This paper aims to predict models for controlling and monitoring greenhouse gases efficiently. Besides, find best mathematical forecasting models for the main greenhouse gas CO2. Statistical and simulation approaches are implemented and evaluated to investigate the contribution of atmospheric processes and predicate the level of the CO2 emission level in sultanate of Oman. Three regression models were implemented and compared (Linear, Exponential and Polynomial) in the simulation phase based on the two factors the accuracy and the complexity of model. The Polynomial predicting model is best fitting the desired data 99% based on the value of R2=0.991. Whereas, the Exponential and Linear models are achieved less fit 92.6% and 84.6% correspondingly. The predicting models prove that there is a significant increase in level of greenhouse gases (CO2) in Oman.

This paper aims to predict models for controlling and monitoring greenhouse gases efficiently. Besides, find best mathematical forecasting models for the main greenhouse gas CO2. Statistical and simulation approaches are implemented and evaluated to investigate the contribution of atmospheric p...