | Diluted water | 15.04 | 47.72 | 5.82 | 0.078 | 7.3 | 6.8 | −0.6 |
Marine | 27.12 | 3.96 | 2.24 | 0.109 | 0.5 | 9.6 | 4.1 | |
March | Diluted water | 20.59 | 78.11 | 0.21 | 0.054 | 6.1 | 9.4 | 6.9 |
Marine | 29.50 | 1.48 | 0.01 | 0.052 | 1.4 | 8.6 | 11.3 | |
Note: PN: particulate nitrogen. |
Source | δ15N-${{\rm {NO}}_3^-} $ | δ18O-${{\rm {NO}}_3^-} $ | |||||
Range/‰ | (Mean ± SD)/‰ | Literature | Range/‰ | (Mean ± SD)/‰ | Literature | ||
Manure and Sewage |
4 – 25 | 10.3 ± 4.0 | Xue et al., 2009 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Fertilizer | −1.87 – 2.96 | 0.04 ± 1.87 | Kendall, 1998; Zhang et al., 2018 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Soil N | −0.05 – 8.25 | 4.52 ± 2.67 | Kendall, 1998; Zhang et al., 2018 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Atmospheric N deposition |
−1.8 – 4.1 | 0.8 ± 1.5 | Chen et al., 2019 | 42.7 – 61.6 | 52.4 ± 5.1 | Chen et al., 2019 |
End-member | Salinity | ${{{\rm {NO}}_3^-} }$ concentration/ (μmol·L−1) |
${{\rm {NH}}_4^+} $ concentration/ (μmol·L−1) |
PN concentration/ (mg·L−1) |
${\text{δ}} $15N-${{\rm {NO}}_3^-} $/ ‰ |
${\text{δ}} $15N-PN/ ‰ |
${\text{δ}} $18O-$ {{\rm {NO}}_3^-} $/ ‰ |
|
September | Diluted water | 15.04 | 47.72 | 5.82 | 0.078 | 7.3 | 6.8 | −0.6 |
Marine | 27.12 | 3.96 | 2.24 | 0.109 | 0.5 | 9.6 | 4.1 | |
March | Diluted water | 20.59 | 78.11 | 0.21 | 0.054 | 6.1 | 9.4 | 6.9 |
Marine | 29.50 | 1.48 | 0.01 | 0.052 | 1.4 | 8.6 | 11.3 | |
Note: PN: particulate nitrogen. |
Source | δ15N-${{\rm {NO}}_3^-} $ | δ18O-${{\rm {NO}}_3^-} $ | |||||
Range/‰ | (Mean ± SD)/‰ | Literature | Range/‰ | (Mean ± SD)/‰ | Literature | ||
Manure and Sewage |
4 – 25 | 10.3 ± 4.0 | Xue et al., 2009 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Fertilizer | −1.87 – 2.96 | 0.04 ± 1.87 | Kendall, 1998; Zhang et al., 2018 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Soil N | −0.05 – 8.25 | 4.52 ± 2.67 | Kendall, 1998; Zhang et al., 2018 | −5 – 15 | 4.08 ± 0.33 | Kendall, 1998; Zhang et al., 2018 | |
Atmospheric N deposition |
−1.8 – 4.1 | 0.8 ± 1.5 | Chen et al., 2019 | 42.7 – 61.6 | 52.4 ± 5.1 | Chen et al., 2019 |