RAS Agricultural ScienceВестник российской сельскохозяйственной науки Vestnik of the Russian Agricultural Science

  • ISSN (Print) 2500-2082
  • ISSN (Online) 3034-5200

Modern methods for determining heavy metals in soil

PII
10.31857/S2500208224040167-1
DOI
10.31857/S2500208224040167
Publication type
Article
Status
Published
Authors
Volume/ Edition
Volume / Issue number 4
Pages
84-89
Abstract
This article discusses the problem of heavy metal detection in soil and its impact on vegetation. Based on the experience of foreign and domestic research, this article discusses global fundamental problems and challenges, modern methods of heavy metal detection, as well as prospects for further research and new challenges facing the scientific community. The aim of the study is to identify modern and established methods for the detection of heavy metals in soil, such as spectral analysis methods and reflectance spectra of plant parts. The review summarizes the results of experimental studies confirming the effectiveness of the combined sampling and spectrometry method for estimating the concentration of heavy metals in soil, as well as the feasibility of using plant reflectance spectra to measure pollution. World experience confirms the expediency of using spectral approaches to determine heavy metals in soil and analyze their impact on vegetation. The results of the research have practical application in the field of ecology, agriculture and nature protection, allow effectively controlling the level of heavy metal pollution and taking measures for its elimination.
Keywords
тяжелые металлы диагностика почв инфракрасная спектроскопия машинное обучение предварительная обработка данных загрязнение почв
Date of publication
18.09.2025
Year of publication
2025
Number of purchasers
0
Views
5

References

  1. 1. Абилова Г.А. Влияние ионов кадмия и свинца на рост и содержание пролина в растениях тритикале (Triticosecale Wittm.) // Труды Карельского научного центра РАН. 2016. С. 27.
  2. 2. Пишик В.И др. Механизмы адаптации растений к тяжелым металлам // Агрофизика. 2015. С. 39–49.
  3. 3. Терехова В.А. и др. Фитотоксичность тяжелых металлов в дерново-подзолистых почвах разной степени окультуренности // Почвоведение. 2021. № 6. С. 757–768.
  4. 4. Шабанов М.В., Стрекулев Г.Б. Геохимические процессы накопления тяжелых металлов в ландшафтах Южного Урала // Известия Томского политехнического университета. Инжиниринг георесурсов. 2021. Т. 332. № 1. С. 184–192.
  5. 5. Adhikari K. et al. Heavy metals concentration in soils across the conterminous USA: Spatial prediction, model uncertainty, and influencing factors // Sci. Total Environ. 2024. V. 919. 170972.
  6. 6. Ali H., Khan E. What are heavy metals? Long-standing controversy over the scientific use of the term ‘heavy metals’ – proposal of a comprehensive definition // Toxicol. Environ. Chem. 2018. Т. 100. № 1. P. 6–19.
  7. 7. Anning A.K., Akoto R. Assisted phytoremediation of heavy metal contaminated soil from a mined site with Typha latifolia and Chrysopogon zizanioides // Ecotoxicol. Environ. Saf. 2018. Т. 148. P. 97–104
  8. 8. Bai B. et al. The remediation efficiency of heavy metal pollutants in water by industrial red mud particle waste // Environ. Technol. Innov. 2022. V. 28. 102944.
  9. 9. Bhuyan M.S. Contamination of Heavy Metals in Agricultural Soils: Ecological and Health Risk Assessment // SF J. Nanochemistry Nanotechnol. 2019
  10. 10. Chen Y.-G. et al. Impacts of heavy metals and medicinal crops on ecological systems, environmental pollution, cultivation, and production processes in China // Ecotoxicol. Environ. Saf. 2021. V. 219. 112336.
  11. 11. Chettri U., Chakrabarty T.K., Joshi S.R. Pollution index assessment of surface water and sediment quality with reference to heavy metals in Teesta River in Eastern Himalayan range, India // Environ. Nanotechnol. Monit. Manag. 2022. V. 18. 100742.
  12. 12. Choudhury T.R. et al. Appraisal of heavy metal contamination and their source apportionment identification in five river water systems of the coastal areas in Bangladesh // Reg. Stud. Mar. Sci. 2024. V. 70. 103378.
  13. 13. Fu P. et al. A novel spectral analysis method for distinguishing heavy metal stress of maize due to copper and lead: RDA and EMD-PSD // Ecotoxicol. Environ. Saf. 2020. V. 206. 111211.
  14. 14. Gani A. et al. An empirical investigation on the elimination of heavy metals using bioremediation method for selected plant species // Phys. Chem. Earth Parts ABC. 2024. Т. 134. 103568
  15. 15. Genova G. et al. Analyzing soil enzymes to assess soil quality parameters in long-term copper accumulation through a machine learning approach // Appl. Soil Ecol. 2024. V. 195. 105261.
  16. 16. Hammam A.A. et al. Assessment of Soil Contamination Using GIS and Multi-Variate Analysis: A Case Study in El-Minia Governorate, Egypt // Agronomy. 2022. V. 12. № 5. 1197.
  17. 17. Hossain Md. M. et al. Heavy metal pollution in the soil-vegetable system of Tannery Estate // Environ. Nanotechnol. Monit. Manag. 2021. T. 16. 100557.
  18. 18. Jadaa W., Mohammed H.K. Heavy Metals – Definition, Natural and Anthropogenic Sources of Releasing into Ecosystems, Toxicity, and Removal Methods – An Overview Study // J. Ecol. Eng. 2023. V. 24. № 6. P. 249–271.
  19. 19. Jannetto P.J., Cowl C.T. Elementary Overview of Heavy Metals // Clin. Chem. 2023. Т. 69. № 4. P. 336–349.
  20. 20. Khumaeni A. et al. Transversely Excited Atmospheric CO2 Laser-Induced Plasma Spectroscopy for the Detection of Heavy Metals in Soil // J. Appl. Spectrosc. 2018. V. 84. № 6. P. 1108–1113.
  21. 21. Lin Y. et al. Estimating low concentration heavy metals in water through hyperspectral analysis and genetic algorithm-partial least squares regression // Sci. Total Environ. 2024. V. 916. 170225.
  22. 22. Liu J. et al. A spatial distribution – Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil // Sci. Total Environ. 2023. V. 859. 160112.
  23. 23. Liu N. et al. Development of smartphone-controlled and machine-learning-powered integrated equipment for automated detection of bioavailable heavy metals in soils // J. Hazard. Mater. 2024. V. 465. 133140.
  24. 24. Liu X. et al. A portable electromagnetic heating-microplasma atomic emission spectrometry for direct determination of heavy metals in soil // Talanta. 2020. V. 219. 121348.
  25. 25. Liu Z. et al. Source apportionment of soil heavy metals based on multivariate statistical analysis and the PMF model: A case study of the Nanyang Basin, China // Environ. Technol. Innov. 2024. V. 33. 103537.
  26. 26. Nawar S. et al. Estimation of key potentially toxic elements in arid agricultural soils using Vis-NIR spectroscopy with variable selection and PLSR algorithms // Front. Environ. Sci. 2023. V. 11.
  27. 27. Optical imaging spectroscopy coupled with machine learning for detecting heavy metal of plants: A review. Li J, Ren J, Cui R, Yu K and Zhao Y. 2022. URL: https://www.frontiersin.org/articles/10.3389/fpls.2022.1007991/full (дата обращения: 04.02.2024).
  28. 28. Potharaju R., Aruna M. A Study on Heavy Metal Pollution in Water, 2024. P. 110–120.
  29. 29. Şener E., Şener Ş., Bulut C. Assessment of heavy metal pollution and quality in lake water and sediment by various index methods and GIS: A case study in Beyşehir Lake, Turkey // Mar. Pollut. Bull. 2023. V. 192. 115101.
  30. 30. Tomczyk P. et al. Assessment of heavy metal contamination of agricultural soils in Poland using contamination indicators // Ecol. Indic. 2023. V. 156. 111161.
  31. 31. Velayatzadeh M. Heavy Metals in Surface Soils and Crops // Heavy Metals – Recent Advances: IntechOpen, 2023
  32. 32. Wang H. et al. Improving prediction of soil heavy metal(loid) concentration by developing a combined Co-kriging and geographically and temporally weighted regression (GTWR) model // J. Hazard. Mater. 2024. V. 468. 133745.
  33. 33. Wang N. et al. Predicting the spatial pollution of soil heavy metals by using the distance determination coefficient method // Sci. Total Environ. 2021. V. 799. p. 149452.
  34. 34. Xie T. et al. Modeling analysis of the characteristics of selenium-rich soil in heavy metal high background area and its impact on main crops // Ecol. Inform. 2021. V. 66. 101420.
  35. 35. Yang S. et al. An integrated analysis on source-exposure risk of heavy metals in agricultural soils near intense electronic waste recycling activities // Environ. Int. 2019. V. 133. 105239.
  36. 36. Yang Y. et al. Beyond mere pollution source identification: Determination of land covers emitting soil heavy metals by combining PCA/APCS, GeoDetector and GIS analysis // CATENA. 2020. V. 185. 104297.
  37. 37. Yao C. et al. Heavy metal pollution in agricultural soils from surrounding industries with low emissions: Assessing contamination levels and sources // Sci. Total Environ. 2024. V. 917. 170610.
  38. 38. Zhang J. et al. Environmental geochemical baseline determination and pollution assessment of heavy metals in farmland soil of typical coal-based cities: A case study of Suzhou City in Anhui Province, China // Heliyon. 2023. V. 9. № 4. e14841.
  39. 39. Zhao G. et al. Simultaneous and on-line detection of organic and heavy metal components in water using a novel nebulization-assisted injection plasma ionization triple quadruple mass spectrometry instrument // Anal. Chim. Acta. 2024. V. 1304. 342531.
  40. 40. Zhao H. et al. Comprehensive assessment of heavy metals in soil-crop system based on PMF and evolutionary game theory // Sci. Total Environ. 2022. V. 849. 157549.
QR
Translate

Индексирование

Scopus

Scopus

Scopus

Crossref

Scopus

Higher Attestation Commission

At the Ministry of Education and Science of the Russian Federation

Scopus

Scientific Electronic Library