Air pollution is a major public health problem that affects economic development, agriculture, and the ecosystem. Lebanon is one of the most polluted countries in the Middle East region due to the increase in the concentrations of atmospheric air pollution which exceed the required levels according to the global guidelines. The main objective of this paper is to identify the extreme concentrations of air pollutants in order to minimize their adverse effects. The peak of concentration of the pollution which is measured within a specific period could be described by using the extreme value theory mainly as one kind of the three different types of the extreme value theory and the record theory as a second kind. These two approaches will be applied to predict the expected extreme concentration in the future and the probability of occurrence of a new record. Whereas daily measurements of SO2, CO, NO, PM10, PM2.5 throughout the period 2016-2019 in the Bekaa Valley. The findings indicate that the concentrations of the 15, 30, 40, and 50-year return pollutant levels are continuously increasing. The percentage of the change of SO2, CO, NO, PM10, PM2.5 after 50 years is 64%, 5%, 3%, 29%, 20% and 12%, respectively. The records have been observed at the beginning of a time series and an interval point prediction was given for each measure. The future record values of SO2, CO, NO, PM10, PM2.5 were increased by 0.2%, 0.7%, 1%, 0.5%, 6%, and 5.7%, respectively, over 1 year. There was a 66% chance to observe a new record-breaking pollutant level that exceeded the guidelines after two years.

During the last decades, air pollution has become a serious environmental hazard. Its impact on public health and safety, as well as on the ecosystem, has been dramatic. Forecasting the levels of air pollution to maintain the climatic conditions and environmental protection becomes crucial for government authorities to develop strategies for the prevention of pollution. This study aims to evaluate the atmospheric air pollution of the city of Zahleh located in the geographic zone of Bekaa. The study aims to determine a relationship between variations in ambient particulate concentrations during a short time. The data was collected from June 2017 to June 2018. In order to predict the Air Quality Index (AQI), Naïve, Exponential Smoothing, TBATS (a forecasting method to model time series data), and Seasonal Autoregressive Integrated Moving Average (SARIMA) models were implemented. The performance of these models for predicting air quality is measured using the Mean Absolute Error (MAE), the Root Mean Square Error (RMSE), and the Relative Error (RE). SARIMA model is the most accurate in prediction of AQI (RMSE = 38.04, MAE = 22.52 and RE = 0.16). The results reveal that SARIMA can be applied to cities like Zahleh to assess the level of air pollution and to prevent harmful impacts on health. Furthermore, the authorities responsible for controlling the air quality may use this model to measure the level of air pollution in the nearest future and establish a mechanism to identify the high peaks of air pollution.