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

Abstract

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.