Published November 2011 | Version v1
Journal article

Grey forecasting model for CO2 emissions: A Taiwan study

  • 1. Department of Business and Entrepreneurial Management, Kainan University, No. 1 Kainan Rd., Luzhu Shiang, Taoyuan 33857, Taiwan, ROC (China)
  • 2. Department and Graduate Institute of Business Administration, Yuanpei University, 306 Yuanpei St., Hsinchu 30015, Taiwan, ROC (China)
  • 3. Department of Management Science, National Chiao Tung University, 1001 Ta Hsueh Rd., Hsinchu 30010, Taiwan, ROC (China)

Description

Highlights: → CO2 is the most frequently implicated in global warming. → The CARMA indicates that the Taichung coal-fired power plants had the highest CO2 emissions in the world. → GM(1,1) prediction accuracy is fairly high. → The results show that the average residual error of the GM(1,1) was below 10%. -- Abstract: Among the various greenhouse gases associated with climate change, CO2 is the most frequently implicated in global warming. The latest data from Carbon Monitoring for Action (CARMA) shows that the coal-fired power plant in Taichung, Taiwan emitted 39.7 million tons of CO2 in 2007 - the highest of any power plant in the world. Based on statistics from Energy International Administration, the annual CO2 emissions in Taiwan have increased 42% from 1997 until 2006. Taiwan has limited natural resources and relies heavily on imports to meet its energy needs, and the government must take serious measures control energy consumption to reduce CO2 emissions. Because the latest data was from 2009, this study applied the grey forecasting model to estimate future CO2 emissions in Taiwan from 2010 until 2012. Forecasts of CO2 emissions in this study show that the average residual error of the GM(1,1) was below 10%. Overall, the GM(1,1) predicted further increases in CO2 emissions over the next 3 years. Although Taiwan is not a member of the United Nations and is not bound by the Kyoto Protocol, the findings of this study provide a valuable reference with which the Taiwanese government could formulate measures to reduce CO2 emissions by curbing the unnecessary the consumption of energy.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.apenergy.2011.05.013

Additional details

Identifiers

DOI
10.1016/j.apenergy.2011.05.013;
PII
S0306-2619(11)00304-7;

Publishing Information

Journal Title
Applied Energy
Journal Volume
88
Journal Issue
11
Journal Page Range
p. 3816-3820
ISSN
0306-2619
CODEN
APENDX

Optional Information

Copyright
Copyright (c) 2011 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.