Forecasting 7Be Concentrations Using Time Series Analysis: A Case Study of Panama City

Beryllium-7 (7Be) is widely used as an atmospheric radiotracer due to its short half-life and ease of detection. Its evaluation and forecasting provide valuable insights into atmospheric behavior and environmental processes. This study aimed to develop a robust explanatory and predictive model for 7Be concentrations in Panama using monthly data from 2006 to 2019 provided by the RN50 Station at the University of Panama. This study employed ARIMA models for time series analysis and forecasting, complemented by error metrics such as Root Mean Squared Error (RMSE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) to assess the accuracy of the results. After verifying data suitability, analyzing series components, and testing stationarity using the Dickey–Fuller test, the SARIMA (2,0,1) (2,1,0) model was identified as optimal. This model successfully forecasted 7Be concentrations for the final five months of 2019, offering a useful tool for understanding airborne particle dynamics in Panama and supporting future applications of 7Be in the study and estimation of soil erosion.