Open AccessForecasting Carbon Dioxide Emission of Asian Countries Using ARIMA and Simple Exponential Smoothing Models
Author(s) -
Samreen Fatima,
Sayed Saad Ali,
Syeda Sadia Zia,
Ehtesham Hussain,
Tayyab Raza Fraz,
Mehwish Shafi Khan
Publication year - 2019
Publication title -
international journal of economic and environment geology
Language(s) - English
Resource type - Journals
ISSN - 2223-957X
DOI - 10.46660/ojs.v10i1.219
Subject(s) - exponential smoothing , autoregressive integrated moving average , sri lanka , china , carbon dioxide , electricity , pollution , environmental science , geography , time series , mathematics , economics , statistics , socioeconomics , engineering , chemistry , ecology , archaeology , organic chemistry , biology , electrical engineering , tanzania
Industrial revolution has increased the level of pollution due to emission of carbon dioxide in the past fewdecades. Resulting changes in the world’s climate are seen in the form of an increase in temperature which causes heatwaves, diseases related to skin, cardiovascular and other respiratory illnesses in humans. According to a past study,overall contribution of continent Asia is 49% - 50% in the production of carbon dioxide. Therefore, data of carbondioxide emission, heat and electricity, manufacturing industries, residential and commercial buildings, transport andother sources of Asian countries namely: Japan, Bangladesh, China, Pakistan, India, Sri Lanka, Iran, Singapore, andNepal from 1971 to 2014 have been taken for the present study. Empirical analysis shows that heat and electricity arethe main cause to increase carbon dioxide emission in Pakistan, Bangladesh, India, Iran and Sri Lanka. Whereas thisemission is increased in China due to residential and commercial buildings and transport variables. On the other hand,for Nepal and Singapore, these variables do not play any significant role in CO2 emission. Simple exponentialsmoothing (SES) and ARIMA models are used to forecast CO2 emissions. Furthermore, simple exponential smoothingis found appropriate for Pakistan and Sri Lanka based on the minimum FMAE. Whereas, for Japan, China, India, Iranand Singapore, ARIMA model is found suitable as it has minimum FMAE value. In Nepal and Bangladesh, bothmodels have significant differences, so any one of them can be used for forecasting.