Use of AI Methods to Assess the Impact of a Lead-Zinc Mining Enterprise on Atmospheric Air

This study evaluates the impact of a lead-zinc ore extraction enterprise on atmospheric air quality using both traditional monitoring techniques and advanced artificial intelligence (AI) methods. The analysis focuses on pollutant dispersion within the sanitary protection zone (SPZ) and adjacent residential areas. Results indicate that pollutant concentrations at the boundary of the SPZ and in nearby communities remain below the Maximum Permissible Concentration (MPC) values, demonstrating adherence to environmental standards. The enterprise, classified as a hazard class 1 facility, maintains a 1000-meter SPZ as required. Comprehensive monitoring is conducted, including quarterly assessments of pollutants such as nitrogen oxides, sulfur dioxide, carbon monoxide, and inorganic dust. To mitigate air quality impacts, the facility employs measures including technological operation control, equipment maintenance, compliance monitoring, and routine repairs. The integration of AI techniques enhances the monitoring process, enabling predictive modeling and scenario analysis to optimize environmental management and ensure sustained air quality protection. This approach underscores the importance of combining traditional and innovative methods for effective environmental oversight and management in industrial settings.