Abstract
In the present paper, different Autoregressive Integrated Moving Average (ARIMA) models were developed to model the carbon dioxide emission by using time series data of forty-four years from 1972-2015. The performance of these developed models was assessed with the help of different selection measure criteria and the model having minimum value of these criteria considered as the best forecasting model. Based on findings, it has been observed that out of different ARIMA models, ARIMA (0, 2, 1) is the best fitted model in predicting the emission of carbon dioxide in Bangladesh. Using this best fitted model, the forecasted value of carbon dioxide emission in Bangladesh, for the year 2016, 2017 and 2018 as obtained from ARIMA (0, 2, 1) was obtained as 83.94657 Metric Tons, 89.90464 Metric Tons and 96.28557 Metric Tons respectively.
Highlights
Emission of carbon dioxide (CO2) from living animals, humans, wetlands, volcanoes, and other sources is nearly balanced by the same amount being removed from the atmosphere by plant photosynthesis and by the oceans
The models developed by this approach are usually called Autoregressive Integrated Moving Average (ARIMA) models because they use a combination of autoregressive (AR), integration (I) - referring to the reverse process of differencing to produce the forecast and moving average (MA) operations [19]
This paper aimed to model the emission of carbon dioxide during 2015 in Bangladesh, by Autoregressive Integrated Moving Average (ARIMA) approach
Summary
Emission of carbon dioxide (CO2) from living animals, humans, wetlands, volcanoes, and other sources is nearly balanced by the same amount being removed from the atmosphere by plant photosynthesis and by the oceans. Human activity is disturbing this equilibrium by generating increased CO2 from fossil fuels like as coal, gas, and petroleum products; and combustion via electricity generation, transportation, industry, and domestic use. The results of these imbalances are believed to be greenhouse effects: global warming, melting of polar ice sheets and caps, a rise in sea levels and subsequent coastal inunda-. There is an increasing trend of greenhouse gas (GHG) emissions worldwide due to human activities, which indicates a substantial increase in atmospheric concentrations of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6) (EPA, 2014) [1]. IPCC (2007) [2] shows that carbon dioxide is the most dominant GHGs (greenhouse gases) which accounted 77% of the total global GHG emission where CH4, N2O and other gases contributed 14%, 8% and 1% respectively
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