Forecasting Models Based CO2 Emission for Sultanate of Oman

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 1 (2017) pp. 95 -100

6 Pages Posted: 12 Feb 2017

See all articles by Jabar Yousif

Jabar Yousif

Sohar University

Nebras Alattar

Sohar University

Mabruk Fekihal

Sohar University

Date Written: January 15, 2017

Abstract

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.

Keywords: Greenhouse gases, air pollution, CO2 emission, forecasting models, EMS, Environment in Oman

Suggested Citation

Yousif, Jabar and Alattar, Nebras and Fekihal, Mabruk, Forecasting Models Based CO2 Emission for Sultanate of Oman (January 15, 2017). International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 1 (2017) pp. 95 -100, Available at SSRN: https://ssrn.com/abstract=2913753

Jabar Yousif (Contact Author)

Sohar University ( email )

P.O Box 44
Al Jameah Street
Sohar, Al Batinah 311
Oman

Nebras Alattar

Sohar University

P.O Box 44
Al Jameah Street
Sohar, Al Batinah 311
Oman

Mabruk Fekihal

Sohar University

P.O Box 44
Al Jameah Street
Sohar, Al Batinah 311
Oman

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