Forecasting health risks for the residents of Southern Russia through satellite and climate-based aridity indicators

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BACKGROUND: The aridification of the Southern region of Russia will lead to a significant rise in the concentration of hazardous substances in groundwater over the long term. This phenomenon poses a serious threat to the environment and public health.

AIM: To assess the potential of the multi-regression climate model in predicting the long-term health risks associated with the ingestion of toxic substances released from groundwater sources.

METHODS: An assessment of non-carcinogenic health risks (HI) was conducted for the period 2017–2022, focusing on three groundwater basins in the Volgograd Trans-Volga region. The study involved the analysis of toxicant concentrations in 1149 water samples at the 95th percentile. NDMI and De Martonne Index (DMI) values were calculated based on modified data obtained through Land Surface Temperature (LST) satellite analysis. These indices were then employed as predictors in our models, with the HI serving as the dependent variable.

RESULTS: A significant contribution of chloroform to the overall risk pattern for groundwater in the Volgograd Trans-Volga region was observed. The maximum values were recorded in the Nizhnevolzhskiy groundwater basin (HQchildren/chloroform=3.20, HQadults/chloroform=1.37) in 2017. The satellite aridity index NDMI makes the greatest contribution to the reliability of the predictive model of long-term health risk dynamics that shape the oral intake of pollutants from groundwater in the Volgograd Trans-Volga region. The lowest multiple regression value was noted for the health risk for adults (ry,x1,x2=–0.909, p=0.012) in the Severo-Prikaspiyskiy basin, the maximum was recorded in Ryn-Peskovsky basin for children (ry,x1,x2=–0.992, p=0.002). The DMI provides insignificant reliability in predicting long-term dynamics of non-carcinogenic health risks associated with toxicants circulating in arid ecosystems of the South of Russia. The greatest contribution of this predictor was observed for the health risk of children in the Ryn-Peskovsky basin (rx2/x1=–0.554, p=0.105).

CONCLUSION: Our findings suggest a significant potential for integrating NDMI in monitoring the social and hygienic quality of underground water in arid zones of Southern Russia. The NDMI indicator has demonstrated high resolution and sensitivity to water quantity in steppe vegetation, reflecting its accuracy for arid topography. This integration holds promise for enhancing the monitoring and management of underground water resources in Southern Russia.

作者简介

Denis Novikov

Volgograd State Medical University

编辑信件的主要联系方式.
Email: dennov89@mail.ru
ORCID iD: 0000-0002-2886-5431
SPIN 代码: 4583-6672
俄罗斯联邦, Volgograd

Natalia Latyshevskaya

Volgograd State Medical University

Email: latyshnata@mail.ru
ORCID iD: 0000-0002-8367-745X
SPIN 代码: 7299-4690

MD, Dr. Sci. (Medicine), professor

俄罗斯联邦, Volgograd

参考

  1. Rakhmanin YuA, Mel’tser AV, Kiselev AV, Erastova NV. Hygienic substantiation of management decisions with the use of the integral assessment of drinking water on indices of chemical harmlessness and epidemiological safety. Hygiene and Sanitation. 2017;96(4):302–305. doi: 10.18821/0016-9900-2017-96-4-302-305
  2. Kosarev AV, Ivanov DE, Mikerov AN, Savina KA. Evaluation of a carcinogenic and non-carcinogenic health risks due to the quality of drinking water by springs in the arid zone. Hygiene and Sanitation. 2020;99(11):1294–1300. EDN: HVDGPU doi: 10.47470/0016-9900-2020-99-11-1294-1300
  3. Feng S, Wu X, Hao Z, et al. A database for characteristics and variations of global compound dry and hot events. Weather and Climate Extremes. 2020;30:100299. doi: 10.1016/j.wace.2020.100299
  4. Zalibekov ZG, Mamaev SA, Biarslanov AB, et al. On the use of fresh groundwater in arid regions of the world in the fight against desertification. Arid ecosystems. 2019;25(2):3–12. EDN: PJYQLZ
  5. Gibbs RJ. Mechanisms controlling world water chemistry. Science. 1970;170(3962):1088–1090. doi: 10.1126/science.170.3962.1088
  6. Komitet prirodnyh resursov, lesnogo hozyajstva i ekologii Volgogradskoj oblasti. Doklad "O sostoyanii okruzhayushchej sredy v Volgogradskoj oblasti v 2022 godu". Volgograd; 2023. 300 p. (In Russ).
  7. Upravlenie Federal'noj sluzhby po nadzoru v sfere zashchity prav potrebitelej i blagopoluchiya cheloveka po Volgogradskoj oblasti. Gosudarstvennyj doklad "O sostoyanii sanitarno-epidemiologicheskogo blagopoluchiya naseleniya v Volgogradskoj oblasti v 2022 godu". Volgograd. 2023. 258 p. (In Russ).
  8. Adamovich TA, Ashikhmina TYa. Aerospace methods in the system of geo-ecological monitoring of natural and anthropogenic areas. Theoretical and Applied Ecology. 2017;(3):15–24. EDN: YMAJIT
  9. Studenikina EM, Stepkin YuI, Klepikov OV, et al. Problematic issues of the geographic information systems use in socio-hygienic monitoring and risk-based supervision. Public Health and Life Environment. 2019;(6):31–36. EDN: OEJXHN doi: 10.35627/2219-5238/2019-315-6-31-36
  10. World Meteorological Organization (WMO) and Global Water Partnership (GWP). Svoboda М, Fuchs BA. Handbook of Drought Indicators and Indices. Integrated Drought Management Programme (IDMP), Integrated Drought Management Tools and Guidelines Series 2. Geneva. 2016. 60 p.
  11. Zelikhina SV, Shartova NV, Mironova VA, Varentsov MI. Ecological and geographical prerequisites for the spread of West Nile fever in Russia. Ecosystems: ecology and dynamics. 2021;5(1):132–150. EDN: DSIXBK doi: 10.24411/2542-2006-2021-10081
  12. Human Health Risk Assessment from Environmental Chemicals. Moscow: Federal Center of Gossanepidnadzor of the Ministry of Health of Russia. 2004. 143 р.
  13. Pellicone G, Caloiero T, Guagliardi I. The De Martonne aridity index in Calabria (Southern Italy). Journal of Maps. 2019;15(2):788–796. doi: 10.1080/17445647.2019.1673840
  14. Gao B. Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space. Imaging Spectrometry. 1995;2480:225–236. doi: 10.1117/12.210877
  15. Agalakova NI, Gusev GP. The influence of inorganic fluorine on living organisms of various phylogenetic levels. Journal of evolutionary biochemistry and physiology. 2011;47(5):337–347. EDN: MSISRJ
  16. Marchenko BI, Zhuravlev PV, Plugotarenko NK, Yuhno AI. Assessment of carcinogenic risk from exposure to organochlorine compounds in water of centralized water supply systems. Hygiene and Sanitation. 2021;100(2):99-110. doi: 10.47470/0016-9900-2021-100-2-99-110
  17. Hunkeler D, Laier T, Breider F, Jacobsen OS. Demonstrating a natural origin of chloroform in groundwater using stable carbon isotopes. Environmental science and technology. 2012;46(11):6096–6101. doi: 10.1021/es204585d
  18. Breider F, Albers CN, Hunkeler D. Assessing the role of trichloroacetyl-containing compounds in the natural formation of chloroform using stable carbon isotopes analysis. Chemosphere. 2013;90(2):441–448. doi: 10.1016/j.chemosphere.2012.07.058
  19. Field JA. Natural Production of Organohalide Compounds in the Environment. In: Adrian L, Löffler F, editors. Organohalide- Respiring. Bacteria. Springer, Berlin, Heidelberg. 2016:7–29. doi: 10.1007/978-3-662-49875-0_2
  20. Peng P, Lu Y, Bosma TNP, et al. Metagenomic- and Cultivation- Based Exploration of Anaerobic Chloroform Biotransformation in Hypersaline Sediments as Natural Source of Chloromethanes. Microorganisms. 2020;8(5):665. doi: 10.3390/microorganisms8050665
  21. Pankova EI, Gorokhova IN, Konyushkova MV, et al. Modern trends in the development of soils of solonetz complexes in the south of the steppe and semi-desert zones under natural conditions and under anthropogenic influences. Ecosystems: ecology and dynamics. 2019;3(2):44-88. doi: 10.24411/2542-2006-2019-10032
  22. Malakhov DV, Tsychuyeva NYu. Calculation of the biophysical parameters of vegetation in an arid area of south-eastern Kazakhstan using the normalized difference moisture index (NDMI). Central Asian Journal of Environmental Science and Technology Innovation. 2020;1(4):189-198. doi: 10.22034/CAJESTI.2020.04.01
  23. Kosarev AV, Ivanov DE, Mikerov AN, et al. Application of geoinformation technologies and remote sensing of the Earth to assess the impact of aridity of the territory on the water quality of small rivers. Hygiene and Sanitation. 2021;100(10):1052–1059. EDN: DZJUBF doi: 10.47470/0016-9900-2021-100-10-1052-1059
  24. Balamurugan P, Kumar PS, Shankar K, et al. Non Carcinogenic Risk Assessment of Groundwater in southern part of Salem District in Tamil Nadu, India. Journal of the Chilean Chemical Society. 2020;65(1):4697–4707. doi: 10.4067/S0717-97072020000104697
  25. Iksanova TI, Malysheva AG, Rastyannikov EG, et al. Hygienic assessment of the complex effect of chloroform in drinking water. Hygiene and Sanitation. 2006.2:10-14.
  26. Jamali Z, Heidarizadi Z. Future changes in dry conditions using statistical downscaling model (SDSM) in the western region of Gorgan plain, Iran. Arid Ecosystems. 2022;28(4):4–12. EDN: YSNQNJ doi: 10.24412/1993-3916-2022-4-4-12
  27. Yamilova OY, Koval’chuk VK. Peculiarities of low-mineralized drinking water chemical contamination influence on health of the population of the Russian Far East. Russian Bulletin of Hygiene. 2021;(3):36–41. EDN: TPVWJE doi: 10.24075/rbh.2021.022

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1. JATS XML
2. Fig. 1. Hydrogeological nature of the Trans-Volga Region within the administrative borders of the Volgograd region.

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3. Fig. 2. Values of long-term trends of health risks for the main targets for developing non-carcinogenic effects in the North Caspian basin of the second order: CNS — central nervous system; CV(S) — cardiovascular system.

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4. Fig. 3. Raster maps of the third order groundwater basins with zonal statistics of the NDMI aridity index (2017–2022).

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5. Fig. 4. Raster maps of the LST indicator in the Volgograd Trans-Volga Region (2017–2022).

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