Geochemical characteristics and safety risk identification of high-fluoride soils in the Nanyang Basin

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Consequently, the sources and safety risks of high-F soils have garnered significant attention. The Nanyang Basin is a major agricultural region in China, known for its wheat and other staple crops. This study investigated the spatial geochemical characteristics of fluoride in surface soils (0–20 cm) and the vertical change characteristics, analyzed the relationship of fluorine content between crop and soil, and identified its potential safety risks. Methods We collected soil samples regionally and crop samples and rhizosphere soil in typical areas, analyzed the geochemical distribution of soil F and its relationship with crop uptake integrating geostatistical analysis with GIS techniques, were. Results The background F content in surface soils of the Nanyang Basin is higher than the background levels of topsoil in Henan Province and China. The primary source of F in surface soils is external input (pollution-related), with geological background having a secondary influence. Conclusions The high-F surface soils in agricultural areas of the basin have a relatively low impact on the safety of wheat and peanut grains. The F content in crop grains is generally below the maximum allowable limits for food, indicating an overall "safe" status, except that a few areas exceeding the maximum allowable limits for food contamination in alkaline soil regions with high F levels,and identifying these areas as potential safety risk zones requiring enhanced monitoring and management. Nanyang Basin Surface soil Fluorine (F) Wheat and peanut crops Safety risk Survey and monitoring Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Fluorine (F), an essential trace element for the human body, is widely distributed across various geospheres, including rocks, water, organisms, and the atmosphere. However, excessive intake of F can pose significant health risks to humans [1–9] .Reports of fluorosis events and subsequent public awareness date back to the 1930s [4–5;10–12] , with extensive research on its biological toxicity mechanisms and safety risks to food crops, such as harmful or lethal threshold concentrations, gaining momentum in the 1960s [4;11;13–18] .Additionally, studies have identified the sources of F in surface soils, which are not only influenced by geological background but also by anthropogenic activities such as emissions of fluoride-containing gases and particulates from steel plants and phosphate chemical factories, as well as the application of phosphate fertilizers in agriculture [19–31] in soil and their plant uptake. Soil serves as the dominant component of the environmental chemical system for F, acting as both a direct receptor of F sources and a provider of F to crops. Consequently, the geochemical characteristics of fluorine in soil F have garnered considerable research attention [32–41] The Nanyang Basin, a major wheat and grain-producing region in China, is also one of the country's endemic fluorosis areas [12] . However, studies addressing the sources of F in surface soils and its associated ecological safety risks in this region remain limited. Based on the 1:250,000 geochemical survey data of arable land in the Nanyang Basin, this study combines geostatistical analysis with GIS techniques to investigate the geochemical distribution characteristics of fluorine in soil in cultivated areas of the basin. Furthermore, it explores the fluorine concentration relationship between in soil and in crops, focusing on wheat, peanuts, and other crops grown in high-F farmland areas and assessing their safety risks. Research background and data sources Overview of the study area The study area, the Nanyang Basin, is a semi-open, fan-shaped basin surrounded by mountains to the west, north, and east, with a slight southeastward tilt. It is located east of the Qinling-Dabashan Mountains and west of the Tongbai-Dabie Mountains. The northern boundary features the eastern terminus of the Qinling Mountains, known as the Funiu Mountain range, while the southern boundary is defined by the eastern terminus of the Dabashan Mountains. The basin's stratigraphy primarily consists of sedimentary layers ranging from the Paleoproterozoic to the Cenozoic, with Cretaceous to Lower Tertiary formations. Quaternary deposits dominate the surface layer in the central plain region of the basin. The soil types in the study area predominantly include cinnamon soil, fluvo-aquic soil, and dark loessial soil. Calcareous fluvo-aquic soil occurs in small quantities, while coarse-textured skeletal soil is sparsely distributed in the piedmont zones of the northern part of the basin. The Nanyang Basin encompasses a cultivated land area of 987,350 hectares, with wheat, maize, and peanuts as the primary crops. In 2023, the total area under grain crop cultivation in the region was 1,308,890 hectares, of which wheat accounted for 728,920 hectares (73.83% of arable land), maize for 472,360 hectares (47.84%), and peanuts for 396,360 hectares (40.14%). Previous studies have shown that soil parent material, influenced by geological processes, is a critical factor affecting the sources and fluorine concentrations in soil. The fluorine concentration varies significantly across soils derived from different parent materials [42–43] . In the Nanyang Basin, fluvial alluvial parent materials are primarily distributed in the southern downstream plain regions, while lacustrine and fluvial-lacustrine deposits are found in the interfluvial zones of the southern plain region. Loess and red soil parent materials exhibit a southwest-to-northeast banded distribution in the northeastern part of the basin. Colluvial deposits dominate interfluvial areas, hilly regions, and transitional zones between hills, plains, and mountains, whereas residual slope deposits are mainly distributed in the mountainous regions and certain transitional zones between hills and mountains (Fig. 1 ). Sample collection and testing The soil monitoring data in this study were collected following the Specification of Multi-Purpose Regional Geochemical Survey (1:250,000) (DZ/T 0258–2014) [44] . Surface soil samples (0–20 cm) from agricultural land were collected using a grid-based approach with GPS positioning, avoiding areas with anthropogenic contamination. A total of 22,950 samples were collected at a density of one sampling point per 1 km 2 . At each point, 3–5 vertical soil cores (0–20 cm) were combined into a composite sample. Over 1 kg of fresh soil was collected at each site, air-dried naturally, processed, and sieved before being bagged and labeled. Subsequently, composite surface soil master samples (totaling 5,772 samples) were prepared by mixing processed sub-samples within 4 km 2 grids. Each master sample weighed over 200 g and was sent to certified laboratories for analysis (Fig. 1 ). To identify crop safety risks, 120 crop seed samples and 120 rhizosphere soil samples were collected at the same sample point over an area of 280 km², where the fluorine concentration in soil is more than 550mg/kg 68% of the area, 120 crop seed samples including 60 seed samples each for wheat and peanuts. The soil samples were tested at the Henan Rock and Mineral Testing Center and the North China Nonferrous Metals (Sanhe) Laboratory in Yanjiao.The total F is tested using the ion-selective electrode (ISE) by China, and pH tested using pH meter. The analytical procedures adhered to the Specification of Analytical Methods for Regional Geochemical Samples (DZ/T 0279–2016) [45] , and the results of the logarithmic error (Δlg) and relative standard deviation (RSD%) between the average value of each element determination and the standard indicated that all quality indicators for F analysis met or exceeded the requirements of the Specification of Multi-Purpose Regional Geochemical Survey (DZ/T 0258–2014)(Table.1) [44] . The F content in wheat and peanut seeds was determined using the diffusion-spectrophotometric method as outlined in the Analytic methods for biologic samples in eco-geochemistry assessment (DZ/T 0253–2014) [46] . The reliability of the fundamental data used in this study was therefore ensured. Table.1 Quality indicators for F analysis Detection Limit(µg/g) accuracy of measurement Precision Standard Analysis result Standard Analysis result Standard Analysis result 100 70 ≤ 0.05 0.000-0.014 ≤ 10.00 3.13–6.20 Data processing and analysis Data statistics and contour map The testing data processing was conducted using Microsoft Excel, and the basic characteristics of the soil data and evaluation results were analyzed using the "Integrated Geochemical Exploration System," developed by the China Geological Survey. Statistical parameters such as maximum, minimum, mean, standard deviation, median, and coefficient of variation were calculated. Semi-variance analysis was performed using GS + software to determine the optimal theoretical semi-variance model and derive the parameters for inverse distance weighting interpolation. Based on these analyses, the spatial distribution contour maps of fluoride concentration in surface soil and the ratio of surface to subsurface soil were generated using the inverse distance weighting method in the "Integrated Geochemical Exploration System." These maps formed the fundamental dataset for this study. Calculation of fluorine concentration in crop seeds Soil pH is one of the prominent Influencing factors affecting the absorption of fluorine from the soil by crops. The bio-concentration factor (BCF) [ 47–49] was linearly correlated with the total F in the soil when the soil pH is less than 7.5 in the study area.The fluoride concentration in crops was calculated based on the function between fluoride concentration in crop seeds and in soil analyzed statistically using Origin software 2024.There is not correlation between the bio-concentration factor and total F in the soil when the soil pH is less than 7.5 in the study area. The fluoride concentration in crops was calculated by comparing one by one based on the fluoride concentration in crops investigated,assuming that the fluoride accumulated by crops from the soil is the same if the soil pH and the total F are basically same or slight difference .The process is implemented through Python programming. Results Spatial geochemical characteristics of F in surface soils In the southeastern and northeastern regions of the Nanyang Basin, isolated areas of surface soil exhibit F concentrations ranging from 2,000 to 22,000 mg·kg -1 , potentially influenced by high geological background levels or anthropogenic activities. After excluding outliers, the fluorine content in surface soil ranged from 271 to 794 mg·kg -1 , with an average value of (532 ± 86) mg·kg -1 , a median of 526 mg·kg -1 , skewness of 1.53, kurtosis of 8.13, and a coefficient of variation of 0.16 (Table 2 ). Across different soil parent material zones within the Nanyang Basin, F concentrations in surface soils showed a uniform distribution pattern. The background F concentration in surface soils, calculated as the mean value after excluding outliers (532 mg·kg -1 ), was slightly higher than the A-layer soil background values for Henan Province (514 mg·kg -1 ) and China (480 mg·kg -1 ) [50] . This indicates elevated F background values in surface soils of the study area, particularly in regions dominated by residual slope deposits, lacustrine and fluvial-lacustrine sediments, and colluvial deposits. Table 2 Statistical characteristics of fluoride content in topsoil Research area Samples Max (mg/kg) Min (mg/kg) Mean (mg/kg) Median (mg/kg) SD Kurtosis coefficient of variation Nanyang Basin 5599 271 794 532 ± 86 526 1.53 8.13 0.16 Material source(parent material) Residual and Colluvial 1912 244 904 557 532 0.61 3.23 0.20 Fluvial Sediment parent material 437 305 714 495 494 0.37 3.30 0.14 Fluvial-lacustrine sedimentary parent material 656 372 758 563 554 0.50 3.24 0.12 Alluvial parent material 2247 282 764 521 517 0.33 3.17 0.15 Loess and red soil parent material 408 332 687 490 488 0.44 3.18 0.13 Regarding spatial distribution, 72.54% of the study area showed surface soil F concentrations exceeding the national A-layer soil background value. F concentrations generally decreased from the low mountains and hills on the basin's periphery towards the central plain. High-F areas were primarily distributed in the western and southeastern low mountain regions with residual slope deposits and in the interfluvial zones with lacustrine and fluvial-lacustrine sediments in the downstream river areas. In contrast, regions along river corridors and the eastern plain exhibited background or low F concentrations (Fig. 2 ). According to the Specification for the Geochemical Evaluation of Land Quality (DZ/T 0295–2016) [45] , the "excess" F area in the Nanyang Basin's surface soils covered 1,572 km 2 , accounting for 6.80% of the total study area (Fig. 3 ). The "high F" area covered 7,292 km 2 , representing 31.56% of the total area. The "suitable" F area comprised only 24.75% of the study area, amounting to 5,720 km 2 . Meanwhile, the "marginal" and "deficient" F areas accounted for 32.20% (7,440 km 2 ) and 4.69% (1,084 km 2 ) of the study area, respectively. Vertical change characteristics in soils In the study area, the F content in deep soils (150–200 cm) is considered unaffected by contemporary anthropogenic activities and thus represents the natural background value (denoted as A na ). If the surface soil F content correlates closely with A na and the enrichment coefficient is ≤ 1.0, it suggests that the elevated F levels in surface soils are primarily due to geological and environmental factors, without significant influence from human activities. Conversely, if the surface soil F content shows no correlation with A na and exceeds A na values, with an enrichment coefficient ≥ 1.0, it indicates that anthropogenic activities might contribute to elevated F levels in surface soils. Analysis of the enrichment coefficient, defined as the ratio of surface soil F content to deep soil (150–200 cm) F content, revealed that over 70% of surface soils in the study area have enrichment coefficients between 0.8 and 1.2. Among these, 63% of the regions exhibit coefficients of 0.8–1.0, primarily in plain areas dominated by farmland, where surface soil F content is similar to that of deep soil (Fig. 3 and Fig. 4 ). This indicates that most of the surface soil F content in the Nanyang Basin is of natural origin. Regions with enrichment coefficients of 1.0–1.2 are mainly distributed in low mountains and hilly areas, influenced by the weathering of upstream mountain parent rocks. Areas with enrichment coefficients below 0.5 are primarily located in "marginal" or "deficient" F regions, where surface soil F content is significantly lower than that of deep soil. Regions with coefficients between 0.5 and 0.8 are distributed in "marginal" F areas, while those with coefficients < 0.5 are found in "deficient" F areas. These patterns are associated with favorable conditions for soil erosion in these locations. The high-F areas of interest in this study, characterized by enrichment coefficients > 1.2, are predominantly located in flat farmland regions or zones affected by industrial waste emissions (orange and red areas in Fig. 4 ). Notably, regions with coefficients > 1.5 exhibit significantly elevated surface soil F levels, forming patchy distributions in the southeastern and northwestern parts of the basin, likely attributable to pollution from local human activities. As shown in Fig. 5 , F content decreases progressively from the surface to deeper soil parent material layers, suggesting that high-F levels in surface soils in areas with "excessive" F content (> 700 mg·kg -1 ) [45;51–52] are not strongly related to local geological conditions. Studies indicate that in natural, undisturbed soil profiles unaffected by anthropogenic pollutants, F content typically increases with depth, a trend particularly pronounced in regions with "marginal" surface soil F content (400–500 mg·kg -1 ). However, in F-polluted areas, F content decreases from the surface downward [53] . In high-F regions (550–700 mg·kg -1 ) and "suitable" areas (500–550 mg·kg -1 ) in the study area, soil profiles exhibit a decreasing trend of F content from the surface to deeper layers. Fluoride content in crops For this study, the northern region of Zhenping County and Fangcheng County in the Nanyang Basin, identified as having "high" or "excessive" F levels (Fig. 1 ), was selected as the "farmland safety risk identification" area. In addition to the previously collected soil samples, 60 samples each of wheat and peanut crops, the main cultivated crops in the Nanyang Basin, were collected. Test results showed that F content in wheat grains ranged from 0.45 to 0.79 mg/kg, while F content in peanut grains ranged from 0.21 to 0.49 mg/kg(Table.3). Table 3 Statistical characteristics of fluoride content in crops Crops Samples Max (mg/kg) Min (mg/kg) Mean (mg/kg) Median (mg/kg) SD Wheat 60 0.79 0.20 0.47 0.45 0.16 Peanut 60 0.54 0.21 0.40 0.40 0.07 Discussion Sources and causes of F anomalies in surface soils The vertical variation of F content in soils is closely related to its source. Geological background conditions primarily control F levels in sub-surface soils [42–43] , while external factors (e.g., human activities) modify surface soil F content, influencing vertical and local profile distribution patterns [8;38,54–55] . For instance, the annual F input from agricultural fertilization in China is less than 0.5% of total soil F content based on the datum form artical [27;56] , and the atmospheric F deposition flux investigated the study area ranges from 17.69 to 76.25 mg/a·m 2 . The ratio of surface soil to deep soil is significantly positively correlated with the atmospheric fluorine deposition,and the changes were also significantly positively correlated with the atmospheric fluorine deposition. Their correlation coefficients are 0.76(p < 0.0001)and 0.59(p < 0.001), respectively(Fig. 6 ).The correlation indicates with the atmospheric fluorine deposition may be one of the main sources of fluorine in soil and the predomaint influencing factors of spatial distribution changes.Long-term cumulative effects and spatial variability in F input from agricultural fertilization and atmospheric dust deposition have altered the surface soil F distribution in localized areas of the Nanyang Basin. Identification of safety risks in high-F farmland areas This study focuses on identifying the safety risks posed by high F levels in surface soils to major crops in farmland areas. F is an essential trace element for the human body, and dietary intake through food and drinking water is a primary source of F. However, F accumulates in the human body, and excessive intake can be detrimental to health. Accordingly, health authorities have established safety standards for F content in soils and crops to safeguard human health. Previous studies indicate that the average F content in the human body is approximately 2.6 g, with a daily requirement of 1.0 mg [57] . The Chinese Ministry of Health recommends a safe daily F intake limit of 3.5 mg/day, while the World Health Organization (WHO) suggests a limit of < 2 mg/day [57] . The Limits of Contaminants in Food (GB 2762 − 2005) specifies that the maximum allowable F content in wheat grains is 1.0 mg/kg, and for peanut grains, it is 1.5 mg/kg [58] . Assuming an average daily consumption of 0.5 kg of wheat flour, the estimated F intake from consuming flour produced in these high-F areas would not exceed 0.37 mg/day based on the tested result, which is below the recommended F intake limits established by health authorities. These findings indicate that the F content in wheat and peanut grains from the high-F areas of the Nanyang Basin is below the safety thresholds specified in the Limits of Contaminants in Food (GB 2762 − 2005). Thus, the surface soil F levels in farmland areas of the Nanyang Basin are generally within a "safe" range. Soluble F is the most bioavailable form for crops [41] .Research has shown that crop uptake of F from soil is influenced by the amount of soluble F [53–54;56] , which is determined by the total F content, its forms, and the soil's physicochemical properties. The rhizosphere soil pH is one of the main factors affecting the bio-concentration factor (BCF) [47–49] .The Statistical analyses in this study revealed a relationship between the bio-concentration factor and the total F content in soils with pH 7.5 (alkaline soils) (Fig. 7 a). The relationship between peanut grain F content and total soil F content (Fig. 7 b) exhibited a similar trend to that observed in wheat ( 7a). Based on the observed relationships between the bio-concentration factor and total F content of rhizosphere soils, and the surface soil pH value was used as a primary physicochemical indicator for farmland soils. Combined with previously obtained surface soil F content data, a simulation analysis was conducted to estimate the cumulative F content in wheat and peanut grains for each survey unit in the study area. The simulation results indicate that the F content in wheat grains across the Nanyang Basin ranges from 0.21 to 1.34 mg/kg, while the F content in peanut grains ranges from 0.17 to 0.72 mg/kg (Table 4 ). These findings confirm that the F content in peanut grains is below the limits specified in the Limits of Contaminants in Food (GB 2762 − 2005). However, in certain units, the F content in wheat grains exceeds the specified limits. Spatially, regions with wheat grain F content between 0.80 and 1.0 mg/kg are distributed as isolated patches(orange and red areas in Fig. 8 ), primarily in alkaline soil zones with high total soil F content (> 1400 mg/kg) (Fig. 2 ). These regions account for less than 5% of the study area. In over 99.5% of the study area, the F content in wheat grains is less than 0.80 mg/kg, with areas where F content is below 0.5 mg/kg comprising 63.76% of the total study area. These low-F regions are mainly located in the eastern part of the Nanyang Basin, where surface soils have low pH values, characterized by strong acidity or acidity. In farmland areas with acidic to neutral soils, the maximum potential dietary F intake from wheat consumption is less than 0.68 mg, which is below the intake limits recommended by the Chinese Ministry of Health and the WHO. These results confirm that the high-F farmland areas in the Nanyang Basin remain in a "safe" state with relatively low risk. Table 4 Simulation statistical characteristics of fluoride content in crop grain in the Nanyang Basin Crop type Samples Max (mg/kg) Min (mg/kg) Mean (mg/kg) Median (mg/kg) Wheat 5777 0.213 1.344 0.516 0.514 Peanut 5777 0.173 0.716 0.437 0.436 Conclusions The surface soils of the Nanyang Basin have relatively high F content, with background values exceeding those of Henan Province and national A-layer soil background values. The enrichment coefficient analysis indicates that the geological background exerts a certain influence on the spatial distribution of F content in surface soils. However, the cumulative inputs of F through long-term agricultural fertilization and atmospheric dust deposition also play a significant role in the formation of high-F zones in localized areas. In the Nanyang Basin, the "excessive" and "high" F areas cover 1,572 km² and 7,292 km², accounting for 6.80% and 31.56% of the total study area, respectively. These areas represent potential risk zones for crop safety and require enhanced monitoring and management. In high-F areas of the Nanyang Basin, the F content in wheat and peanut grains is within acceptable levels for human consumption, below the limits specified in the Limits of Contaminants in Food (GB 2762 − 2005). Moreover, the estimated dietary F intake from consuming wheat grains is lower than the limits recommended by the Chinese Ministry of Health and the WHO. 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Environmental Pollution,2025(367) Jinhang Song, Jing Song , Chang Che, et al.Study on interaction, feedback, and response between perfluorinated compounds and soil environments. Emerging Contaminants,2025(11) Yang Mu-Zhuang,Lai QI-Hong，Zhou Shun-Gui.Relationship of the soil fluorine enrichment and marine invasion in the pearl river delta. Marine Geology&Quaternary Geology,2008,(5): 17-20. Zhang Nai-ming.Distribution of fluorine and its affection factors in soil in ShanXi.ACTC Pedologiac Sinica,2001,38(2): 284-287. Ministry of Natural Resources of the People's Republic of China.Specification of multi-poupose regional geochemical survey(1:250000)DZT2014-0258) Ministry of Natural Resources of the People's Republic of China.Specification of land quality geochemical assessment（DZ /T 0295-2016）。 Ministry of Natural Resources of the People's Republic of China.Analytic methods for biologic samples in eco-geochemistry assessment (DZ/T 0253-2014) Yang Yiming,Nan Zhongren,Zhao Zhuanjun,Wang Shengli,Wang Zhaowei ,Wang, Xia.Chemical fractionations and bioavailability of cadmium and zinc to cole (Brassica campestris L.) grown in the multi-metals contaminated oasis soil, northwest of China.Journal of Environmental Sciences, 2011,.23(2): 275-281. Zhiliang Wu,Qingye Hou,Zhongfang Yang,et al.Driving factors of molybdenum (Mo) bioconcentration in maize in the Longitudinal Range–Gorge Region of Southwestern China. Environ Geochem Health, (2024) 46:499 Xu Liao,Yanmei Li,Raúl Miranda‑Avilés ,et al.Assessments of Pollution Status and Human Health Risk of Potentially Toxic Elements in Primary Crops and Agricultural Soils in Guanajuato, Mexico. Water Air Soil Pollut , (2023) 234:670 Ministry of Ecology and Enviroment of the People's Republic of China,China National Enviromental Monitoring Centre. Background value of soil elements in China. China Environmental Press,1990 Xie Zheng-miao,‚LI Jing1,XU Jian-ming,WU Wei-hong.Quality evaluationof soil Fluorine on Hangjiahu Plain based on GIS.Evironmental Science,2006,(5): 1026-1030. Li Xiao-liang,ChenXiao-min,Sun Li,Yu Qun-yin.Study on the fluoride and its affecting factors in paddy soils derived from different parent meterials of Anhui Province.Journal of NanJing Agriculture University,2009,(1): 73-77. Jiao You, Wei Kexun. Study on the fluoride status of soil and groundwater and the characteristics of soil fluoride absorption in high fluoride areas of Henan. Research Of Soil And Water Conservation,1994,(201): 88-89. Amol N. Joshi. A review of processes for separation and utilization of fluorine from phosphoric acid and phosphate fertilizers.Chemical Papers.2022(76)6033-6045 Xie Zheng-miao;LI Jing;XU Jian-ming;WU Wei-hong. Spatial distribution character of fluorine element in soils on Hang-Jia-Hu Plain. China Environmental Science,2005,25(6): 719-723. Yang Jinyan;GOU Min. The Research Status of Fluorine Contamination in Soils of China. Ecology and Environmental Sciences,2017,26(3): 506-513. Li Jing. Study on Evaluation and Health Guideline for Heavy Metals and Fluorine of Environmental Quality[D]. Zhejia University,2006. National Health Commission of the People's Republic of China,State Administration for Market Regulation《Maximum levels of contaminants in food》( GB 2762-2005). Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6223153","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431958838,"identity":"412dbd51-5b4b-40a0-a43b-e823d4f203aa","order_by":0,"name":"Mingjiang Yan","email":"","orcid":"https://orcid.org/0009-0007-2756-4737","institution":"Institue of Hydrogeology and Enviromental Geology,Chinese Academy of Geological Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mingjiang","middleName":"","lastName":"Yan","suffix":""},{"id":431958839,"identity":"189e88b3-7800-4558-a938-8bbfc919d480","order_by":0,"name":"Mingjiang Yan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Mingjiang","middleName":"","lastName":"Yan","suffix":""},{"id":431958840,"identity":"e659c42d-491d-4e6c-9c92-f1735992127a","order_by":1,"name":"Qian Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Wang","suffix":""},{"id":431958841,"identity":"619e989a-05ba-4fee-8ed5-b563700ca7b7","order_by":2,"name":"Yanliang Tian","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0001-4103-590X","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Yanliang","middleName":"","lastName":"Tian","suffix":""},{"id":431958842,"identity":"2ec0b654-b521-44bf-b1ef-7d5816207987","order_by":3,"name":"Qingfeng Xie","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Qingfeng","middleName":"","lastName":"Xie","suffix":""},{"id":431958843,"identity":"6d1ca940-a16a-470e-affc-f3637e2c0164","order_by":4,"name":"Haohao Cui","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Haohao","middleName":"","lastName":"Cui","suffix":""},{"id":431958844,"identity":"7d65c029-76fe-4cc1-848e-a6a7af05b270","order_by":5,"name":"Xiaohui Lv","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiaohui","middleName":"","lastName":"Lv","suffix":""},{"id":431958845,"identity":"fc830f31-fddf-45e3-90c5-0ecfe6d40155","order_by":6,"name":"Yanan Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yanan","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-03-14 02:19:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6223153/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6223153/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79550409,"identity":"26900e3e-a376-4c69-99ca-03c719829619","added_by":"auto","created_at":"2025-03-31 06:32:56","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1007386,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution characteristics of soil parent materials and locations of sampling\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/1e46094360314f8a08bcee69.jpeg"},{"id":79550410,"identity":"9ec33bdc-a4e0-4a62-a223-59abf1b7c938","added_by":"auto","created_at":"2025-03-31 06:32:56","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":459850,"visible":true,"origin":"","legend":"\u003cp\u003eGeochemical Contour map of fluoride in topsoil in Nanyang Basin\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/ef8b2adb56305e63b8bca412.jpeg"},{"id":79550414,"identity":"ae01f807-580c-4e09-b108-5f078c05ee52","added_by":"auto","created_at":"2025-03-31 06:32:56","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":475240,"visible":true,"origin":"","legend":"\u003cp\u003eMap of fluoride nutrient abundance and deficiency geochemical grades in topsoil\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/32b6eef6efa3adb5bf9708e3.jpeg"},{"id":79551554,"identity":"425b99c1-bb53-4c02-bb89-b6bfe793d676","added_by":"auto","created_at":"2025-03-31 06:40:56","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":514196,"visible":true,"origin":"","legend":"\u003cp\u003eConcentration distribution map of fluorine content in topsoil compared to subsoil\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/23d86b8f3394f2431e0ac337.jpeg"},{"id":79550424,"identity":"f88a91a3-c8c6-47da-abfb-548be1bca86b","added_by":"auto","created_at":"2025-03-31 06:32:56","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":475891,"visible":true,"origin":"","legend":"\u003cp\u003eThe vertical profile changes characteristics of fluoride content in soil\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/27ab869dd85ecbf6429186cb.jpeg"},{"id":79550418,"identity":"5d4e93ab-581d-45cc-82ff-f8a2d60e1ec0","added_by":"auto","created_at":"2025-03-31 06:32:56","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":85450,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between the change of fluoride content in the surface soil and the fluoride deposition\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/1b26dad94ea76a661821c734.jpeg"},{"id":79550426,"identity":"4042b2ee-c9e8-4bbd-bd5d-c348c2c37044","added_by":"auto","created_at":"2025-03-31 06:32:56","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":104229,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship of the total F content and pH of rhizosphere soils with the bio-concentration factor\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/7c1a15bc049dcea77530f170.jpeg"},{"id":79550427,"identity":"bdb427ed-36fb-4363-9dce-88a13e802435","added_by":"auto","created_at":"2025-03-31 06:32:56","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":849682,"visible":true,"origin":"","legend":"\u003cp\u003eSimulation of spatial distribution characteristics of fluoride content in wheat grain in the Nanyang Basin\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/1cecda8f8fe54806edd3056b.jpeg"},{"id":108803611,"identity":"4f559f5d-c2a1-47cc-81c6-b1b5d1cac0b4","added_by":"auto","created_at":"2026-05-08 15:01:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4286917,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6223153/v1/803b6248-8cbf-456e-b305-4b6b7612a327.pdf"}],"financialInterests":"","formattedTitle":"Geochemical characteristics and safety risk identification of high-fluoride soils in the Nanyang Basin","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFluorine (F), an essential trace element for the human body, is widely distributed across various geospheres, including rocks, water, organisms, and the atmosphere. However, excessive intake of F can pose significant health risks to humans \u003csup\u003e[1\u0026ndash;9]\u003c/sup\u003e.Reports of fluorosis events and subsequent public awareness date back to the 1930s \u003csup\u003e[4\u0026ndash;5;10\u0026ndash;12]\u003c/sup\u003e, with extensive research on its biological toxicity mechanisms and safety risks to food crops, such as harmful or lethal threshold concentrations, gaining momentum in the 1960s \u003csup\u003e[4;11;13\u0026ndash;18]\u003c/sup\u003e.Additionally, studies have identified the sources of F in surface soils, which are not only influenced by geological background but also by anthropogenic activities such as emissions of fluoride-containing gases and particulates from steel plants and phosphate chemical factories, as well as the application of phosphate fertilizers in agriculture \u003csup\u003e[19\u0026ndash;31]\u003c/sup\u003ein soil and their plant uptake. Soil serves as the dominant component of the environmental chemical system for F, acting as both a direct receptor of F sources and a provider of F to crops. Consequently, the geochemical characteristics of fluorine in soil F have garnered considerable research attention \u003csup\u003e[32\u0026ndash;41]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe Nanyang Basin, a major wheat and grain-producing region in China, is also one of the country's endemic fluorosis areas \u003csup\u003e[12]\u003c/sup\u003e. However, studies addressing the sources of F in surface soils and its associated ecological safety risks in this region remain limited. Based on the 1:250,000 geochemical survey data of arable land in the Nanyang Basin, this study combines geostatistical analysis with GIS techniques to investigate the geochemical distribution characteristics of fluorine in soil in cultivated areas of the basin. Furthermore, it explores the fluorine concentration relationship between in soil and in crops, focusing on wheat, peanuts, and other crops grown in high-F farmland areas and assessing their safety risks.\u003c/p\u003e"},{"header":"Research background and data sources","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eOverview of the study area\u003c/h2\u003e \u003cp\u003eThe study area, the Nanyang Basin, is a semi-open, fan-shaped basin surrounded by mountains to the west, north, and east, with a slight southeastward tilt. It is located east of the Qinling-Dabashan Mountains and west of the Tongbai-Dabie Mountains. The northern boundary features the eastern terminus of the Qinling Mountains, known as the Funiu Mountain range, while the southern boundary is defined by the eastern terminus of the Dabashan Mountains. The basin's stratigraphy primarily consists of sedimentary layers ranging from the Paleoproterozoic to the Cenozoic, with Cretaceous to Lower Tertiary formations. Quaternary deposits dominate the surface layer in the central plain region of the basin. The soil types in the study area predominantly include cinnamon soil, fluvo-aquic soil, and dark loessial soil. Calcareous fluvo-aquic soil occurs in small quantities, while coarse-textured skeletal soil is sparsely distributed in the piedmont zones of the northern part of the basin. The Nanyang Basin encompasses a cultivated land area of 987,350 hectares, with wheat, maize, and peanuts as the primary crops. In 2023, the total area under grain crop cultivation in the region was 1,308,890 hectares, of which wheat accounted for 728,920 hectares (73.83% of arable land), maize for 472,360 hectares (47.84%), and peanuts for 396,360 hectares (40.14%).\u003c/p\u003e \u003cp\u003ePrevious studies have shown that soil parent material, influenced by geological processes, is a critical factor affecting the sources and fluorine concentrations in soil. The fluorine concentration varies significantly across soils derived from different parent materials \u003csup\u003e[42\u0026ndash;43]\u003c/sup\u003e. In the Nanyang Basin, fluvial alluvial parent materials are primarily distributed in the southern downstream plain regions, while lacustrine and fluvial-lacustrine deposits are found in the interfluvial zones of the southern plain region. Loess and red soil parent materials exhibit a southwest-to-northeast banded distribution in the northeastern part of the basin. Colluvial deposits dominate interfluvial areas, hilly regions, and transitional zones between hills, plains, and mountains, whereas residual slope deposits are mainly distributed in the mountainous regions and certain transitional zones between hills and mountains (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample collection and testing\u003c/h3\u003e\n\u003cp\u003eThe soil monitoring data in this study were collected following the \u003cem\u003eSpecification of Multi-Purpose Regional Geochemical Survey (1:250,000)\u003c/em\u003e (DZ/T 0258\u0026ndash;2014) \u003csup\u003e[44]\u003c/sup\u003e. Surface soil samples (0\u0026ndash;20 cm) from agricultural land were collected using a grid-based approach with GPS positioning, avoiding areas with anthropogenic contamination. A total of 22,950 samples were collected at a density of one sampling point per 1 km\u003csup\u003e2\u003c/sup\u003e. At each point, 3\u0026ndash;5 vertical soil cores (0\u0026ndash;20 cm) were combined into a composite sample. Over 1 kg of fresh soil was collected at each site, air-dried naturally, processed, and sieved before being bagged and labeled. Subsequently, composite surface soil master samples (totaling 5,772 samples) were prepared by mixing processed sub-samples within 4 km\u003csup\u003e2\u003c/sup\u003e grids. Each master sample weighed over 200 g and was sent to certified laboratories for analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To identify crop safety risks, 120 crop seed samples and 120 rhizosphere soil samples were collected at the same sample point over an area of 280 km\u0026sup2;, where the fluorine concentration in soil is more than 550mg/kg 68% of the area, 120 crop seed samples including 60 seed samples each for wheat and peanuts.\u003c/p\u003e \u003cp\u003eThe soil samples were tested at the Henan Rock and Mineral Testing Center and the North China Nonferrous Metals (Sanhe) Laboratory in Yanjiao.The total F is tested using the ion-selective electrode (ISE) by China, and pH tested using pH meter.\u003c/p\u003e \u003cp\u003eThe analytical procedures adhered to the \u003cem\u003eSpecification of Analytical Methods for Regional Geochemical Samples\u003c/em\u003e (DZ/T 0279\u0026ndash;2016)\u003csup\u003e[45]\u003c/sup\u003e, and the results of the logarithmic error (Δlg) and relative standard deviation (RSD%) between the average value of each element determination and the standard indicated that all quality indicators for F analysis met or exceeded the requirements of the \u003cem\u003eSpecification of Multi-Purpose Regional Geochemical Survey\u003c/em\u003e (DZ/T 0258\u0026ndash;2014)(Table.1) \u003csup\u003e[44]\u003c/sup\u003e. The F content in wheat and peanut seeds was determined using the diffusion-spectrophotometric method as outlined in the \u003cem\u003eAnalytic methods for biologic samples in eco-geochemistry assessment\u003c/em\u003e (DZ/T 0253\u0026ndash;2014)\u003csup\u003e[46]\u003c/sup\u003e. The reliability of the fundamental data used in this study was therefore ensured.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable.1 Quality indicators for F analysis\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDetection Limit(\u0026micro;g/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eaccuracy of measurement\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePrecision\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnalysis result\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnalysis result\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAnalysis result\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.13\u0026ndash;6.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData processing and analysis\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData statistics and contour map\u003c/h2\u003e \u003cp\u003eThe testing data processing was conducted using Microsoft Excel, and the basic characteristics of the soil data and evaluation results were analyzed using the \"Integrated Geochemical Exploration System,\" developed by the China Geological Survey. Statistical parameters such as maximum, minimum, mean, standard deviation, median, and coefficient of variation were calculated. Semi-variance analysis was performed using GS\u003csup\u003e+\u003c/sup\u003e software to determine the optimal theoretical semi-variance model and derive the parameters for inverse distance weighting interpolation. Based on these analyses, the spatial distribution contour maps of fluoride concentration in surface soil and the ratio of surface to subsurface soil were generated using the inverse distance weighting method in the \"Integrated Geochemical Exploration System.\" These maps formed the fundamental dataset for this study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCalculation of fluorine concentration in crop seeds\u003c/h3\u003e\n\u003cp\u003eSoil pH is one of the prominent Influencing factors affecting the absorption of fluorine from the soil by crops. The bio-concentration factor (BCF)\u003csup\u003e[ 47\u0026ndash;49]\u003c/sup\u003e was linearly correlated with the total F in the soil when the soil pH is less than 7.5 in the study area.The fluoride concentration in crops was calculated based on the function between fluoride concentration in crop seeds and in soil analyzed statistically using Origin software 2024.There is not correlation between the bio-concentration factor and total F in the soil when the soil pH is less than 7.5 in the study area. The fluoride concentration in crops was calculated by comparing one by one based on the fluoride concentration in crops investigated,assuming that the fluoride accumulated by crops from the soil is the same if the soil pH and the total F are basically same or slight difference .The process is implemented through Python programming.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSpatial geochemical characteristics of F in surface soils\u003c/h2\u003e \u003cp\u003eIn the southeastern and northeastern regions of the Nanyang Basin, isolated areas of surface soil exhibit F concentrations ranging from 2,000 to 22,000 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e, potentially influenced by high geological background levels or anthropogenic activities. After excluding outliers, the fluorine content in surface soil ranged from 271 to 794 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e, with an average value of (532\u0026thinsp;\u0026plusmn;\u0026thinsp;86) mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e, a median of 526 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e, skewness of 1.53, kurtosis of 8.13, and a coefficient of variation of 0.16 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Across different soil parent material zones within the Nanyang Basin, F concentrations in surface soils showed a uniform distribution pattern. The background F concentration in surface soils, calculated as the mean value after excluding outliers (532 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e), was slightly higher than the A-layer soil background values for Henan Province (514 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e) and China (480 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e)\u003csup\u003e[50]\u003c/sup\u003e. This indicates elevated F background values in surface soils of the study area, particularly in regions dominated by residual slope deposits, lacustrine and fluvial-lacustrine sediments, and colluvial deposits.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical characteristics of fluoride content in topsoil\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResearch area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ecoefficient of variation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNanyang Basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e532\u0026thinsp;\u0026plusmn;\u0026thinsp;86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eMaterial source(parent material)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual and Colluvial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluvial Sediment parent material\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluvial-lacustrine sedimentary\u003c/p\u003e \u003cp\u003eparent material\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlluvial parent material\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoess and red soil parent material\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding spatial distribution, 72.54% of the study area showed surface soil F concentrations exceeding the national A-layer soil background value. F concentrations generally decreased from the low mountains and hills on the basin's periphery towards the central plain. High-F areas were primarily distributed in the western and southeastern low mountain regions with residual slope deposits and in the interfluvial zones with lacustrine and fluvial-lacustrine sediments in the downstream river areas. In contrast, regions along river corridors and the eastern plain exhibited background or low F concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccording to the \u003cem\u003eSpecification for the Geochemical Evaluation of Land Quality\u003c/em\u003e (DZ/T 0295\u0026ndash;2016) \u003csup\u003e[45]\u003c/sup\u003e, the \"excess\" F area in the Nanyang Basin's surface soils covered 1,572 km\u003csup\u003e2\u003c/sup\u003e, accounting for 6.80% of the total study area (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The \"high F\" area covered 7,292 km\u003csup\u003e2\u003c/sup\u003e, representing 31.56% of the total area. The \"suitable\" F area comprised only 24.75% of the study area, amounting to 5,720 km\u003csup\u003e2\u003c/sup\u003e. Meanwhile, the \"marginal\" and \"deficient\" F areas accounted for 32.20% (7,440 km\u003csup\u003e2\u003c/sup\u003e) and 4.69% (1,084 km\u003csup\u003e2\u003c/sup\u003e) of the study area, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVertical change characteristics in soils\u003c/h3\u003e\n\u003cp\u003eIn the study area, the F content in deep soils (150\u0026ndash;200 cm) is considered unaffected by contemporary anthropogenic activities and thus represents the natural background value (denoted as A\u003csub\u003ena\u003c/sub\u003e). If the surface soil F content correlates closely with A\u003csub\u003ena\u003c/sub\u003e and the enrichment coefficient is \u0026le;\u0026thinsp;1.0, it suggests that the elevated F levels in surface soils are primarily due to geological and environmental factors, without significant influence from human activities. Conversely, if the surface soil F content shows no correlation with A\u003csub\u003ena\u003c/sub\u003e and exceeds A\u003csub\u003ena\u003c/sub\u003e values, with an enrichment coefficient\u0026thinsp;\u0026ge;\u0026thinsp;1.0, it indicates that anthropogenic activities might contribute to elevated F levels in surface soils.\u003c/p\u003e \u003cp\u003eAnalysis of the enrichment coefficient, defined as the ratio of surface soil F content to deep soil (150\u0026ndash;200 cm) F content, revealed that over 70% of surface soils in the study area have enrichment coefficients between 0.8 and 1.2. Among these, 63% of the regions exhibit coefficients of 0.8\u0026ndash;1.0, primarily in plain areas dominated by farmland, where surface soil F content is similar to that of deep soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This indicates that most of the surface soil F content in the Nanyang Basin is of natural origin. Regions with enrichment coefficients of 1.0\u0026ndash;1.2 are mainly distributed in low mountains and hilly areas, influenced by the weathering of upstream mountain parent rocks. Areas with enrichment coefficients below 0.5 are primarily located in \"marginal\" or \"deficient\" F regions, where surface soil F content is significantly lower than that of deep soil. Regions with coefficients between 0.5 and 0.8 are distributed in \"marginal\" F areas, while those with coefficients\u0026thinsp;\u0026lt;\u0026thinsp;0.5 are found in \"deficient\" F areas. These patterns are associated with favorable conditions for soil erosion in these locations. The high-F areas of interest in this study, characterized by enrichment coefficients\u0026thinsp;\u0026gt;\u0026thinsp;1.2, are predominantly located in flat farmland regions or zones affected by industrial waste emissions (orange and red areas in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Notably, regions with coefficients\u0026thinsp;\u0026gt;\u0026thinsp;1.5 exhibit significantly elevated surface soil F levels, forming patchy distributions in the southeastern and northwestern parts of the basin, likely attributable to pollution from local human activities.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, F content decreases progressively from the surface to deeper soil parent material layers, suggesting that high-F levels in surface soils in areas with \"excessive\" F content (\u0026gt;\u0026thinsp;700 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e) \u003csup\u003e[45;51\u0026ndash;52]\u003c/sup\u003e are not strongly related to local geological conditions. Studies indicate that in natural, undisturbed soil profiles unaffected by anthropogenic pollutants, F content typically increases with depth, a trend particularly pronounced in regions with \"marginal\" surface soil F content (400\u0026ndash;500 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eHowever, in F-polluted areas, F content decreases from the surface downward \u003csup\u003e[53]\u003c/sup\u003e. In high-F regions (550\u0026ndash;700 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e) and \"suitable\" areas (500\u0026ndash;550 mg\u0026middot;kg\u003csup\u003e-1\u003c/sup\u003e) in the study area, soil profiles exhibit a decreasing trend of F content from the surface to deeper layers.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFluoride content in crops\u003c/h2\u003e \u003cp\u003eFor this study, the northern region of Zhenping County and Fangcheng County in the Nanyang Basin, identified as having \"high\" or \"excessive\" F levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), was selected as the \"farmland safety risk identification\" area. In addition to the previously collected soil samples, 60 samples each of wheat and peanut crops, the main cultivated crops in the Nanyang Basin, were collected. Test results showed that F content in wheat grains ranged from 0.45 to 0.79 mg/kg, while F content in peanut grains ranged from 0.21 to 0.49 mg/kg(Table.3).\u003c/p\u003e \u003cp\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 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical characteristics of fluoride content in crops\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrops\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeanut\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSources and causes of F anomalies in surface soils\u003c/h2\u003e \u003cp\u003eThe vertical variation of F content in soils is closely related to its source. Geological background conditions primarily control F levels in sub-surface soils \u003csup\u003e[42\u0026ndash;43]\u003c/sup\u003e, while external factors (e.g., human activities) modify surface soil F content, influencing vertical and local profile distribution patterns \u003csup\u003e[8;38,54\u0026ndash;55]\u003c/sup\u003e. For instance, the annual F input from agricultural fertilization in China is less than 0.5% of total soil F content based on the datum form artical \u003csup\u003e[27;56]\u003c/sup\u003e, and the atmospheric F deposition flux investigated the study area ranges from 17.69 to 76.25 mg/a\u0026middot;m\u003csup\u003e2\u003c/sup\u003e. The ratio of surface soil to deep soil is significantly positively correlated with the atmospheric fluorine deposition,and the changes were also significantly positively correlated with the atmospheric fluorine deposition. Their correlation coefficients are 0.76(p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001)and 0.59(p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively(Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).The correlation indicates with the atmospheric fluorine deposition may be one of the main sources of fluorine in soil and the predomaint influencing factors of spatial distribution changes.Long-term cumulative effects and spatial variability in F input from agricultural fertilization and atmospheric dust deposition have altered the surface soil F distribution in localized areas of the Nanyang Basin.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of safety risks in high-F farmland areas\u003c/h2\u003e \u003cp\u003eThis study focuses on identifying the safety risks posed by high F levels in surface soils to major crops in farmland areas. F is an essential trace element for the human body, and dietary intake through food and drinking water is a primary source of F. However, F accumulates in the human body, and excessive intake can be detrimental to health. Accordingly, health authorities have established safety standards for F content in soils and crops to safeguard human health.\u003c/p\u003e \u003cp\u003ePrevious studies indicate that the average F content in the human body is approximately 2.6 g, with a daily requirement of 1.0 mg \u003csup\u003e[57]\u003c/sup\u003e. The Chinese Ministry of Health recommends a safe daily F intake limit of 3.5 mg/day, while the World Health Organization (WHO) suggests a limit of \u0026lt;\u0026thinsp;2 mg/day \u003csup\u003e[57]\u003c/sup\u003e. The \u003cem\u003eLimits of Contaminants in Food\u003c/em\u003e (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2005) specifies that the maximum allowable F content in wheat grains is 1.0 mg/kg, and for peanut grains, it is 1.5 mg/kg \u003csup\u003e[58]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAssuming an average daily consumption of 0.5 kg of wheat flour, the estimated F intake from consuming flour produced in these high-F areas would not exceed 0.37 mg/day based on the tested result, which is below the recommended F intake limits established by health authorities. These findings indicate that the F content in wheat and peanut grains from the high-F areas of the Nanyang Basin is below the safety thresholds specified in the \u003cem\u003eLimits of Contaminants in Food\u003c/em\u003e (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2005). Thus, the surface soil F levels in farmland areas of the Nanyang Basin are generally within a \"safe\" range.\u003c/p\u003e \u003cp\u003eSoluble F is the most bioavailable form for crops \u003csup\u003e[41]\u003c/sup\u003e.Research has shown that crop uptake of F from soil is influenced by the amount of soluble F \u003csup\u003e[53\u0026ndash;54;56]\u003c/sup\u003e, which is determined by the total F content, its forms, and the soil's physicochemical properties. The rhizosphere soil pH is one of the main factors affecting the bio-concentration factor (BCF)\u003csup\u003e[47\u0026ndash;49]\u003c/sup\u003e.The Statistical analyses in this study revealed a relationship between the bio-concentration factor and the total F content in soils with pH\u0026thinsp;\u0026lt;\u0026thinsp;7.5 (moderately acidic soils) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). However, this correlation was weak for wheat grains in soils with pH\u0026thinsp;\u0026gt;\u0026thinsp;7.5 (alkaline soils) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). The relationship between peanut grain F content and total soil F content (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb) exhibited a similar trend to that observed in wheat ( 7a).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the observed relationships between the bio-concentration factor and total F content of rhizosphere soils, and the surface soil pH value was used as a primary physicochemical indicator for farmland soils. Combined with previously obtained surface soil F content data, a simulation analysis was conducted to estimate the cumulative F content in wheat and peanut grains for each survey unit in the study area. The simulation results indicate that the F content in wheat grains across the Nanyang Basin ranges from 0.21 to 1.34 mg/kg, while the F content in peanut grains ranges from 0.17 to 0.72 mg/kg (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These findings confirm that the F content in peanut grains is below the limits specified in the \u003cem\u003eLimits of Contaminants in Food\u003c/em\u003e (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2005). However, in certain units, the F content in wheat grains exceeds the specified limits. Spatially, regions with wheat grain F content between 0.80 and 1.0 mg/kg are distributed as isolated patches(orange and red areas in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), primarily in alkaline soil zones with high total soil F content (\u0026gt;\u0026thinsp;1400 mg/kg) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These regions account for less than 5% of the study area. In over 99.5% of the study area, the F content in wheat grains is less than 0.80 mg/kg, with areas where F content is below 0.5 mg/kg comprising 63.76% of the total study area. These low-F regions are mainly located in the eastern part of the Nanyang Basin, where surface soils have low pH values, characterized by strong acidity or acidity. In farmland areas with acidic to neutral soils, the maximum potential dietary F intake from wheat consumption is less than 0.68 mg, which is below the intake limits recommended by the Chinese Ministry of Health and the WHO. These results confirm that the high-F farmland areas in the Nanyang Basin remain in a \"safe\" state with relatively low risk.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSimulation statistical characteristics of fluoride content in crop grain in the Nanyang Basin\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrop type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeanut\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe surface soils of the Nanyang Basin have relatively high F content, with background values exceeding those of Henan Province and national A-layer soil background values. The enrichment coefficient analysis indicates that the geological background exerts a certain influence on the spatial distribution of F content in surface soils. However, the cumulative inputs of F through long-term agricultural fertilization and atmospheric dust deposition also play a significant role in the formation of high-F zones in localized areas.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIn the Nanyang Basin, the \"excessive\" and \"high\" F areas cover 1,572 km\u0026sup2; and 7,292 km\u0026sup2;, accounting for 6.80% and 31.56% of the total study area, respectively. These areas represent potential risk zones for crop safety and require enhanced monitoring and management.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIn high-F areas of the Nanyang Basin, the F content in wheat and peanut grains is within acceptable levels for human consumption, below the limits specified in the \u003cem\u003eLimits of Contaminants in Food\u003c/em\u003e (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2005). Moreover, the estimated dietary F intake from consuming wheat grains is lower than the limits recommended by the Chinese Ministry of Health and the WHO. Thus, the F content in surface soils across the agricultural lands of the Nanyang Basin is generally within a \"safe\" range, with low associated risks.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of Competing Interest\u003c/h2\u003e \u003cp\u003es: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 \u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e \u003cp\u003eThis research was funded by the Geological Survey and Mineral Resources Assessment Project (102202220200000009064, DD20230557), Henan Institute of Geological Sciences Research Project(JTZCKY2023015)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen, J., et al. Assessment of arsenic and fluoride pollution in groundwater in Dawukou area, Northwest China, and the associated health risk for inhabitants. Environmental Earth Sciences.2017,76(8).\u003c/li\u003e\n\u003cli\u003eBhattacharya, P., et al.. Assessment of potential health risk of fluoride consumption through rice, pulses, and vegetables in addition to consumption of fluoride-contaminated drinking water of West Bengal, India. Environmental Science and Pollution Research.2017, 24(25): 20300-20314\u003c/li\u003e\n\u003cli\u003eAndhra Pradesh Nagaraju, A.;Thejaswi, A.;Aitkenhead-Peterson, J.A..Fluoride and heavy metal accumulation by vegetation in the fluoride affected area of Talupula, Anantapur district, Andhra Pradesh.Journal of the Geological Society of India,2017, 89(1): 27-32\u003c/li\u003e\n\u003cli\u003eNichole R. Johnston，Scott A. Strobel. Principles of fluoride toxicity and the cellular response: a review. 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Zhejia University,2006.\u003c/li\u003e\n\u003cli\u003eNational Health Commission of the People\u0026apos;s Republic of China,State Administration for Market Regulation《Maximum levels of contaminants in food》( GB 2762-2005).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Nanyang Basin, Surface soil, Fluorine (F), Wheat and peanut crops, Safety risk, Survey and monitoring","lastPublishedDoi":"10.21203/rs.3.rs-6223153/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6223153/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and aims\u003c/strong\u003e Fluorine (F) is an essential trace element for humans, but excessive F poses risks to human health. Consequently, the sources and safety risks of high-F soils have garnered significant attention. The Nanyang Basin is a major agricultural region in China, known for its wheat and other staple crops.\u003c/p\u003e\n\u003cp\u003eThis study investigated the spatial geochemical characteristics of fluoride in surface soils (0–20 cm) and the vertical change characteristics, analyzed the relationship of fluorine content between crop and soil, and identified its potential safety risks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e We collected soil samples regionally and crop samples and rhizosphere soil in typical areas, analyzed the geochemical distribution of soil F and its relationship with crop uptake integrating geostatistical analysis with GIS techniques, were.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e The background F content in surface soils of the Nanyang Basin is higher than the background levels of topsoil in Henan Province and China. The primary source of F in surface soils is external input (pollution-related), with geological background having a secondary influence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e The high-F surface soils in agricultural areas of the basin have a relatively low impact on the safety of wheat and peanut grains. The F content in crop grains is generally below the maximum allowable limits for food, indicating an overall \"safe\" status, except that a few areas exceeding the maximum allowable limits for food contamination in alkaline soil regions with high F levels,and identifying these areas as potential safety risk zones requiring enhanced monitoring and management.\u003c/p\u003e","manuscriptTitle":"Geochemical characteristics and safety risk identification of high-fluoride soils in the Nanyang Basin","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 06:32:51","doi":"10.21203/rs.3.rs-6223153/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a4b15ea0-7907-4899-99b0-e76724efdb59","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T18:19:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-31 06:32:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6223153","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6223153","identity":"rs-6223153","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}