Source, Distribution, and Risk Estimation of Hazardous Elements in Farmland Soils in a Typical Alluvial–Lacustrine Transition Basin, Hunan Province
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Profile
2.2. Sample Test Methods
2.3. Statistical Analysis of the Data
2.3.1. Pollution Index
2.3.2. Geo-Accumulation Index
2.3.3. Potential Ecological Risk Index
2.3.4. Positive Matrix Factorization Model
2.4. Data Processing
3. Results and Discussion
3.1. Descriptive Statistics of Heavy Metals and Metalloids in Soils
3.2. Spatial Distribution of Heavy Metals and Metalloids in Topsoil
3.2.1. Distribution of Total Heavy Metals and Metalloids
3.2.2. Distributions of Bioavailable Heavy Metals and Metalloids
3.3. Distribution of Heavy Metals and Metalloids in Profile Soil
3.3.1. Distribution of Total Heavy Metals and Metalloids
3.3.2. Distribution of Bioavailable Metals in Profile Soil
3.4. pH and Organic Matter Are the Main Factors Affecting the Spatial Distribution of Heavy Metals in Soil
3.5. Analysis of the Sources of Heavy Metals and Metalloids
3.6. Risk Assessment of Soil Heavy Metals and Metalloids
4. Conclusions
- (1)
- The average concentrations of heavy metals and metalloids in the topsoil and profile soil samples were less than the pollution risk screening values. However, they exceeded the heavy metal background values for the Dongting Lake area. The variability of Sb in the topsoil and profile soil samples exceeded 100%, indicating that soil Sb was strongly regulated by anthropogenic activities in the study area.
- (2)
- The bioavailability of Cd and Pb in topsoil was mainly influenced by soil pH and organic matter, whereas that of topsoil Zn was mainly influenced by pH. Soil pH, organic matter, and clay content had a combined effect on bioavailable Cd in the profile soil. pH was the main factor affecting bioavailable Pb, organic matter was the main regulator of bioavailable As and Zn, and soil clay content was the main factor affecting bioavailable Sb.
- (3)
- Qualitative and quantitative analyses of the sources of soil metals and metalloids revealed that Sb (65.3%) was mainly derived from mining activities, Cd (53.2%) and Zn (53.7%) were related to industrial production and agricultural fertilization emissions, and As (55.6%) was mainly derived from weathering of the soil parent material. Pb in soil was related to both natural and anthropogenic factors, with the latter including agricultural fertilization, vehicle emissions, and the atmospheric deposition of industrial emissions.
- (4)
- There were low soil pollution levels of As, Pb, and Zn in the top and profile soil samples. Heavy metal pollution in topsoil was relatively serious compared to that in the profile soil samples, particularly for Sb; this should receive increasing attention. Although there is a relatively low potential ecological risk in the study area, there is a need for increased attention to the potential ecological risk of Cd in topsoil.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Yang, Q.; Li, Z.; Lu, X.; Duan, Q.; Huang, L.; Bi, J. A review of soil heavy metal pollution from industrial and agricultural regions in China: Pollution and risk assessment. Sci. Total Environ. 2018, 642, 690–700. [Google Scholar] [PubMed]
- Liu, L.; Li, W.; Song, W.; Guo, M. Remediation techniques for heavy metal-contaminated soils: Principles and applicability. Sci. Total Environ. 2018, 633, 206–219. [Google Scholar] [CrossRef] [PubMed]
- MEP of China (Ministry of Environmental Protection of China). National Soil Pollution Survey Bulletin. 2014. Available online: http://www.gov.cn/foot/site1/20140417/782bcb88840814ba158d01.pdf (accessed on 16 June 2022).
- Qin, G.; Niu, Z.; Yu, J.; Li, Z.; Ma, J.; Xiang, P. Soil heavy metal pollution and food safety in China: Effects, sources and removing technology. Chemosphere 2021, 267, 129205. [Google Scholar] [CrossRef] [PubMed]
- Ke, W.; Zeng, J.; Zhu, F.; Luo, X.; Feng, J.; He, J.; Xue, S. Geochemical partitioning and spatial distribution of heavy metals in soils contaminated by lead smelting. Environ. Pollut. 2022, 307, 119486. [Google Scholar] [CrossRef]
- Xu, L.; Dai, H.; Skuza, L.; Xu, J.; Shi, J.; Wang, Y.; Shentu, J.; Wei, S. Integrated survey on the heavy metal distribution, sources and risk assessment of soil in a commonly developed industrial area. Ecotoxicol. Environ. Saf. 2022, 236, 113462. [Google Scholar] [CrossRef]
- Wang, Y.; Duan, X.; Wang, L. Spatial distribution and source analysis of heavy metals in soils influenced by industrial enterprise distribution: Case study in Jiangsu Province. Sci. Total Environ. 2020, 710, 134953. [Google Scholar]
- Ji, Y.; Xu, J.; Zhu, L. Impact of a super typhoon on heavy metal distribution, migration, availability in agricultural soils. Environ. Pollut. 2021, 289, 117835. [Google Scholar] [CrossRef]
- Li, S.; Zhao, B.; Jin, M.; Hu, L.; Zhong, H.; He, Z. A comprehensive survey on the horizontal and vertical distribution of heavy metals and microorganisms in soils of a Pb/Zn smelter. J. Hazard. Mater. 2020, 400, 123255. [Google Scholar] [CrossRef]
- Fei, X.; Lou, Z.; Xiao, R.; Ren, Z.; Lv, X. Source analysis and source-oriented risk assessment of heavy metal pollution in agricultural soils of different cultivated land qualities. J. Clean. Prod. 2022, 341, 130942. [Google Scholar]
- Liu, R.; Bao, K.; Yao, S.; Yang, F.; Wang, X. Ecological risk assessment and distribution of potentially harmful trace elements in lake sediments of Songnen Plain, NE China. Ecotoxicol. Environ. Saf. 2018, 163, 117–124. [Google Scholar] [CrossRef]
- Zhu, Y.; Sun, X.; Hu, Y. Content characteristics of heavy metals in Artemisia selengensis in Datong Lake and East Dongting Lake. Jiangsu Agric. Sci. 2014, 42, 248–250. [Google Scholar]
- Facchinelli, A.; Sacchi, E.; Mallen, L. Multivariate statistical and GIS-based approach to identify heavy metal sources in soils. Environ. Pollut. 2001, 114, 313–324. [Google Scholar] [PubMed]
- Sun, C.; Liu, J.; Wang, Y.; Sun, L.; Yu, H. Multivariate and geostatistical analyses of the spatial distribution and sources of heavy metals in agricultural soil in Dehui, Northeast China. Chemosphere 2013, 92, 517–523. [Google Scholar] [CrossRef] [PubMed]
- Khan, S.; Cao, Q.; Zheng, Y.M.; Huang, Y.Z.; Zhu, Y.G. Health risks of heavy metals in contaminated soils and food crops irrigated with wastewater in Beijing, China. Environ. Pollut. 2008, 152, 686–692. [Google Scholar] [CrossRef] [PubMed]
- Han, W.; Gao, G.; Geng, J.; Li, Y.; Wang, Y. Ecological and health risks assessment and spatial distribution of residual heavy metals in the soil of an e-waste circular economy park in Tianjin, China. Chemosphere 2018, 197, 325–335. [Google Scholar] [CrossRef]
- Dong, B.; Zhang, R.; Gan, Y.; Cai, L.; Freidenreich, A.; Wang, K.; Guo, T.; Wang, H. Multiple methods for the identification of heavy metal sources in cropland soils from a resource-based region. Sci. Total Environ. 2019, 651, 3127–3138. [Google Scholar] [CrossRef] [PubMed]
- Liu, H.; Zhang, Y.; Yang, J.; Wang, H.; Li, Y.; Shi, Y.; Li, D.; Holm, P.E.; Ou, Q.; Hu, W. Quantitative source apportionment, risk assessment and distribution of heavy metals in agricultural soils from southern Shandong Peninsula of China. Sci. Total Environ. 2021, 767, 144879. [Google Scholar] [CrossRef] [PubMed]
- Lv, B.; Xing, M.; Yang, J. Speciation and transformation of heavy metals during vermicomposting of animal manure. Bioresour. Technol. 2016, 209, 397–401. [Google Scholar] [CrossRef]
- Tong, T. Element concentrations in river delta sediments and mineral resources potential in the drainage basin: A case study in the xiangjiang, zishui, yuanjiang, and lishui rivers basins. Quat Sci. 2005, 3, 298–305. [Google Scholar]
- Müller, G. Schwermetalle in den sedimenten des Rheins-Veräderungenseit. Umschau 1971, 79, 778–783. [Google Scholar]
- Zhang, J. Soil geochemical baseline and pollution level division in Dongting lake area. Geophys. Geochem. Explor. 2014, 38, 793–799. [Google Scholar]
- Zhong, L.; Liu, L.; Liu, Y. Natural Disaster Risk Assessment of Grain Production in Dongting Lake Area, China. Agric. Agric. Sci. Procedia 2010, 1, 24–32. [Google Scholar] [CrossRef]
- Hakanson, L. An ecological risk index for aquatic pollution control.a sedimentological approach. Water Res. 1980, 14, 975–1001. [Google Scholar] [CrossRef]
- Wu, J.; Li, J.; Teng, Y.; Chen, H.; Wang, Y. A partition computing-based positive matrix factorization (PC-PMF) approach for the source apportionment of agricultural soil heavy metal contents and associated health risks. J. Hazard. Mater. 2020, 388, 121766. [Google Scholar] [CrossRef]
- Magesh, N.S.; Tiwari, A.; Botsa, S.M.; da Lima Leitao, T. Hazardous heavy metals in the pristine lacustrine systems of Antarctica: Insights from PMF model and ERA techniques. J. Hazard. Mater. 2021, 412, 125263. [Google Scholar] [CrossRef]
- Lin, Y.; Wang, J.; Lin, C. Vertical changes in the geochemical distributions of iron, manganese and heavy metals in wetland soil cores from cold temperate zones in northeastern China. J. Hazard. Mater. 2022, 6, 100085. [Google Scholar] [CrossRef]
- Li, K.; Wang, J.; Zhang, Y. Heavy metal pollution risk of cultivated land from industrial production in China: Spatial pattern and its enlightenment. Sci. Total Environ. 2022, 828, 154382. [Google Scholar] [CrossRef]
- Wang, Y.; Zhang, L.; Wang, J.; Lv, J. Identifying quantitative sources and spatial distributions of potentially toxic elements in soils by using three receptor models and sequential indicator simulation. Chemosphere 2020, 242, 125266. [Google Scholar] [CrossRef]
- Wu, C.; Wu, J.; Luo, Y.; Zhang, H.; Teng, Y. Statistical and geoestatistical characterization of heavy metal concentrations in a contaminated area taking into account soil map units. Geoderma 2008, 144, 171–179. [Google Scholar] [CrossRef]
- Cheng, W.; Lei, S.; Bian, Z.; Zhao, Y.; Li, Y.; Gan, Y. Geographic distribution of heavy metals and identification of their sources in soils near large, open-pit coal mines using positive matrix factorization. J. Hazard. Mater. 2020, 387, 121666. [Google Scholar] [CrossRef]
- Wang, Y.; Chen, M.; Wang, D.; Xu, Y.; Chen, Z.; Liang, T. Discussion on main antimony ore concentration areas and their resource potential in China. Geol. China 2013, 40, 1366–1378. [Google Scholar]
- Yu, H.; Hou, J.; Dang, Q.; Cui, D.; Xi, B.; Tan, W. Decrease in bioavailability of soil heavy metals caused by the presence of microplastics varies across aggregate levels. J. Hazard. Mater. 2020, 395, 122690. [Google Scholar] [CrossRef]
- Lei, M.; Liao, B.; Qin, P. Assessment of bioavailability heavy metal in contaminated soils with chemical fractionation. Ecol. Environ. 2007, 5, 1551–1556. [Google Scholar]
- Alvarenga, P.; Palma, P.; de Varennes, A.; Cunha-Queda, A.C. A contribution towards the risk assessment of soils from the São Domingos Mine (Portugal): Chemical, microbial and ecotoxicological indicators. Environ. Pollut. 2012, 161, 50–56. [Google Scholar] [CrossRef] [PubMed]
- Li, Q.; Wang, Y.; Li, Y.; Li, L.; Tang, M.; Hu, W.; Chen, L.; Ai, S. Speciation of heavy metals in soils and their immobilization at micro-scale interfaces among diverse soil components. Sci. Total Environ. 2022, 825, 153862. [Google Scholar] [CrossRef]
- Liu, C.; Huang, Y.; Lei, M.; Hao, X.; Li, X.; Tie, B. Assessment of ecological risks of heavy metal contaminated soils in the Zijiang river region by toxicity characteristic leaching procedure. Environ. Chem. 2011, 30, 1582–1589. [Google Scholar]
- Gonzalez, L.H.; Rivera, V.A.; Phillips, C.B.; Haug, L.A.; Hatch, S.L.; Yeager, L.E.; Chang, H.; Alvarez, J.; Gnaedinger, K.J.; Miller, W.M. Sediments, Characterization of soil profiles and elemental concentrations reveals deposition of heavy metals and phosphorus in a Chicago-area nature preserve, Gensburg Markham Prairie. J. Soils Sediments 2019, 19, 3817–3831. [Google Scholar] [CrossRef]
- Li, Z.; Huang, B.; Huang, J.; Chen, G.; Zhang, C.; Nie, X. Influence of removal of organic matter and iron and manganese oxides on cadmium adsorption by red paddy soil aggregates. RSC Adv. 2015, 5, 90588–90595. [Google Scholar] [CrossRef]
- Mao, P.; Zhuang, P.; Li, F.; McBride, M.B.; Ren, W.; Li, Y.; Mo, H.; Fu, H.; Li, Z. Phosphate addition diminishes the efficacy of wollastonite in decreasing Cd uptake by rice (Oryza sativa L.) in paddy soil. Sci. Total Environ. 2019, 687, 441–450. [Google Scholar] [CrossRef]
- El-Naggar, A.; Shaheen, S.M.; Ok, Y.S.; Rinklebe, J. Biochar affects the dissolved and colloidal concentrations of Cd, Cu, Ni, and Zn and their phytoavailability and potential mobility in a mining soil under dynamic redox-conditions. Sci. Total Environ. 2018, 624, 1059–1071. [Google Scholar] [CrossRef]
- Verbeeck, M.; Thiry, Y.; Smolders, E. Soil organic matter affects arsenic and antimony sorption in anaerobic soils. Environ. Pollut. 2020, 257, 113566. [Google Scholar] [CrossRef] [PubMed]
- Usiyama, T.; Fukushi, K. Predictive model for Pb(II) adsorption on soil minerals (oxides and low-crystalline aluminum silicate) consistent with spectroscopic evidence. Geochim. Cosmochim. Acta. 2016, 190, 134–155. [Google Scholar] [CrossRef]
- Shen, B.; Wang, X.; Zhang, Y.; Zhang, M.; Wang, K.; Xie, P.; Ji, H. The optimum pH and Eh for simultaneously minimizing bioavailable cadmium and arsenic contents in soils under the organic fertilizer application. Sci. Total Environ. 2020, 711, 135229. [Google Scholar] [CrossRef] [PubMed]
- Bondu, R.; Cloutier, V.; Rosa, E.; Benzaazoua, M. Mobility and speciation of geogenic arsenic in bedrock groundwater from the Canadian Shield in western Quebec, Canada. Sci. Total Environ. 2017, 574, 509–519. [Google Scholar] [CrossRef]
- Wu, Q.; Hu, W.; Wang, H.; Liu, P.; Wang, X.; Huang, B. Spatial distribution, ecological risk and sources of heavy metals in soils from a typical economic development area, Southeastern China. Sci. Total Environ. 2021, 780, 146557. [Google Scholar] [CrossRef]
- Sepehrnia, N.; Fishkis, O.; Huwe, B. Natural colloid mobilization and leaching in wettable and water repellent soil under saturated condition. J. Hydrol. Hydromech. 2018, 66, 50–58. [Google Scholar] [CrossRef]
- Han, C.; Wang, L.; Gong, Z.; Xu, H. Chemical forms of soil heavy metals and their environmental significance. Chin. J. Ecol. 2005, 12, 1499–1502. [Google Scholar]
- Wang, S.; Cai, L.-M.; Wen, H.-H.; Luo, J.; Wang, Q.-S.; Liu, X. Spatial distribution and source apportionment of heavy metals in soil from a typical county-level city of Guangdong Province, China. Sci. Total Environ. 2019, 655, 92–101. [Google Scholar] [CrossRef]
- Mu, H.Y.; Zhuang, Z.; Li, Y.M.; Qiao, Y.; Chen, Q.; Xiong, J. Heavy Metal Contents in Animal Manure in China and the Related Soil Accumulation Risks. Environ. Sci. 2020, 41, 986–996. [Google Scholar]
- Liang, J.; Feng, C.; Zeng, G.; Gao, X.; Zhong, M.; Li, X.; Li, X.; He, X.; Fang, Y. Spatial distribution and source identification of heavy metals in surface soils in a typical coal mine city, Lianyuan, China. Environ. Pollut. 2017, 225, 681–690. [Google Scholar] [CrossRef]
- Wang, Y.; Xu, Y.; Zhang, C.; Wang, C.; Chen, Z.; Huang, F. Summary of Metallogenic Regularity of Antimony Deposits in China. Acta Geol. Sin. 2014, 88, 2208–2215. [Google Scholar]
- Mo, C.; Wu, F.; Fu, Z.; Zhu, J.; Ran, L. Antimony, Arsenic and Mercury Pollution in Agricultural Soil of Antimony Mine Area in Xikuangshan, Hunan. Acta Mineral. Sin. 2013, 33, 344–350. [Google Scholar]
- Tao, Z.; Guo, Q.; Wei, R.; Dong, X.; Han, X.; Guo, Z. Atmospheric lead pollution in a typical megacity: Evidence from lead isotopes. Sci. Total Environ. 2021, 778, 145810. [Google Scholar] [CrossRef] [PubMed]
- Hu, W.; Wang, H.; Dong, L.; Huang, B.; Borggaard, O.K.; Bruun Hansen, H.C.; He, Y.; Holm, P.E. Source identification of heavy metals in peri-urban agricultural soils of southeast China: An integrated approach. Environ. Pollut. 2018, 237, 650–661. [Google Scholar] [CrossRef]
- Osman, K. Soil Resources and Soil Degradation. In Soil Degradation, Conservation and Remediation; Springer: Dordrecht, The Netherlands, 2014; pp. 1–43. [Google Scholar]
- Feng, W.; Guo, Z.; Peng, C.; Xiao, X.; Shi, L.; Zeng, P.; Ran, H.; Xue, Q. Atmospheric bulk deposition of heavy metal(loid)s in central south China: Fluxes, influencing factors and implication for paddy soils. J. Hazard. Mater. 2019, 371, 634–642. [Google Scholar] [CrossRef]
- Guo, X.; Wang, K.; He, M.; Liu, Z.; Yang, H.; Li, S. Antimony smelting process generating solid wastes and dust: Characterization and leaching behaviors. J. Environ. Sci. 2014, 26, 1549–1556. [Google Scholar] [CrossRef]
- Ding, J.; Zhang, Y.; Ma, Y.; Wang, Y.; Zhang, J.; Zhang, T. Metallogenic characteristics and resource potential of antimony in China. J. Geochem.Explor. 2021, 230, 106834. [Google Scholar] [CrossRef]
- Hao, C.; Zhang, W.; Gui, H. Hydrogeochemistry characteristic contrasts between low- and high-antimony in shallow drinkable groundwater at the largest antimony mine in hunan province, China. Appl. Geochem. 2020, 117, 104584. [Google Scholar] [CrossRef]
- Zhang, Z.; Lu, Y.; Li, H.; Tu, Y.; Liu, B.; Yang, Z. Assessment of heavy metal contamination, distribution and source identification in the sediments from the Zijiang River, China. Sci. Total Environ. 2018, 645, 235–243. [Google Scholar] [CrossRef]
Sample No. | Longitude /° | Latitude /° | Sample Depth /cm | Sediment Type I | Sediment Type II |
---|---|---|---|---|---|
XB-P01-01 | 112.7136 | 28.7606 | 0–30 | Downstream lacustrine deposits | Offshore |
XB-P01-02 | 112.6733 | 28.7678 | 0–30 | Downstream lacustrine deposits | Nearshore |
XB-P01-03 | 112.6244 | 28.7539 | 0–30 | Downstream lacustrine deposits | Nearshore |
XB-P01-04 | 112.6426 | 28.7453 | 0–30 | Downstream lacustrine deposits | Nearshore |
XB-P01-05 | 112.6680 | 28.7261 | 0–30 | Downstream lacustrine deposits | Offshore |
XB-P02-01 | 112.5980 | 28.7189 | 0–30 | Midstream alluvium | Nearshore |
XB-P02-02 | 112.5668 | 28.6988 | 0–30 | Midstream alluvium | Nearshore |
XB-P02-03 | 112.5999 | 28.6690 | 0–30 | Midstream alluvium | Offshore |
XB-P02-04 | 112.6479 | 28.6954 | 0–30 | Midstream alluvium | Offshore |
LX-P01-01 | 112.5654 | 28.6441 | 0–30 | Midstream alluvium | Offshore |
LX-P01-02 | 112.5179 | 28.6738 | 0–30 | Midstream alluvium | Nearshore |
LX-P01-03 | 112.4743 | 28.6369 | 0–30 | Upstream alluvium | Nearshore |
LX-P01-04 | 112.5160 | 28.6067 | 0–30 | Upstream alluvium | Offshore |
LX-P02-01 | 112.3832 | 28.5894 | 0–30 | Midstream alluvium | Nearshore |
LX-P02-02 | 112.4259 | 28.6216 | 0–30 | Upstream alluvium | Nearshore |
LX-P02-03 | 112.4614 | 28.5794 | 0–30 | Upstream alluvium | Offshore |
LX-P02-04 | 112.4158 | 28.5616 | 0–30 | Upstream alluvium | Offshore |
XB-P01 * | 112.6745 | 28.7479 | 0–160 | Downstream lacustrine deposits | Offshore |
XB-P02 * | 112.6164 | 28.6912 | 0–160 | Midstream alluvium | Offshore |
LX-P01 * | 112.5212 | 28.6198 | 0–160 | Upstream alluvium | Offshore |
LX-P02 * | 112.4463 | 28.5866 | 0–140 | Upstream alluvium | Offshore |
No. | Forms | Extraction Methods |
---|---|---|
I | water-soluble fraction | 2.5000 g sample 25 mL water extraction |
II | ion-exchangeable fraction | The residue was extracted with 25 mL MgCl2 solution |
T | Total content | 0.1000 g soil was digested with 2:2:1 HNO3-HF-HClO4 at 180–210 °C |
Element | As | Cd | Pb | Zn | Sb | pH | OM | |
---|---|---|---|---|---|---|---|---|
Units | mg·kg−1 | - | % | |||||
Topsoil | Max | 25.9 | 0.86 | 42.6 | 114.5 | 46.38 | 7.78 | 2.89 |
Min | 8.5 | 0.1 | 27.6 | 60.8 | 1.4 | 5.03 | 0.44 | |
Mean | 16.33 | 0.39 | 34.74 | 84.97 | 7.35 | 6.03 | 1.55 | |
SD | 4.26 | 0.19 | 3.71 | 17.69 | 10.56 | 0.68 | 0.69 | |
CV(%) | 26.06 | 48.09 | 10.67 | 20.82 | 143.72 | 11.32 | 44.67 | |
Profile Soil | Max | 41.6 | 0.32 | 51.8 | 151.5 | 15.35 | 7.14 | 1.07 |
Min | 7.3 | 0.03 | 24.39 | 41.7 | 0.75 | 4.94 | 0.19 | |
Mean | 19.46 | 0.13 | 31.97 | 89.22 | 2.54 | 6.15 | 0.43 | |
SD | 7.32 | 0.07 | 5.99 | 26.08 | 2.58 | 0.64 | 0.21 | |
CV(%) | 37.63 | 59.41 | 18.73 | 29.23 | 101.5 | 10.43 | 48.57 | |
Background value of Dongting Lake area [28] | 12.35 | 0.31 | 31.69 | 86.1 | 1.32 | |||
Risk screening value (GB 15618-2018) | 45 | 0.3 | 80 | 200 | pH ≤ 5.5 | |||
40 | 0.4 | 100 | 200 | 5.5 < pH ≤ 6.5 | ||||
35 | 0.6 | 140 | 250 | 6.5 < pH ≤ 7.5 |
As (%) | Cd (%) | Pb (%) | Zn (%) | Sb (%) | pH (-) | OM (%) | |
---|---|---|---|---|---|---|---|
Max | 6.02 | 59.96 | 6.66 | 5.16 | 8.72 | 7.78 | 2.89 |
Min | 0.16 | 9.17 | 0.22 | 0.39 | 0.72 | 5.03 | 0.44 |
Mean | 1.81 | 37.76 | 2.31 | 2.23 | 2.11 | 6.03 | 1.55 |
SD | 1.38 | 13.61 | 1.67 | 1.10 | 1.82 | 0.68 | 0.69 |
CV (%) | 76.17 | 36.05 | 72.48 | 49.21 | 86.31 | 11.32 | 44.67 |
As (%) | Cd (%) | Pb (%) | Zn (%) | Sb (%) | pH (-) | OM (%) | |
---|---|---|---|---|---|---|---|
Max | 0.98 | 49.37 | 5.59 | 3.18 | 15.40 | 7.14 | 1.07 |
Min | 0.10 | 4.55 | 0.23 | 0.58 | 0.10 | 4.94 | 0.19 |
Mean | 0.41 | 21.00 | 2.12 | 1.40 | 1.58 | 6.14 | 0.42 |
SD | 0.21 | 12.12 | 1.32 | 0.53 | 2.45 | 0.65 | 0.21 |
CV (%) | 50.86 | 57.71 | 62.12 | 38.15 | 154.63 | 10.55 | 49.76 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Chen, Z.; Wang, B.; Shi, C.; Ding, Y.; Liu, T.; Zhang, J. Source, Distribution, and Risk Estimation of Hazardous Elements in Farmland Soils in a Typical Alluvial–Lacustrine Transition Basin, Hunan Province. Int. J. Environ. Res. Public Health 2022, 19, 10971. https://doi.org/10.3390/ijerph191710971
Chen Z, Wang B, Shi C, Ding Y, Liu T, Zhang J. Source, Distribution, and Risk Estimation of Hazardous Elements in Farmland Soils in a Typical Alluvial–Lacustrine Transition Basin, Hunan Province. International Journal of Environmental Research and Public Health. 2022; 19(17):10971. https://doi.org/10.3390/ijerph191710971
Chicago/Turabian StyleChen, Zihan, Bingguo Wang, Chongwen Shi, Yonghui Ding, Tianqi Liu, and Junshuai Zhang. 2022. "Source, Distribution, and Risk Estimation of Hazardous Elements in Farmland Soils in a Typical Alluvial–Lacustrine Transition Basin, Hunan Province" International Journal of Environmental Research and Public Health 19, no. 17: 10971. https://doi.org/10.3390/ijerph191710971