Innovative Approaches for Enhancing Air Pollution Forecast Accuracy in Environmental Science

Air pollution has been on the rise due to human activities including urbanisation and population increase, which is having serious consequences for people's health. A thorough familiarity with air quality and the related environmental health concerns is essential for effective environmental management. Data collected from air pollution monitoring also gives important information on air quality, which may be used to better understand and regulate pollution levels. Reason being, crucial information about air quality is also provided by the data. Pollutant concentration predictions are generated by a number of forecasting systems using meteorological data at different time periods, including hourly, daily, and monthly cycles. Predictions are the way these forecasts are conveyed. The whole forecasting procedure is based on these predictions. The goal of describing these approaches is achieved through the use of several strategies. To lessen the air pollution's detrimental impacts on human and environmental health, very accurate forecasting is crucial. In comparison to more conventional methods based on Attention U-Net, CNN, DMN, GAN, and MMF-Net, the suggested model outperforms them experimentally, with precision, recall, Fl-score, and accuracy all reaching 0.97.