PREDICTABILITY OF MINING WASTEWATER POLLUTION BASED ON FRACTAL TIME SERIES ANALYSIS
Аннотация
The quality of life and public health are deteriorating due to the contamination of water resources with heavy metals, especially near mining and ore-processing sites. The most severe pollution is associated with the extraction of Cu, Zn and Pb. This study conducted a fractal R/S-analysis of time series data (turbidity, electrical conductivity, flow, and pH) of wastewater from a site in the Sayak ore district (Republic of Kazakhstan). A sharp increase in flow was observed from July 10 to July 15, 2024, and an increase in electrical conductivity from July 4 to July 26, 2024, although without exceeding critical levels. The Hurst exponent for electrical conductivity exceeds 0.56, indicating the presence of long-term memory and the stability of the process. Minor variations in turbidity indicate no serious harm to the environment. However, the data are limited and do not allow for an assessment of all deposits in the region, making it difficult to draw conclusions about the impact on the environmental safety of the Balkhash urban region. Despite the high risk of chronic diseases in the area, the results confirm that fractal analysis can serve as a useful indicator of environmental conditions and a basis for monitoring systems.
Автор
Biloshchytskyi Andrii
Kuchanskyi Oleksandr
Andrashko Yurii
Biloshchytska Svitlana
Medetbek Arailym
DOI
10.48081/UFNH5611
Ключевые слова
time series analysis
R/S analysis
Hurst exponent
mining wastewater
environmental monitoring
Год
2025
Номер
Выпуск 3