Fractal Analysis of Mining Wastewater Time Series Parameters: Balkhash Urban Region and Sayak Ore District

The population life and health quality are significantly reduced due to water resources pollution caused by heavy metals, especially in urban agglomerations located close to metal ore mining and processing facilities. The greatest environmental pollution occurs during the extraction of Cu, Zn, and Pb. In this study, a fractal R/S analysis of wastewater discharge indicators time series from a metal ore mining facility located in the Sayak ore district in the Republic of Kazakhstan (turbidity, electrical conductivity, flow magnitude, and pH level) was carried out. A sharp increase in the flow rate was recorded from 10 to 15 July 2024 and an increase in the electrical conductivity from 4 to 26 July 2024. However, the latest type of indicator assessment does not exceed the critical level for life. The presence of electrical conductivity indicators time series long-term memory and persistence was also recorded (the Hurst exponent for the electrical conductivity time series is fixed in the 0.56 to 0.59 range and does not go below the threshold value for randomness according to the Anis-Lloyd formula). Thus, the value-changing process is controlled and stable, and minor changes in turbidity indicate that these releases do not significantly harm the environment. Despite this, the results obtained do not allow for a comprehensive analysis of the state of releases as the data from all deposits is not available. Therefore, due to the time constraints of the data provided for analysis, it is difficult to fully assess the impact of specific metal ore mining facilities on the environmental safety of the Balkhash urban region. In addition, many studies indicate very high risks of chronic diseases for the population living in this region. The findings of this study enable us to conclude that the application of fractal analysis and the calculation of fractal characteristics for time series of emissions can serve as an indicator of the environmental status within the given area. This information can be used by environmental services to build reliable environmental pollution monitoring systems.