Automated environmental management tool for air pollution forecasting in Villa Clara

Abstract

Air pollution has emerged as one of the most alarming disasters facing humanity in the 21st century, becoming a crisis at both the global and local levels. In this context, early warning systems are presented as an effective solution for reporting on the potential consequences associated with this environmental phenomenon. In the province of Villa Clara, Cuba, the Provincial Meteorological
Center has participated in monitoring stationary sources of pollution in the area. Through the analysis of this process, clear limitations were found in terms of efficiency, accuracy, and timeliness in detecting potential negative events. Due to this problem, the objective of this research is to develop an automated early warning tool for forecasting critical pollution episodes in Villa Clara. The implemented method links the analysis of meteorological variables, as well as the geographic location of stationary sources of pollution and population settlements, making use of technologies such as meteorological forecasting models and geospatial analysis tools. As a result, a desktop application
was developed that can classify the hazard level of these pollution episodes and generate accessible reports to support decision-making. This comprehensive approach improves the efficiency and accuracy of reporting harmful events, making it a useful tool for environmental management in the region