Chemical speciation, source apportionment, and pollution assessment of phosphorus in sediments from typical urban lakes in Southern China

Chemical speciation, source apportionment, and pollution assessment of phosphorus in sediments from typical urban lakes in Southern China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Chemical speciation, source apportionment, and pollution assessment of phosphorus in sediments from typical urban lakes in Southern China Tianning Li, Linsen Tang, Huiyang Qiu, Fangwen Zheng, Ping Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7828473/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Urban lakes play a vital role in flood disaster mitigation, water supply, and climate maintenance. However, excessive phosphorus inputs resulting from urban development constitute a significant factor in the deterioration of aquatic ecosystems. In this study, samples of sediment profiles (within 40 cm) from three representative urban lakes (Xianghu Lake, Qianhu Lake, and Aixihu Lake) in Nanchang were collected to investigate the chemical speciation characteristics, analyze the sources and assess the pollution condition of phosphorus. Results indicated that sediments in Qianhu Lake exhibited the highest concentration of total phosphorus (923.06–1630.17 mg/kg), followed by Aixihu Lake (616.58–1532.88 mg/kg), while Xianghu Lake exhibited the lowest levels (538.79–1481.57 mg/kg). Calcium-bound phosphorus (Ca-P) dominated in all three lakes (accounting for over 30% of total phosphorus), followed by iron-bound phosphorus (Fe-P) and detrital phosphorus (De-P). While the organic phosphorus (Org-P) and exchangeable phosphorus (Ex-P) constituted the lowest proportions, with lower than 15% of each speciation. The distribution of phosphorus speciation in the lake sediments exhibited vertical spatial heterogeneity, reflecting the differentiation of influencing factors and sources. In all the lakes, clay dominated the sediment composition (≥ 34%), followed by coarse silt, while fine silt was the least abundant. Correlation analysis revealed that grain size and organic matter constrained the concentrations of phosphorus speciation. The Absolute Principal Component Score-Multiple Linear Regression model (APCS-MLR) revealed that phosphorus pollution in Xianghu Lake, Qianhu Lake, and Aixihu Lake was predominantly driven by agricultural non-point sources, with the contributions of more than 35%, followed by industrial emissions and domestic sewage, which corresponded with the extensive agricultural land around the lake. Nemerow integrated pollution index analysis revealed that all the lakes were heavily polluted, and ranked as follows: Qianhu Lake (F ≥ 2.26) > Aixihu Lake (F ≥ 2.04) > Xianghu Lake (F ≥ 1.92). Consequently, comprehensive management measures, including optimizing agricultural fertilization–irrigation forms and restricting pollutant discharges, are required to prevent further deterioration. This study is of practical significance for the prevention of lake eutrophication. Also, it provides a scientific basis for research on biogeochemical cycles and the protection and management of aquatic ecosystems in the urban lakes. Urban lakes Sediments Phosphorus speciation Source apportionment Pollution assessment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Lakes, as vital components of urban ecosystems, play an irreplaceable ecological role in regulating regional climate, sustaining biodiversity, and safeguarding water resource security (Radosavljevic et al., 2024 ). Currently, the combined effects of global climate change and intensive human activities have significantly accelerated lake eutrophication processes. Excessive phosphorus inputs and endogenous release are recognized as core factors of water eutrophication (Jovana et al., 2022 ). The dynamic behavior of phosphorus at the sediment-water interface directly influences lake nutrient cycling and algal growth mechanisms. Consequently, the identification of its speciation, sources and pollution assessment has emerged as a frontier topic within environmental science (Wu et al., 2024 ). Sediments serve as significant reservoirs for phosphorus, with their compositional characteristics directly governing phosphorus bioavailability. Components such as clay minerals, iron oxides, and organic matter dominate phosphorus redistribution through processes including surface adsorption, chemical bonding, and biological effects (Paerl et al., 2024 ). It is generally recognized that phosphorus in sediments exists in multiple forms, each exhibiting distinct responses to environmental factors. Among these, iron-bound phosphorus (Fe-P) and organic phosphorus (Org-P) constitute the primary active components for endogenous phosphorus release, whereas calcium-bound phosphorus (Ca-P) and detrital phosphorus (De-P) exhibit greater stability (Malecki et al., 2004 ; Yang et al., 2017 ). The grain size of sediments influences the adsorption capacity of phosphorus by altering specific surface area, with fine-grained sediments typically containing higher Fe-P concentrations than coarse-grained sediments (Wang et al., 2021 ). Furthermore, the effect of the organic matter furtherly changes the spatiotemporal heterogeneity of phosphorus flux (Ye et al., 2019 ). The diversity of speciation renders traditional total phosphorus (TP) indicators inadequate for accurately analyzing the characteristics of phosphorus in sediments, therefore, it is necessary to develop multi-speciation analysis techniques. Currently, numerous studies have extensively investigated the influencing factors and sources of phosphorus speciation in sediments from lakes, estuaries, and marine regions. Zhao et al. ( 2022 ) examined the mechanisms governing phosphorus speciation transformation in the sediment of Ulansuhai Nur and explored how pH alters the distribution of phosphorus speciation within sediments. Through examining phosphorus speciation in sediments along the Ton River, Kozyrev et al. ( 2023 ) found that Fe-P and Org-P concentrations increased with decreasing sediment grain size. Conversely, Ca-P exhibits a relatively uniform distribution across all grain sizes. Guo et al. ( 2024 ) investigated sources of phosphorus in sediments from the Beibu Gulf, China, and identified that terrestrial organic matter was the primary contributor. Compared with the regions above, urban lakes—owing to their semi-enclosed hydrological characteristics, extensive transportation networks, and intensive anthropogenic disturbances—exhibit unique phosphorus cycling patterns (Zhao et al., 2025 ). Exogenous inputs such as domestic sewage, industrial effluents, and agricultural wastewater result in phosphorus loads in urban sediments that are significantly higher than those in natural lakes (Song et al., 2017 ; Putt et al., 2019 ). Existing research on the geochemistry behavior of phosphorus has primarily focused on natural lakes, while comparatively limited attention has been directed toward urban lakes (Zhao et al., 2022 ; Kozyrev et al., 2023 ). In this study, the profile sediments from three representative lakes—Qianhu Lake, Xianghu Lake, and Aixihu Lake, in Nanchang, a typical lakeshore city in the Southern China, were collected. The distributions of grain size and phosphorus speciation in sediments were revealed, the sources’ contributions of sedimentary phosphorus were identified through multivariate statistical approaches, and the phosphorus pollution indices were estimated in these lakes. The findings provide theoretical and technical support for the prevention and control of eutrophication in urban lakes, they also offer a scientific basis for the protection and management of water resources and aquatic ecosystems in urban environments. 2. Study area and methodology 2.1 Study area Nanchang is the capital of Jiangxi Province in the Southeastern China (115.45°–116.58°E, 28.17°–29.18°N, Fig. 1 a and b) and situated in the middle and lower reaches of the Yangtze River. It spans approximately 121 kilometers from north to south and 108 kilometers from east to west. Nanchang is adjacent to Poyang Lake—the largest freshwater lake in China—while its central area is traversed by the Gan and Fu rivers (Jia et al., 2019 ) (Fig. 1 b). Xianghu Lake, Qianhu Lake and Aixihu Lake are the three major representative lakes in Nanchang and serve as important habitats for migratory birds in the city (Fig. 1 c, d and e). Xianghu Lake, located in the southwestern urban area, covers an area of 7.81 km² (Fig. 1 d). Aixihu Lake, situated in the northeast, has an area of approximately 1.67 km² (Fig. 1 e). Both Xianghu Lake and Aixihu Lake are primarily fed by the Fu River and surrounding urban water systems (Shao et al., 2019 ; Zheng et al., 2025). Qianhu Lake, located in the western part of the city to the west of the Gan River, covers an area of about 1.66 km² and mainly receives water from the tributaries of the Gan River (Zeng et al., 2024 ) (Fig. 1 c). Nanchang experiences a subtropical humid monsoon climate, characterized by long summers and winters and short springs and autumns. The annual average temperature and sunshine duration range from 17.1°C to 17.8°C and 1723 to 1820 hours, respectively. Prevailing winds are northerly in winter and southerly in summer (Wu et al., 2023 ). The long-term mean annual precipitation of the city is 1645 mm, with the rainy season (April to July) accounting for more than 55% of the total, while the dry season (October to January) contributes less than 15% (Sun et al., 2021 ). 2.2 Methodology 2.2.1 Field sampling In November 2024, systematic sampling was conducted at Xianghu Lake, Qianhu Lake and Aixihu Lake (Fig. 1 ). For each lake, three representative sites were evenly distributed to cover different functional zones, including the inflow, central area and outflow. Sediment cores were collected using a gravity corer (HD-TRC3) and the samples were collected at 2 cm intervals. All samples were placed in clean, PVC sealed bags, labeled with geographic coordinates and layer identification numbers, and immediately transferred to a cooler for preservation prior to laboratory analysis. 2.2.2 Sample pretreatment and analysis For each site, a 0.5 g sediment sample was placed in 900 mL of ultrapure water, dispersed by ultrasonic, and analyzed for grain size using a laser size analyzer (HELOS-SUCELLi, SYMPATEC GmbH, Germany), with a measurement error of less than 3% (Sehgal et al., 2022 ). Following the Udden–Wentworth classification system, grain size fractions were categorized as clay (< 4 µm), fine silt (4–20 µm), and coarse silt (20–63 µm). Organic matter content was determined using the loss-on-ignition method at 550°C, as described by Nakhli et al. ( 2018 ). Phosphorus fractions were sequentially extracted and classified as exchangeable phosphorus (Ex-P), iron-bound phosphorus (Fe-P), calcium-bound phosphorus (Ca-P), detrital phosphorus (De-P), and organic phosphorus (Org-P). After drying and removing impurities, sufficient amounts of sediment were ground to < 74 µm. Ex-P was extracted with 1 M MgCl 2 for two hours (pH 8, 25°C); Fe-P with CDB (0.3 M sodium citrate, 0.14 M sodium dithionite, 1.0 M sodium bicarbonate) for six h (pH 7.6, 25°C); Ca-P with 1 M acetate buffer for six hours (pH 4, 25°C); De-P with 1 M HCl solution for 16 h at 25°C; and Org-P with 1 M HCl solution for 16 hours at 25°C after the residue was heated to ash at 550°C for two hours (Saha et al., 2024 ). Following each extraction step, solid–liquid separation was performed by centrifugation at 5000 r/min. The supernatant liquid was analyzed for phosphorus concentrations based on an AA3 continuous flow analyzer (SEAL Analytical, UK), with an analytical error of less than 5% (Capasso et al., 2020 ). Inorganic phosphorus (IP) was calculated as the sum of Ex-P, Fe-P, Ca-P, and De-P, while total phosphorus (TP) was defined as the sum of IP and Org-P. 2.2.3 Data processing The sampling site location map was produced by ArcGIS 10.1 (Environmental Systems Research Institute, Inc., USA), while statistical graphics were generated by Origin 2024 (OriginLab Corporation, USA). One-way ANOVA was employed to evaluate the discrepancies of phosphorus concentrations between the different lakes. The one-way ANOVA analysis, the correlation analysis (CA), the principal component analysis (PCA), and the APCS-MLR (introduced in below) were based on SPSS (version 23.0; International Business Machines Corporation, USA). The APCS-MLR model represents a conventional receptor modelling approach for quantitative source apportionment in datasets featuring multiple independent variables and a single dependent variable. It integrates the Multiple Linear Regression (MLR) model with Absolute Principal Component Scores (APCS) (Varol et al., 2022 ). It is noteworthy that this model serves solely to evaluate the goodness-of-fit of regression models and cannot account for uncertainties in contribution rate calculations (Wu et al., 2023 ). Consequently, the contribution rates for each principal component in the APCS-MLR model computations do not incorporate uncertainty. The single factor pollution index (Formula 1) and Nemerow integrated pollution index (Formula 2) are frequently employed to assess sediment contamination. The single factor pollution index is advantageous for its simplicity and ease of application, making it suitable for preliminary environmental assessments. The Nemerow integrated pollution index considers the combined impact of multiple factors on environmental quality, rendering it appropriate for complex environments and multi-pollutant scenarios (Maskooni et al., 2020 ; Behairy et al., 2021 ; Zhang et al., 2023). Combining both approaches allows for a balance between pollution targeting and systemic comprehensiveness. The present study employed both methods to calculate the pollution evaluation index for sediments. The formulas were as follows: S i = C i /C s, i (1) F = \(\:\sqrt{{\text{(}{\text{S}}_{\text{ave}}}^{\text{2}}\text{+}{{\text{S}}_{\text{max}}}^{\text{2}})/\text{2}}\) (2) S i denotes the single factor pollution index for sample; S i >1 indicate that the index exceeds the evaluation standard value; C i represents the measured value of the sample; C s, i denotes the standard value for the factor; F represents the integrated pollution index; S ave denotes the arithmetic mean of the single factor pollution index (S i ); S max denotes the maximum single pollution index. Considering that the integrated pollution index requires at least two indicators, and that TN and TP in lake sediments often share a common origin, their combination can reflect the overall local pollution level (Chen et al., 2020 ; Ebrahimi et al., 2022 ; Guo et al., 2024 ), this study employs TP and TN (unpublished) data for the calculation of the integrated pollution index. The standard values adopted were the historical average values for TN and TP in southern Chinese lake sediments (1000 mg/kg and 420 mg/kg, respectively). The standards and levels of the single factor pollution index and the Nemerow integrated pollution index were exhibited in Table 1 . Table 1 Standard and level of pollution index in sediments Level S TP F Type Ⅰ S TP <0.5 F<1.0 Clean Ⅱ 0.5 ≤ S TP ≤1.0 1.0 ≤ F ≤ 1.5 Lightly polluted Ⅲ 1.0<S TP ≤1.5 1.51.5 F>2.0 Heavy polluted Note: S TP and F denoted single factor pollution index and Nemerow integrated pollution index, respectively. 3. Results 3.1 Grain size characteristics of sediments in the lakes The median grain sizes of sediment profiles XH1, XH2, and XH3 in Xianghu Lake were 4.68 µm, 5.10 µm, and 5.26 µm, respectively (Supplementary Table 1 and Fig. 2 ). Clay accounted for the largest proportion in each profile, with average concentrations of 44.09%, 41.55% and 39.87%, respectively. Followed by fine silt, with average proportions of 27.53%, 27.72% and 28.23%, respectively, the concentrations of coarse silt were comparable to those of fine silt (Supplementary Table 1 and Fig. 2 ). In all three profiles, the fine silt content remained relatively stable with depth, while clay and coarse silt contents were stable from the surface to 12 cm and subsequently increased and decreased, respectively, with further depth. (Supplementary Table 1 and Fig. 2 ). The median grain size of sediments in the Qianhu Lake was slightly higher than that in the Xianghu Lake, with the values of QH1, QH2, and QH3 being 4.58 µm, 5.43 µm, and 6.40 µm, respectively. Clay accounted for the largest proportion in each profile, with average concentrations of 51.49%, 45.07%, and 39.25%, respectively, followed by fine silt. The coarse silt had the lowest concentrations, with the values of 19.49%, 28.23% and 33.28%, respectively (Supplementary Table 1 and Fig. 2 ). With increasing depth, the concentrations of the three grain size compositions in QH1 and clay and coarse silt in QH2 exhibited significant fluctuations, whereas those of the other composition and profile exhibited relative stability (Supplementary Table 1 and Fig. 2 ). The median grain size of sediments in the Aixihu Lake was similar to that of Qianhu Lake, with the values of AXH1, AXH2, and AXH3 being 4.67 µm, 4.97 µm, and 6.58 µm, respectively. Clay accounted for the highest proportion in all three profiles, with average concentrations of 43.15%, 41.28%, and 34.65%, respectively, followed by coarse silt, while fine silt represented the lowest fraction, with average concentrations of 24.94%, 22.78%, and 23.09%, respectively (Supplementary Table 1 and Fig. 2 ). In profiles AXH2 and AXH3, the proportions of the three grain size compositions remained relatively stable with depth. In AXH1, however, within the upper 10 cm, clay content exhibited an increasing–then–decreasing trend, whereas coarse silt showed the opposite pattern, while fine silt remained stable (Supplementary Table 1 and Fig. 2 ). The differences in grain size compositions among the three lakes reflect inconsistencies in sediment provenance and hydrodynamic conditions. 3.2 Characteristics of organic matter in sediment profiles The concentration of organic matter in Xianghu Lake sediments ranged from 3.76% to 15.01%. The values of XH1 ranged from 6.30% to 15.01%, with pronounced fluctuations occurring at depths of 6 cm and 20 cm (Supplementary Table 1 and Fig. 2 ). In XH2, organic matter concentration varied between 3.76% and 11.63%, with substantial fluctuations observed at depths of 8–14 cm. In XH3, organic matter concentration ranged from 4.87% to 10.84%, showing overall variability (Fig. 2 ). The organic matter concentration in Qianhu Lake sediments ranged from 4.58% to 12.41%, comparable to that in Xianghu Lake. In QH1, the values ranged from 4.58% to 9.83%, with the most pronounced variation occurring from the surface to 10 cm depth (Supplementary Table 1 and Fig. 2 ). In QH2, the organic matter concentration ranged from 6.40% to 12.41%, with marked variation between 10 and 20 cm depth (Fig. 2 ). In QH3, the value increased from the surface to 20 cm depth, followed by a decreasing trend in deeper layer (Fig. 2 ). The organic matter concentration in Aixihu Lake sediments ranged from 4.53% to 9.55%, lower than that in Xianghu and Qianhu lakes. In AXH1, organic matter concentration ranged from 6.11% to 9.55%, showing a decreasing trend with depth (Supplementary Table 1 and Fig. 2 ). In AXH2, value ranged from 5.17% to 9.50%, with a marked decrease at depths of 12–20 cm (Fig. 2 ). In AXH3, organic matter concentration ranged from 4.53% to 7.88%, with the high value occurring at 12 cm depth. At the same time, it remained relatively stable at other depths (Fig. 2 ). 3.3 Characteristics of phosphorus speciation in sediments The total phosphorus (TP) concentration of sediments in the Xianghu Lake ranged from 538.79 to 1481.57 mg/kg. In profiles XH1 and XH2, TP concentrations were 587.80–1481.57 mg/kg and 538.79–1170.85 mg/kg, respectively, both showing a decreasing trend with depth. TP concentrations in XH3 (586.49–1119.94 mg/kg) were lower than those in the other two profiles and exhibited no variation trend overall (Supplementary Table 1 and Fig. 3 ). Among the phosphorus speciation, Ca-P exhibited the highest concentrations, ranging from 164.35 to 508.70 mg/kg, without evident variation with depth (Supplementary Table 1 and Fig. 3 ). Followed by De-P, which ranged from 62.75 to 422.00 mg/kg, and showed two rounds of increasing-then-decreasing trends from the surface to 30 cm, with the maximum value observed at 18 cm (Supplementary Table 1 and Fig. 3 ). Fe-P concentrations ranged from 79.45 to 297.92 mg/kg, and increased from the surface to 12 cm before declining thereafter. Org-P (52.94–290.91 mg/kg) and Ex-P (35.00–396.19 mg/kg) had the lowest concentrations, and both decreased with depth (Supplementary Table 1 and Fig. 3 ). The TP concentration in Qianhu Lake sediments ranged from 923.06 to 1630.17 mg/kg. In profiles QH2 and QH3, TP concentrations were 934.42–1592.52 mg/kg and 926.66–1630.17 mg/kg, respectively, both showing a decreasing trend with depth. In contrast, TP concentrations in QH1 were lower, ranging from 923.06 to 1382.46 mg/kg, and exhibited no clear variation trend (Supplementary Table 1 and Fig. 3 ). Among the phosphorus speciation, Ca-P exhibited the highest concentrations (234.49–608.37 mg/kg), decreasing from the surface to 20 cm depth before increasing thereafter. De-P concentrations (32.40–452.90 mg/kg) ranked second, displaying pronounced fluctuations throughout the profile (Supplementary Table 1 and Fig. 3 ). Fe-P (106.01–312.04 mg/kg), Org-P (79.06–283.46 mg/kg) and Ex-P (87.32–267.76 mg/kg) exhibited comparable concentrations, with Org-P and Ex-P both decreasing with depth (Fig. 3 ). The TP concentration in Aixihu Lake sediments ranged from 616.58 to 1532.88 mg/kg. In AXH1, TP concentrations were 749.88–1090.04 mg/kg, and decreased from the surface to 8 cm depth (Supplementary Table 1 and Fig. 3 ). In AXH2, TP concentrations ranged from 616.58 to 1105.08 mg/kg, similar to those in AXH1, and decreased with depth. AXH3 showed the highest TP concentrations (864.84–1532.88 mg/kg), with a variation pattern similar to that of AXH2 (Supplementary Table 1 and Fig. 3 ). Among the phosphorus speciation, Ca-P exhibited the highest concentrations (251.45–610.85 mg/kg), followed by Fe-P (90.42–414.04 mg/kg), and they increased and decreased with depth, respectively. The concentration of De-P (63.79–275.86 mg/kg), Ex-P (61.69–299.71 mg/kg) and Org-P (45.67–220.42 mg/kg) were relatively low, and all of them decreased with depth (Supplementary Table 1 and Fig. 3 ). The differences in phosphorus speciation concentrations (p < 0.5, one-way ANOVA) and distributions among the three lakes highlight the distinct influences of grain size, organic matter and source inputs through regions. 4. Discussion 4.1 The effect of grain size and organic matter concentration on phosphorus speciation Previous studies have demonstrated that phosphorus speciation in sediments is primarily regulated by grain-size characteristics and organic matter concentrations (Li et al., 2018 ; Ebrahimi et al., 2022 ). In Xianghu Lake, Fe-P exhibited a positive correlation with clay (r = 0.51, p < 0.01) and a negative correlation with coarse silt (r = − 0.49, p < 0.01) (Fig. 4 a). The large specific surface area and dense structure of clay enhance its capacity to retain Fe-P. This mechanism was also observed in the sediments of Xingkai Lake and Taihu Lake (Omari et al., 2019 ; Wang et al., 2019 ; Zhao et al., 2021 ). Ca-P showed a positive correlation with organic matter (r = 0.41, p < 0.05) (Fig. 4 a). Previous research has suggested that Ca-P commonly co-precipitates with CaCO 3 , and the decomposition of organic matter promotes the release of Ca 2+ from CaCO 3 , thereby facilitating Ca-P formation (House et al., 2002; Guillemette et al., 2017 ). In contrast, Org-P exhibited a negative correlation with organic matter (r = − 0.45, p < 0.05) (Fig. 4 a), indicating that in areas of Xianghu Lake where organic matter decomposition is active, organic phosphorus may be transformed into soluble phosphorus or mineralized into inorganic phosphorus (Rahutomo et al., 2018 ). In Qianhu Lake, Ex-P showed no significant correlations with either grain size or organic matter (r 0.3, p < 0.05) (Fig. 4 b), suggesting potential interconversion among these fractions. Similar to Xianghu Lake, Ca-P in Qianhu Lake sediments displayed a positive correlation with organic matter (r = 0.37, p < 0.05) (Fig. 4 b), while Org-P showed a negative correlation with it (r = − 0.81, p < 0.05) (Fig. 4 b). In addition, organic matter was weakly positively correlated with TP, this is possibly because Ca-P accounts for a relatively high proportion of TP in Qianhu Lake sediments. In Aixihu Lake, Fe-P concentration showed a strong positive correlation with coarse silt (r = 0.67, p < 0.01) and a negative correlation with clay (r < -0.68, p < 0.01) (Fig. 4 c). This suggests that the clay fraction in Aixihu Lake is associated with hypoxic conditions, where reducing environments destabilize Fe-P, whereas coarse silt typically occurs under oxic conditions and provides larger surfaces for iron oxide attachment (Osafo et al., 2022 ; Sun et al., 2025 ). Moreover, clay was negatively correlated with TP (Fig. 4 c), likely because Fe-P accounts for a large proportion of TP in this lake. Ex-P also exhibited a strong positive correlation with De-P (r = 0.57, p < 0.01) (Fig. 4 c). Combined with the positive correlation between Ex-P and coarse silt, this suggested that coarse detrital phosphate minerals may adsorb Ex-P. 4.2 Identification of phosphorus sources in lake sediments 4.2.1 Phosphorus sources of sediments in Xianghu Lake The contribution of the F1 in the Xianghu Lake was 40.20% (Fig. 5 a). Fe-P contributed significantly to F1, with a rate of 28.24% (Fig. 5 a), and showed a strong correlation with clay content (Fig. 4 a). Typically, long-term flooding of paddy fields promotes the reduction of Fe³⁺ to Fe²⁺, which adsorbs phosphate to form Fe-P and binds with clay (Tang et al., 2024 ; Ishida et al., 2025 ). Although Ex-P showed no correlation with grain size or organic matter (Fig. 4 a), it accounted for as much as 54.97% of F1 (Fig. 5 a). Ex-P reflects the release of labile phosphorus from the dissolution of chemical fertilizers (Gao et al., 2023 ; Schott et al., 2023 ). Since the study area is located in the periphery of Nanchang, where agricultural land use is extensive and densely distributed (Fig. 1 ), agricultural input was identified as the dominant source for this component. The contribution of F2 was 27.81% (Fig. 5 a). TP and organic matter contributed 93.81% and 69.34% to F2, respectively (Fig. 5 a). Of them, the organic matter usually reflects inputs from agricultural sewage and livestock wastewater. It could also be seen that clay showed a relatively high contribution (59.55%) (Fig. 5 a), furtherly confirming the association with agricultural activities that require fine grained soils. Furthermore, Ca-P also contributed substantially to F2 (77.94%, Fig. 5 a). Since Ca-P is commonly associated with phosphate fertilizer production, fertilizer application and metallurgical and chemical industries (Sun et al., 2011 ; Jin et al., 2024 ), this suggested that F2 may be associated with both agricultural and industrial activities. The moderate correlation between Ca-P and organic matter (r = 0.41, p < 0.05, Fig. 4 a) furtherly indicated potential combined contributions from agricultural and industrial wastewater (Kozyrev et al., 2023 ). Thus, F2 could be characterized as a mixed pollution pattern primarily controlled by agricultural inputs, with additional influence from industrial activities. F3 had the contribution of 17.45% (Fig. 5 a). Among all the grain size fractions, clay exhibited the highest contribution to F3 (19.91%), followed by the coarse silt (17.87%), suggesting the deposition characteristics of sediments (Fig. 5 a), In addition, the Org-P and organic matter contributed 28.06% and 22.62% to F3, respectively (Fig. 5 a), while the contribution of TP was only 1.97%, indicating that agricultural pollution had little impact on this factor. Considering the high contributions of clay and coarse silt and their natural sedimentary characteristics, F3 was interpreted as natural transport and deposition processes of sediments, and the relatively high contributions of organic matter and Org-P may be attributed to their adsorption onto fine- and coarse-grained sediments (Kang et al., 2017 ). The contribution of F4 was 11.5% (Fig. 5 a). De-P contributed as much as 22.10% to F4 (Fig. 5 a). In the sediments of Xianghu Lake, De-P showed weak associations with other phosphorus speciation (Fig. 5 a). This phosphorus speciation is generally considered relatively stable and often linked to igneous and metamorphic rocks (Ruttenberg, 1992 ). It has also been widely used as a tracer of sediment sources (Acharya et al., 2016 ). Therefore, F4 was interpreted as the detrital phosphate minerals associated with sediment provenance. 4.2.2 Phosphorus sources of sediments in Qianhu Lake The contribution of the F1 in the Qianhu Lake was 35.72% (Fig. 5 b). TP contributed 91.62% to F1 (Fig. 5 b), indicating that phosphorus pollution was the core feature of this component. The high contributions of Ca-P (64.56%) and Ex-P (59.29%) further support this inference (Fig. 5 b). Ca-P is generally associated with fertilizer production and application (Sun et al., 2011 ; Jin et al., 2024 ), whereas Ex-P directly reflects the release of labile phosphorus from fertilizer dissolution (Gao et al., 2023 ; Schott et al., 2023 ). Furthermore, De-P contributed 36.36% to F1 (Fig. 5 b), representing the provenance of the sediments to which it was attached (Acharya et al., 2016 ), and possibly indicating the deposition processes of particulate phosphorus carried by agricultural runoff. Therefore, F1 likely represented phosphorus inputs primarily derived from agricultural activities such as irrigation. F2 had the contribution of 27.27% (Fig. 5 b). Coarse silt and clay contributed 94.34% and 96.84% to this factor, respectively (Fig. 5 b), reflecting the migration and deposition processes of the sediments (Zhao et al., 2020 ). As carriers of phosphorus speciation, sediments play an important role in facilitating the transport and cycling of phosphorus (Spohn, 2020 ; Sims et al., 2023 ). Therefore, F2 possibly reflected the migration of sediments. The contribution of F3 was 22.79% (Fig. 5 b). Organic matter and Org-P contributed 76.22% and 85.79% to this factor, respectively (Fig. 5 b). However, the clay and coarse silt had the low contributions of < 3%, which were different from the F3 in Xianghu Lake. Therefore, F3 mainly represented the coupled processes of organic matter input and dynamic transformation of organic phosphorus, which could also be seen from the negative correlation between organic matter and Org-P (r = − 0.81). The contribution of F4 was 14.22% (Fig. 5 b). De-P and Fe-P contributed 9.00% and 17.81% to F4, respectively (Fig. 5 b). Since Ex-P made only a little contribution to F4 and the correlation between Fe-P and Ex-P was weak, Fe-P in this component did not represent agricultural pollution, which was different from F1 of the Xianghu Lake. Previous studies have shown that Fe-P can also be associated with domestic sewage (Wu et al., 2017 ). Taking into account the substantial residential settlements adjacent to the study area. Therefore, F4 was interpreted as the combined input of domestic sewage and sediments through the surface runoff. 4.2.3 Phosphorus sources of sediments in Aixihu Lake The contribution of F1 was 46.58% in the Aixihu Lake sediments (Fig. 5 c). Fe-P and Org-P contributed 67.18% and 38.17% to F1, respectively. Given their positive correlation and the surrounding land-use types (Fig. 1 ), F1 was interpreted as pollution derived from irrigation wastewater in the study area. The contribution of F2 was 22.02% (Fig. 5 c). Fine silt, Ca-P and organic matter contributed 87.36%, 71.40% and 66.98% to this factor, respectively. Ca-P reflects agricultural activities such as fertilizer application, while organic matter reflects wastewater from livestock farming (Sun et al., 2011 ). Therefore, F2 was interpreted as representing pollution arising from fertilizer application and the breeding industry. Factor 3 had the contribution of 19.70% (Fig. 5 c). Ex-P and De-P contributed 40.11% and 27.92%, respectively. Previous studies have shown that De-P can release phosphate into lake water under weathering processes, and the released phosphate could be subsequently adsorbed by sediments to form Ex-P. The significant correlation coefficient between De-P and Ex-P (r = 0.57, Fig. 4 c) suggested potential transformation between these two fractions (Jiang et al., 2021 ; Poblete-Grant et al., 2022 ). In addition, fine silt made the highest contribution among the three grain-size fractions, suggesting that F3 represents the input of silt detrital phosphate minerals. Factor 4 had the contribution of 11.70% (Fig. 5 c). Clay contributed 17.98% to this component, which was higher than the other index (Fig. 5 c). As clay is typically produced by long-term weathering, F4 represented natural processes such as geological weathering and the input of terrigenous sediments into the lake. In summary, the primary sources of phosphorus pollution in Xianghu Lake, Qianhu Lake and Aixihu Lake were agricultural activities such as livestock breeding, irrigation and fertilizer application, followed by inputs from domestic sewage and industrial discharges. These lakes are located around Nanchang, where extensive farmlands and large residential areas are present. Phosphorus generated from agricultural practices (crop cultivation and livestock farming) entered the lakes mainly through surface runoff and irrigation return flow (Fig. 1 ) and constitutes the dominant non-point source pollution. It could be seen that there are no large-scale industrial lands around the lakes, and only a few enterprises contributed only limited point-source pollution (Fig. 1 ). Meanwhile, strict regulations on industrial wastewater discharge effectively reduced phosphorus transport. 4.3 Evaluation of lake pollution and management recommendations To evaluate the pollution status of the lakes, the single factor pollution index (S TP ) analysis was conducted on the profile sediments, while the Nemerow integrated pollution index (F) was applied to surface sediments, as they can reflect the recent pollution status of the lakes. Based on F values, Xianghu Lake, Qianhu Lake and Aixihu Lake were all classified as heavily polluted (Table 2 ), with Qianhu Lake showing the highest level (F ≥ 2.26), followed by Aixihu Lake (F ≥ 2.04) and Xianghu Lake (F ≥ 1.92) (Fig. 6 a and Table 2 ). According to the S TP index, the surface sediments of profiles XH2 and XH3 in the Xianghu Lake were moderately polluted (Fig. 6 a and Table 2 ), with S TP values consistently exceeding 1.0 within the 0–10 cm depth (Fig. 6 a and Table 2 ). Profile XH1 exhibited the most severe pollution, with the pollution peak concentrated at 8–12 cm (S TP >3.0) (Fig. 6 a and Table 2 ). In Qianhu Lake, the S TP values of the three profiles (2.20–3.88) indicated severe pollution (Fig. 6 b and Table 2 ), with QH1 and QH3 showing peak values (S TP >2.0) at 4–8 cm depth (Fig. 6 b and Table 2 ), and QH2 at 10–20 cm depth (Fig. 6 b and Table 2 ). In Aixihu Lake, profiles AXH1 and AXH3, which had heavy pollution, exhibited their highest S TP values at the surface and decreased with depth (Fig. 6 c and Table 2 ). At the same time, AXH2 showed moderate pollution at the surface and a heavy pollution peak at 5–10 cm depth (Fig. 6 c and Table 2 ). Table 2 The pollution indices of profile sediments in the urban lakes from Nanchang Sediment profile S TP (pollution grade) F (pollution grade) XH1 1.40 (moderate) ~ 3.53 (heavy) 2.91 (heavy) XH2 1.28 (moderate) ~ 2.79 (heavy) 1.92 (heavy) XH3 1.40 (moderate) ~ 2.67 (heavy) 2.46 (heavy) QH1 2.20 (heavy) ~ 3.29 (heavy) 2.64 (heavy) QH2 2.22 (heavy) ~ 3.79 (heavy) 2.75 (heavy) QH3 2.21 (heavy) ~ 3.88 (heavy) 2.26 (heavy) AXH1 1.79 (heavy) ~ 2.60 (heavy) 2.63 (heavy) AXH2 1.47 (heavy) ~ 2.63 (heavy) 2.33 (heavy) AXH3 2.06 (heavy) ~ 3.65 (heavy) 2.04 (heavy) Note: S TP and F denoted single factor pollution index and Nemerow integrated pollution index, respectively. In summary, the sediments of urban lakes in Nanchang generally suffer from heavy phosphorus pollution, underscoring the need for comprehensive and targeted mitigation strategies to alleviate current pollution levels and prevent further deterioration. Given that Xianghu Lake, Qianhu Lake and Aixihu Lake share similar land-use patterns in their surroundings, mitigation should include optimizing urban planning, strengthening the construction and maintenance of wastewater treatment facilities and improving farmland irrigation and drainage systems. 5. Conclusion This study investigated the characteristics, sources, and pollution level of phosphorus speciation in sediments from three typical urban lakes in Nanchang: Xianghu Lake, Qianhu Lake, and Aixihu Lake. The primary conclusions are as follows: 1) Sediments from Xianghu Lake, Qianhu Lake, and Aixihu Lake predominantly comprise clay (ranging from 34.65% to 51.49%), followed by coarse silt, with fine silt being the least abundant. Organic matter concentration in Xianghu Lake sediments ranged from 3.76% to 15.01%, similar to those in Qianhu Lake, whereas Aixihu Lake showed lower concentrations (4.53%–9.55%). The total phosphorus concentration in Xianghu Lake sediments ranged from 538.79 to 1481.57 mg/kg, which was lower than that in Qianhu Lake (923.06–1630.17 mg/kg) and Aixihu Lake sediments (616.58–1532.88 mg/kg). All three lakes exhibited the highest Ca-P content (> 160 mg/kg), followed by De-P and Fe-P, with Org-P and Ex-P being the lowest. Spatial heterogeneity in Concentrations of grain size, organic matter, and phosphorus speciation had vertical heterogeneity. 2) Statistical analysis revealed that sediment Fe-P exhibited a positive correlation with clay, reflecting the adsorption of Fe-P by clay. Concurrently, Ca-P and Org-P exhibited positive and negative correlations with organic matter, respectively, indicating that organic matter decomposition promotes the formation of calcium-bound phosphorus and mineralization of organic phosphorus. Based on the APCS-MLR, it could be indicated that the primary source of phosphorus pollution in Xianghu Lake, Qianhu Lake, and Aixihu Lake stemmed from agricultural activity such as aquaculture, irrigation, and fertilizer application, and the domestic sewage and industrial discharges were a supplement. This pattern corresponded with the land use types around the study area. 3) The Nemerow integrated pollution index confirmed that Xianghu Lake, Qianhu Lake, and Aixihu Lake all exhibited severe phosphorus pollution with F ≥ 1.92 in the surface. The single factor pollution index indicated moderate to severe phosphorus contamination in the profiles of the lakes. Therefore, it is necessary to improve farmland irrigation, fertilization, and drainage patterns, optimize the land planning and reduce the discharge of industrial, agricultural and domestic sewage. This study has promoted the research on lake environment governance and biogeochemical cycles. However, there are still some shortcomings. For example, mineral composition, temperature and biological disturbances can affect the phosphorus speciation, and future studies will take them into consideration. In addition, phosphate and oxygen isotopes, as stable environmental indices, can trace the source of phosphorus efficiently, and will be employed in the next steps to provide a more reliable basis for sediment pollution prevention in the urban lakes. Declarations Author Contributions: Conceptualization: Tianning Li, Fangwen Zheng; Data curation: Tianning Li, Linsen Tang; Formal analysis: Linsen Tang, Fangwen Zheng; Funding acquisition: Fangwen Zheng, Huiyang Qiu; Laboratory analysis: Ping Liu, Jinfu Liu; Methodology: Tianning Li, Fangwen Zheng, Ping Liu, Jinfu Liu; Writing: Fangwen Zheng, Ping Liu. All authors have read and agreed to the published version of the manuscript. Funding: This study was financially supported by the China Railway Group Limited Technology Research and Development Plan (No. 2022-Key Project-08), Key Innovation Training Project at the Provincial Level of Jiangxi Province (202411319001) and Nanjing Institute of Environmental Sciences specific fundings for basic scientific research (GYZX240409). Institutional Review Board Statement: The authors confirm that the data supporting the findings of this study are available within the article. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7828473","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":544193767,"identity":"93b12941-77f0-4cd2-8e70-4104275ba595","order_by":0,"name":"Tianning Li","email":"","orcid":"","institution":"Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment","correspondingAuthor":false,"prefix":"","firstName":"Tianning","middleName":"","lastName":"Li","suffix":""},{"id":544193768,"identity":"06498ef4-01a9-43b0-9921-107c38c106c9","order_by":1,"name":"Linsen Tang","email":"","orcid":"","institution":"China Railway 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Environment","correspondingAuthor":true,"prefix":"","firstName":"Huiyang","middleName":"","lastName":"Qiu","suffix":""},{"id":544193770,"identity":"c9cca118-2215-4fd1-aad8-ae80a25b61a9","order_by":3,"name":"Fangwen Zheng","email":"","orcid":"","institution":"Jiangxi University of Water Resources and Electric Power","correspondingAuthor":false,"prefix":"","firstName":"Fangwen","middleName":"","lastName":"Zheng","suffix":""},{"id":544193771,"identity":"776f50e1-699d-48b9-a06f-6f81035a8cca","order_by":4,"name":"Ping Liu","email":"","orcid":"","institution":"Jiangxi University of Water Resources and Electric Power","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Liu","suffix":""},{"id":544193772,"identity":"4a24449b-0733-47c2-a2da-5e10ae7ff7a2","order_by":5,"name":"Jinfu Liu","email":"","orcid":"","institution":"Jiangxi University of Water Resources and Electric Power","correspondingAuthor":false,"prefix":"","firstName":"Jinfu","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-10-10 15:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7828473/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7828473/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96453140,"identity":"3d7db362-4e14-4182-99a1-ff806a0e327f","added_by":"auto","created_at":"2025-11-21 09:58:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1743470,"visible":true,"origin":"","legend":"","description":"","filename":"Paper.docx","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/4cb4289a70af4b570a222081.docx"},{"id":96387870,"identity":"8b1503f3-9e7b-4af9-a28a-6e9072fe0d47","added_by":"auto","created_at":"2025-11-20 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13:41:04","extension":"html","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":161082,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/beb3f39fe02088d45521d0bc.html"},{"id":96453150,"identity":"3ab09ce0-16a5-4202-8031-5cef922d7e88","added_by":"auto","created_at":"2025-11-21 09:58:32","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":377688,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMap of the research area and sampling sites (a and b show the geographical location of Nanchang; c, d, and e indicate sediment sampling sites of Qianhu Lake, Xianghu Lake and Aixihu Lake, respectively; f depicts land use type proportions for Nanchang City and the lakes)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/1c3cd5b3c1be415a47ffecfe.jpeg"},{"id":96387869,"identity":"730769c6-a6bb-47e1-b2db-2039562b80c3","added_by":"auto","created_at":"2025-11-20 13:41:03","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":530791,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics of grain size and organic matter concentrations in sediment profiles with depth at Xianghu Lake (XH), Qianhu Lake (QH), and Aixihu Lake (AX) from Nanchang\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/d238efc58362c47c330bdd98.jpeg"},{"id":96387873,"identity":"04c4fea5-3b66-44e2-b99f-1738e801e816","added_by":"auto","created_at":"2025-11-20 13:41:03","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":605654,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics of phosphorus speciation concentrations in sediment profiles with depth at Xianghu Lake (XH), Qianhu Lake (QH), and Aixihu Lake (AX) from Nanchang\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/73bdec40809c7d724a768fc3.jpeg"},{"id":96387875,"identity":"4e860ae7-9409-48cb-b079-df4adc1686bf","added_by":"auto","created_at":"2025-11-20 13:41:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":154961,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe correlationsbetween phosphorus speciation, grain size composition, and organic matter of sediments\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/ee7b56b91a1fb0cdbb4419fc.png"},{"id":96453322,"identity":"dded893f-42c1-4356-8510-078790f2679a","added_by":"auto","created_at":"2025-11-21 09:59:14","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":432409,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eContributions of main factors to the lakes (pie diagram) and of phosphorus speciation to the factors (stacked bar diagram)based on the APCS-MLR model\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/2e169c87753155b987fe0799.jpeg"},{"id":96387876,"identity":"90d1ca82-be60-4024-ac1a-17836fcb26ed","added_by":"auto","created_at":"2025-11-20 13:41:03","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":121918,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSingle factor pollution indices of profile sediments in the urban lakes from Nanchang\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/4570c28617c73c1319119537.jpeg"},{"id":96603094,"identity":"f576d85a-fda9-452f-8db1-d80db697ea33","added_by":"auto","created_at":"2025-11-24 09:06:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3487273,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/d86ff7d5-26ba-4882-96eb-eff2a1151348.pdf"},{"id":96453312,"identity":"3eeb6377-ba75-460c-ade0-bd2b6a9d359a","added_by":"auto","created_at":"2025-11-21 09:59:12","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":25969,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7828473/v1/e5cf24c75eb067e4cbd9f916.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chemical speciation, source apportionment, and pollution assessment of phosphorus in sediments from typical urban lakes in Southern China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLakes, as vital components of urban ecosystems, play an irreplaceable ecological role in regulating regional climate, sustaining biodiversity, and safeguarding water resource security (Radosavljevic et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Currently, the combined effects of global climate change and intensive human activities have significantly accelerated lake eutrophication processes. Excessive phosphorus inputs and endogenous release are recognized as core factors of water eutrophication (Jovana et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The dynamic behavior of phosphorus at the sediment-water interface directly influences lake nutrient cycling and algal growth mechanisms. Consequently, the identification of its speciation, sources and pollution assessment has emerged as a frontier topic within environmental science (Wu et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSediments serve as significant reservoirs for phosphorus, with their compositional characteristics directly governing phosphorus bioavailability. Components such as clay minerals, iron oxides, and organic matter dominate phosphorus redistribution through processes including surface adsorption, chemical bonding, and biological effects (Paerl et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It is generally recognized that phosphorus in sediments exists in multiple forms, each exhibiting distinct responses to environmental factors. Among these, iron-bound phosphorus (Fe-P) and organic phosphorus (Org-P) constitute the primary active components for endogenous phosphorus release, whereas calcium-bound phosphorus (Ca-P) and detrital phosphorus (De-P) exhibit greater stability (Malecki et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The grain size of sediments influences the adsorption capacity of phosphorus by altering specific surface area, with fine-grained sediments typically containing higher Fe-P concentrations than coarse-grained sediments (Wang et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, the effect of the organic matter furtherly changes the spatiotemporal heterogeneity of phosphorus flux (Ye et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The diversity of speciation renders traditional total phosphorus (TP) indicators inadequate for accurately analyzing the characteristics of phosphorus in sediments, therefore, it is necessary to develop multi-speciation analysis techniques.\u003c/p\u003e\u003cp\u003eCurrently, numerous studies have extensively investigated the influencing factors and sources of phosphorus speciation in sediments from lakes, estuaries, and marine regions. Zhao et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) examined the mechanisms governing phosphorus speciation transformation in the sediment of Ulansuhai Nur and explored how pH alters the distribution of phosphorus speciation within sediments. Through examining phosphorus speciation in sediments along the Ton River, Kozyrev et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that Fe-P and Org-P concentrations increased with decreasing sediment grain size. Conversely, Ca-P exhibits a relatively uniform distribution across all grain sizes. Guo et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) investigated sources of phosphorus in sediments from the Beibu Gulf, China, and identified that terrestrial organic matter was the primary contributor.\u003c/p\u003e\u003cp\u003eCompared with the regions above, urban lakes\u0026mdash;owing to their semi-enclosed hydrological characteristics, extensive transportation networks, and intensive anthropogenic disturbances\u0026mdash;exhibit unique phosphorus cycling patterns (Zhao et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Exogenous inputs such as domestic sewage, industrial effluents, and agricultural wastewater result in phosphorus loads in urban sediments that are significantly higher than those in natural lakes (Song et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Putt et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Existing research on the geochemistry behavior of phosphorus has primarily focused on natural lakes, while comparatively limited attention has been directed toward urban lakes (Zhao et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kozyrev et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, the profile sediments from three representative lakes\u0026mdash;Qianhu Lake, Xianghu Lake, and Aixihu Lake, in Nanchang, a typical lakeshore city in the Southern China, were collected. The distributions of grain size and phosphorus speciation in sediments were revealed, the sources\u0026rsquo; contributions of sedimentary phosphorus were identified through multivariate statistical approaches, and the phosphorus pollution indices were estimated in these lakes. The findings provide theoretical and technical support for the prevention and control of eutrophication in urban lakes, they also offer a scientific basis for the protection and management of water resources and aquatic ecosystems in urban environments.\u003c/p\u003e"},{"header":"2. Study area and methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study area\u003c/h2\u003e\n \u003cp\u003eNanchang is the capital of Jiangxi Province in the Southeastern China (115.45\u0026deg;\u0026ndash;116.58\u0026deg;E, 28.17\u0026deg;\u0026ndash;29.18\u0026deg;N, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea and b) and situated in the middle and lower reaches of the Yangtze River. It spans approximately 121 kilometers from north to south and 108 kilometers from east to west. Nanchang is adjacent to Poyang Lake\u0026mdash;the largest freshwater lake in China\u0026mdash;while its central area is traversed by the Gan and Fu rivers (Jia et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb). Xianghu Lake, Qianhu Lake and Aixihu Lake are the three major representative lakes in Nanchang and serve as important habitats for migratory birds in the city (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec, d and e). Xianghu Lake, located in the southwestern urban area, covers an area of 7.81 km\u0026sup2; (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ed). Aixihu Lake, situated in the northeast, has an area of approximately 1.67 km\u0026sup2; (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ee). Both Xianghu Lake and Aixihu Lake are primarily fed by the Fu River and surrounding urban water systems (Shao et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zheng et al., 2025). Qianhu Lake, located in the western part of the city to the west of the Gan River, covers an area of about 1.66 km\u0026sup2; and mainly receives water from the tributaries of the Gan River (Zeng et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec).\u003c/p\u003e\n \u003cp\u003eNanchang experiences a subtropical humid monsoon climate, characterized by long summers and winters and short springs and autumns. The annual average temperature and sunshine duration range from 17.1\u0026deg;C to 17.8\u0026deg;C and 1723 to 1820 hours, respectively. Prevailing winds are northerly in winter and southerly in summer (Wu et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The long-term mean annual precipitation of the city is 1645 mm, with the rainy season (April to July) accounting for more than 55% of the total, while the dry season (October to January) contributes less than 15% (Sun et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Methodology\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 Field sampling\u003c/h2\u003e\n \u003cp\u003eIn November 2024, systematic sampling was conducted at Xianghu Lake, Qianhu Lake and Aixihu Lake (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). For each lake, three representative sites were evenly distributed to cover different functional zones, including the inflow, central area and outflow. Sediment cores were collected using a gravity corer (HD-TRC3) and the samples were collected at 2 cm intervals. All samples were placed in clean, PVC sealed bags, labeled with geographic coordinates and layer identification numbers, and immediately transferred to a cooler for preservation prior to laboratory analysis.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Sample pretreatment and analysis\u003c/h2\u003e\n \u003cp\u003eFor each site, a 0.5 g sediment sample was placed in 900 mL of ultrapure water, dispersed by ultrasonic, and analyzed for grain size using a laser size analyzer (HELOS-SUCELLi, SYMPATEC GmbH, Germany), with a measurement error of less than 3% (Sehgal et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Following the Udden\u0026ndash;Wentworth classification system, grain size fractions were categorized as clay (\u0026lt;\u0026thinsp;4 \u0026micro;m), fine silt (4\u0026ndash;20 \u0026micro;m), and coarse silt (20\u0026ndash;63 \u0026micro;m). Organic matter content was determined using the loss-on-ignition method at 550\u0026deg;C, as described by Nakhli et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003ePhosphorus fractions were sequentially extracted and classified as exchangeable phosphorus (Ex-P), iron-bound phosphorus (Fe-P), calcium-bound phosphorus (Ca-P), detrital phosphorus (De-P), and organic phosphorus (Org-P). After drying and removing impurities, sufficient amounts of sediment were ground to \u0026lt;\u0026thinsp;74 \u0026micro;m. Ex-P was extracted with 1 M MgCl\u003csub\u003e2\u003c/sub\u003e for two hours (pH 8, 25\u0026deg;C); Fe-P with CDB (0.3 M sodium citrate, 0.14 M sodium dithionite, 1.0 M sodium bicarbonate) for six h (pH 7.6, 25\u0026deg;C); Ca-P with 1 M acetate buffer for six hours (pH 4, 25\u0026deg;C); De-P with 1 M HCl solution for 16 h at 25\u0026deg;C; and Org-P with 1 M HCl solution for 16 hours at 25\u0026deg;C after the residue was heated to ash at 550\u0026deg;C for two hours (Saha et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Following each extraction step, solid\u0026ndash;liquid separation was performed by centrifugation at 5000 r/min. The supernatant liquid was analyzed for phosphorus concentrations based on an AA3 continuous flow analyzer (SEAL Analytical, UK), with an analytical error of less than 5% (Capasso et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Inorganic phosphorus (IP) was calculated as the sum of Ex-P, Fe-P, Ca-P, and De-P, while total phosphorus (TP) was defined as the sum of IP and Org-P.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.3 Data processing\u003c/h2\u003e\n \u003cp\u003eThe sampling site location map was produced by ArcGIS 10.1 (Environmental Systems Research Institute, Inc., USA), while statistical graphics were generated by Origin 2024 (OriginLab Corporation, USA). One-way ANOVA was employed to evaluate the discrepancies of phosphorus concentrations between the different lakes. The one-way ANOVA analysis, the correlation analysis (CA), the principal component analysis (PCA), and the APCS-MLR (introduced in below) were based on SPSS (version 23.0; International Business Machines Corporation, USA).\u003c/p\u003e\n \u003cp\u003eThe APCS-MLR model represents a conventional receptor modelling approach for quantitative source apportionment in datasets featuring multiple independent variables and a single dependent variable. It integrates the Multiple Linear Regression (MLR) model with Absolute Principal Component Scores (APCS) (Varol et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). It is noteworthy that this model serves solely to evaluate the goodness-of-fit of regression models and cannot account for uncertainties in contribution rate calculations (Wu et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, the contribution rates for each principal component in the APCS-MLR model computations do not incorporate uncertainty.\u003c/p\u003e\n \u003cp\u003eThe single factor pollution index (Formula 1) and Nemerow integrated pollution index (Formula 2) are frequently employed to assess sediment contamination. The single factor pollution index is advantageous for its simplicity and ease of application, making it suitable for preliminary environmental assessments. The Nemerow integrated pollution index considers the combined impact of multiple factors on environmental quality, rendering it appropriate for complex environments and multi-pollutant scenarios (Maskooni et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Behairy et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., 2023). Combining both approaches allows for a balance between pollution targeting and systemic comprehensiveness. The present study employed both methods to calculate the pollution evaluation index for sediments. The formulas were as follows:\u003c/p\u003e\n \u003cp\u003eS\u003csub\u003ei\u003c/sub\u003e = C\u003csub\u003ei\u003c/sub\u003e/C\u003csub\u003es, i\u003c/sub\u003e (1)\u003c/p\u003e\n \u003cp\u003eF = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sqrt{{\\text{(}{\\text{S}}_{\\text{ave}}}^{\\text{2}}\\text{+}{{\\text{S}}_{\\text{max}}}^{\\text{2}})/\\text{2}}\\)\u003c/span\u003e\u003c/span\u003e (2)\u003c/p\u003e\n \u003cp\u003eS\u003csub\u003ei\u003c/sub\u003e denotes the single factor pollution index for sample; S\u003csub\u003ei\u003c/sub\u003e \u0026gt;1 indicate that the index exceeds the evaluation standard value; C\u003csub\u003ei\u003c/sub\u003e represents the measured value of the sample; C\u003csub\u003es, i\u003c/sub\u003e denotes the standard value for the factor; F represents the integrated pollution index; S\u003csub\u003eave\u003c/sub\u003e denotes the arithmetic mean of the single factor pollution index (S\u003csub\u003ei\u003c/sub\u003e); S\u003csub\u003emax\u003c/sub\u003e denotes the maximum single pollution index. Considering that the integrated pollution index requires at least two indicators, and that TN and TP in lake sediments often share a common origin, their combination can reflect the overall local pollution level (Chen et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ebrahimi et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Guo et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), this study employs TP and TN (unpublished) data for the calculation of the integrated pollution index. The standard values adopted were the historical average values for TN and TP in southern Chinese lake sediments (1000 mg/kg and 420 mg/kg, respectively). The standards and levels of the single factor pollution index and the Nemerow integrated pollution index were exhibited in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eStandard and level of pollution index in sediments\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS\u003csub\u003eTP\u003c/sub\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003csub\u003eTP\u003c/sub\u003e\u0026lt;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026lt;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClean\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026le;\u0026thinsp;S\u003csub\u003eTP\u003c/sub\u003e\u0026le;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u0026thinsp;\u0026le;\u0026thinsp;F\u0026thinsp;\u0026le;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLightly polluted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u0026lt;S\u003csub\u003eTP\u003c/sub\u003e\u0026le;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5\u0026lt;F\u0026thinsp;\u0026le;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerately polluted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003csub\u003eTP\u003c/sub\u003e\u0026gt;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026gt;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeavy polluted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNote: S\u003csub\u003eTP\u003c/sub\u003e and F denoted single factor pollution index and Nemerow integrated pollution index, respectively.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Grain size characteristics of sediments in the lakes\u003c/h2\u003e\u003cp\u003eThe median grain sizes of sediment profiles XH1, XH2, and XH3 in Xianghu Lake were 4.68 \u0026micro;m, 5.10 \u0026micro;m, and 5.26 \u0026micro;m, respectively (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Clay accounted for the largest proportion in each profile, with average concentrations of 44.09%, 41.55% and 39.87%, respectively. Followed by fine silt, with average proportions of 27.53%, 27.72% and 28.23%, respectively, the concentrations of coarse silt were comparable to those of fine silt (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In all three profiles, the fine silt content remained relatively stable with depth, while clay and coarse silt contents were stable from the surface to 12 cm and subsequently increased and decreased, respectively, with further depth. (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe median grain size of sediments in the Qianhu Lake was slightly higher than that in the Xianghu Lake, with the values of QH1, QH2, and QH3 being 4.58 \u0026micro;m, 5.43 \u0026micro;m, and 6.40 \u0026micro;m, respectively. Clay accounted for the largest proportion in each profile, with average concentrations of 51.49%, 45.07%, and 39.25%, respectively, followed by fine silt. The coarse silt had the lowest concentrations, with the values of 19.49%, 28.23% and 33.28%, respectively (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). With increasing depth, the concentrations of the three grain size compositions in QH1 and clay and coarse silt in QH2 exhibited significant fluctuations, whereas those of the other composition and profile exhibited relative stability (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe median grain size of sediments in the Aixihu Lake was similar to that of Qianhu Lake, with the values of AXH1, AXH2, and AXH3 being 4.67 \u0026micro;m, 4.97 \u0026micro;m, and 6.58 \u0026micro;m, respectively. Clay accounted for the highest proportion in all three profiles, with average concentrations of 43.15%, 41.28%, and 34.65%, respectively, followed by coarse silt, while fine silt represented the lowest fraction, with average concentrations of 24.94%, 22.78%, and 23.09%, respectively (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In profiles AXH2 and AXH3, the proportions of the three grain size compositions remained relatively stable with depth. In AXH1, however, within the upper 10 cm, clay content exhibited an increasing\u0026ndash;then\u0026ndash;decreasing trend, whereas coarse silt showed the opposite pattern, while fine silt remained stable (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The differences in grain size compositions among the three lakes reflect inconsistencies in sediment provenance and hydrodynamic conditions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Characteristics of organic matter in sediment profiles\u003c/h2\u003e\u003cp\u003eThe concentration of organic matter in Xianghu Lake sediments ranged from 3.76% to 15.01%. The values of XH1 ranged from 6.30% to 15.01%, with pronounced fluctuations occurring at depths of 6 cm and 20 cm (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In XH2, organic matter concentration varied between 3.76% and 11.63%, with substantial fluctuations observed at depths of 8\u0026ndash;14 cm. In XH3, organic matter concentration ranged from 4.87% to 10.84%, showing overall variability (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe organic matter concentration in Qianhu Lake sediments ranged from 4.58% to 12.41%, comparable to that in Xianghu Lake. In QH1, the values ranged from 4.58% to 9.83%, with the most pronounced variation occurring from the surface to 10 cm depth (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In QH2, the organic matter concentration ranged from 6.40% to 12.41%, with marked variation between 10 and 20 cm depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In QH3, the value increased from the surface to 20 cm depth, followed by a decreasing trend in deeper layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe organic matter concentration in Aixihu Lake sediments ranged from 4.53% to 9.55%, lower than that in Xianghu and Qianhu lakes. In AXH1, organic matter concentration ranged from 6.11% to 9.55%, showing a decreasing trend with depth (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In AXH2, value ranged from 5.17% to 9.50%, with a marked decrease at depths of 12\u0026ndash;20 cm (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In AXH3, organic matter concentration ranged from 4.53% to 7.88%, with the high value occurring at 12 cm depth. At the same time, it remained relatively stable at other depths (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Characteristics of phosphorus speciation in sediments\u003c/h2\u003e\u003cp\u003eThe total phosphorus (TP) concentration of sediments in the Xianghu Lake ranged from 538.79 to 1481.57 mg/kg. In profiles XH1 and XH2, TP concentrations were 587.80\u0026ndash;1481.57 mg/kg and 538.79\u0026ndash;1170.85 mg/kg, respectively, both showing a decreasing trend with depth. TP concentrations in XH3 (586.49\u0026ndash;1119.94 mg/kg) were lower than those in the other two profiles and exhibited no variation trend overall (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the phosphorus speciation, Ca-P exhibited the highest concentrations, ranging from 164.35 to 508.70 mg/kg, without evident variation with depth (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Followed by De-P, which ranged from 62.75 to 422.00 mg/kg, and showed two rounds of increasing-then-decreasing trends from the surface to 30 cm, with the maximum value observed at 18 cm (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Fe-P concentrations ranged from 79.45 to 297.92 mg/kg, and increased from the surface to 12 cm before declining thereafter. Org-P (52.94\u0026ndash;290.91 mg/kg) and Ex-P (35.00\u0026ndash;396.19 mg/kg) had the lowest concentrations, and both decreased with depth (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe TP concentration in Qianhu Lake sediments ranged from 923.06 to 1630.17 mg/kg. In profiles QH2 and QH3, TP concentrations were 934.42\u0026ndash;1592.52 mg/kg and 926.66\u0026ndash;1630.17 mg/kg, respectively, both showing a decreasing trend with depth. In contrast, TP concentrations in QH1 were lower, ranging from 923.06 to 1382.46 mg/kg, and exhibited no clear variation trend (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the phosphorus speciation, Ca-P exhibited the highest concentrations (234.49\u0026ndash;608.37 mg/kg), decreasing from the surface to 20 cm depth before increasing thereafter. De-P concentrations (32.40\u0026ndash;452.90 mg/kg) ranked second, displaying pronounced fluctuations throughout the profile (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Fe-P (106.01\u0026ndash;312.04 mg/kg), Org-P (79.06\u0026ndash;283.46 mg/kg) and Ex-P (87.32\u0026ndash;267.76 mg/kg) exhibited comparable concentrations, with Org-P and Ex-P both decreasing with depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe TP concentration in Aixihu Lake sediments ranged from 616.58 to 1532.88 mg/kg. In AXH1, TP concentrations were 749.88\u0026ndash;1090.04 mg/kg, and decreased from the surface to 8 cm depth (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In AXH2, TP concentrations ranged from 616.58 to 1105.08 mg/kg, similar to those in AXH1, and decreased with depth. AXH3 showed the highest TP concentrations (864.84\u0026ndash;1532.88 mg/kg), with a variation pattern similar to that of AXH2 (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the phosphorus speciation, Ca-P exhibited the highest concentrations (251.45\u0026ndash;610.85 mg/kg), followed by Fe-P (90.42\u0026ndash;414.04 mg/kg), and they increased and decreased with depth, respectively. The concentration of De-P (63.79\u0026ndash;275.86 mg/kg), Ex-P (61.69\u0026ndash;299.71 mg/kg) and Org-P (45.67\u0026ndash;220.42 mg/kg) were relatively low, and all of them decreased with depth (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe differences in phosphorus speciation concentrations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.5, one-way ANOVA) and distributions among the three lakes highlight the distinct influences of grain size, organic matter and source inputs through regions.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.1 The effect of grain size and organic matter concentration on phosphorus speciation\u003c/h2\u003e\u003cp\u003ePrevious studies have demonstrated that phosphorus speciation in sediments is primarily regulated by grain-size characteristics and organic matter concentrations (Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ebrahimi et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Xianghu Lake, Fe-P exhibited a positive correlation with clay (r\u0026thinsp;=\u0026thinsp;0.51, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and a negative correlation with coarse silt (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The large specific surface area and dense structure of clay enhance its capacity to retain Fe-P. This mechanism was also observed in the sediments of Xingkai Lake and Taihu Lake (Omari et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhao et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Ca-P showed a positive correlation with organic matter (r\u0026thinsp;=\u0026thinsp;0.41, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Previous research has suggested that Ca-P commonly co-precipitates with CaCO\u003csub\u003e3\u003c/sub\u003e, and the decomposition of organic matter promotes the release of Ca\u003csup\u003e2+\u003c/sup\u003e from CaCO\u003csub\u003e3\u003c/sub\u003e, thereby facilitating Ca-P formation (House et al., 2002; Guillemette et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In contrast, Org-P exhibited a negative correlation with organic matter (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.45, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), indicating that in areas of Xianghu Lake where organic matter decomposition is active, organic phosphorus may be transformed into soluble phosphorus or mineralized into inorganic phosphorus (Rahutomo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Qianhu Lake, Ex-P showed no significant correlations with either grain size or organic matter (r\u0026thinsp;\u0026lt;\u0026thinsp;0.20) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). However, positive correlations were observed among Ex-P, Ca-P and De-P (r\u0026thinsp;\u0026gt;\u0026thinsp;0.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), suggesting potential interconversion among these fractions. Similar to Xianghu Lake, Ca-P in Qianhu Lake sediments displayed a positive correlation with organic matter (r\u0026thinsp;=\u0026thinsp;0.37, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), while Org-P showed a negative correlation with it (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). In addition, organic matter was weakly positively correlated with TP, this is possibly because Ca-P accounts for a relatively high proportion of TP in Qianhu Lake sediments.\u003c/p\u003e\u003cp\u003eIn Aixihu Lake, Fe-P concentration showed a strong positive correlation with coarse silt (r\u0026thinsp;=\u0026thinsp;0.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and a negative correlation with clay (r \u0026lt; -0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). This suggests that the clay fraction in Aixihu Lake is associated with hypoxic conditions, where reducing environments destabilize Fe-P, whereas coarse silt typically occurs under oxic conditions and provides larger surfaces for iron oxide attachment (Osafo et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sun et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Moreover, clay was negatively correlated with TP (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec), likely because Fe-P accounts for a large proportion of TP in this lake. Ex-P also exhibited a strong positive correlation with De-P (r\u0026thinsp;=\u0026thinsp;0.57, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Combined with the positive correlation between Ex-P and coarse silt, this suggested that coarse detrital phosphate minerals may adsorb Ex-P.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Identification of phosphorus sources in lake sediments\u003c/h2\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e4.2.1 Phosphorus sources of sediments in Xianghu Lake\u003c/h2\u003e\u003cp\u003eThe contribution of the F1 in the Xianghu Lake was 40.20% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Fe-P contributed significantly to F1, with a rate of 28.24% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), and showed a strong correlation with clay content (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Typically, long-term flooding of paddy fields promotes the reduction of Fe\u0026sup3;⁺ to Fe\u0026sup2;⁺, which adsorbs phosphate to form Fe-P and binds with clay (Tang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ishida et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Although Ex-P showed no correlation with grain size or organic matter (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), it accounted for as much as 54.97% of F1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Ex-P reflects the release of labile phosphorus from the dissolution of chemical fertilizers (Gao et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Schott et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Since the study area is located in the periphery of Nanchang, where agricultural land use is extensive and densely distributed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), agricultural input was identified as the dominant source for this component.\u003c/p\u003e\u003cp\u003eThe contribution of F2 was 27.81% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). TP and organic matter contributed 93.81% and 69.34% to F2, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Of them, the organic matter usually reflects inputs from agricultural sewage and livestock wastewater. It could also be seen that clay showed a relatively high contribution (59.55%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), furtherly confirming the association with agricultural activities that require fine grained soils. Furthermore, Ca-P also contributed substantially to F2 (77.94%, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Since Ca-P is commonly associated with phosphate fertilizer production, fertilizer application and metallurgical and chemical industries (Sun et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), this suggested that F2 may be associated with both agricultural and industrial activities. The moderate correlation between Ca-P and organic matter (r\u0026thinsp;=\u0026thinsp;0.41, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) furtherly indicated potential combined contributions from agricultural and industrial wastewater (Kozyrev et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Thus, F2 could be characterized as a mixed pollution pattern primarily controlled by agricultural inputs, with additional influence from industrial activities.\u003c/p\u003e\u003cp\u003eF3 had the contribution of 17.45% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Among all the grain size fractions, clay exhibited the highest contribution to F3 (19.91%), followed by the coarse silt (17.87%), suggesting the deposition characteristics of sediments (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), In addition, the Org-P and organic matter contributed 28.06% and 22.62% to F3, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), while the contribution of TP was only 1.97%, indicating that agricultural pollution had little impact on this factor. Considering the high contributions of clay and coarse silt and their natural sedimentary characteristics, F3 was interpreted as natural transport and deposition processes of sediments, and the relatively high contributions of organic matter and Org-P may be attributed to their adsorption onto fine- and coarse-grained sediments (Kang et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe contribution of F4 was 11.5% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). De-P contributed as much as 22.10% to F4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). In the sediments of Xianghu Lake, De-P showed weak associations with other phosphorus speciation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). This phosphorus speciation is generally considered relatively stable and often linked to igneous and metamorphic rocks (Ruttenberg, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). It has also been widely used as a tracer of sediment sources (Acharya et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, F4 was interpreted as the detrital phosphate minerals associated with sediment provenance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e4.2.2 Phosphorus sources of sediments in Qianhu Lake\u003c/h2\u003e\u003cp\u003eThe contribution of the F1 in the Qianhu Lake was 35.72% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). TP contributed 91.62% to F1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), indicating that phosphorus pollution was the core feature of this component. The high contributions of Ca-P (64.56%) and Ex-P (59.29%) further support this inference (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Ca-P is generally associated with fertilizer production and application (Sun et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), whereas Ex-P directly reflects the release of labile phosphorus from fertilizer dissolution (Gao et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Schott et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, De-P contributed 36.36% to F1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), representing the provenance of the sediments to which it was attached (Acharya et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and possibly indicating the deposition processes of particulate phosphorus carried by agricultural runoff. Therefore, F1 likely represented phosphorus inputs primarily derived from agricultural activities such as irrigation.\u003c/p\u003e\u003cp\u003eF2 had the contribution of 27.27% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Coarse silt and clay contributed 94.34% and 96.84% to this factor, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), reflecting the migration and deposition processes of the sediments (Zhao et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As carriers of phosphorus speciation, sediments play an important role in facilitating the transport and cycling of phosphorus (Spohn, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sims et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, F2 possibly reflected the migration of sediments.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe contribution of F3 was 22.79% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Organic matter and Org-P contributed 76.22% and 85.79% to this factor, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). However, the clay and coarse silt had the low contributions of \u0026lt;\u0026thinsp;3%, which were different from the F3 in Xianghu Lake. Therefore, F3 mainly represented the coupled processes of organic matter input and dynamic transformation of organic phosphorus, which could also be seen from the negative correlation between organic matter and Org-P (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.81).\u003c/p\u003e\u003cp\u003eThe contribution of F4 was 14.22% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). De-P and Fe-P contributed 9.00% and 17.81% to F4, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Since Ex-P made only a little contribution to F4 and the correlation between Fe-P and Ex-P was weak, Fe-P in this component did not represent agricultural pollution, which was different from F1 of the Xianghu Lake. Previous studies have shown that Fe-P can also be associated with domestic sewage (Wu et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Taking into account the substantial residential settlements adjacent to the study area. Therefore, F4 was interpreted as the combined input of domestic sewage and sediments through the surface runoff.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e4.2.3 Phosphorus sources of sediments in Aixihu Lake\u003c/h2\u003e\u003cp\u003eThe contribution of F1 was 46.58% in the Aixihu Lake sediments (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Fe-P and Org-P contributed 67.18% and 38.17% to F1, respectively. Given their positive correlation and the surrounding land-use types (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), F1 was interpreted as pollution derived from irrigation wastewater in the study area. The contribution of F2 was 22.02% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Fine silt, Ca-P and organic matter contributed 87.36%, 71.40% and 66.98% to this factor, respectively. Ca-P reflects agricultural activities such as fertilizer application, while organic matter reflects wastewater from livestock farming (Sun et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Therefore, F2 was interpreted as representing pollution arising from fertilizer application and the breeding industry.\u003c/p\u003e\u003cp\u003eFactor 3 had the contribution of 19.70% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Ex-P and De-P contributed 40.11% and 27.92%, respectively. Previous studies have shown that De-P can release phosphate into lake water under weathering processes, and the released phosphate could be subsequently adsorbed by sediments to form Ex-P. The significant correlation coefficient between De-P and Ex-P (r\u0026thinsp;=\u0026thinsp;0.57, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec) suggested potential transformation between these two fractions (Jiang et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Poblete-Grant et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, fine silt made the highest contribution among the three grain-size fractions, suggesting that F3 represents the input of silt detrital phosphate minerals.\u003c/p\u003e\u003cp\u003eFactor 4 had the contribution of 11.70% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Clay contributed 17.98% to this component, which was higher than the other index (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). As clay is typically produced by long-term weathering, F4 represented natural processes such as geological weathering and the input of terrigenous sediments into the lake.\u003c/p\u003e\u003cp\u003eIn summary, the primary sources of phosphorus pollution in Xianghu Lake, Qianhu Lake and Aixihu Lake were agricultural activities such as livestock breeding, irrigation and fertilizer application, followed by inputs from domestic sewage and industrial discharges. These lakes are located around Nanchang, where extensive farmlands and large residential areas are present. Phosphorus generated from agricultural practices (crop cultivation and livestock farming) entered the lakes mainly through surface runoff and irrigation return flow (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and constitutes the dominant non-point source pollution. It could be seen that there are no large-scale industrial lands around the lakes, and only a few enterprises contributed only limited point-source pollution (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Meanwhile, strict regulations on industrial wastewater discharge effectively reduced phosphorus transport.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Evaluation of lake pollution and management recommendations\u003c/h2\u003e\u003cp\u003eTo evaluate the pollution status of the lakes, the single factor pollution index (S\u003csub\u003eTP\u003c/sub\u003e) analysis was conducted on the profile sediments, while the Nemerow integrated pollution index (F) was applied to surface sediments, as they can reflect the recent pollution status of the lakes. Based on F values, Xianghu Lake, Qianhu Lake and Aixihu Lake were all classified as heavily polluted (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with Qianhu Lake showing the highest level (F\u0026thinsp;\u0026ge;\u0026thinsp;2.26), followed by Aixihu Lake (F\u0026thinsp;\u0026ge;\u0026thinsp;2.04) and Xianghu Lake (F\u0026thinsp;\u0026ge;\u0026thinsp;1.92) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). According to the S\u003csub\u003eTP\u003c/sub\u003e index, the surface sediments of profiles XH2 and XH3 in the Xianghu Lake were moderately polluted (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with S\u003csub\u003eTP\u003c/sub\u003e values consistently exceeding 1.0 within the 0\u0026ndash;10 cm depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Profile XH1 exhibited the most severe pollution, with the pollution peak concentrated at 8\u0026ndash;12 cm (S\u003csub\u003eTP\u003c/sub\u003e \u0026gt;3.0) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In Qianhu Lake, the S\u003csub\u003eTP\u003c/sub\u003e values of the three profiles (2.20\u0026ndash;3.88) indicated severe pollution (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with QH1 and QH3 showing peak values (S\u003csub\u003eTP\u003c/sub\u003e \u0026gt;2.0) at 4\u0026ndash;8 cm depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and QH2 at 10\u0026ndash;20 cm depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In Aixihu Lake, profiles AXH1 and AXH3, which had heavy pollution, exhibited their highest S\u003csub\u003eTP\u003c/sub\u003e values at the surface and decreased with depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). At the same time, AXH2 showed moderate pollution at the surface and a heavy pollution peak at 5\u0026ndash;10 cm depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe pollution indices of profile sediments in the urban lakes from Nanchang\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSediment profile\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eS\u003csub\u003eTP\u003c/sub\u003e (pollution grade)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF (pollution grade)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.40 (moderate)\u0026thinsp;~\u0026thinsp;3.53 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.91 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.28 (moderate)\u0026thinsp;~\u0026thinsp;2.79 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.92 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXH3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.40 (moderate)\u0026thinsp;~\u0026thinsp;2.67 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.46 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.20 (heavy)\u0026thinsp;~\u0026thinsp;3.29 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.64 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.22 (heavy)\u0026thinsp;~\u0026thinsp;3.79 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.75 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQH3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.21 (heavy)\u0026thinsp;~\u0026thinsp;3.88 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.26 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAXH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.79 (heavy)\u0026thinsp;~\u0026thinsp;2.60 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.63 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAXH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.47 (heavy)\u0026thinsp;~\u0026thinsp;2.63 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.33 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAXH3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.06 (heavy)\u0026thinsp;~\u0026thinsp;3.65 (heavy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.04 (heavy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: S\u003csub\u003eTP\u003c/sub\u003e and F denoted single factor pollution index and Nemerow integrated pollution index, respectively.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn summary, the sediments of urban lakes in Nanchang generally suffer from heavy phosphorus pollution, underscoring the need for comprehensive and targeted mitigation strategies to alleviate current pollution levels and prevent further deterioration. Given that Xianghu Lake, Qianhu Lake and Aixihu Lake share similar land-use patterns in their surroundings, mitigation should include optimizing urban planning, strengthening the construction and maintenance of wastewater treatment facilities and improving farmland irrigation and drainage systems.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study investigated the characteristics, sources, and pollution level of phosphorus speciation in sediments from three typical urban lakes in Nanchang: Xianghu Lake, Qianhu Lake, and Aixihu Lake. The primary conclusions are as follows:\u003c/p\u003e\u003cp\u003e1) Sediments from Xianghu Lake, Qianhu Lake, and Aixihu Lake predominantly comprise clay (ranging from 34.65% to 51.49%), followed by coarse silt, with fine silt being the least abundant. Organic matter concentration in Xianghu Lake sediments ranged from 3.76% to 15.01%, similar to those in Qianhu Lake, whereas Aixihu Lake showed lower concentrations (4.53%\u0026ndash;9.55%). The total phosphorus concentration in Xianghu Lake sediments ranged from 538.79 to 1481.57 mg/kg, which was lower than that in Qianhu Lake (923.06\u0026ndash;1630.17 mg/kg) and Aixihu Lake sediments (616.58\u0026ndash;1532.88 mg/kg). All three lakes exhibited the highest Ca-P content (\u0026gt;\u0026thinsp;160 mg/kg), followed by De-P and Fe-P, with Org-P and Ex-P being the lowest. Spatial heterogeneity in Concentrations of grain size, organic matter, and phosphorus speciation had vertical heterogeneity.\u003c/p\u003e\u003cp\u003e2) Statistical analysis revealed that sediment Fe-P exhibited a positive correlation with clay, reflecting the adsorption of Fe-P by clay. Concurrently, Ca-P and Org-P exhibited positive and negative correlations with organic matter, respectively, indicating that organic matter decomposition promotes the formation of calcium-bound phosphorus and mineralization of organic phosphorus. Based on the APCS-MLR, it could be indicated that the primary source of phosphorus pollution in Xianghu Lake, Qianhu Lake, and Aixihu Lake stemmed from agricultural activity such as aquaculture, irrigation, and fertilizer application, and the domestic sewage and industrial discharges were a supplement. This pattern corresponded with the land use types around the study area.\u003c/p\u003e\u003cp\u003e3) The Nemerow integrated pollution index confirmed that Xianghu Lake, Qianhu Lake, and Aixihu Lake all exhibited severe phosphorus pollution with F\u0026thinsp;\u0026ge;\u0026thinsp;1.92 in the surface. The single factor pollution index indicated moderate to severe phosphorus contamination in the profiles of the lakes. Therefore, it is necessary to improve farmland irrigation, fertilization, and drainage patterns, optimize the land planning and reduce the discharge of industrial, agricultural and domestic sewage.\u003c/p\u003e\u003cp\u003eThis study has promoted the research on lake environment governance and biogeochemical cycles. However, there are still some shortcomings. For example, mineral composition, temperature and biological disturbances can affect the phosphorus speciation, and future studies will take them into consideration. In addition, phosphate and oxygen isotopes, as stable environmental indices, can trace the source of phosphorus efficiently, and will be employed in the next steps to provide a more reliable basis for sediment pollution prevention in the urban lakes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization: Tianning Li, Fangwen Zheng; Data curation: Tianning Li, Linsen Tang; Formal analysis: Linsen Tang, Fangwen Zheng; Funding acquisition: Fangwen Zheng, Huiyang Qiu; Laboratory analysis: Ping Liu, Jinfu Liu; Methodology: Tianning Li, Fangwen Zheng, Ping Liu, Jinfu Liu; Writing: Fangwen Zheng, Ping Liu. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was financially supported by the China Railway Group Limited Technology Research and Development Plan (No. 2022-Key Project-08), Key Innovation Training Project at the Provincial Level of Jiangxi Province (202411319001) and Nanjing Institute of Environmental Sciences specific fundings for basic scientific research (GYZX240409).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e The authors confirm that the data supporting the findings of this study are available within the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e We sincerely thank Chi Zhang for the invaluable suggestions provided for this thesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Competing Interest:\u003c/strong\u003e The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAcharya, S.S., Panigrahi, M.K., Kurian, J., Gupta, A.K., Tripathy, S., 2016. 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Health. 13, 349\u0026ndash;359. https://doi.org/10.1007/s11869-020-00798-7.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Urban lakes, Sediments, Phosphorus speciation, Source apportionment, Pollution assessment","lastPublishedDoi":"10.21203/rs.3.rs-7828473/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7828473/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUrban lakes play a vital role in flood disaster mitigation, water supply, and climate maintenance. However, excessive phosphorus inputs resulting from urban development constitute a significant factor in the deterioration of aquatic ecosystems. In this study, samples of sediment profiles (within 40 cm) from three representative urban lakes (Xianghu Lake, Qianhu Lake, and Aixihu Lake) in Nanchang were collected to investigate the chemical speciation characteristics, analyze the sources and assess the pollution condition of phosphorus. Results indicated that sediments in Qianhu Lake exhibited the highest concentration of total phosphorus (923.06\u0026ndash;1630.17 mg/kg), followed by Aixihu Lake (616.58\u0026ndash;1532.88 mg/kg), while Xianghu Lake exhibited the lowest levels (538.79\u0026ndash;1481.57 mg/kg). Calcium-bound phosphorus (Ca-P) dominated in all three lakes (accounting for over 30% of total phosphorus), followed by iron-bound phosphorus (Fe-P) and detrital phosphorus (De-P). While the organic phosphorus (Org-P) and exchangeable phosphorus (Ex-P) constituted the lowest proportions, with lower than 15% of each speciation. The distribution of phosphorus speciation in the lake sediments exhibited vertical spatial heterogeneity, reflecting the differentiation of influencing factors and sources. In all the lakes, clay dominated the sediment composition (\u0026ge;\u0026thinsp;34%), followed by coarse silt, while fine silt was the least abundant. Correlation analysis revealed that grain size and organic matter constrained the concentrations of phosphorus speciation. The Absolute Principal Component Score-Multiple Linear Regression model (APCS-MLR) revealed that phosphorus pollution in Xianghu Lake, Qianhu Lake, and Aixihu Lake was predominantly driven by agricultural non-point sources, with the contributions of more than 35%, followed by industrial emissions and domestic sewage, which corresponded with the extensive agricultural land around the lake. Nemerow integrated pollution index analysis revealed that all the lakes were heavily polluted, and ranked as follows: Qianhu Lake (F\u0026thinsp;\u0026ge;\u0026thinsp;2.26)\u0026thinsp;\u0026gt;\u0026thinsp;Aixihu Lake (F\u0026thinsp;\u0026ge;\u0026thinsp;2.04)\u0026thinsp;\u0026gt;\u0026thinsp;Xianghu Lake (F\u0026thinsp;\u0026ge;\u0026thinsp;1.92). Consequently, comprehensive management measures, including optimizing agricultural fertilization\u0026ndash;irrigation forms and restricting pollutant discharges, are required to prevent further deterioration. This study is of practical significance for the prevention of lake eutrophication. Also, it provides a scientific basis for research on biogeochemical cycles and the protection and management of aquatic ecosystems in the urban lakes.\u003c/p\u003e","manuscriptTitle":"Chemical speciation, source apportionment, and pollution assessment of phosphorus in sediments from typical urban lakes in Southern China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 13:40:59","doi":"10.21203/rs.3.rs-7828473/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-23T17:30:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-22T11:46:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-18T09:00:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-03T12:52:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"97751210333507093078019885376654009922","date":"2025-11-28T05:41:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278420047639909980591386302662623390446","date":"2025-11-27T09:22:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135255195471778434994330260716599041490","date":"2025-11-25T00:46:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-23T08:12:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69878015866246158790818238271036474407","date":"2025-11-11T01:09:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-10T17:37:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T04:14:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-14T04:13:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2025-10-10T15:08:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3f2a3509-ce37-4d86-9298-98453ae84c0b","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-20T02:23:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 13:40:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7828473","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7828473","identity":"rs-7828473","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}