ІНТЕГРАЦІЯ МОДЕЛЕЙ ПРОГНОЗУВАННЯ ДЛЯ ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ МОНІТОРИНГУ ТРАНСПОРТНОГО ВПЛИВУ НА ДОВКІЛЛЯ

Urban air pollution caused by vehicle emissions is becoming a growing problem, especially in industrially loaded cities such as Kryvyi Rih. Constant heavy traffic and the operation of vehicles that do not meet modern environmental standards significantly affect the quality of atmospheric air. Traditional methods of pollution control are often insufficient to respond in a timely manner to continuous changes in air quality, resulting in the introduction of restrictions only after critical levels of pollution have been reached. This approach is ineffective for long-term air quality management. The article considers the importance of implementing forecasting systems as an integral component of environmental monitoring. Forecasting systems make it possible to assess changes in atmospheric air quality in advance and to take measures in time to minimize the harmful effects of motor vehicles. Such systems are especially important in high-traffic areas where the accumulation of pollutants can quickly exceed safe levels. The implementation of such technologies will allow cities to manage traffic flows more effectively, reducing the intensity of traffic during periods when the risk of pollution is the highest. This research focuses on developing approaches for integrating forecasting models with real-time monitoring systems. Such integration allows for a more accurate picture of the impact of transport on the air environment and timely response to potential environmental threats. In addition, the results show that the management of traffic flows based on predictive models can significantly reduce emissions, especially in areas of the highest load, such as transport hubs and highways. The implementation of such systems provides the possibility of planning urban transport networks taking into account environmental factors, which in turn increases the comfort of life of residents and reduces the negative impact on the environment.